research paper about distance learning in the philippines

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Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines

Jessie s. barrot.

College of Education, Arts and Sciences, National University, Manila, Philippines

Ian I. Llenares

Leo s. del rosario, associated data.

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Recently, the education system has faced an unprecedented health crisis that has shaken up its foundation. Given today’s uncertainties, it is vital to gain a nuanced understanding of students’ online learning experience in times of the COVID-19 pandemic. Although many studies have investigated this area, limited information is available regarding the challenges and the specific strategies that students employ to overcome them. Thus, this study attempts to fill in the void. Using a mixed-methods approach, the findings revealed that the online learning challenges of college students varied in terms of type and extent. Their greatest challenge was linked to their learning environment at home, while their least challenge was technological literacy and competency. The findings further revealed that the COVID-19 pandemic had the greatest impact on the quality of the learning experience and students’ mental health. In terms of strategies employed by students, the most frequently used were resource management and utilization, help-seeking, technical aptitude enhancement, time management, and learning environment control. Implications for classroom practice, policy-making, and future research are discussed.

Introduction

Since the 1990s, the world has seen significant changes in the landscape of education as a result of the ever-expanding influence of technology. One such development is the adoption of online learning across different learning contexts, whether formal or informal, academic and non-academic, and residential or remotely. We began to witness schools, teachers, and students increasingly adopt e-learning technologies that allow teachers to deliver instruction interactively, share resources seamlessly, and facilitate student collaboration and interaction (Elaish et al., 2019 ; Garcia et al., 2018 ). Although the efficacy of online learning has long been acknowledged by the education community (Barrot, 2020 , 2021 ; Cavanaugh et al., 2009 ; Kebritchi et al., 2017 ; Tallent-Runnels et al., 2006 ; Wallace, 2003 ), evidence on the challenges in its implementation continues to build up (e.g., Boelens et al., 2017 ; Rasheed et al., 2020 ).

Recently, the education system has faced an unprecedented health crisis (i.e., COVID-19 pandemic) that has shaken up its foundation. Thus, various governments across the globe have launched a crisis response to mitigate the adverse impact of the pandemic on education. This response includes, but is not limited to, curriculum revisions, provision for technological resources and infrastructure, shifts in the academic calendar, and policies on instructional delivery and assessment. Inevitably, these developments compelled educational institutions to migrate to full online learning until face-to-face instruction is allowed. The current circumstance is unique as it could aggravate the challenges experienced during online learning due to restrictions in movement and health protocols (Gonzales et al., 2020 ; Kapasia et al., 2020 ). Given today’s uncertainties, it is vital to gain a nuanced understanding of students’ online learning experience in times of the COVID-19 pandemic. To date, many studies have investigated this area with a focus on students’ mental health (Copeland et al., 2021 ; Fawaz et al., 2021 ), home learning (Suryaman et al., 2020 ), self-regulation (Carter et al., 2020 ), virtual learning environment (Almaiah et al., 2020 ; Hew et al., 2020 ; Tang et al., 2020 ), and students’ overall learning experience (e.g., Adarkwah, 2021 ; Day et al., 2021 ; Khalil et al., 2020 ; Singh et al., 2020 ). There are two key differences that set the current study apart from the previous studies. First, it sheds light on the direct impact of the pandemic on the challenges that students experience in an online learning space. Second, the current study explores students’ coping strategies in this new learning setup. Addressing these areas would shed light on the extent of challenges that students experience in a full online learning space, particularly within the context of the pandemic. Meanwhile, our nuanced understanding of the strategies that students use to overcome their challenges would provide relevant information to school administrators and teachers to better support the online learning needs of students. This information would also be critical in revisiting the typology of strategies in an online learning environment.

Literature review

Education and the covid-19 pandemic.

