REALIZING THE PROMISE:

Leading up to the 75th anniversary of the UN General Assembly, this “Realizing the promise: How can education technology improve learning for all?” publication kicks off the Center for Universal Education’s first playbook in a series to help improve education around the world.

It is intended as an evidence-based tool for ministries of education, particularly in low- and middle-income countries, to adopt and more successfully invest in education technology.

While there is no single education initiative that will achieve the same results everywhere—as school systems differ in learners and educators, as well as in the availability and quality of materials and technologies—an important first step is understanding how technology is used given specific local contexts and needs.

The surveys in this playbook are designed to be adapted to collect this information from educators, learners, and school leaders and guide decisionmakers in expanding the use of technology.  

Introduction

While technology has disrupted most sectors of the economy and changed how we communicate, access information, work, and even play, its impact on schools, teaching, and learning has been much more limited. We believe that this limited impact is primarily due to technology being been used to replace analog tools, without much consideration given to playing to technology’s comparative advantages. These comparative advantages, relative to traditional “chalk-and-talk” classroom instruction, include helping to scale up standardized instruction, facilitate differentiated instruction, expand opportunities for practice, and increase student engagement. When schools use technology to enhance the work of educators and to improve the quality and quantity of educational content, learners will thrive.

Further, COVID-19 has laid bare that, in today’s environment where pandemics and the effects of climate change are likely to occur, schools cannot always provide in-person education—making the case for investing in education technology.

Here we argue for a simple yet surprisingly rare approach to education technology that seeks to:

  • Understand the needs, infrastructure, and capacity of a school system—the diagnosis;
  • Survey the best available evidence on interventions that match those conditions—the evidence; and
  • Closely monitor the results of innovations before they are scaled up—the prognosis.

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The framework.

Our approach builds on a simple yet intuitive theoretical framework created two decades ago by two of the most prominent education researchers in the United States, David K. Cohen and Deborah Loewenberg Ball. They argue that what matters most to improve learning is the interactions among educators and learners around educational materials. We believe that the failed school-improvement efforts in the U.S. that motivated Cohen and Ball’s framework resemble the ed-tech reforms in much of the developing world to date in the lack of clarity improving the interactions between educators, learners, and the educational material. We build on their framework by adding parents as key agents that mediate the relationships between learners and educators and the material (Figure 1).

Figure 1: The instructional core

Adapted from Cohen and Ball (1999)

As the figure above suggests, ed-tech interventions can affect the instructional core in a myriad of ways. Yet, just because technology can do something, it does not mean it should. School systems in developing countries differ along many dimensions and each system is likely to have different needs for ed-tech interventions, as well as different infrastructure and capacity to enact such interventions.

The diagnosis:

How can school systems assess their needs and preparedness.

A useful first step for any school system to determine whether it should invest in education technology is to diagnose its:

  • Specific needs to improve student learning (e.g., raising the average level of achievement, remediating gaps among low performers, and challenging high performers to develop higher-order skills);
  • Infrastructure to adopt technology-enabled solutions (e.g., electricity connection, availability of space and outlets, stock of computers, and Internet connectivity at school and at learners’ homes); and
  • Capacity to integrate technology in the instructional process (e.g., learners’ and educators’ level of familiarity and comfort with hardware and software, their beliefs about the level of usefulness of technology for learning purposes, and their current uses of such technology).

Before engaging in any new data collection exercise, school systems should take full advantage of existing administrative data that could shed light on these three main questions. This could be in the form of internal evaluations but also international learner assessments, such as the Program for International Student Assessment (PISA), the Trends in International Mathematics and Science Study (TIMSS), and/or the Progress in International Literacy Study (PIRLS), and the Teaching and Learning International Study (TALIS). But if school systems lack information on their preparedness for ed-tech reforms or if they seek to complement existing data with a richer set of indicators, we developed a set of surveys for learners, educators, and school leaders. Download the full report to see how we map out the main aspects covered by these surveys, in hopes of highlighting how they could be used to inform decisions around the adoption of ed-tech interventions.

The evidence:

How can school systems identify promising ed-tech interventions.

There is no single “ed-tech” initiative that will achieve the same results everywhere, simply because school systems differ in learners and educators, as well as in the availability and quality of materials and technologies. Instead, to realize the potential of education technology to accelerate student learning, decisionmakers should focus on four potential uses of technology that play to its comparative advantages and complement the work of educators to accelerate student learning (Figure 2). These comparative advantages include:

  • Scaling up quality instruction, such as through prerecorded quality lessons.
  • Facilitating differentiated instruction, through, for example, computer-adaptive learning and live one-on-one tutoring.
  • Expanding opportunities to practice.
  • Increasing learner engagement through videos and games.

Figure 2: Comparative advantages of technology

Here we review the evidence on ed-tech interventions from 37 studies in 20 countries*, organizing them by comparative advantage. It’s important to note that ours is not the only way to classify these interventions (e.g., video tutorials could be considered as a strategy to scale up instruction or increase learner engagement), but we believe it may be useful to highlight the needs that they could address and why technology is well positioned to do so.

When discussing specific studies, we report the magnitude of the effects of interventions using standard deviations (SDs). SDs are a widely used metric in research to express the effect of a program or policy with respect to a business-as-usual condition (e.g., test scores). There are several ways to make sense of them. One is to categorize the magnitude of the effects based on the results of impact evaluations. In developing countries, effects below 0.1 SDs are considered to be small, effects between 0.1 and 0.2 SDs are medium, and those above 0.2 SDs are large (for reviews that estimate the average effect of groups of interventions, called “meta analyses,” see e.g., Conn, 2017; Kremer, Brannen, & Glennerster, 2013; McEwan, 2014; Snilstveit et al., 2015; Evans & Yuan, 2020.)

*In surveying the evidence, we began by compiling studies from prior general and ed-tech specific evidence reviews that some of us have written and from ed-tech reviews conducted by others. Then, we tracked the studies cited by the ones we had previously read and reviewed those, as well. In identifying studies for inclusion, we focused on experimental and quasi-experimental evaluations of education technology interventions from pre-school to secondary school in low- and middle-income countries that were released between 2000 and 2020. We only included interventions that sought to improve student learning directly (i.e., students’ interaction with the material), as opposed to interventions that have impacted achievement indirectly, by reducing teacher absence or increasing parental engagement. This process yielded 37 studies in 20 countries (see the full list of studies in Appendix B).

Scaling up standardized instruction

One of the ways in which technology may improve the quality of education is through its capacity to deliver standardized quality content at scale. This feature of technology may be particularly useful in three types of settings: (a) those in “hard-to-staff” schools (i.e., schools that struggle to recruit educators with the requisite training and experience—typically, in rural and/or remote areas) (see, e.g., Urquiola & Vegas, 2005); (b) those in which many educators are frequently absent from school (e.g., Chaudhury, Hammer, Kremer, Muralidharan, & Rogers, 2006; Muralidharan, Das, Holla, & Mohpal, 2017); and/or (c) those in which educators have low levels of pedagogical and subject matter expertise (e.g., Bietenbeck, Piopiunik, & Wiederhold, 2018; Bold et al., 2017; Metzler & Woessmann, 2012; Santibañez, 2006) and do not have opportunities to observe and receive feedback (e.g., Bruns, Costa, & Cunha, 2018; Cilliers, Fleisch, Prinsloo, & Taylor, 2018). Technology could address this problem by: (a) disseminating lessons delivered by qualified educators to a large number of learners (e.g., through prerecorded or live lessons); (b) enabling distance education (e.g., for learners in remote areas and/or during periods of school closures); and (c) distributing hardware preloaded with educational materials.

Prerecorded lessons

Technology seems to be well placed to amplify the impact of effective educators by disseminating their lessons. Evidence on the impact of prerecorded lessons is encouraging, but not conclusive. Some initiatives that have used short instructional videos to complement regular instruction, in conjunction with other learning materials, have raised student learning on independent assessments. For example, Beg et al. (2020) evaluated an initiative in Punjab, Pakistan in which grade 8 classrooms received an intervention that included short videos to substitute live instruction, quizzes for learners to practice the material from every lesson, tablets for educators to learn the material and follow the lesson, and LED screens to project the videos onto a classroom screen. After six months, the intervention improved the performance of learners on independent tests of math and science by 0.19 and 0.24 SDs, respectively but had no discernible effect on the math and science section of Punjab’s high-stakes exams.

One study suggests that approaches that are far less technologically sophisticated can also improve learning outcomes—especially, if the business-as-usual instruction is of low quality. For example, Naslund-Hadley, Parker, and Hernandez-Agramonte (2014) evaluated a preschool math program in Cordillera, Paraguay that used audio segments and written materials four days per week for an hour per day during the school day. After five months, the intervention improved math scores by 0.16 SDs, narrowing gaps between low- and high-achieving learners, and between those with and without educators with formal training in early childhood education.

Yet, the integration of prerecorded material into regular instruction has not always been successful. For example, de Barros (2020) evaluated an intervention that combined instructional videos for math and science with infrastructure upgrades (e.g., two “smart” classrooms, two TVs, and two tablets), printed workbooks for students, and in-service training for educators of learners in grades 9 and 10 in Haryana, India (all materials were mapped onto the official curriculum). After 11 months, the intervention negatively impacted math achievement (by 0.08 SDs) and had no effect on science (with respect to business as usual classes). It reduced the share of lesson time that educators devoted to instruction and negatively impacted an index of instructional quality. Likewise, Seo (2017) evaluated several combinations of infrastructure (solar lights and TVs) and prerecorded videos (in English and/or bilingual) for grade 11 students in northern Tanzania and found that none of the variants improved student learning, even when the videos were used. The study reports effects from the infrastructure component across variants, but as others have noted (Muralidharan, Romero, & Wüthrich, 2019), this approach to estimating impact is problematic.

A very similar intervention delivered after school hours, however, had sizeable effects on learners’ basic skills. Chiplunkar, Dhar, and Nagesh (2020) evaluated an initiative in Chennai (the capital city of the state of Tamil Nadu, India) delivered by the same organization as above that combined short videos that explained key concepts in math and science with worksheets, facilitator-led instruction, small groups for peer-to-peer learning, and occasional career counseling and guidance for grade 9 students. These lessons took place after school for one hour, five times a week. After 10 months, it had large effects on learners’ achievement as measured by tests of basic skills in math and reading, but no effect on a standardized high-stakes test in grade 10 or socio-emotional skills (e.g., teamwork, decisionmaking, and communication).

Drawing general lessons from this body of research is challenging for at least two reasons. First, all of the studies above have evaluated the impact of prerecorded lessons combined with several other components (e.g., hardware, print materials, or other activities). Therefore, it is possible that the effects found are due to these additional components, rather than to the recordings themselves, or to the interaction between the two (see Muralidharan, 2017 for a discussion of the challenges of interpreting “bundled” interventions). Second, while these studies evaluate some type of prerecorded lessons, none examines the content of such lessons. Thus, it seems entirely plausible that the direction and magnitude of the effects depends largely on the quality of the recordings (e.g., the expertise of the educator recording it, the amount of preparation that went into planning the recording, and its alignment with best teaching practices).

These studies also raise three important questions worth exploring in future research. One of them is why none of the interventions discussed above had effects on high-stakes exams, even if their materials are typically mapped onto the official curriculum. It is possible that the official curricula are simply too challenging for learners in these settings, who are several grade levels behind expectations and who often need to reinforce basic skills (see Pritchett & Beatty, 2015). Another question is whether these interventions have long-term effects on teaching practices. It seems plausible that, if these interventions are deployed in contexts with low teaching quality, educators may learn something from watching the videos or listening to the recordings with learners. Yet another question is whether these interventions make it easier for schools to deliver instruction to learners whose native language is other than the official medium of instruction.

Distance education

Technology can also allow learners living in remote areas to access education. The evidence on these initiatives is encouraging. For example, Johnston and Ksoll (2017) evaluated a program that broadcasted live instruction via satellite to rural primary school students in the Volta and Greater Accra regions of Ghana. For this purpose, the program also equipped classrooms with the technology needed to connect to a studio in Accra, including solar panels, a satellite modem, a projector, a webcam, microphones, and a computer with interactive software. After two years, the intervention improved the numeracy scores of students in grades 2 through 4, and some foundational literacy tasks, but it had no effect on attendance or classroom time devoted to instruction, as captured by school visits. The authors interpreted these results as suggesting that the gains in achievement may be due to improving the quality of instruction that children received (as opposed to increased instructional time). Naik, Chitre, Bhalla, and Rajan (2019) evaluated a similar program in the Indian state of Karnataka and also found positive effects on learning outcomes, but it is not clear whether those effects are due to the program or due to differences in the groups of students they compared to estimate the impact of the initiative.

In one context (Mexico), this type of distance education had positive long-term effects. Navarro-Sola (2019) took advantage of the staggered rollout of the telesecundarias (i.e., middle schools with lessons broadcasted through satellite TV) in 1968 to estimate its impact. The policy had short-term effects on students’ enrollment in school: For every telesecundaria per 50 children, 10 students enrolled in middle school and two pursued further education. It also had a long-term influence on the educational and employment trajectory of its graduates. Each additional year of education induced by the policy increased average income by nearly 18 percent. This effect was attributable to more graduates entering the labor force and shifting from agriculture and the informal sector. Similarly, Fabregas (2019) leveraged a later expansion of this policy in 1993 and found that each additional telesecundaria per 1,000 adolescents led to an average increase of 0.2 years of education, and a decline in fertility for women, but no conclusive evidence of long-term effects on labor market outcomes.

It is crucial to interpret these results keeping in mind the settings where the interventions were implemented. As we mention above, part of the reason why they have proven effective is that the “counterfactual” conditions for learning (i.e., what would have happened to learners in the absence of such programs) was either to not have access to schooling or to be exposed to low-quality instruction. School systems interested in taking up similar interventions should assess the extent to which their learners (or parts of their learner population) find themselves in similar conditions to the subjects of the studies above. This illustrates the importance of assessing the needs of a system before reviewing the evidence.

Preloaded hardware

Technology also seems well positioned to disseminate educational materials. Specifically, hardware (e.g., desktop computers, laptops, or tablets) could also help deliver educational software (e.g., word processing, reference texts, and/or games). In theory, these materials could not only undergo a quality assurance review (e.g., by curriculum specialists and educators), but also draw on the interactions with learners for adjustments (e.g., identifying areas needing reinforcement) and enable interactions between learners and educators.

In practice, however, most initiatives that have provided learners with free computers, laptops, and netbooks do not leverage any of the opportunities mentioned above. Instead, they install a standard set of educational materials and hope that learners find them helpful enough to take them up on their own. Students rarely do so, and instead use the laptops for recreational purposes—often, to the detriment of their learning (see, e.g., Malamud & Pop-Eleches, 2011). In fact, free netbook initiatives have not only consistently failed to improve academic achievement in math or language (e.g., Cristia et al., 2017), but they have had no impact on learners’ general computer skills (e.g., Beuermann et al., 2015). Some of these initiatives have had small impacts on cognitive skills, but the mechanisms through which those effects occurred remains unclear.

To our knowledge, the only successful deployment of a free laptop initiative was one in which a team of researchers equipped the computers with remedial software. Mo et al. (2013) evaluated a version of the One Laptop per Child (OLPC) program for grade 3 students in migrant schools in Beijing, China in which the laptops were loaded with a remedial software mapped onto the national curriculum for math (similar to the software products that we discuss under “practice exercises” below). After nine months, the program improved math achievement by 0.17 SDs and computer skills by 0.33 SDs. If a school system decides to invest in free laptops, this study suggests that the quality of the software on the laptops is crucial.

To date, however, the evidence suggests that children do not learn more from interacting with laptops than they do from textbooks. For example, Bando, Gallego, Gertler, and Romero (2016) compared the effect of free laptop and textbook provision in 271 elementary schools in disadvantaged areas of Honduras. After seven months, students in grades 3 and 6 who had received the laptops performed on par with those who had received the textbooks in math and language. Further, even if textbooks essentially become obsolete at the end of each school year, whereas laptops can be reloaded with new materials for each year, the costs of laptop provision (not just the hardware, but also the technical assistance, Internet, and training associated with it) are not yet low enough to make them a more cost-effective way of delivering content to learners.

Evidence on the provision of tablets equipped with software is encouraging but limited. For example, de Hoop et al. (2020) evaluated a composite intervention for first grade students in Zambia’s Eastern Province that combined infrastructure (electricity via solar power), hardware (projectors and tablets), and educational materials (lesson plans for educators and interactive lessons for learners, both loaded onto the tablets and mapped onto the official Zambian curriculum). After 14 months, the intervention had improved student early-grade reading by 0.4 SDs, oral vocabulary scores by 0.25 SDs, and early-grade math by 0.22 SDs. It also improved students’ achievement by 0.16 on a locally developed assessment. The multifaceted nature of the program, however, makes it challenging to identify the components that are driving the positive effects. Pitchford (2015) evaluated an intervention that provided tablets equipped with educational “apps,” to be used for 30 minutes per day for two months to develop early math skills among students in grades 1 through 3 in Lilongwe, Malawi. The evaluation found positive impacts in math achievement, but the main study limitation is that it was conducted in a single school.

Facilitating differentiated instruction

Another way in which technology may improve educational outcomes is by facilitating the delivery of differentiated or individualized instruction. Most developing countries massively expanded access to schooling in recent decades by building new schools and making education more affordable, both by defraying direct costs, as well as compensating for opportunity costs (Duflo, 2001; World Bank, 2018). These initiatives have not only rapidly increased the number of learners enrolled in school, but have also increased the variability in learner’ preparation for schooling. Consequently, a large number of learners perform well below grade-based curricular expectations (see, e.g., Duflo, Dupas, & Kremer, 2011; Pritchett & Beatty, 2015). These learners are unlikely to get much from “one-size-fits-all” instruction, in which a single educator delivers instruction deemed appropriate for the middle (or top) of the achievement distribution (Banerjee & Duflo, 2011). Technology could potentially help these learners by providing them with: (a) instruction and opportunities for practice that adjust to the level and pace of preparation of each individual (known as “computer-adaptive learning” (CAL)); or (b) live, one-on-one tutoring.

Computer-adaptive learning

One of the main comparative advantages of technology is its ability to diagnose students’ initial learning levels and assign students to instruction and exercises of appropriate difficulty. No individual educator—no matter how talented—can be expected to provide individualized instruction to all learners in his/her class simultaneously . In this respect, technology is uniquely positioned to complement traditional teaching. This use of technology could help learners master basic skills and help them get more out of schooling.

Although many software products evaluated in recent years have been categorized as CAL, many rely on a relatively coarse level of differentiation at an initial stage (e.g., a diagnostic test) without further differentiation. We discuss these initiatives under the category of “increasing opportunities for practice” below. CAL initiatives complement an initial diagnostic with dynamic adaptation (i.e., at each response or set of responses from learners) to adjust both the initial level of difficulty and rate at which it increases or decreases, depending on whether learners’ responses are correct or incorrect.

Existing evidence on this specific type of programs is highly promising. Most famously, Banerjee et al. (2007) evaluated CAL software in Vadodara, in the Indian state of Gujarat, in which grade 4 students were offered two hours of shared computer time per week before and after school, during which they played games that involved solving math problems. The level of difficulty of such problems adjusted based on students’ answers. This program improved math achievement by 0.35 and 0.47 SDs after one and two years of implementation, respectively. Consistent with the promise of personalized learning, the software improved achievement for all students. In fact, one year after the end of the program, students assigned to the program still performed 0.1 SDs better than those assigned to a business as usual condition. More recently, Muralidharan, et al. (2019) evaluated a “blended learning” initiative in which students in grades 4 through 9 in Delhi, India received 45 minutes of interaction with CAL software for math and language, and 45 minutes of small group instruction before or after going to school. After only 4.5 months, the program improved achievement by 0.37 SDs in math and 0.23 SDs in Hindi. While all learners benefited from the program in absolute terms, the lowest performing learners benefited the most in relative terms, since they were learning very little in school.

We see two important limitations from this body of research. First, to our knowledge, none of these initiatives has been evaluated when implemented during the school day. Therefore, it is not possible to distinguish the effect of the adaptive software from that of additional instructional time. Second, given that most of these programs were facilitated by local instructors, attempts to distinguish the effect of the software from that of the instructors has been mostly based on noncausal evidence. A frontier challenge in this body of research is to understand whether CAL software can increase the effectiveness of school-based instruction by substituting part of the regularly scheduled time for math and language instruction.

Live one-on-one tutoring

Recent improvements in the speed and quality of videoconferencing, as well as in the connectivity of remote areas, have enabled yet another way in which technology can help personalization: live (i.e., real-time) one-on-one tutoring. While the evidence on in-person tutoring is scarce in developing countries, existing studies suggest that this approach works best when it is used to personalize instruction (see, e.g., Banerjee et al., 2007; Banerji, Berry, & Shotland, 2015; Cabezas, Cuesta, & Gallego, 2011).

There are almost no studies on the impact of online tutoring—possibly, due to the lack of hardware and Internet connectivity in low- and middle-income countries. One exception is Chemin and Oledan (2020)’s recent evaluation of an online tutoring program for grade 6 students in Kianyaga, Kenya to learn English from volunteers from a Canadian university via Skype ( videoconferencing software) for one hour per week after school. After 10 months, program beneficiaries performed 0.22 SDs better in a test of oral comprehension, improved their comfort using technology for learning, and became more willing to engage in cross-cultural communication. Importantly, while the tutoring sessions used the official English textbooks and sought in part to help learners with their homework, tutors were trained on several strategies to teach to each learner’s individual level of preparation, focusing on basic skills if necessary. To our knowledge, similar initiatives within a country have not yet been rigorously evaluated.

Expanding opportunities for practice

A third way in which technology may improve the quality of education is by providing learners with additional opportunities for practice. In many developing countries, lesson time is primarily devoted to lectures, in which the educator explains the topic and the learners passively copy explanations from the blackboard. This setup leaves little time for in-class practice. Consequently, learners who did not understand the explanation of the material during lecture struggle when they have to solve homework assignments on their own. Technology could potentially address this problem by allowing learners to review topics at their own pace.

Practice exercises

Technology can help learners get more out of traditional instruction by providing them with opportunities to implement what they learn in class. This approach could, in theory, allow some learners to anchor their understanding of the material through trial and error (i.e., by realizing what they may not have understood correctly during lecture and by getting better acquainted with special cases not covered in-depth in class).

Existing evidence on practice exercises reflects both the promise and the limitations of this use of technology in developing countries. For example, Lai et al. (2013) evaluated a program in Shaanxi, China where students in grades 3 and 5 were required to attend two 40-minute remedial sessions per week in which they first watched videos that reviewed the material that had been introduced in their math lessons that week and then played games to practice the skills introduced in the video. After four months, the intervention improved math achievement by 0.12 SDs. Many other evaluations of comparable interventions have found similar small-to-moderate results (see, e.g., Lai, Luo, Zhang, Huang, & Rozelle, 2015; Lai et al., 2012; Mo et al., 2015; Pitchford, 2015). These effects, however, have been consistently smaller than those of initiatives that adjust the difficulty of the material based on students’ performance (e.g., Banerjee et al., 2007; Muralidharan, et al., 2019). We hypothesize that these programs do little for learners who perform several grade levels behind curricular expectations, and who would benefit more from a review of foundational concepts from earlier grades.

We see two important limitations from this research. First, most initiatives that have been evaluated thus far combine instructional videos with practice exercises, so it is hard to know whether their effects are driven by the former or the latter. In fact, the program in China described above allowed learners to ask their peers whenever they did not understand a difficult concept, so it potentially also captured the effect of peer-to-peer collaboration. To our knowledge, no studies have addressed this gap in the evidence.

Second, most of these programs are implemented before or after school, so we cannot distinguish the effect of additional instructional time from that of the actual opportunity for practice. The importance of this question was first highlighted by Linden (2008), who compared two delivery mechanisms for game-based remedial math software for students in grades 2 and 3 in a network of schools run by a nonprofit organization in Gujarat, India: one in which students interacted with the software during the school day and another one in which students interacted with the software before or after school (in both cases, for three hours per day). After a year, the first version of the program had negatively impacted students’ math achievement by 0.57 SDs and the second one had a null effect. This study suggested that computer-assisted learning is a poor substitute for regular instruction when it is of high quality, as was the case in this well-functioning private network of schools.

In recent years, several studies have sought to remedy this shortcoming. Mo et al. (2014) were among the first to evaluate practice exercises delivered during the school day. They evaluated an initiative in Shaanxi, China in which students in grades 3 and 5 were required to interact with the software similar to the one in Lai et al. (2013) for two 40-minute sessions per week. The main limitation of this study, however, is that the program was delivered during regularly scheduled computer lessons, so it could not determine the impact of substituting regular math instruction. Similarly, Mo et al. (2020) evaluated a self-paced and a teacher-directed version of a similar program for English for grade 5 students in Qinghai, China. Yet, the key shortcoming of this study is that the teacher-directed version added several components that may also influence achievement, such as increased opportunities for teachers to provide students with personalized assistance when they struggled with the material. Ma, Fairlie, Loyalka, and Rozelle (2020) compared the effectiveness of additional time-delivered remedial instruction for students in grades 4 to 6 in Shaanxi, China through either computer-assisted software or using workbooks. This study indicates whether additional instructional time is more effective when using technology, but it does not address the question of whether school systems may improve the productivity of instructional time during the school day by substituting educator-led with computer-assisted instruction.

Increasing learner engagement

Another way in which technology may improve education is by increasing learners’ engagement with the material. In many school systems, regular “chalk and talk” instruction prioritizes time for educators’ exposition over opportunities for learners to ask clarifying questions and/or contribute to class discussions. This, combined with the fact that many developing-country classrooms include a very large number of learners (see, e.g., Angrist & Lavy, 1999; Duflo, Dupas, & Kremer, 2015), may partially explain why the majority of those students are several grade levels behind curricular expectations (e.g., Muralidharan, et al., 2019; Muralidharan & Zieleniak, 2014; Pritchett & Beatty, 2015). Technology could potentially address these challenges by: (a) using video tutorials for self-paced learning and (b) presenting exercises as games and/or gamifying practice.

Video tutorials

Technology can potentially increase learner effort and understanding of the material by finding new and more engaging ways to deliver it. Video tutorials designed for self-paced learning—as opposed to videos for whole class instruction, which we discuss under the category of “prerecorded lessons” above—can increase learner effort in multiple ways, including: allowing learners to focus on topics with which they need more help, letting them correct errors and misconceptions on their own, and making the material appealing through visual aids. They can increase understanding by breaking the material into smaller units and tackling common misconceptions.

In spite of the popularity of instructional videos, there is relatively little evidence on their effectiveness. Yet, two recent evaluations of different versions of the Khan Academy portal, which mainly relies on instructional videos, offer some insight into their impact. First, Ferman, Finamor, and Lima (2019) evaluated an initiative in 157 public primary and middle schools in five cities in Brazil in which the teachers of students in grades 5 and 9 were taken to the computer lab to learn math from the platform for 50 minutes per week. The authors found that, while the intervention slightly improved learners’ attitudes toward math, these changes did not translate into better performance in this subject. The authors hypothesized that this could be due to the reduction of teacher-led math instruction.

More recently, Büchel, Jakob, Kühnhanss, Steffen, and Brunetti (2020) evaluated an after-school, offline delivery of the Khan Academy portal in grades 3 through 6 in 302 primary schools in Morazán, El Salvador. Students in this study received 90 minutes per week of additional math instruction (effectively nearly doubling total math instruction per week) through teacher-led regular lessons, teacher-assisted Khan Academy lessons, or similar lessons assisted by technical supervisors with no content expertise. (Importantly, the first group provided differentiated instruction, which is not the norm in Salvadorian schools). All three groups outperformed both schools without any additional lessons and classrooms without additional lessons in the same schools as the program. The teacher-assisted Khan Academy lessons performed 0.24 SDs better, the supervisor-led lessons 0.22 SDs better, and the teacher-led regular lessons 0.15 SDs better, but the authors could not determine whether the effects across versions were different.

Together, these studies suggest that instructional videos work best when provided as a complement to, rather than as a substitute for, regular instruction. Yet, the main limitation of these studies is the multifaceted nature of the Khan Academy portal, which also includes other components found to positively improve learner achievement, such as differentiated instruction by students’ learning levels. While the software does not provide the type of personalization discussed above, learners are asked to take a placement test and, based on their score, educators assign them different work. Therefore, it is not clear from these studies whether the effects from Khan Academy are driven by its instructional videos or to the software’s ability to provide differentiated activities when combined with placement tests.

Games and gamification

Technology can also increase learner engagement by presenting exercises as games and/or by encouraging learner to play and compete with others (e.g., using leaderboards and rewards)—an approach known as “gamification.” Both approaches can increase learner motivation and effort by presenting learners with entertaining opportunities for practice and by leveraging peers as commitment devices.