In December 2019, an outbreak of a novel coronavirus, known as COVID-19, occurred in China and has spread rapidly across the globe within a few months. COVID-19 is an infectious disease caused by a new strain of coronavirus that attacks the respiratory system (World Health Organization, 2020 ). As of January 2021, COVID-19 has infected 94 million people and has caused 2 million deaths in 191 countries and territories (John Hopkins University, 2021 ). This pandemic has created a massive disruption of the educational systems, affecting over 1.5 billion students. It has forced the government to cancel national examinations and the schools to temporarily close, cease face-to-face instruction, and strictly observe physical distancing. These events have sparked the digital transformation of higher education and challenged its ability to respond promptly and effectively. Schools adopted relevant technologies, prepared learning and staff resources, set systems and infrastructure, established new teaching protocols, and adjusted their curricula. However, the transition was smooth for some schools but rough for others, particularly those from developing countries with limited infrastructure (Pham & Nguyen, 2020 ; Simbulan, 2020 ).

Inevitably, schools and other learning spaces were forced to migrate to full online learning as the world continues the battle to control the vicious spread of the virus. Online learning refers to a learning environment that uses the Internet and other technological devices and tools for synchronous and asynchronous instructional delivery and management of academic programs (Usher & Barak, 2020 ; Huang, 2019 ). Synchronous online learning involves real-time interactions between the teacher and the students, while asynchronous online learning occurs without a strict schedule for different students (Singh & Thurman, 2019 ). Within the context of the COVID-19 pandemic, online learning has taken the status of interim remote teaching that serves as a response to an exigency. However, the migration to a new learning space has faced several major concerns relating to policy, pedagogy, logistics, socioeconomic factors, technology, and psychosocial factors (Donitsa-Schmidt & Ramot, 2020 ; Khalil et al., 2020 ; Varea & González-Calvo, 2020 ). With reference to policies, government education agencies and schools scrambled to create fool-proof policies on governance structure, teacher management, and student management. Teachers, who were used to conventional teaching delivery, were also obliged to embrace technology despite their lack of technological literacy. To address this problem, online learning webinars and peer support systems were launched. On the part of the students, dropout rates increased due to economic, psychological, and academic reasons. Academically, although it is virtually possible for students to learn anything online, learning may perhaps be less than optimal, especially in courses that require face-to-face contact and direct interactions (Franchi, 2020 ).

Related studies

Recently, there has been an explosion of studies relating to the new normal in education. While many focused on national policies, professional development, and curriculum, others zeroed in on the specific learning experience of students during the pandemic. Among these are Copeland et al. ( 2021 ) and Fawaz et al. ( 2021 ) who examined the impact of COVID-19 on college students’ mental health and their coping mechanisms. Copeland et al. ( 2021 ) reported that the pandemic adversely affected students’ behavioral and emotional functioning, particularly attention and externalizing problems (i.e., mood and wellness behavior), which were caused by isolation, economic/health effects, and uncertainties. In Fawaz et al.’s ( 2021 ) study, students raised their concerns on learning and evaluation methods, overwhelming task load, technical difficulties, and confinement. To cope with these problems, students actively dealt with the situation by seeking help from their teachers and relatives and engaging in recreational activities. These active-oriented coping mechanisms of students were aligned with Carter et al.’s ( 2020 ), who explored students’ self-regulation strategies.

In another study, Tang et al. ( 2020 ) examined the efficacy of different online teaching modes among engineering students. Using a questionnaire, the results revealed that students were dissatisfied with online learning in general, particularly in the aspect of communication and question-and-answer modes. Nonetheless, the combined model of online teaching with flipped classrooms improved students’ attention, academic performance, and course evaluation. A parallel study was undertaken by Hew et al. ( 2020 ), who transformed conventional flipped classrooms into fully online flipped classes through a cloud-based video conferencing app. Their findings suggested that these two types of learning environments were equally effective. They also offered ways on how to effectively adopt videoconferencing-assisted online flipped classrooms. Unlike the two studies, Suryaman et al. ( 2020 ) looked into how learning occurred at home during the pandemic. Their findings showed that students faced many obstacles in a home learning environment, such as lack of mastery of technology, high Internet cost, and limited interaction/socialization between and among students. In a related study, Kapasia et al. ( 2020 ) investigated how lockdown impacts students’ learning performance. Their findings revealed that the lockdown made significant disruptions in students’ learning experience. The students also reported some challenges that they faced during their online classes. These include anxiety, depression, poor Internet service, and unfavorable home learning environment, which were aggravated when students are marginalized and from remote areas. Contrary to Kapasia et al.’s ( 2020 ) findings, Gonzales et al. ( 2020 ) found that confinement of students during the pandemic had significant positive effects on their performance. They attributed these results to students’ continuous use of learning strategies which, in turn, improved their learning efficiency.