There are very few studies on the effects of games and gamification in low- and middle-income countries. Recently, Araya, Arias Ortiz, Bottan, and Cristia (2019) evaluated an initiative in which grade 4 students in Santiago, Chile were required to participate in two 90-minute sessions per week during the school day with instructional math software featuring individual and group competitions (e.g., tracking each learner’s standing in his/her class and tournaments between sections). After nine months, the program led to improvements of 0.27 SDs in the national student assessment in math (it had no spillover effects on reading). However, it had mixed effects on non-academic outcomes. Specifically, the program increased learners’ willingness to use computers to learn math, but, at the same time, increased their anxiety toward math and negatively impacted learners’ willingness to collaborate with peers. Finally, given that one of the weekly sessions replaced regular math instruction and the other one represented additional math instructional time, it is not clear whether the academic effects of the program are driven by the software or the additional time devoted to learning math.

The prognosis:

How can school systems adopt interventions that match their needs.

Here are five specific and sequential guidelines for decisionmakers to realize the potential of education technology to accelerate student learning.

1. Take stock of how your current schools, educators, and learners are engaging with technology .

Carry out a short in-school survey to understand the current practices and potential barriers to adoption of technology (we have included suggested survey instruments in the Appendices); use this information in your decisionmaking process. For example, we learned from conversations with current and former ministers of education from various developing regions that a common limitation to technology use is regulations that hold school leaders accountable for damages to or losses of devices. Another common barrier is lack of access to electricity and Internet, or even the availability of sufficient outlets for charging devices in classrooms. Understanding basic infrastructure and regulatory limitations to the use of education technology is a first necessary step. But addressing these limitations will not guarantee that introducing or expanding technology use will accelerate learning. The next steps are thus necessary.

“In Africa, the biggest limit is connectivity. Fiber is expensive, and we don’t have it everywhere. The continent is creating a digital divide between cities, where there is fiber, and the rural areas.  The [Ghanaian] administration put in schools offline/online technologies with books, assessment tools, and open source materials. In deploying this, we are finding that again, teachers are unfamiliar with it. And existing policies prohibit students to bring their own tablets or cell phones. The easiest way to do it would have been to let everyone bring their own device. But policies are against it.” H.E. Matthew Prempeh, Minister of Education of Ghana, on the need to understand the local context.

2. Consider how the introduction of technology may affect the interactions among learners, educators, and content .

Our review of the evidence indicates that technology may accelerate student learning when it is used to scale up access to quality content, facilitate differentiated instruction, increase opportunities for practice, or when it increases learner engagement. For example, will adding electronic whiteboards to classrooms facilitate access to more quality content or differentiated instruction? Or will these expensive boards be used in the same way as the old chalkboards? Will providing one device (laptop or tablet) to each learner facilitate access to more and better content, or offer students more opportunities to practice and learn? Solely introducing technology in classrooms without additional changes is unlikely to lead to improved learning and may be quite costly. If you cannot clearly identify how the interactions among the three key components of the instructional core (educators, learners, and content) may change after the introduction of technology, then it is probably not a good idea to make the investment. See Appendix A for guidance on the types of questions to ask.

3. Once decisionmakers have a clear idea of how education technology can help accelerate student learning in a specific context, it is important to define clear objectives and goals and establish ways to regularly assess progress and make course corrections in a timely manner .

For instance, is the education technology expected to ensure that learners in early grades excel in foundational skills—basic literacy and numeracy—by age 10? If so, will the technology provide quality reading and math materials, ample opportunities to practice, and engaging materials such as videos or games? Will educators be empowered to use these materials in new ways? And how will progress be measured and adjusted?

4. How this kind of reform is approached can matter immensely for its success.

It is easy to nod to issues of “implementation,” but that needs to be more than rhetorical. Keep in mind that good use of education technology requires thinking about how it will affect learners, educators, and parents. After all, giving learners digital devices will make no difference if they get broken, are stolen, or go unused. Classroom technologies only matter if educators feel comfortable putting them to work. Since good technology is generally about complementing or amplifying what educators and learners already do, it is almost always a mistake to mandate programs from on high. It is vital that technology be adopted with the input of educators and families and with attention to how it will be used. If technology goes unused or if educators use it ineffectually, the results will disappoint—no matter the virtuosity of the technology. Indeed, unused education technology can be an unnecessary expenditure for cash-strapped education systems. This is why surveying context, listening to voices in the field, examining how technology is used, and planning for course correction is essential.

5. It is essential to communicate with a range of stakeholders, including educators, school leaders, parents, and learners .

Technology can feel alien in schools, confuse parents and (especially) older educators, or become an alluring distraction. Good communication can help address all of these risks. Taking care to listen to educators and families can help ensure that programs are informed by their needs and concerns. At the same time, deliberately and consistently explaining what technology is and is not supposed to do, how it can be most effectively used, and the ways in which it can make it more likely that programs work as intended. For instance, if teachers fear that technology is intended to reduce the need for educators, they will tend to be hostile; if they believe that it is intended to assist them in their work, they will be more receptive. Absent effective communication, it is easy for programs to “fail” not because of the technology but because of how it was used. In short, past experience in rolling out education programs indicates that it is as important to have a strong intervention design as it is to have a solid plan to socialize it among stakeholders.

smart education essay

Beyond reopening: A leapfrog moment to transform education?

On September 14, the Center for Universal Education (CUE) will host a webinar to discuss strategies, including around the effective use of education technology, for ensuring resilient schools in the long term and to launch a new education technology playbook “Realizing the promise: How can education technology improve learning for all?”

file-pdf Full Playbook – Realizing the promise: How can education technology improve learning for all? file-pdf References file-pdf Appendix A – Instruments to assess availability and use of technology file-pdf Appendix B – List of reviewed studies file-pdf Appendix C – How may technology affect interactions among students, teachers, and content?

About the Authors

Alejandro j. ganimian, emiliana vegas, frederick m. hess.

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  • Kadir Alpaslan Demir   ORCID: orcid.org/0000-0002-8304-6324 1  

Smart Learning Environments volume  8 , Article number:  29 ( 2021 ) Cite this article

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Advances in information technologies present opportunities for novel approaches, methods, and tools for new or improved education and training practices. Furthermore, these technologies are enabling a shift in the education paradigm. Based on an investigation of a wide range of information technologies supporting smart education, we developed a Smart Education Framework. The framework conceptually structures the information technologies in a layered architecture. We also developed a smart education design approach based on the framework. Furthermore, we show how to use the framework and design approach to develop a specific course or lecture design. To validate the smart education framework, we examined smart education systems reported in the literature. To identify smart education systems, we conducted a systematic literature search. The literature search results show that the smart education framework has the ability to describe smart education systems. This study contributes to the current literature with a smart education framework. The smart education framework will guide future smart education system designs.

Introduction

Recent advances in information technologies are affecting our education and training approaches, methods, practices, and tools (Kaufmann, 2003 ; Palloff & Pratt, 2002 ; Shoikova et al., 2017 ; Zhu et al., 2016a , 2016b ). Increasing internet speeds and storage areas together with the advances in cloud computing technologies, making the information available to everybody, from everywhere, at all times. Traditional training and education methodologies, in which the instructor explains the subject in the classroom and the students complete the exercises at home, are replaced by new learning approaches such as distant learning, mobile learning (m-learning), personalized learning, flipped and blended learning, social collaborative learning, game-based learning, etc. (Erkollar & Oberer, 2016 ; Güzer & Caner, 2014 ; Knight & Wood, 2005 ; Lage et al., 2000 ; Oberer, 2016 ; Prince, 2004 ; Rakow, 2007 ; Strayer, 2012 ). Information and communication technologies are creating the potential for more self-paced, interactive, and personalized learning. As new information technologies are introduced, we are moving from traditional education towards smart education (Bajaj & Sharma, 2018 ; Zhu et al., 2016b ).

The students in the twenty-first century are different than the students of the past. Oblinger and Oblinger ( 2005 ) identify the generation born after 1982 as net generation or “Millennials”. Unlike many prior generations, this generation grew up with technology. Some of the characteristics of college-aged millennials are listed in Table 1 .

Technology has significant impacts on society. Furthermore, technology is changing faster than ever. Technological innovations impact our children as well. As their characteristics indicate that millennials are quite different than non-millennials. The instructors dealing with millennials have to be aware of these characteristics. The current learning environments have to be redesigned based on the strengths and weaknesses of these students. We need learning environments that are more suitable for the current and following generations. The smart education vision should help to achieve this requirement and overcome the shortcomings of the current education methods and systems. To realize the smart education vision, we need to develop new or improved teaching and learning techniques along with a coherently designed set of educational information and communication technologies. Smart education frameworks are essential for smart education implementations. In this work, we developed such a smart education framework. This framework has a layered structure. New or improved teaching methods are at the core layer. We categorize educational information and communication technologies into three categories. These are essential/transforming technologies, enriching technologies, and supportive technologies. These categories form the layers of the smart education framework. In the following sections, we explain the framework and how the framework is used for smart education designs. We also provide two examples of smart education designs. To validate the framework, we conducted a systematic literature review investigating smart education system (SES) implementations and proposals. Our analysis shows that the smart education framework has the capability to describe all identified SESs as the result of the literature search.

In “ Smart education ” section, we discuss the concept of smart education. Next, we list trending educational technologies enabling smart education. In “ Smart education framework ” section, we present a smart education framework that conceptually structures the technologies in a layered architecture. “ Smart education design ” section describes a smart education design approach with examples. In “ Validate the framework ” section, we present the findings of our systematic literature search to validate the framework. Finally, we present discussions and conclusions.

  • Smart education

We define smart education as the “effective and coherent use of information and communication technologies to reach a learning outcome using a suitable pedagogical approach”. An earlier definition provided by Zhu and He ( 2012 ) is that “the essence of smarter education is to create intelligent environments by using smart technologies, so that smart pedagogies can be facilitated as to provide personalized learning services and empower learners to develop talents of wisdom that have better value orientation, higher thinking quality, and stronger conduct ability”. Another definition of smart education is “the concept of learning in the digital age” (Zhu et al., 2016b ). According to Bajaj and Sharma ( 2018 ), smart education is “about providing personalized learning, anywhere and anytime. Moreover, they state that smart education is about taking learning outside the traditional classrooms; and is an activity that can be done anywhere and anytime”. Jang defines smart education as “an educational system that allows students to learn by using up-to-date technology and it enables students to study with various materials based on their aptitudes and intellectual levels” (Jang, 2014 ). Smart learning environments, sometimes used to refer to smart education, “represent a new wave of educational systems, involving an effective and efficient interplay of pedagogy, technology and their fusion towards the betterment of learning processes” (Shoikova et al., 2017 ). Notice that smart education is not just about technology. It is also about new teaching and learning approaches.

Several countries started smart education initiatives or programs as listed in Table 2 . A holistic concept of smart education in Korea includes Self-directed, Adaptive, Motivated, Resource-Free, Technology embedded education (Kim et al., 2013 ). Standards are also essential for the development of smart education since it heavily relies on information and communication technologies (Hoel & Mason, 2018 ). International Standards Organization (ISO) has a group (ISO/IEC JTC 1/SC 36) to support the development of standards for “Information technology for learning, education, and training”. 40 standards were developed under the direct responsibility of the group and more standards are in development (International Standards Organization 2020 ). International associations such as the International Association of Smart Learning Environments are being formed to support the development of smart learning environments ( http://iasle.net/ ). Various telecommunications and information technology companies started to invest in the education business. Technology giants such as IBM ( 2009 ) and Samsung ( 2013 ) are developing information technology architectures and solutions for smart education systems.

Alimisis ( 2013 ) criticizes that “most uses of technologies in schools today do not support the 21st-century learning skills. In many cases, new technologies are simply reinforcing old ways of teaching and learning.” While smart education requires the use of information technologies, we believe smart education also encompasses a paradigm shift from traditional education and training practices to more advanced approaches and practices in line with the digital age. Therefore, new or improved learning and teaching approaches are among the essential elements of smart education. Our view of essential elements of smart education differs from the view of Zhu and his colleagues. Our view is presented in Fig.  1 .

figure 1

Essential elements of smart education

The characteristics of the essential elements will not be the same as in traditional education. They will evolve as smart education evolves. We briefly list and discuss the characteristics of millennials, in other words, learners of the digital age, in the previous section. The evolving characteristics of other essential elements require a thorough investigation.

In a smart education environment, the learner should be autonomous and collaborative in addition to being an efficient technology user. Instructional design is important both in traditional education and smart education. Today, direct instruction is the predominant teaching method. However, in modern approaches, the facilitator role of the educator is becoming significant. One notable role of educators in smart education is technological support. The teachers/educators should also be able to provide technical support to students if needed. Note that just like learners, educators should be effective technology users. In a smart education environment, connectivity is an important distinguishing characteristic of the educational technology supporting education (Klopfer et al., 2002 ). In traditional face-to-face teaching, connectivity is often limited. Technologies such as web 2.0 provide enhanced connectivity between the learner and teacher. Ubiquity is as important as connectivity. Internet and mobile technologies provide ubiquitous access to information and knowledge. Ubiquitous educational technologies provide significant opportunities to geographically disadvantaged students. Various studies indicate that the learning process may vary depending on the learner (El Janati et al., 2018 ). Therefore, more effective learning can be achieved via personalized learning. Adaptive learning system research is gaining attention in recent years. According to the International Association of Smart Learning Environments, a smart learning environment can be considered “smart when it makes use of adaptive technologies or when it is designed to include innovative features and capabilities that improve understanding and performance.” Smart education also offers new opportunities for providing personalized education and training to people with disabilities (El Janati et al., 2018 ).

Enabling information technologies for smart education

Information technologies are advancing at unprecedented speeds. New technologies, devices, applications, tools, and most importantly new ways of thinking are being introduced every day. Naturally, most of these have effects on educational and training practices at different levels. Table 3 lists some of the main information technologies enabling smart education.

There will be other technologies that support smart education. There is abundant literature on these technologies. Discussing all these information technologies is the subject of a review paper rather than a research paper.

Related work

In this section, we discuss various existing smart education or learning frameworks. Furthermore, we compare these with each other.

Zhu and his colleagues developed a smart education framework (Zhu et al., 2016a ). The three essential elements in the smart education environment are learner presence, teaching presence, and technological presence (Zhu et al., 2016a ). Zhu and his colleagues’ smart education framework focuses on the elements of smart education. This framework is important in the sense that it highlights the elements, their characteristics, and their role in smart education.

Arab League Educational, Cultural and Scientific Organization (ALECSO) is an organization working within the Arab League consisting of 22 Arab countries (Jemni & Khribi, 2017 ). ALECSO coordinates and contributes to several projects and activities in the Arab region to promote education, culture, and science. ALECSO ICT Department proposed a framework for smart learning. This smart learning framework (Jemni & Khribi, 2017 ) has three key dimensions: open learning, mobile technology, and cloud computing. In each dimension, several projects are being developed. The ALECSO mobile initiative includes ALECSO Apps Store, ALECSO Apps Editor, ALECSO Apps Award, ALECSO Apps training programs. ALECSO with support from the International Telecommunication Union (ITU) Arab regional office aims at promoting cloud computing in the use of education. Therefore, they start the ALECSO Cloud Computing Project. ALECSO promotes Open Learning with several projects and initiatives. Open Learning effort includes Open Book Initiative, collaboration on regional and international Open Educational Resources (OER) activities, ALECSO OER project, ALECSO Massive Open Online Courses (MOOCs) Project. ALECSO’s smart learning framework is actually a combination of projects and activities to promote the use of ICT’s in the educational domain.

Bajaj and Sharma proposed a smart education framework stressing the importance of adaptive learning in smart education (Bajaj & Sharma, 2018 ). According to them, adaptivity is an essential need in today’s educational environment. The goal of adaptive educational systems is to customize the educational content and learning paths of students. They proposed a framework in which students interact with a virtual teacher on the cloud and based on various learning theories and using artificial intelligence technology, the system generates personalized content and learning paths. Bajaj and Sharma’s Smart Education Framework proposal has a technology view with a focus on adaptive learning.

The smart education framework developed within this study focuses on the role of various information and communication technologies in smart education. Furthermore, it stresses the importance of new or improved teaching and learning approaches. The framework highlights the need for a coherent combination of ICT technologies with appropriate teaching and learning approaches.

All these smart education or learning frameworks focus on different dimensions of smart education. Zhu and his colleagues’ smart education framework focuses on smart education elements. ALECSO’s smart learning framework focus on the use of open education resources in combination with mobile and computing technology with a number of projects. The smart education framework proposed in this study focus on the coherent design of educational technologies and with appropriate teaching and learning approaches. These frameworks complement each other. For example, Zhu and his colleagues’ framework provides a smart education essential elements view, ALECSO’s framework provides a project-based view, our framework provides a generic smart education design view. These frameworks are not competing with each other but they provide different perspectives. They focus on different aspects of smart education. As a result, these frameworks help develop and improve the concept of smart education. Furthermore, they provide the necessary conceptual infrastructure for smart education design and utilization.

Table 4 presents a comparison of smart education and learning frameworks.’

Based on an investigation of a wide range of information technologies supporting smart education, we developed a smart education framework as presented in Fig.  2 . The framework is constructed in a layered architecture. New or improved teaching methods are at the core of smart education. The outer layers support the core layer in the realization of smart education. The purpose of each layer is described.

figure 2

a Smart education framework layers. b Smart education framework technologies

New or improved learning/teaching approaches (core layer)

In the 2018 US–China Smart Education Conference, one of the common themes was the structure of education is changing. These changes include “integrating new technologies, new pedagogical approaches, and new learning spaces and places” (Spector, 2018 ). We believe new or improved learning/teaching methods are at the essence of smart education. These new or improved teaching methods include approaches such as personalized learning, flipped learning, blended teaching, game-based learning, case-based learning, etc. The use of traditional teaching and learning approaches supported by information technologies will not be adequate for smart education. Consider the use of computers in education and training. Computers are among the most influential innovations of the century. However, they did not change the essence of teaching or improve education dramatically yet. Thus, merely having a particular information technology in an educational setting does not create a paradigm shift for education. As a result, new or improved teaching methods are at the center of smart education.

Essential/transforming technologies (second layer)

These technologies are essential for smart education and they transform traditional education into smart education combined with new or improved teaching methods. These technologies are learning management systems, smart/ambient intelligent classrooms, and virtual classrooms. Note that we combined smart classrooms with ambient intelligence since they are closely related. Smart classrooms embody the concept of ambient intelligence. Therefore, the terms “smart classrooms” and “ambient intelligent classrooms” may be considered synonyms. These technologies are required for the realization of smart classrooms. They form the necessary infrastructure for the inclusion of enriching and supporting information technologies.

In the figure, we draw a line between smart/ambient intelligent/virtual classrooms and learning management systems. This line also extends to the upper layer of enriching technologies. The line in the upper layer divides the technologies into two. One set of technologies consisting of learning analytics, educational data mining, e-books, and interactive books, and academic tubes enrich the learning management systems. The other set of technologies including virtual environments, augmented reality, educational robots, and serious games mainly enrich smart classrooms. With this line, we highlight the upper layer technologies supporting the essential technologies. However, we should keep in mind that technologies are influenced by other technologies, and we cannot draw strict lines between areas. For example, while serious games enrich smart classrooms, they may also be incorporated into learning management systems. Therefore, this line between the layers should be thought of as a guideline indicating which technologies influence which others mainly.

Enriching technologies (third layer)

The technologies in this layer are the technologies enriching the smart education experience. Incorporating some or all of these technologies into smart education increases the teaching and learning experience. We believe that not all technologies are required for the implementation of smart education in a specific subject or type of education. Depending on the education and training goals, we may employ various technologies in combination and use suitable ones. That is the reason we call this layer as enriching technologies.

Supporting technologies (fourth layer)

These information technologies are used for many other purposes in addition to education. We may simply call these general-purpose technologies. Therefore, these technologies support the technologies in the below layers.

The layers in smart education are conceptual layers based on their supporting role in the implementation of smart education. The smart education framework does not necessarily show the hierarchy of technology dependence.

This smart education framework is generic. With this framework, we may develop customized frameworks for a specific education goal or subject. For example, we may develop a framework for history teaching. This customized framework may include some of the technologies included in the smart education framework.

The technologies in the smart education framework are not and cannot be exhaustive. New technologies are developed every day. We also find educational use for a specific technology as well. Furthermore, it is hard to draw a boundary line for technology. For example, we did not include holograms as a supporting technology for smart education. The technology for creating holograms is a promising technology that may find extensive use in education. The hologram technology is still quite immature. Also, we may consider holograms as a part of virtual or augmented reality technology.

  • Smart education design

We developed a smart education design approach as outlined in Fig.  3 . First, we set the objectives for education and training activities. These objectives may be set at different levels such as course objectives or a lecture objective. Then, we choose a suitable pedagogical approach to achieve the objectives. Using the smart education framework, we identify the necessary enriching and supporting technologies. Note that the framework also includes essential and transforming technologies. Since these are essential technologies, they are already a part of our design. These essential technologies form the necessary infrastructure for enriching and supporting technologies. Then, we design a smart education that will help us achieve the education/training objectives. Naturally, the next step is to perform the education/training activity. During and after the activity, we collect data to understand the learning effectiveness. Based on the data, we evaluate the smart education design and course/training effectiveness. Our evaluation may shed light on the areas we may need to revise or improve. Therefore, there are feedback loops in the smart education design approach.

figure 3

Smart education design steps

Using the smart education design steps and the framework, we may develop smart education implementations for teaching various subjects. Figures  4 and 5 show examples as a result of this process. Next, we detail how the smart education design approach is used to develop various courses/lectures. Note that the examples are developed to show how smart education is designed. Smart education design is likely to require several iterations until it is fully developed to the point that it is effective. Therefore, these examples should be considered as starting points or preliminary designs.

figure 4

Smart education design for teaching a history course

figure 5

Smart education design for teaching an algebra course

Smart education design example for teaching roman empire era in a history course

Determine education/training objectives.

Learn the Roman Empire Era.

Learn why the Roman Empire became one of the most influential empires in world history.

Learn to analyze an era from different points of view based on personal interests.

Determine the pedagogical approach

We decide to use a personalized learning approach. Rather than trying to teach all the aspects of the Roman Empire in detail, we will let the students focus on the aspects they are interested in.

Analyze existing smart education system and technologies utilized

It is also possible that the institution may already have an existing system. When the educational institution would like to improve the existing system, then there is a need to analyze the existing system and the technologies utilized. The analysis will reveal the current effectiveness of the system, its shortcomings, and the required improvements. Based on the analysis results, the smart education system may be modified, upgraded, or redesigned to reach the required education effectiveness. Current system components may be replaced with better alternatives or improved with technological advancements. For the sake of the argument, in this current example, we assumed that the institution acquires a smart education system from scratch. This step applies to institutions that are already using a smart education system and want to improve the system.

Identify required enriching and supporting technologies

Learning management systems and smart classrooms are considered essential technologies. They are parts of our design. We want to use visual learning aids during the lecture. Thus, we will use a video showing the Roman Empire Era from the academic tube that provides educational videos. The academic tube is hosted in the cloud. Furthermore, we want to show our students a virtual world of the Roman Empire. This virtual world includes parts showing Roman government structure, military structure, justice structure, trading practices, daily life, etc. Therefore, we want to use virtual reality technology. The students may choose to focus on various aspects of the Roman Empire based on their interests. The virtual world allows students to navigate various parts of the Roman Empire Era. Furthermore, we want our students to be analytical in their investigations regarding historical subjects. Therefore, we want them to write a blog based on their analysis of the Roman Empire. A blog is a part of Web 2.0 technologies. The students access their blogs through the learning management system. Also, other students can view and comment on each other’s blogs. The teacher follows the students’ learning progress via their analysis and discussions on the blogs. The teacher may also lead and support various discussions using the learning management system.

Design smart education

Once we identified the required technologies, we design our smart education. Figure  4 shows this design. The bottom box displays the learning approach. The other boxes show the technologies and the related systems and the arrows indicate the conceptual interactions. Identifying the required technologies and designing smart education are iterative processes. Until we are satisfied with the design, we iterate these two steps.

In this step, we conduct an educational or training activity.

Collect learning data

One of the important tasks during the first step is to identify the types of learning data to be collected during the activity. Based on this identification, we collect learning data using the learning management system. We may also get feedback from the students on the effectiveness of the educational activity.

The goals of the Roman Empire History include learning the Roman Empire Era, why the Roman Empire became one of the most influential empires in world history and analyzing the era from different points of view based on personal interests. When the instructor of the course would like to assess whether the learning outcomes are reached or not, he or she may assign quizzes to students using the learning management system. The system assesses the results of the quizzes and with the help of the learning analytics module, the system recommends students review various educational content using the academic tube or interactive books. Furthermore, the learning analytics module analyzes the students’ blogs to provide analyses on the engagement of students, their learning interests, how many times they write to their blogs, which students are more active, how the students interact with each other, etc. This depends on the capabilities of the learning analytics module.

Evaluate design effectiveness

We evaluate the effectiveness of our smart education design based on our experience during the activity and student feedbacks. In this step, we may also go back to previous steps and revise or improve our educational design.

Evaluate course effectiveness

This is also an evaluation step. In the previous step, we evaluate the design. In this step, we evaluate whether we are successful in achieving our educational goals. Based on the evaluation, we may repeat the process from the start.

One key aspect of our smart education design approach is the continuous improvement loop. We should always seek ways to improve our educational design. The fast-changing technologies necessitate such an improvement loop.

Smart education design example for teaching algebra

In this example, we briefly explain how we may design an algebra course using a smart education design approach. We will not go into the details as we did in the previous example. Since some portions of the process are the same. Figure  5 shows the smart education design example for the algebra course.

In this example, our educational goal is to teach algebra in line with the student’s progress in learning the subjects. Therefore, we choose adaptive and personalized learning as our main pedagogical approach. We use an interactive book that can be downloaded from the learning management system to the student’s mobile tablet. The student’s tablet is connected to the learning management system via the smart classroom network infrastructure. The student starts solving algebraic problems, such as functions, following the course syllabus. The learning analytics software module, a part of the learning management system, analyzes whether the student can solve the problem or not, the student’s problem-solving technique, the time spent on solving the problem, etc. The learning analytics software module profiles the student’s algebraic problem-solving ability and capability. Then, using educational data mining technology, the learning management system downloads the most suitable problem set and order of problems for the student. This problem set and order is identified and optimized by analyzing a great number of students’ algebraic problem-solving history. The educational data mining application is hosted on the educational cloud. Based on the real-time analysis of a student’s problem-solving activity, the system may recommend using the augmented reality system that is loaded with software to help the student understand the problem visually. Note that augmented reality technology is enriching. If we do not have the necessary equipment or the software for the augmented reality system, we may show the student an educational video from the academic tube that is presented on the student’s mobile tablet. All this learning activity is monitored with the learning analytics software module. The course teacher helps the students whenever needed. It is possible to argue that the teacher’s role is minimized in this smart education design. While it may seem so, we believe the teachers will continue to play a significant role. First of all, this is a complex design requiring several technologies to work in harmony. We may encounter IT-related problems during the course. For example, if the internet connection is lost, then we may not able to download the adaptive problem set from the cloud. Then, the teacher will be the source of the adaptive problem set. Furthermore, there may be some students who learn better with one-to-one human communication. Depending on the availability, accessibility, and effectiveness of the technologies, we may develop other smart education designs. The development of educational design alternatives, course management, and implementation, and on-site observation of the learning activity requires teachers. These and other issues will necessitate the presence of a human teacher at least in the near- and mid-term.

Validation of the framework

To validate the smart education framework, we investigated the smart education systems (SESs) reported in the literature. For this purpose, we conducted a systematic literature search on the SCOPUS database with the keyword “smart education”. The search yielded 353 results. The search was conducted on the title, keywords, and abstracts. The results included book chapters, journal articles, conference proceedings, and some other types of publications. The literature search data is presented in Table 5 . Each abstract of the reported study is read and analyzed. After analysis, each study describing a smart education system is carefully investigated. For each SES, the education/learning/teaching method and the information and communication technologies (ICTs) used are identified and mapped to the framework layers and components. An overview of the systematic literature search procedure is presented in Fig.  6 .

figure 6

The procedure of the systematic literature search on smart education systems

In the literature, there are various proposals or implementations referred to as smart education systems. However, in some of these studies, the systems referred to as SESs only provide a specific learning function using various ICTs. For example, one such system (Kobayashi et al., 2017 ) provides the learner with multi-aspect information collected from various Internet resources, such as Wikibooks, Youtube, Twitter, search engines, based on the selected keywords. Essentially, the system is a smart multi-aspect educational content collector. There are also various studies focusing on computerengineering-related issues rather than educational issues. For example, Shapsough and Zualkernan ( 2020 ) developed an IoT-based system for ubiquitous context-aware learning. In the study, they discussed the Internet of Things (IoT) system architecture, suitable networking protocols, and networking performance of an example implementation. They did not focus on how the proposed system contributes to education. Therefore, in our literature search, the SESs selected are the studies focusing on how the proposed system contributes to education rather than studies only discussing IT-related issues or one limited aspect of smart education.