Finally, there are those that focused on students’ overall online learning experience during the COVID-19 pandemic. One such study was that of Singh et al. ( 2020 ), who examined students’ experience during the COVID-19 pandemic using a quantitative descriptive approach. Their findings indicated that students appreciated the use of online learning during the pandemic. However, half of them believed that the traditional classroom setting was more effective than the online learning platform. Methodologically, the researchers acknowledge that the quantitative nature of their study restricts a deeper interpretation of the findings. Unlike the above study, Khalil et al. ( 2020 ) qualitatively explored the efficacy of synchronized online learning in a medical school in Saudi Arabia. The results indicated that students generally perceive synchronous online learning positively, particularly in terms of time management and efficacy. However, they also reported technical (internet connectivity and poor utility of tools), methodological (content delivery), and behavioral (individual personality) challenges. Their findings also highlighted the failure of the online learning environment to address the needs of courses that require hands-on practice despite efforts to adopt virtual laboratories. In a parallel study, Adarkwah ( 2021 ) examined students’ online learning experience during the pandemic using a narrative inquiry approach. The findings indicated that Ghanaian students considered online learning as ineffective due to several challenges that they encountered. Among these were lack of social interaction among students, poor communication, lack of ICT resources, and poor learning outcomes. More recently, Day et al. ( 2021 ) examined the immediate impact of COVID-19 on students’ learning experience. Evidence from six institutions across three countries revealed some positive experiences and pre-existing inequities. Among the reported challenges are lack of appropriate devices, poor learning space at home, stress among students, and lack of fieldwork and access to laboratories.

Although there are few studies that report the online learning challenges that higher education students experience during the pandemic, limited information is available regarding the specific strategies that they use to overcome them. It is in this context that the current study was undertaken. This mixed-methods study investigates students’ online learning experience in higher education. Specifically, the following research questions are addressed: (1) What is the extent of challenges that students experience in an online learning environment? (2) How did the COVID-19 pandemic impact the online learning challenges that students experience? (3) What strategies did students use to overcome the challenges?

Conceptual framework

The typology of challenges examined in this study is largely based on Rasheed et al.’s ( 2020 ) review of students’ experience in an online learning environment. These challenges are grouped into five general clusters, namely self-regulation (SRC), technological literacy and competency (TLCC), student isolation (SIC), technological sufficiency (TSC), and technological complexity (TCC) challenges (Rasheed et al., 2020 , p. 5). SRC refers to a set of behavior by which students exercise control over their emotions, actions, and thoughts to achieve learning objectives. TLCC relates to a set of challenges about students’ ability to effectively use technology for learning purposes. SIC relates to the emotional discomfort that students experience as a result of being lonely and secluded from their peers. TSC refers to a set of challenges that students experience when accessing available online technologies for learning. Finally, there is TCC which involves challenges that students experience when exposed to complex and over-sufficient technologies for online learning.

To extend Rasheed et al. ( 2020 ) categories and to cover other potential challenges during online classes, two more clusters were added, namely learning resource challenges (LRC) and learning environment challenges (LEC) (Buehler, 2004 ; Recker et al., 2004 ; Seplaki et al., 2014 ; Xue et al., 2020 ). LRC refers to a set of challenges that students face relating to their use of library resources and instructional materials, whereas LEC is a set of challenges that students experience related to the condition of their learning space that shapes their learning experiences, beliefs, and attitudes. Since learning environment at home and learning resources available to students has been reported to significantly impact the quality of learning and their achievement of learning outcomes (Drane et al., 2020 ; Suryaman et al., 2020 ), the inclusion of LRC and LEC would allow us to capture other important challenges that students experience during the pandemic, particularly those from developing regions. This comprehensive list would provide us a clearer and detailed picture of students’ experiences when engaged in online learning in an emergency. Given the restrictions in mobility at macro and micro levels during the pandemic, it is also expected that such conditions would aggravate these challenges. Therefore, this paper intends to understand these challenges from students’ perspectives since they are the ones that are ultimately impacted when the issue is about the learning experience. We also seek to explore areas that provide inconclusive findings, thereby setting the path for future research.