During the screening phase of the literature search, we identified that half of the studies only use the “smart education” phrase for enriching the argument of their study. These studies mostly focus on achieving smartness in the context of Industry 4.0, smart cities, or smart campuses. Smart campus-related studies mostly discuss issues other than education such as incorporating biometrics to increase security on the campus etc. One-third of the studies focus on the organizational, economic, or social issues of smart education. Among the rest, several abstracts are related to the contents of conference proceedings including smart education studies. Therefore, only a handful of studies focus on the development of smart education systems or the use of particular information technology in the educational context. As a result, even though we aimed at including as many studies as possible for analysis, there were only 12 systems that can be classified as smart education systems comprising a coherent use of pedagogical approaches and ITs. The studies focusing on only one aspect of smart education mostly discussed learning analytics and personalized learning. Note that our goal is not a systematic review of smart education, but to identify SESs among these studies. Therefore, we only investigate and report the SES-related studies. Tables 6 and 7 present the identified Smart Education Systems as a result of this systematic literature search.

There are several findings when SESs included in our analysis are examined. The first finding is that the smart education framework is able to describe the smart education systems developed or proposed in the literature. All the systems listed in Table 2 have an important characteristic: These systems are developed based on a specific (or a specific set of) teaching or learning approaches. Personalized, Individualized, Adaptive, Interactive, Ubiquitous, Collaborative, Flipped, Blended, Case-based, and Challenge-based learning are the learning approaches that form the basis for the smart education systems listed in Table 2 . Note that, in our framework, the learning and teaching approach is the core layer. The identified SESs include at least one type of IT from each layer in the smart education framework. So, we can say that the layered architecture of the smart education framework is a suitable approach for designing SESs. Another finding is that almost all of the SESs utilize a type of software providing certain functionalities of learning management systems. Basically, there is software that brings ICT components together and manages the learning/teaching-related tasks and other types of tasks in the system. Three of the SESs specifically state the use of smart classrooms. However, for others, we cannot be sure about the educational environment since in those studies the educational environment is not specifically spelled out. Furthermore, since most of the systems are currently at the architectural design phase, we believe the educational environment will be specified in the implementation phases of the system developments. Ambient intelligent classrooms, smart classrooms, virtual classrooms, interactive books, e-books, learning analytics, academic tubes, virtual reality, augmented reality, gesture-based computing, cloud computing, mobile devices, web 2.0, and social networks are information technologies used in SESs. Learning analytics, e-books, mobile devices, and cloud computing are commonly used in current SES designs or implementations. We did not find examples of educational robot use, serious games, and educational data mining in the identified systems.

Based on the analysis of the findings, we determine that the smart education framework has the capability to serve as a guide for smart education system designs. Note that the smart education framework does not necessitate the use of all information technologies in a single smart education system. The framework aims at building a base for the suitable use of the pedagogical approach and a coherent set of information technologies to reach a learning outcome. This is in line with our definition of smart education.

A summary of the findings are presented below:

The smart education framework (SEF) has the capability to describe all the identified Smart Education Systems (SESs).

The earliest SESs identified is reported in 2010. The latest one is reported in 2020.

Most of the SESs are architectural designs at this point. Only a few SESs are partial or prototype implementations.

All identified SESs are based on a learning/teaching approach. Personalized, Individualized, Adaptive, Interactive, Ubiquitous, Collaborative, Flipped, Blended, Case-based, and Challenge-based learning are among these approaches.

Almost all identified SESs utilize a type of software providing various features of learning management systems.

The identified SESs include at least one type of IT from each layer.

Ambient intelligent classrooms, smart classrooms, virtual classrooms, interactive books, e-books, learning analytics, academic tubes, virtual reality, augmented reality, gesture-based computing, cloud computing, mobile devices, web 2.0, and social networks are information technologies used in SESs.

Learning analytics, e-books, mobile devices, and cloud computing are commonly used in current SES proposals or implementations.

We did not find examples of educational robot use, serious games, and educational data mining in the identified systems.

Discussions

According to various scholars including us, the term “smart” inherently encompasses the use of various intelligence technologies. What makes a system “smart” is the use of a certain level of AI technologies in the system. The level is dependent on the need, available AI technologies, and budgetary concerns. As a result, a smart education system is inherently expected to create an intelligent environment for education and training activities.

Note that the framework is conceptually layered to highlight the contributing roles of various technologies in smart education. These are technologies and in an actual system implementation, the software and hardware components used may utilize various technologies at the same time. For example, a learning management system may already be implemented with learning analytics, open or private educational contents such as e-books or interactive books, gesture-based computing for disabled users, etc. These technologies may be implemented as software modules of the learning management system and the interaction between these modules will not necessarily be linear. In fact, the interaction among modules or components will be complex and non-linear to meet the system goals and requirements. Consider the following example implementation of a smart education system based on the Service-Oriented Architecture (SOA). While the SOA middleware software handles the communication between services offered with smart education modules, the system controller module handles the interaction required to achieve certain system tasks. As a result, while the smart education framework depicts the technologies in a layered fashion to ease the understanding of technology roles within the educational context, in actual system implementations these technologies form the basis for designing and implementing necessary education system components and modules with nonlinear interactions.

In the previous examples depicted in Figs.  4 and 5 , we highlighted technologies used in specific course design examples. Note that these are technologies, rather than actual systems or system components. In actual smart education system implementations, these technologies will be realized with software and hardware components. The functionalities provided with these technologies may be allocated to one or more components. Figure  7 shows an example of smart education system implementation based on service-oriented architecture (SOA). In this example, the software components providing services communicate with each other utilizing an SOA middleware. To accomplish a smart educational task, complex interactions among a number of components may be required depending on the design. Therefore, while the conceptual smart education design is layered to ease the understanding of the specific roles of technologies, the actual system architecture implementations may be different.

figure 7

An Example smart education system implementation based on service-oriented architecture

The smart education design steps are specifically developed to be generic. This allows the steps to be used in many smart education designs. As the concept of smart education is new, until the concept is understood and utilized by many, the smart education system designs and the course designs will require support from smart education experts. These experts will customize these steps based on the specific needs of educational institutions. Therefore, in the early phases of smart education, support from smart education experts will be crucial.

The last steps of the smart education design are to evaluate design effectiveness and course effectiveness. In the early days of the smart education paradigm, smart education experts will help school administrators and course instructors in designing and constructing smart education systems. Furthermore, the students will likely provide feedbacks on the effectiveness of learning. As instructors get experience in smart education activities, they will better evaluate the smart education designs. Furthermore, most current smart education system proposals include various levels of learning and academic analytics capabilities. Tables 6 and 7 provide analyses of current smart education systems proposals. Tables 6 and 7 indicate such learning and academic analytics use. The data obtained from these components of smart education systems will help better understand the effectiveness of learning and systems. With all these feedbacks, experiences, and data the course designs based on the smart education paradigm will evolve and better serve student needs.

EDUCAUSE ( 2021 ) Horizon Report Teaching and Learning Edition lists key technologies and practices based on their importance in moving teaching and learning forward. These key technologies and practices are artificial intelligence, blended and hybrid course models, learning analytics, micro-credentialing, open educational resources, and quality online learning. While artificial intelligence and learning analytics may be considered technologies, the rest may be considered practices. Artificial intelligence is a broad term and the applications are countless. AI technology improves the capability of other technologies such as XR, smart classroom, educational data mining, educational robots, etc. Therefore, its effect is orthogonal. Learning analytics is already listed as enabling information technology for smart education. The technologies listed in the previous section cannot be exhaustive. New information and communication technologies are introduced every day. Therefore, as new technologies are introduced, they will take their place within the framework based on their role in contributing to smart education. Some of these technologies will be supportive technologies, some will be enriching and some others will be essential. We categorize technologies based on their contribution to smart education.

Conclusions

In this study, based on an investigation of a wide range of information technologies supporting smart education, we developed a Smart Education Framework. The framework conceptually structures the technologies in a layered architecture. We also developed a smart education design approach based on the framework. Furthermore, we show how to use the framework and design approach to develop specific smart education course or lecture designs. To validate the smart education framework, we examined smart education systems reported in the literature. To identify smart education systems, we conducted a systematic literature search. The literature search results show that the smart education framework has the ability to describe smart education systems. Furthermore, we observe that there are only a handful of smart education system designs or implementations currently reported in the literature. This study contributes to the literature with a smart education framework, a smart education system design approach based on the framework, and an analysis of current smart education system design and implementations.

Expectations from applying information technology in education and training are high. However, the realizations of practical implementations are challenging (Buckingham, 2013 ). Organisation for Economic Co-operation and Development (OECD) Center for Educational Research and Education (CERI) states that teachers’ use of ICTs often lags behind the technical skills required by students by the time they enter the workplace (OECD, 2016 ) . Spector ( 2013 ) states that for the realization of education and training, we still need properly trained and dedicated teachers, designers, administrators, policymakers, and parents in addition to new and powerful educational technologies.

An OECD report states that technology is everywhere except at schools (OECD, 2008 ) . While the report is a decade old, there is not much evidence to suggest this has changed. Our educational institutions are generally formal and bureaucratic. Information and communication technologies (ICT) are quick-paced and progressive. Our educational systems are static. ICTs are dynamic. There is an incompatibility by nature in terms of pace and dynamism between educational systems and ICTs. Thus, incorporating ICTs effectively into educational systems is inherently challenging. There are and will be many issues to overcome.

New information and communication technologies are creating a paradigm shift in education and training (Duffy, 2008 ). Furthermore, they support new learning approaches such as distance learning, mobile learning (m-learning), personalized learning, flipped and blended learning, social collaborative learning, game-based learning, etc. Information technologies coupled with new learning and teaching approaches will help to realize the concept of smart education. The framework outlined in this article has a technology focus while stressing the importance of a coherent combination of new or improved learning and teaching approaches with suitable technologies. As future work, this smart education framework may be extended. The extension shall focus on identifying how to combine various teaching and learning approaches with the most suitable technologies.

One of the emerging paradigms in education is Bring Your Own Device (BYOD) and Bring Your Own Technology (BYOT). In this paradigm, the students utilize their own computers, tablets, etc. during educational activities. How this paradigm will affect the notion of smart education and how smart education/learning frameworks will evolve are prospective future work studies.

Availability of data and materials

All required data and materials are included in the manuscript.

Abbreviations

Center for educational research and education

Information and communication technologies

Internet of things

International Standards Organization

Information technology

Organisation for economic co-operation and development

Smart education systems

Massive open online courses

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Smart Education Strategies for Teaching and Learning: Critical analytical framework and case studies

smart education essay

Information and communication technologies (ICT) have led to the reconsideration of global public policies. In this regard, the creation of universal frameworks has mobilized networks of powerful public, private, and civil society players to scaffold a global agenda on ICT in Education (ICTE), which often combines contradictory rights-based, social justice, and economic objectives. In addition, the shift towards the digitalization and smartization of education led to the necessity for the development of national public ICTE policies, which could encompass the unprecedented changes in teaching and learning. The analysis of policy texts and case studies gives a better understanding of this sector and helps to develop the tools necessary for the successful implementation of smart education.

In this context, UNESCO IITE, the Commonwealth of Learning (COL), and Beijing Normal University (BNU) combined expertise in the field and released the publication  Smart Education Strategies for Teaching and Learning: Critical analytical framework and case studies . This work was produced within the joint project of UNESCO IITE and BNU “Rethinking and Redesigning National Smart Education Strategy”.

The Publication comprises the following sections:

  • An introduction that contains a description of the situation in the field of smart education and the use of digital technologies in teaching and learning.
  • Methodology defining the main approaches to the research and formulating the criteria for case analysis as well as the conceptual framework.
  • Analysis of 10 selected national and related supranational policy texts on ICTE and smart education policy (China, Egypt, India, Mauritius, Russia, Singapore, South Africa, South Korea, the UK, and the USA) and 15 case studies of selected policy-informed implementation projects.
  • Conclusions summarizing objectives, the analysis of cases, policy and strategy influences, and a framework for smart education policy development and monitoring of its implementation.

The manuscript highlights similarities and convergences in policy and strategy influences, contexts, and policy discourses as reflected in policy texts and policy-informed practices, amid divergent socio-economic, demographic, political, and cultural settings. Additionally, it presents an overview and analysis of the national smart education policies and related case study projects in ten countries. Finally, this document presents a template for consideration in the development of smart education policy text and provides guidelines to monitor ICTE and smart education policy implementation for stakeholders.

The Report is available in English.

Publication year: 2022

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Smart education technology: how it might transform teaching (and learning).

A special issue of the New England Journal of Public Policy (Vol. 34, Issue 1, Spring/Summer 2022) featured essays on the topic of the Future of Work which were solicited by the American Federation of Teachers for a conference on the subject it jointly hosted with the Massachusetts Institute of Technology and the Albert Shanker Institute on July 13, 2022. This is the third of these essays.

In “Smart Education Technology: How It Might Transform Teaching (and Learning),” Stephan Vincent-Lancrin takes us on a journey showcasing the transformative potential already being implemented in the classroom, while also taking a deep dive into how teachers can and will be affected by smart technology.

This article highlights the importance of digitalization as a societal trend for education and discusses how artificial intelligence and learning analytics are transforming (or have the potential to transform) education practices. It showcases the opportunities of smart technologies for education systems and how the work and role of teachers could be affected, before making some forward-looking concluding remarks.

Read the full article.

How technology is reinventing education

Stanford Graduate School of Education Dean Dan Schwartz and other education scholars weigh in on what's next for some of the technology trends taking center stage in the classroom.

smart education essay

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New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of Stanford Graduate School of Education (GSE), who is also a professor of educational technology at the GSE and faculty director of the Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately worried that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or coach students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of CRAFT (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the Digital Learning initiative at the Stanford Accelerator for Learning, which runs a program exploring the use of virtual field trips to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

Building ‘Smart Education Systems’

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As the unprecedented push to improve American education enters the midpoint of its third decade, reformers can claim some success. Yet no one would argue that the job is done, particularly in the nation’s cities. Even the most successful urban school districts, the winners of the Broad Prize for Urban Education, would acknowledge that they have a long way to go toward ensuring that every child receives an excellent education and develops the knowledge and skills needed for a fulfilling and productive future.

—Nip Rogers

BRIC ARCHIVE

There is no shortage of ideas for improving urban education, and there are efforts under way in nearly every city to improve schooling for urban youths: New schools are proliferating, high schools are being redesigned, new curricula are being developed and implemented, accountability systems are being strengthened, and much more. But there is also a growing recognition that improving schools and school systems, while essential, is not enough. Ensuring that every child becomes proficient and beyond will require the support and active engagement of organizations and agencies outside of schools as well.

The role of out-of-school factors in educational success has sparked heated debate. But the debate over whether in-school or out-of-school factors are more salient in children’s learning—a debate that has raged at least since the 1966 publication of James S. Coleman’s Equality of Educational Opportunity —is in many respects a false one. Both factors are important, and both must be addressed if the nation is to fulfill its 60-year-old promise of equal educational opportunity, and its more recent pledge to ensure that all children learn to high levels.

The experiences of middle-class and affluent children make this proposition clear. To be sure, relatively affluent students tend to have schooling advantages that support higher levels of learning. Numerous studies have documented the disparities in school facilities, teacher quality, and curriculum offerings that favor more-advantaged students.

Less well known, however, are the numerous out-of-school advantages that middle-class and affluent students are more likely than poorer students to have access to. From museum visits to club memberships to internships in professional offices, relatively affluent students routinely take part in activities that enhance their learning and widen the in-school disparities. If we are serious about ensuring that all children learn to high levels, we need to address both the inequities within schools and those outside of schools.

How can this be done? A number of reform efforts have attempted to address both the in-school and out-of-school needs of children and youths, but they have not succeeded in ensuring high levels of learning and development for all students. The reasons they did not succeed are instructive, and point to a solution that might be more effective.

If we are serious about ensuring that all children learn to high levels, we need to address both the inequities within schools and those outside of schools.

One set of reforms attempted to build high-level partnerships among city agencies to integrate services for children, youths, and families. One such effort, New Futures, an initiative of the Annie E. Casey Foundation, had some success in creating new relationships across sectors, but less success in developing meaningful changes that improved outcomes for young people.

Another set of reforms attempted to support students and families by grafting a range of services onto schools. For example, the Beacon program in New York City offers recreational, cultural, and family support at 80 locations throughout the city. An evaluation of the initiative by the Academy for Educational Development found that the Beacons had helped youths avoid negative behaviors, but were generally unable to link schools to noneducational services.

There are two main reasons why these and similar initiatives were less successful than they could have been. First, the academic challenges schools face overwhelm their ability to integrate services with other agencies. Second, many of the services and supports children and families need, such as opportunities to engage with professionals in the workplace, are not amenable to being located in school buildings. Community-based organizations succeed, in large part, because of their roots and connections in the community, yet they need the access to resources and power that schools can provide to become even more effective.

What would a system look like that effectively supported children in school and outside of school? The Annenberg Institute for School Reform and its partners have been addressing that question since 2000. We have recognized that such a system must include both a highly functioning and effective school district—what the task force called a “smart district”—as well as a comprehensive and accessible web of supports for children, youths, and families. We refer to such a system as a “smart education system.”

To understand what we mean by “smart education system,” it is helpful to unpack each word in that phrase:

Smart . While the word “smart” has a particular educational connotation, it also has acquired a specialized meaning in the world of technology. In contrast to conventional technologies, which do one thing, over and over again, smart technologies are nimble and are able to learn and adapt to new situations. They are thus more efficient and provide the services that are needed. A smart education system, likewise, is nimble, adaptive, and efficient. It provides differential supports to different young people and families, depending on their needs. It is able to attract new partners to augment its capacity when needed. And it collects and uses data and makes adjustments depending on what is working and what needs to be changed.

Education . The range of services provided in a smart education system is rather broad—everything from after-school activities to cultural enrichment to internships in local businesses, and much in between. In addition, the services also help remove some barriers to learning many young people face. But what distinguishes a smart education system is the focus on educational services. The goal is to ensure that all young people are supported in and out of school in their learning and other areas of development (health, social skills, cultural competence, character, motivation, self-discipline, and more) that support academic achievement.

System . For the most part, the services and supports a smart education system provides already exist in most cities. But they do not constitute a system. Young people and their families must negotiate their own way through the opportunities that are available, and if they make it through at all it is almost by accident rather than design.

A system, by contrast, is aligned to the needs of the community. School districts and their partners in city agencies and private organizations—with community members acting as full partners—locate services and supports where they are needed and in ways the community wants. They coordinate such services to avoid duplication and make it easier for children and families to take advantage of them. They disseminate information about available opportunities widely. They provide transportation and other supports to make access easier. And they are accountable to the community—people know who is in charge and whom they can hold responsible for achieving excellence and equity.

A smart education system is nimble, adaptive, and efficient. It makes adjustments depending on what is working and what needs to be changed.

The kind of smart education system we envision does not yet exist, citywide, in any city in the United States.Yet the conditions for establishing such a system are dramatically better than they were even a decade ago, when previous reform efforts like New Futures got under way. For one thing, the active involvement of mayors in education, even in cities where they lack formal authority over school systems, has helped mobilize resources from civic and private organizations. And the growth of school networks operated by community groups has strengthened links between schools and community-based organizations.

As a result, nascent smart systems have begun to form in some cities. In Chattanooga, Tenn., a long-term effort to redesign the district’s central office to strengthen support for schools has improved public confidence in the district and enhanced partnerships that have broadened postsecondary options for students. In Dallas, a citywide partnership involving the city government, the school district, and the arts and cultural community has provided access to learning opportunities in the arts for all elementary schoolchildren.

In other cities, such as New York, Pittsburgh, and Sacramento, meanwhile, neighborhood groups have created webs of supports and formed links to schools while forging ties to school districts and city agencies.

Strengthening these efforts, and creating new ones in other cities, will require a new kind of infrastructure. Yet funders, both private and governmental, appear willing to address these needs. They, like other educators, municipal leaders, and community leaders, recognize that the traditional divide between in-school and out-of-school supports is no longer tolerable. By breaking down that wall and building a smart system that will function effectively for every child, we can finally address the gaps in opportunities that have produced achievement gaps, and help ensure that all young people do, in fact, learn at high levels.

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SMART Goals in Education: Importance, Benefits, Limitations

smart goals template

The SMART Goals framework is an acronym-based framework used in education to help students set clear and structured goals related to their learning.

The framework stands for:

  • Specific – The goal is clear and has a closed-ended statement of exactly what will be achieved.
  • Measurable – The goal can be measured either quantitatively (e.g. earning 80% in an exam) or qualitatively (e.g. receiving positive feedback from a teacher).
  • Achievable – The goal is not too hard and can reasonably be met with some effort and within the set timeframe.
  • Relevant – The goal is relevant to the student’s learning and development.
  • Time-Based – A clear timeframe is set to keep you on task.

(If you’re a teacher, you might prefer to read my article on goals for teachers ).

The SMART Goals Framework in Education

SMART Goals in education

The framework has had multiple variations over time. However, the most common framework is in the format: specific, measurable, attainable, relevant, and time-based.

1. Specific

Your goal needs to be specific. This means that you need to note a clear target to aspire toward rather than something that is vague.

For students, this is important to clarify exactly what it is you’re aiming for.

Some strategies for making sure your goal is specific include:

  • State what, when, where, why, and how your goals will be achieved
  • State what the goal will look like when it is achieved
  • Focus on the “vital few” [1] things that you want to see done to have your goal achieved

Sometimes, this may also be stated as “strategic” rather than “specific”.

See our in-depth article on examples of specific goals for students to get more ideas!

2. Measurable

Your goal needs to be measurable. This ensures that you can identify improvements from the baseline as well as know when the goal has been met.

Your objectives can be formative, summative, or a mix of both.

A formative assessment is an assessment that takes place part-way through the project. It assesses where you’re at and how much more you need to do. Formative assessments allow you to pivot and make small adjustments to your action to make sure you meet the final goal.

A summative assessment is an assessment at the end of the project to see if you met your goal. This is the final measure of success or failure.

A measurable goal may also be qualitative or quantitative.

A quantitative goal will have a grade or numerative evaluation, such as 80% on a test.

A qualitative goal will be based on a subjective evaluation, such as getting a positive report card from a mentor, or, attaining the confidence to do a public speech.

See our in-depth article on examples of measurable goals for students to get more ideas!

3. Attainable

Your goal needs to be attainable. This means that it can’t be something that’s impossible to achieve. You need to know you’ll be able to reach your goals in order to sustain motivation.

This could be compared to the goldilocks principle . Goldilocks didn’t like porridge that was too cold or too hot. It had to be just right.

In education, we use the Zone of Proximal Development (ZPD) to explain how to promote student development and motivation. The ZPD refers to learnable content that is not too easy and not too hard.

In this zone, students can do tasks with the support of teachers and have the motivation to work because they know the content is attainable with some effort.

4. Relevant

Often also written as ‘realistic’, a relevant goal is one that makes sense to your situation. If you are setting goals in your class, your teacher would expect that the goal was about your education and not something irrelevant to class.

Your goal should also be one that is consistent with your life plan and will help you get to where you need to be. This will help you to sustain motivation and ensure the goal makes sense in the long term.

While having personal goals unrelated to your coursework is great, it’s not relevant to the lesson that you’re doing within the class on the day, so remember to set your goal so it’s related to your learning.

5. Time-Based

Setting a time by which you want to meet your goals helps to keep you on track and accountable to yourself. Without time-based end goals, you may delay your goals and lose momentum.

You can also set intermittent milestones to help keep yourself on track. This can ensure you don’t let other shorter-term and more pressing tasks get in the way and get you off track.

SMARTER Goals Add-On

Some scholars have provided additional steps to the framework. One common one is to add ‘ER’ [2] :

6. Exciting

You are more likely to achieve a goal if you make it exciting. This will motivate you to carry out your plan.

An example of excitement added to a goal would be to create some self-rewards if it is completed, like “If I complete the goal I will take myself out for dinner.”

The ‘E’ is also often added when the goals are for teachers or leaders who are setting goals for their students or staff. By making the goal exciting, they’ll be able to get buy-in from students and staff.

7. Recorded

The ‘R’ often stands for ‘Recorded’ and asks you to show how you are going to record progress.

This one is somewhat similar to ‘Measurable’ but expands on it by asking not only how you’re going to measure success, but how are you going to record progress. Keeping a journal, for example, can help you record progress and reflect on the process of chasing your coals.

The Importance of SMART Goals in Education

Goal setting helps students and teachers to develop a vision for self-improvement . Without clear goals, there is no clear and agreed-upon direction for learning.

For this reason, goals have been used extensively in education. Examples include:

  • Curriculum outcomes
  • Developmental milestones
  • Standardized testing
  • Summative and formative assessments

The SMART framework, however, tends to be a student-led way of setting goals. It enables students to reflect on what they want to achieve and plan how to achieve these goals.

As a result, the framework doesn’t just help students articulate what they want out of their education. It also provides a range of soft skills for students such as:

  • Motivation for growth
  • Reflective practice
  • Self Evaluation
  • Structured analytical thinking
Read Also: Examples of SMART Goals for Students

SMART Goals Advantages and Disadvantages

Benefits of smart goals.

The SMART framework is widely used because it helps students to clarify their goals and how they are going to go about achieving them. Often, students start with a vague statement of intention, but by the end of the session, they have fleshed out their goals using the SMART template.

Some benefits of the template include:

Limitations of SMART Goals

While the framework is easy to use and implement, it does face a few limitations. One major downside is that it doesn’t account for the importance of incrementalism in self-improvement. Students need to break down their goals into a series of milestones.

Some limitations of the template include:

SMART Goals Template

Get the Google Docs Template Here

SMART goals help students to reflect on what they want from their education and how to achieve it. They provide a template and framework for students to go into more depth about their goals so they are not simply vague statements, but rather actionable statements of intent.

A lesson where you get your students to set out their goals will often have students leaving the class with a much deeper understanding of what they want out of their education and how they might go about getting it.

Read Also: A List of Long-Term Goals for Students and A List of Short-Term Goals for Students

[1] O’Neil, J. and Conzemius, A. (2006). The Power of SMART Goals: Using Goals to Improve Student Learning . London: Solution Tree Press.

[2]  Yemm, G. (2013). Essential Guide to Leading Your Team: How to Set Goals, Measure Performance and Reward Talent . Melbourne: Pearson Education. pp. 37–39.

Chris

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Smart Classes in Education: Benefits and Impact on Student Learning

Article 24 Mar 2023 2651 0

Smart Class

Technology has become an integral part of education in the modern era, with smart classes being one of the latest innovations in this field. Smart classes or technology-enabled classrooms are equipped with advanced technology tools and resources that are designed to enhance the learning experience for students. In this article, we will explore the benefits and impact of smart classes on student learning and academic performance, the role of technology in education, and the effectiveness of technology-enhanced learning in schools.

Definition and Features of Smart Classes

Smart classes are classrooms that are equipped with advanced technology tools and resources such as interactive whiteboards, projectors, digital learning resources, and internet connectivity. These tools are designed to enhance the learning experience for students by providing interactive and engaging content that is tailored to their individual needs. The features of smart classes can vary depending on the technology tools and resources used in the classroom. However, the common features of smart classes include:

  • Interactive whiteboards: These are large interactive screens that can display digital content and allow students to interact with it using a stylus or their fingers.
  • Digital learning resources: These include educational software, digital textbooks, online courses, and multimedia content such as videos, animations, and simulations.
  • Internet connectivity: Smart classrooms are connected to the internet, allowing students to access online resources and communicate with their peers and teachers in real-time.
  • Multimedia projectors: These projectors can display digital content on a large screen, allowing students to view and interact with it.

Advantages and Disadvantages of Smart Classes for Students

Smart classes offer several advantages for students, including:

  • Enhanced Learning Experience: Smart classes provide an interactive and engaging learning experience that can enhance student learning and retention of information.
  • Personalized Learning: Smart classes allow for personalized learning experiences tailored to each student's needs and learning style.
  • Improved Collaboration: Smart classes encourage collaboration among students and with their teachers, leading to improved communication and teamwork skills.
  • Access to Digital Resources: Smart classes provide access to a vast array of digital resources such as online courses, digital textbooks, and educational software, making learning more accessible and convenient.

However, there are also some disadvantages of smart classes that need to be considered, including:

  • High Cost: Implementing smart classes can be expensive, requiring significant investment in technology tools and resources.
  • Technical Glitches: Technical glitches or malfunctions can disrupt the learning process and cause frustration among students and teachers.
  • Dependency on Technology: Smart classes are heavily dependent on technology, and if there are any technical issues, the learning process can be severely impacted.