Material and methods

The present study adopted a descriptive, mixed-methods approach to address the research questions. This approach allowed the researchers to collect complex data about students’ experience in an online learning environment and to clearly understand the phenomena from their perspective.

Participants

This study involved 200 (66 male and 134 female) students from a private higher education institution in the Philippines. These participants were Psychology, Physical Education, and Sports Management majors whose ages ranged from 17 to 25 ( x ̅  = 19.81; SD  = 1.80). The students have been engaged in online learning for at least two terms in both synchronous and asynchronous modes. The students belonged to low- and middle-income groups but were equipped with the basic online learning equipment (e.g., computer, headset, speakers) and computer skills necessary for their participation in online classes. Table ​ Table1 1 shows the primary and secondary platforms that students used during their online classes. The primary platforms are those that are formally adopted by teachers and students in a structured academic context, whereas the secondary platforms are those that are informally and spontaneously used by students and teachers for informal learning and to supplement instructional delivery. Note that almost all students identified MS Teams as their primary platform because it is the official learning management system of the university.

Participants’ Online Learning Platforms

Informed consent was sought from the participants prior to their involvement. Before students signed the informed consent form, they were oriented about the objectives of the study and the extent of their involvement. They were also briefed about the confidentiality of information, their anonymity, and their right to refuse to participate in the investigation. Finally, the participants were informed that they would incur no additional cost from their participation.

Instrument and data collection

The data were collected using a retrospective self-report questionnaire and a focused group discussion (FGD). A self-report questionnaire was considered appropriate because the indicators relate to affective responses and attitude (Araujo et al., 2017 ; Barrot, 2016 ; Spector, 1994 ). Although the participants may tell more than what they know or do in a self-report survey (Matsumoto, 1994 ), this challenge was addressed by explaining to them in detail each of the indicators and using methodological triangulation through FGD. The questionnaire was divided into four sections: (1) participant’s personal information section, (2) the background information on the online learning environment, (3) the rating scale section for the online learning challenges, (4) the open-ended section. The personal information section asked about the students’ personal information (name, school, course, age, and sex), while the background information section explored the online learning mode and platforms (primary and secondary) used in class, and students’ length of engagement in online classes. The rating scale section contained 37 items that relate to SRC (6 items), TLCC (10 items), SIC (4 items), TSC (6 items), TCC (3 items), LRC (4 items), and LEC (4 items). The Likert scale uses six scores (i.e., 5– to a very great extent , 4– to a great extent , 3– to a moderate extent , 2– to some extent , 1– to a small extent , and 0 –not at all/negligible ) assigned to each of the 37 items. Finally, the open-ended questions asked about other challenges that students experienced, the impact of the pandemic on the intensity or extent of the challenges they experienced, and the strategies that the participants employed to overcome the eight different types of challenges during online learning. Two experienced educators and researchers reviewed the questionnaire for clarity, accuracy, and content and face validity. The piloting of the instrument revealed that the tool had good internal consistency (Cronbach’s α = 0.96).

The FGD protocol contains two major sections: the participants’ background information and the main questions. The background information section asked about the students’ names, age, courses being taken, online learning mode used in class. The items in the main questions section covered questions relating to the students’ overall attitude toward online learning during the pandemic, the reasons for the scores they assigned to each of the challenges they experienced, the impact of the pandemic on students’ challenges, and the strategies they employed to address the challenges. The same experts identified above validated the FGD protocol.

Both the questionnaire and the FGD were conducted online via Google survey and MS Teams, respectively. It took approximately 20 min to complete the questionnaire, while the FGD lasted for about 90 min. Students were allowed to ask for clarification and additional explanations relating to the questionnaire content, FGD, and procedure. Online surveys and interview were used because of the ongoing lockdown in the city. For the purpose of triangulation, 20 (10 from Psychology and 10 from Physical Education and Sports Management) randomly selected students were invited to participate in the FGD. Two separate FGDs were scheduled for each group and were facilitated by researcher 2 and researcher 3, respectively. The interviewers ensured that the participants were comfortable and open to talk freely during the FGD to avoid social desirability biases (Bergen & Labonté, 2020 ). These were done by informing the participants that there are no wrong responses and that their identity and responses would be handled with the utmost confidentiality. With the permission of the participants, the FGD was recorded to ensure that all relevant information was accurately captured for transcription and analysis.

Data analysis

To address the research questions, we used both quantitative and qualitative analyses. For the quantitative analysis, we entered all the data into an excel spreadsheet. Then, we computed the mean scores ( M ) and standard deviations ( SD ) to determine the level of challenges experienced by students during online learning. The mean score for each descriptor was interpreted using the following scheme: 4.18 to 5.00 ( to a very great extent ), 3.34 to 4.17 ( to a great extent ), 2.51 to 3.33 ( to a moderate extent ), 1.68 to 2.50 ( to some extent ), 0.84 to 1.67 ( to a small extent ), and 0 to 0.83 ( not at all/negligible ). The equal interval was adopted because it produces more reliable and valid information than other types of scales (Cicchetti et al., 2006 ).

For the qualitative data, we analyzed the students’ responses in the open-ended questions and the transcribed FGD using the predetermined categories in the conceptual framework. Specifically, we used multilevel coding in classifying the codes from the transcripts (Birks & Mills, 2011 ). To do this, we identified the relevant codes from the responses of the participants and categorized these codes based on the similarities or relatedness of their properties and dimensions. Then, we performed a constant comparative and progressive analysis of cases to allow the initially identified subcategories to emerge and take shape. To ensure the reliability of the analysis, two coders independently analyzed the qualitative data. Both coders familiarize themselves with the purpose, research questions, research method, and codes and coding scheme of the study. They also had a calibration session and discussed ways on how they could consistently analyze the qualitative data. Percent of agreement between the two coders was 86 percent. Any disagreements in the analysis were discussed by the coders until an agreement was achieved.

This study investigated students’ online learning experience in higher education within the context of the pandemic. Specifically, we identified the extent of challenges that students experienced, how the COVID-19 pandemic impacted their online learning experience, and the strategies that they used to confront these challenges.

The extent of students’ online learning challenges

Table ​ Table2 2 presents the mean scores and SD for the extent of challenges that students’ experienced during online learning. Overall, the students experienced the identified challenges to a moderate extent ( x ̅  = 2.62, SD  = 1.03) with scores ranging from x ̅  = 1.72 ( to some extent ) to x ̅  = 3.58 ( to a great extent ). More specifically, the greatest challenge that students experienced was related to the learning environment ( x ̅  = 3.49, SD  = 1.27), particularly on distractions at home, limitations in completing the requirements for certain subjects, and difficulties in selecting the learning areas and study schedule. It is, however, found that the least challenge was on technological literacy and competency ( x ̅  = 2.10, SD  = 1.13), particularly on knowledge and training in the use of technology, technological intimidation, and resistance to learning technologies. Other areas that students experienced the least challenge are Internet access under TSC and procrastination under SRC. Nonetheless, nearly half of the students’ responses per indicator rated the challenges they experienced as moderate (14 of the 37 indicators), particularly in TCC ( x ̅  = 2.51, SD  = 1.31), SIC ( x ̅  = 2.77, SD  = 1.34), and LRC ( x ̅  = 2.93, SD  = 1.31).