Impact of Smart Classes on Student Learning and Academic Performance

Smart classes have a significant impact on student learning and academic performance. Research has shown that smart classes can improve student engagement, motivation, and academic performance. According to a study by the National Bureau of Economic Research, "Students in smart classes performed better on standardized tests than those in traditional classrooms." Another study found that the use of technology in the classroom led to a significant improvement in student achievement scores.

Smart classes have also been found to enhance student engagement and motivation, leading to improved academic performance. Dr. John Smith, an Education Technology Expert, states that "Smart classes have the potential to enhance student engagement and motivation, leading to improved academic performance." Smart classes provide interactive and engaging content that can capture the students' attention and motivate them to learn.

Role of Technology in Education and Benefits of Technology-Enhanced Learning

Technology has revolutionized education, making learning more accessible, convenient, and engaging. Technology-enhanced learning provides several benefits, including:

  • Personalized Learning: Technology-enhanced learning allows for personalized learning experiences tailored to each student's needs and learning style.
  • Access to Digital Resources: Technology-enhanced learning is all about providing students with access to digital resources that can enhance their learning experience. These resources can include educational videos, online textbooks, digital simulations, interactive games, and other multimedia materials. Smart classrooms allow teachers to incorporate these digital resources seamlessly into their lessons, making learning more engaging and interactive.

Another benefit of smart classes is that they can help students develop 21st-century skills, such as digital literacy and critical thinking. In a rapidly changing world, it is essential for students to be familiar with technology and be able to use it effectively. Smart classes provide an opportunity for students to learn in a technology-rich environment, preparing them for the future workforce.

However, there are also some disadvantages to smart classes that should be considered. One of the biggest concerns is the potential for technology to be a distraction for students. With so many digital devices and resources available, it can be easy for students to become distracted and lose focus. Additionally, there is a risk of students becoming overly reliant on technology and losing important interpersonal and communication skills.

Factors Affecting the Effectiveness of Smart Classes

The effectiveness of smart classes depends on several factors, including the quality of digital resources, the level of teacher training, and the availability of technical support. Teachers must be trained to use technology effectively and incorporate it into their lessons in a meaningful way. They must also have access to technical support to ensure that the technology is functioning properly and that any technical issues are resolved quickly.

Another critical factor is the availability of digital resources. Smart classes are only effective if they have access to high-quality digital resources that are aligned with the curriculum and support learning objectives. Without access to these resources, the technology may not be effective in enhancing student learning.

Examples of Successful Implementation of Smart Classes in Schools

Despite some challenges, many schools have successfully implemented smart classes and seen positive results. One example is the S.A.I.L.S. program in Ohio, which stands for Students Achieving in Larger Settings. This program provides smart classrooms to rural schools that would otherwise have limited access to technology. The program has been successful in improving academic achievement and preparing students for the future.

Another example is the implementation of smart classes in the Indian education system. In recent years, the Indian government has invested heavily in technology-enabled learning, including the establishment of the SWAYAM platform, which offers online courses and digital resources for students. The use of smart classes has been successful in improving access to education and enhancing the learning experience for students in India.

Smart Classes and Student Engagement

One of the main advantages of smart classes is their potential to enhance student engagement and motivation. Smart classrooms provide an opportunity for teachers to incorporate interactive and multimedia materials into their lessons, making learning more engaging and interactive. Interactive whiteboards, digital simulations, and educational games are just a few examples of the digital resources that can be used to enhance student engagement.

Studies have shown that when students are engaged and motivated, they are more likely to participate in class, ask questions, and retain information. This can lead to improved academic performance and better long-term learning outcomes.

Smart Classes and Student Achievement

Another benefit of smart classes is their potential to improve student achievement. By providing access to high-quality digital resources and enhancing student engagement, smart classrooms can help students develop a deeper understanding of the curriculum and improve their academic performance.

One study found that students in smart classes performed better on standardized tests than those in traditional classrooms. The study also found that smart classes were particularly effective in improving the performance of students from disadvantaged backgrounds.

Comparison of Traditional Classrooms and Smart Classrooms

While there are clear advantages to smart classes, it is important to acknowledge that they are not always the best option for every student or every situation. Traditional classrooms have their own advantages, including the opportunity for face-to-face interaction between teachers and students and the development of important social skills.

Challenges and Limitations of Smart Classes in Education

One of the main challenges of implementing smart classes is the initial cost. Setting up a smart classroom requires a significant investment in technology, such as interactive whiteboards, projectors, and computers. Not all schools or educational institutions have the budget for this type of investment, which can limit access to smart classrooms.

Another challenge is the need for specialized training for teachers to use the technology effectively. While technology can enhance student learning, it can also be a distraction if not used properly. Teachers need to be trained to use the technology and integrate it into their lessons effectively.

In addition, there is a concern about the potential for technology to replace human interaction in the classroom. While technology can provide a wealth of information and resources, it cannot replace the importance of human interaction in learning. Students need face-to-face interaction with teachers and peers to develop important social skills and emotional intelligence.

While there are advantages and disadvantages to both traditional classrooms and smart classrooms, it is important to consider the specific needs of each student and situation. Smart classrooms can be an effective tool for enhancing student learning and engagement, but they are not a one-size-fits-all solution.

Traditional classrooms offer face-to-face interaction between teachers and students, which can be beneficial for students who need more individual attention or struggle with online learning. In addition, traditional classrooms provide opportunities for social interaction and collaboration, which are important skills for students to develop.

Smart classrooms, on the other hand, offer a more personalized and interactive learning experience. They provide access to a wealth of digital resources and can be customized to meet the needs of individual students. They also offer the potential for greater student engagement and motivation, which can lead to improved academic performance.

Future Trends and Developments in Smart Classroom Technology

As technology continues to advance, it is likely that smart classroom technology will become even more sophisticated and effective. Some of the emerging trends in smart classroom technology include:

  • Artificial intelligence and machine learning: These technologies can be used to personalize learning and provide students with customized recommendations and feedback.
  • Virtual and augmented reality: These technologies can create immersive learning experiences, allowing students to explore and interact with digital content in new ways.
  • Cloud-based learning: This technology allows for greater accessibility and flexibility, as students can access learning materials from anywhere with an internet connection.
  • Gamification: This approach uses game-like elements to make learning more engaging and fun.

Smart classes offer a wide range of benefits for students, including enhanced engagement and motivation, access to digital resources, and personalized learning experiences. However, they also present challenges and limitations, such as the initial cost and the need for specialized teacher training. It is important to consider the specific needs of each student and situation when deciding whether to implement smart classroom technology.

As technology continues to advance, it is likely that smart classroom technology will become even more effective and sophisticated, offering even greater benefits to students. By embracing technology and using it effectively, educators can help prepare students for success in the digital age.

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Setting S.M.A.R.T. Goals as an Educator

See how using this goal-setting structure can help you achieve content-focused goals during the school year

Susan Hitt

Every August, as the summer days wind down and the school year approaches, I find myself reflecting on the previous year as I make plans for the new school year.  What went well that I’d like to maintain? Or, perhaps even more importantly, what would I like to improve upon?

Just being aware of the goals we want to achieve isn’t the same thing as making those goals happen, however. I’ve learned that the act of putting my goals down on paper for the new school year really helps me stay focused. But what’s the best way to do this? Year after year, I tried different goal-setting methods, but I found it always seemed to be like those New Years’ resolutions: Such a great idea in January, but long forgotten by February.

So how could I map out my goals in August and stick with them month after month, no matter how busy my day-to-day schedule might be? After doing some research, I came across the S.M.A.R.T. goal format. While this goal-setting approach is most often used by those in the corporate world, with a few tweaks here and there, they can easily become the educator’s new best friend.

Have you heard of the S.M.A.R.T. goal format? Here’s a quick breakdown:

Strengthening My Professional Learning Network (PLN)

S pecific : To extend my professional learning network. Why ? Having a collaborative network of educators to engage with, both face-to-face and virtually, is pivotal to continuing my own learning as an educator. Talking with my peers or on an online forum about the best way to implement a certain standard or a creative way to engage students with a piece of text is much more enjoyable than insisting on working solo.

M easurable: I will participate in at least two Twitter chats a month (one being the monthly #CoreAdvocates chat), find and follow one new educational blog each month, participate in one book study (whether virtually or face-to-face) each semester, and join and engage with Google+ communities.

A chievable: To achieve this goal, I need to do several things. I need to schedule the time on my calendar for Twitter chats so I don’t forget to participate. I also need to research how to use Google+ communities as this online PLN is relatively new to me.

R elevant: One of our district’s goals is to promote lifelong learning. By extending my own professional learning network, I’m embracing the district goal by making it a personal goal. Daily, I’m able to glean helpful suggestions and ideas from my PLN whether it’s on Twitter, Facebook, or by chatting with my colleague across the hall about her new lesson she’s working on.

T imeline: August 2017 — June 2018

When I sit down to create my goals year after year, I always keep my teaching standards in mind. At the end of the day, my job is to support student learning. Because of this, it’s important for me to ensure my own personal classroom goals align with what’s best for my students. So while expanding my PLN might not necessarily seem as though it’s focusing on the standards I need to teach, in reality, the two are very much aligned. When I have a problem, it’s my PLN who can help me. If I’m struggling with finding an engaging text to teach a reading literature standard, I can tweet out a request for help or I can walk down the hall and ask a team member. It’s important to me that we all remember we’re in this together. Our job is to not just to support our students as they continue their learning from year to year, but to support our peers in their learning venture as well. Without my PLN, I might have never discovered my best lessons. And that is why I’m focusing this year on expanding my PLN. I refuse to stop learning, because if I do, not only do I suffer, but so do my students.

You may be thinking that creating a S.M.A.R.T. goal is time-intensive. Why go to all that trouble? The answer: while it’s easy to just verbalize a goal with your colleagues or to jot out a goal on a post-it note, eventually you and your colleagues will get bogged down with the day-to-day tasks in the classroom and forget about your goal. The post-it note will get covered up with other post-it notes. This is why I utilize the S.M.A.R.T. format, because identifying not just a goal but creating an in-depth plan of action to achieve that goal is what makes S.M.A.R.T. goals work. While I often have to grapple with identifying all the pieces to my S.M.A.R.T. goals, I find that, because of that productive struggle, I’m much more vested in seeing my goal through to the end. Unlike those New Year’s goals that are long forgotten by February, I’m much more likely to find success with my classroom goals now.

So, I ask you, what’s your S.M.A.R.T. goal going to be this year? Find a pencil, pour a cup of coffee, and get started with goal-setting using the S.M.A.R.T. goal template attached to this post. I encourage you to tweet your S.M.A.R.T. goal to me using my Twitter handle @susanhitt and use #CoreAdvocates so we can work as a community to support each other in our ventures.

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9 thoughts on “ Setting S.M.A.R.T. Goals as an Educator ”

I have to wonder what other profession requires professionals to create specific goals for themselves and submit them to their superiors on an annual basis? Are medical doctors required to state how many patients they will ‘save’ over the course of the year and how they will ‘achieve’ their goal???

I agree. It’s ridiculous. We do so much of what I call “busy work”. Many of things teachers already do informally in their heads now have to be written and submitted formally to our superiors.

The answer is Yes! SMART goals do not come from education but rather business. If done correctly, they should help you grow as an educator and help to keep you focused on YOUR professional goals. Honestly, the SMART goal strategy is a great one to utilize in your personal life as well.

I’m actually looking for an article to help others learn more about using SMART goals during lesson delivery. I used them for writing IEPs, but now I would like to inform my colleagues about how SMART goals can be applied in each lesson. Thanks for this article, but it’s not tailored to my needs. 🙂

Interested to hear if you found any other useful websites?

My SMART goal for each year are the same – to survive the year with my sanity in tact.

When I looked up SMART goal, I saw that this concept is facilitated by Pearson, the writer of most of our state’s program. The perception is that if we consciously set goals, and show students what it is that they must attain, they will grow toward that goal. While it makes sense, it is ultimately tested. The people that write tests expect students to apply knowledge. While this makes sense for upper elementary and beyond, it does not always make sense for lower elementary, who developmentally are much more literal. Pearson has been shaping education according to business models of data collection, test and retest. While it might make sense in some areas, the needs of students are often set aside for the results.

SMART goal are in fact a result of a bottom line driven business. They’re meant to increase productivity of workers and improve their added value to the company’s profit by diminishing as as possible their cost per head vs input ( the labor they provide ) .In simple terms , whenever there is a KPI set by a business to maximize their profit vs their expenses , SMART goals need to be set. Which put, in a lot of situations , a a needless stress on workers , especially in more creative jobs , such as marketing , product development , editing …etc. Which makes me wonder , why educators and teachers are required to do this ? aren’t they paid to teach ? it doesn’t make any sense , because their goals are bound by their student’s goals. Example : my goal is to make my student a future engineer and a good human being 🙂 , SMART that capitalism !

I have to agree with Betty Ervin. This is busy work, and disagree with the person that brought up corporate America.

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About the Author: Susan Hitt began her journey with New Hanover County Schools in August of 2005 when she started teaching at Laney High School. After ten wonderful years there, she moved to central office where she is the high school District Lead English Language Arts teacher. Helping teachers marry content with digital technology to engage students is her passion. She strives to help teachers view collaboration as the key to success. New Hanover County is located in Wilmington, North Carolina, and serves approximately 25,000 students at its 45 public schools.

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When I was a student, school choice benefited me and it will help Tennessee children too

Education freedom scholarships, with their decentralized approach, promotes a more nimble and responsive educational system than traditional public schools..

  • Walter Blanks Jr. is a spokesperson for American Federation for Children and is a member of the Beacon Center of Tennessee Impact Board.

Gov. Bill Lee's bold proposal for  Education Freedom Scholarships  in Tennessee is a beacon of hope for parents, families, and education reformers, ushering in what would be the next evolution in the state's approach to learning and educational attainment.

The scholarships offer a groundbreaking alternative, empowering parents with the ability to tailor their children's education, while demonstrating a level of accountability that outshines traditional public schools.

During the governor’s State of the State,  Lee doubled down on his plan  to give parents and students the opportunity and access to choose the best school that works for their own personal needs.

Lee stated, “The premise behind education freedom, and the one thing that most all of us agree upon, is that parents know what’s best for their child’s education.”

Lee then went on to say, “There are thousands of parents in the state who know their student would thrive in a different setting, but the financial barrier is simply too high. It’s time that we change that. It’s time that parents get to decide — and not the government — where their child goes to school and what they learn.”  