The Extent of Students’ Challenges during the Interim Online Learning

Out of 200 students, 181 responded to the question about other challenges that they experienced. Most of their responses were already covered by the seven predetermined categories, except for 18 responses related to physical discomfort ( N  = 5) and financial challenges ( N  = 13). For instance, S108 commented that “when it comes to eyes and head, my eyes and head get ache if the session of class was 3 h straight in front of my gadget.” In the same vein, S194 reported that “the long exposure to gadgets especially laptop, resulting in body pain & headaches.” With reference to physical financial challenges, S66 noted that “not all the time I have money to load”, while S121 claimed that “I don't know until when are we going to afford budgeting our money instead of buying essentials.”

Impact of the pandemic on students’ online learning challenges

Another objective of this study was to identify how COVID-19 influenced the online learning challenges that students experienced. As shown in Table ​ Table3, 3 , most of the students’ responses were related to teaching and learning quality ( N  = 86) and anxiety and other mental health issues ( N  = 52). Regarding the adverse impact on teaching and learning quality, most of the comments relate to the lack of preparation for the transition to online platforms (e.g., S23, S64), limited infrastructure (e.g., S13, S65, S99, S117), and poor Internet service (e.g., S3, S9, S17, S41, S65, S99). For the anxiety and mental health issues, most students reported that the anxiety, boredom, sadness, and isolation they experienced had adversely impacted the way they learn (e.g., S11, S130), completing their tasks/activities (e.g., S56, S156), and their motivation to continue studying (e.g., S122, S192). The data also reveal that COVID-19 aggravated the financial difficulties experienced by some students ( N  = 16), consequently affecting their online learning experience. This financial impact mainly revolved around the lack of funding for their online classes as a result of their parents’ unemployment and the high cost of Internet data (e.g., S18, S113, S167). Meanwhile, few concerns were raised in relation to COVID-19’s impact on mobility ( N  = 7) and face-to-face interactions ( N  = 7). For instance, some commented that the lack of face-to-face interaction with her classmates had a detrimental effect on her learning (S46) and socialization skills (S36), while others reported that restrictions in mobility limited their learning experience (S78, S110). Very few comments were related to no effect ( N  = 4) and positive effect ( N  = 2). The above findings suggest the pandemic had additive adverse effects on students’ online learning experience.

Summary of students’ responses on the impact of COVID-19 on their online learning experience

Students’ strategies to overcome challenges in an online learning environment

The third objective of this study is to identify the strategies that students employed to overcome the different online learning challenges they experienced. Table ​ Table4 4 presents that the most commonly used strategies used by students were resource management and utilization ( N  = 181), help-seeking ( N  = 155), technical aptitude enhancement ( N  = 122), time management ( N  = 98), and learning environment control ( N  = 73). Not surprisingly, the top two strategies were also the most consistently used across different challenges. However, looking closely at each of the seven challenges, the frequency of using a particular strategy varies. For TSC and LRC, the most frequently used strategy was resource management and utilization ( N  = 52, N  = 89, respectively), whereas technical aptitude enhancement was the students’ most preferred strategy to address TLCC ( N  = 77) and TCC ( N  = 38). In the case of SRC, SIC, and LEC, the most frequently employed strategies were time management ( N  = 71), psychological support ( N  = 53), and learning environment control ( N  = 60). In terms of consistency, help-seeking appears to be the most consistent across the different challenges in an online learning environment. Table ​ Table4 4 further reveals that strategies used by students within a specific type of challenge vary.

Students’ Strategies to Overcome Online Learning Challenges

Discussion and conclusions

The current study explores the challenges that students experienced in an online learning environment and how the pandemic impacted their online learning experience. The findings revealed that the online learning challenges of students varied in terms of type and extent. Their greatest challenge was linked to their learning environment at home, while their least challenge was technological literacy and competency. Based on the students’ responses, their challenges were also found to be aggravated by the pandemic, especially in terms of quality of learning experience, mental health, finances, interaction, and mobility. With reference to previous studies (i.e., Adarkwah, 2021 ; Copeland et al., 2021 ; Day et al., 2021 ; Fawaz et al., 2021 ; Kapasia et al., 2020 ; Khalil et al., 2020 ; Singh et al., 2020 ), the current study has complemented their findings on the pedagogical, logistical, socioeconomic, technological, and psychosocial online learning challenges that students experience within the context of the COVID-19 pandemic. Further, this study extended previous studies and our understanding of students’ online learning experience by identifying both the presence and extent of online learning challenges and by shedding light on the specific strategies they employed to overcome them.

Overall findings indicate that the extent of challenges and strategies varied from one student to another. Hence, they should be viewed as a consequence of interaction several many factors. Students’ responses suggest that their online learning challenges and strategies were mediated by the resources available to them, their interaction with their teachers and peers, and the school’s existing policies and guidelines for online learning. In the context of the pandemic, the imposed lockdowns and students’ socioeconomic condition aggravated the challenges that students experience.

While most studies revealed that technology use and competency were the most common challenges that students face during the online classes (see Rasheed et al., 2020 ), the case is a bit different in developing countries in times of pandemic. As the findings have shown, the learning environment is the greatest challenge that students needed to hurdle, particularly distractions at home (e.g., noise) and limitations in learning space and facilities. This data suggests that online learning challenges during the pandemic somehow vary from the typical challenges that students experience in a pre-pandemic online learning environment. One possible explanation for this result is that restriction in mobility may have aggravated this challenge since they could not go to the school or other learning spaces beyond the vicinity of their respective houses. As shown in the data, the imposition of lockdown restricted students’ learning experience (e.g., internship and laboratory experiments), limited their interaction with peers and teachers, caused depression, stress, and anxiety among students, and depleted the financial resources of those who belong to lower-income group. All of these adversely impacted students’ learning experience. This finding complemented earlier reports on the adverse impact of lockdown on students’ learning experience and the challenges posed by the home learning environment (e.g., Day et al., 2021 ; Kapasia et al., 2020 ). Nonetheless, further studies are required to validate the impact of restrictions on mobility on students’ online learning experience. The second reason that may explain the findings relates to students’ socioeconomic profile. Consistent with the findings of Adarkwah ( 2021 ) and Day et al. ( 2021 ), the current study reveals that the pandemic somehow exposed the many inequities in the educational systems within and across countries. In the case of a developing country, families from lower socioeconomic strata (as in the case of the students in this study) have limited learning space at home, access to quality Internet service, and online learning resources. This is the reason the learning environment and learning resources recorded the highest level of challenges. The socioeconomic profile of the students (i.e., low and middle-income group) is the same reason financial problems frequently surfaced from their responses. These students frequently linked the lack of financial resources to their access to the Internet, educational materials, and equipment necessary for online learning. Therefore, caution should be made when interpreting and extending the findings of this study to other contexts, particularly those from higher socioeconomic strata.

Among all the different online learning challenges, the students experienced the least challenge on technological literacy and competency. This is not surprising considering a plethora of research confirming Gen Z students’ (born since 1996) high technological and digital literacy (Barrot, 2018 ; Ng, 2012 ; Roblek et al., 2019 ). Regarding the impact of COVID-19 on students’ online learning experience, the findings reveal that teaching and learning quality and students’ mental health were the most affected. The anxiety that students experienced does not only come from the threats of COVID-19 itself but also from social and physical restrictions, unfamiliarity with new learning platforms, technical issues, and concerns about financial resources. These findings are consistent with that of Copeland et al. ( 2021 ) and Fawaz et al. ( 2021 ), who reported the adverse effects of the pandemic on students’ mental and emotional well-being. This data highlights the need to provide serious attention to the mediating effects of mental health, restrictions in mobility, and preparedness in delivering online learning.

Nonetheless, students employed a variety of strategies to overcome the challenges they faced during online learning. For instance, to address the home learning environment problems, students talked to their family (e.g., S12, S24), transferred to a quieter place (e.g., S7, S 26), studied at late night where all family members are sleeping already (e.g., S51), and consulted with their classmates and teachers (e.g., S3, S9, S156, S193). To overcome the challenges in learning resources, students used the Internet (e.g., S20, S27, S54, S91), joined Facebook groups that share free resources (e.g., S5), asked help from family members (e.g., S16), used resources available at home (e.g., S32), and consulted with the teachers (e.g., S124). The varying strategies of students confirmed earlier reports on the active orientation that students take when faced with academic- and non-academic-related issues in an online learning space (see Fawaz et al., 2021 ). The specific strategies that each student adopted may have been shaped by different factors surrounding him/her, such as available resources, student personality, family structure, relationship with peers and teacher, and aptitude. To expand this study, researchers may further investigate this area and explore how and why different factors shape their use of certain strategies.