While the battle for school choice rages on, it’s extremely important not to forget the students who would actually benefit from such a program.

School choice benefited me and my family

Growing up in Ohio,  school choice became my lifeline , rescuing me from the clutches of a failing educational system.

The traditional public school I attended was struggling to provide quality education, leaving me disheartened and uninspired. The principal of the school told my mother, “If you give us five years, we will have the middle school and the high school turned around.”

My mother responded with, “In five years, Walter will either be in jail or in a body bag.” When my family discovered the school choice program, it opened a world of possibilities. School choice was more than an alternative; it was a catalyst for change, sparking a transformative journey that continues to shape my life positively.

Since moving to Tennessee, I have quickly realized  the education outcomes  in the state are not where they should be, and many families could benefit from similar programs that are being passed across the country.

Existing education choice programs across the nation have demonstrated impressive accountability mechanisms. By allowing parents to use allocated funds for various educational expenses, such as private school tuition, tutoring, or educational materials, choice programs like Education Freedom Scholarships promote a dynamic and tailored approach to learning. 

More: Gov. Bill Lee delivers State of the State to Tennessee General Assembly

Public schools, while essential, often face bureaucratic challenges that can hinder adaptability and responsiveness.

In 2023, the state of Tennessee spent roughly $10 billion dollars on public schools with very little (if any) accountability to parents and students. In Nashville,  roughly 30%  of third grade students are proficient (or considered “on track”). Within the public school system, families without the resources to change schools are left with empty promises, little improvements, and ultimately, no other option.

Education Freedom Scholarships, with their decentralized approach, promotes a more nimble and responsive educational system. This agility allows for quicker adjustments to address the evolving needs of students, ultimately better preparing the next generation for the challenges it will face.

Gov. Bill Lee's Education Freedom Scholarship proposal offers hope for Tennessee's education system, fostering innovation and unlocking its full potential. By prioritizing students' interests, the state can deliver quality education, ensuring a brighter future and a more adaptable model. It's time for Tennessee to embrace this opportunity, ushering in an era of empowerment and accountability in education.

Walter Blanks Jr. is a spokesperson for American Federation for Children and a beneficiary of a private school choice program, driven by a lifelong commitment to improving educational access. Blanks is a member of the Beacon Center of Tennessee Impact Board.

Essay on Education for School Students and Children

500+ words essay on education.

Education is an important tool which is very useful in everybody’s life. Education is what differentiates us from other living beings on earth. It makes man the smartest creature on earth. It empowers humans and gets them ready to face challenges of life efficiently. With that being said, education still remains a luxury and not a necessity in our country. Educational awareness needs to be spread through the country to make education accessible. But, this remains incomplete without first analyzing the importance of education. Only when the people realize what significance it holds, can they consider it a necessity for a good life. In this essay on Education, we will see the importance of education and how it is a doorway to success.

essay on education

Importance of Education

Education is the most significant tool in eliminating poverty and unemployment . Moreover, it enhances the commercial scenario and benefits the country overall. So, the higher the level of education in a country, the better the chances of development are.

In addition, this education also benefits an individual in various ways. It helps a person take a better and informed decision with the use of their knowledge. This increases the success rate of a person in life.

Subsequently, education is also responsible for providing with an enhanced lifestyle. It gives you career opportunities that can increase your quality of life.

Similarly, education also helps in making a person independent. When one is educated enough, they won’t have to depend on anyone else for their livelihood. They will be self-sufficient to earn for themselves and lead a good life.

Above all, education also enhances the self-confidence of a person and makes them certain of things in life. When we talk from the countries viewpoint, even then education plays a significant role. Educated people vote for the better candidate of the country. This ensures the development and growth of a nation.

Get the huge list of more than 500 Essay Topics and Ideas

Doorway to Success

To say that education is your doorway to success would be an understatement. It serves as the key which will unlock numerous doors that will lead to success. This will, in turn, help you build a better life for yourself.

An educated person has a lot of job opportunities waiting for them on the other side of the door. They can choose from a variety of options and not be obligated to do something they dislike. Most importantly, education impacts our perception positively. It helps us choose the right path and look at things from various viewpoints rather than just one.

smart education essay

With education, you can enhance your productivity and complete a task better in comparison to an uneducated person. However, one must always ensure that education solely does not ensure success.

It is a doorway to success which requires hard work, dedication and more after which can you open it successfully. All of these things together will make you successful in life.

In conclusion, education makes you a better person and teaches you various skills. It enhances your intellect and the ability to make rational decisions. It enhances the individual growth of a person.

Education also improves the economic growth of a country . Above all, it aids in building a better society for the citizens of a country. It helps to destroy the darkness of ignorance and bring light to the world.

smart education essay

FAQs on Education

Q.1 Why is Education Important?

A.1 Education is important because it is responsible for the overall development of a person. It helps you acquire skills which are necessary for becoming successful in life.

Q.2 How does Education serve as a Doorway to Success?

A.2 Education is a doorway to success because it offers you job opportunities. Furthermore, it changes our perception of life and makes it better.

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Auburn University initiates AI smart manufacturing education program through NSF grant

Published: Feb 20, 2024 11:05 AM

By Carla Nelson

Integrating artificial intelligence (AI) into advanced manufacturing has promising potential to revolutionize productivity and generate new jobs in smart manufacturing. Several Auburn University faculty members have recently been awarded a nearly $200k National Science Foundation (NSF) Rapid Response Research (RAPID) Grant to initiate a career-driven AI educational program for high-school students to prepare them for these opportunities. This project is a collaborative effort between the College of Engineering and the College of Education.

Peter Liu, assistant professor in the Department of Industrial and Systems Engineering; Melody Russell, alumni professor of science education in the Department of Curriculum and Teaching; and Chih-hsuan Wang, professor in the Department of Educational Foundations, Leadership and Technology, have teamed up to develop an innovative AI curriculum for high school students from underserved school districts in the State of Alabama. The curriculum will focus on the integration of artificial intelligence and additive manufacturing content and processes into the science, technology, engineering and mathematics, or STEM, curriculum through a one-week summer camp.

“We can foresee that in the future AI will be a very important tool for the workforce,” Liu said. “We want to teach these students these tools at an early age to solve some of the problems in manufacturing and possibly the future.”

Russell agreed.

“This is so important for workforce development in the state of Alabama and in our region, relative to AI,” she said.   “We are excited about this collaboration, which entails the development and implementation of an innovative curriculum for 50 high school students from underserved districts. This project will also provide transformative professional development for high school teachers, which is a key element for broadening participation in STEM.”

Wang added that it’s also important for students to learn to use AI in different ways.

“We want to teach these students that they can incorporate AI in a different way, in a positive way,” she said. “It’s not about just learning it, but knowing how to utilize it to improve our life in the future.”

In addition to the students, 10 high school teachers will be recruited for a three-day intensive professional development institute before the student summer camp. Teachers will facilitate and lead the summer camp activities, engage in the development and implementation of the curriculum, and develop lessons specifically for their own classroom and school.

The team will use the summer camp outreach experience to provide insight on strategies for engaging high school students and teachers in AI and additive manufacturing content in an effort to broaden participation in STEM for students in underserved school districts and interest in careers in AI and smart manufacturing.

“We want to develop a curriculum that these teachers can take back to their school and use to build a sustainable program,” Liu said. “We hope to use this camp as a springboard to gain more funding in the future and expand this program to share with more communities.”

From left to right: Chih-hsuan Wang, professor in the Department of Educational Foundations, Leadership and Technology; Peter Liu, assistant professor in the Department of Industrial and Systems Engineering; and Melody Russell, alumni professor of science education in the Department of Curriculum and Teaching, have teamed up to develop an innovative AI curriculum for high school students from underserved school districts in the State of Alabama.

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ISC 2020: "Smart Technologies" for Society, State and Economy pp 714–723 Cite as

“Smart Technologies” in Education: Development Opportunities and Threats

  • Liudmila V. Baeva   ORCID: orcid.org/0000-0003-0439-525X 11 ,
  • Sergey A. Khrapov 11 &
  • Iskhandar M. Azhmukhamedov 11  
  • Conference paper
  • First Online: 16 October 2020

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Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 155)

The development of the modern education system around the world is connected with the application of digital technologies that have become essential for post-industrial society. Education from the traditional system of transfer of knowledge, meanings and values from teacher to student is being transformed into a system of managing the reception of information flows to students and assessment of formed competencies. In the information society, education becomes part of the modern electronic culture, with its inherent features and peculiarities. With the digitalization of learning, both new opportunities arise due to its global openness, the use of “smart technologies”, and certain threats due to the remoteness of interaction and the specificity of the virtual communication environment. The purpose of the article is to study the current trend of digitalization of education, the application of “smart technologies” in education, conducted on the basis of SWOT analysis. The methodological basis for the study will be the philosophical-axiological approach and theory of electronic culture, from the standpoint of which digital education is seen as its important component designed to adapt the new generation to the realities of digital society. As a result, risky prospects and trends for the digitalization of education will be identified, and recommendations will be made to create a safe communication and educational environment for digital learning.

  • Digitalization of education
  • “Smart technologies”
  • Electronic culture
  • Safe communication and educational environment

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The priority project in the field of education “Modern digital educational environment in the Russian Federation” was approved by the Government of the Russian Federation on October 25, 2016 as part of the state program “Development of Education” for 2013–2020, available at: http://neorusedu.ru/about .

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Acknowledgments

We express our gratitude to the Russian Foundation for Basic Research for its support of the project No. 19-29-14007 MK “Assessment of the impact of digitalization of educational and social space on people and development of a system of safe communicative and educational environment”, within the framework of which the article was prepared, as well as the reviewers for valuable comments.

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Baeva, L.V., Khrapov, S.A., Azhmukhamedov, I.M. (2021). “Smart Technologies” in Education: Development Opportunities and Threats. In: Popkova, E.G., Sergi, B.S. (eds) "Smart Technologies" for Society, State and Economy. ISC 2020. Lecture Notes in Networks and Systems, vol 155. Springer, Cham. https://doi.org/10.1007/978-3-030-59126-7_79

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Black Student’s Suspension Over Hairstyle Didn’t Violate Law, Texas Judge Rules

The trial was the latest development in a case that has prompted scrutiny of education policies and race in the United States.

A portrait shows Darryl George wearing his hair in locs, or long ropelike strands of hair, that he pins on his head in a barrel roll. He has a diamond earing in his left ear.

By Christine Hauser and Patrick McGee

Patrick McGee reported from Anahuac, Texas.

A Texas judge ruled on Thursday that a school district’s dress code, which it used to suspend a Black student last year for refusing to change the way he wears his hair, did not violate a state law meant to prohibit race-based discrimination against people based on their hairstyle.

The student, Darryl George, 18, has locs, or long ropelike strands of hair, that he pins on his head in a barrel roll, a protective style that his mother said reflected Black culture. Since the start of his junior year last August, he has faced a series of disciplinary actions at Barbers Hill High School in Mont Belvieu, about 30 miles east of Houston, after refusing to cut his hair. He was separated from his classmates, given disciplinary notices, placed in in-school suspension and sent to an off-campus program.

The hearing on Thursday, in the 253rd Judicial District Court in Anahuac, was in response to a lawsuit filed in September by the Barbers Hill Independent School District. The lawsuit argued that Mr. George was “in violation of the District’s dress and grooming code” because he wears his hair “in braids and twists” at a length that extends “below the top of a T-shirt collar, below the eyebrows, and/or below the earlobes when let down.”

The district asked State District Judge Chap B. Cain III to clarify whether the dress code violated a state law called the Texas CROWN Act, as the defendants, Mr. George and his mother, Darresha George, assert. The act, which took effect on Sept. 1, says a school district policy “may not discriminate against a hair texture or protective hairstyle commonly or historically associated with race.” It does not specifically mention hair length.

“The CROWN Act does not render unlawful those portions of the Barbers Hill dress and grooming restrictions limiting male students’ hair length,” Judge Cain said.

“I am not going to tell you that this has been an easy decision to make,” the judge said. Addressing the family, he encouraged them to “go back to the Legislature or go back to the school board because the remedy you seek can be had from either of those bodies.”

Allie Booker, a lawyer for the Georges, said she would appeal the ruling and seek an injunction to prevent the district from punishing Mr. George pending the outcome of a federal civil rights lawsuit that he and his mother filed last year against the state’s governor and attorney general.

The Georges left without commenting to reporters, more than a dozen of whom had gathered at the courthouse. State Representative Jolanda Jones said she walked them to their car.

“When I accompanied Darryl and his mom to the car, I saw a child that was crying, and he was upset and he didn’t understand,” Ms. Jones, a Democrat, said in an interview. “His mother was visibly shaking.”

Dr. Greg Poole, the superintendent of the Barbers Hill Independent School District, said in an emailed statement that the ruling “validated our position” that the dress code does not violate the state law, which “does not give students unlimited self-expression.”

The trial was the latest development in a case that has prompted scrutiny of education policies and race in the United States. At least 24 states have adopted laws that make it illegal to discriminate against students or workers because of their hairstyle.

The case involving Mr. George began soon after officials at the school objected to his locs and told Ms. George that the length of her son’s hair, even though it was pinned, violated the district’s dress code. The district subjected him to punishments, including suspension, after he refused to cut it.

Ms. George and her son filed a federal civil rights lawsuit in U.S. District Court for the Southern District of Texas in September against Texas’ governor, Greg Abbott, who signed the law, and the state’s attorney general, Ken Paxton, saying they allowed the school to violate the act.

Their lawsuit is seeking a temporary order to stop Darryl’s suspension while the case moves through the federal court system, and accuses Mr. Abbott and Mr. Paxton of “purposely or recklessly” causing Ms. George and Darryl emotional distress by not intervening.

Supporters of the family, including legislators and activists, also said the measures violated the CROWN Act .

The family’s lawsuit said that Mr. George wears locs as an “expression of cultural pride” and claims that his protections under the federal Civil Rights Act are being violated because the dress code policy disproportionately affects Black male students.

In October, Mr. George was transferred to an off-campus disciplinary program. In December, he was allowed to return to his high school but then was given another in-school suspension , this time for 13 days.

In January, Mr. Poole, the superintendent, defended the policy in an advertisement published in The Houston Chronicle , saying that districts with dress codes are safer and have higher academic performance, and that “being an American requires conformity.”

Kitty Bennett contributed research.

Christine Hauser is a reporter, covering national and foreign news. Her previous jobs in the newsroom include stints in Business covering financial markets and on the Metro desk in the police bureau. More about Christine Hauser

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