Several implications can be drawn from the findings of this study. First, this study highlighted the importance of emergency response capability and readiness of higher education institutions in case another crisis strikes again. Critical areas that need utmost attention include (but not limited to) national and institutional policies, protocol and guidelines, technological infrastructure and resources, instructional delivery, staff development, potential inequalities, and collaboration among key stakeholders (i.e., parents, students, teachers, school leaders, industry, government education agencies, and community). Second, the findings have expanded our understanding of the different challenges that students might confront when we abruptly shift to full online learning, particularly those from countries with limited resources, poor Internet infrastructure, and poor home learning environment. Schools with a similar learning context could use the findings of this study in developing and enhancing their respective learning continuity plans to mitigate the adverse impact of the pandemic. This study would also provide students relevant information needed to reflect on the possible strategies that they may employ to overcome the challenges. These are critical information necessary for effective policymaking, decision-making, and future implementation of online learning. Third, teachers may find the results useful in providing proper interventions to address the reported challenges, particularly in the most critical areas. Finally, the findings provided us a nuanced understanding of the interdependence of learning tools, learners, and learning outcomes within an online learning environment; thus, giving us a multiperspective of hows and whys of a successful migration to full online learning.

Some limitations in this study need to be acknowledged and addressed in future studies. One limitation of this study is that it exclusively focused on students’ perspectives. Future studies may widen the sample by including all other actors taking part in the teaching–learning process. Researchers may go deeper by investigating teachers’ views and experience to have a complete view of the situation and how different elements interact between them or affect the others. Future studies may also identify some teacher-related factors that could influence students’ online learning experience. In the case of students, their age, sex, and degree programs may be examined in relation to the specific challenges and strategies they experience. Although the study involved a relatively large sample size, the participants were limited to college students from a Philippine university. To increase the robustness of the findings, future studies may expand the learning context to K-12 and several higher education institutions from different geographical regions. As a final note, this pandemic has undoubtedly reshaped and pushed the education system to its limits. However, this unprecedented event is the same thing that will make the education system stronger and survive future threats.

Authors’ contributions

Jessie Barrot led the planning, prepared the instrument, wrote the report, and processed and analyzed data. Ian Llenares participated in the planning, fielded the instrument, processed and analyzed data, reviewed the instrument, and contributed to report writing. Leo del Rosario participated in the planning, fielded the instrument, processed and analyzed data, reviewed the instrument, and contributed to report writing.

No funding was received in the conduct of this study.

Availability of data and materials

Declarations.

The study has undergone appropriate ethics protocol.

Informed consent was sought from the participants.

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Online classes and learning in the Philippines during the Covid-19 Pandemic

The COVID-19 pandemic brought great disruption to all aspects of life specifically on how classes were conducted both in an offline and online modes. The sudden shift to purely online method of teaching and learning was a result of the lockdowns that were imposed by the Philippine government. While some institutions have dealt with the situation by shutting down operations, others continued to deliver instructions and lessons using the Internet and different applications that support online learning. The continuation of classes online had caused several issues from students and teachers ranging from lack of technology to mental health matters. Finally, recommendations were asserted to mitigate the presented concerns and improve the delivery of the necessary quality education to the intended learners.

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Knowing that education has been inaccessible and ineffective to some students in the Philippines, it is crucial to know the efficacy and success of the new learning setup during this time of the pandemic to assess if these new modalities are beneficial to the students or not. This paper reviewed and studied the various perceptions and lived experiences of selected students in a private university in Manila regarding online classes amidst the pandemic. Using a phenomenological approach, the researchers gathered data by interviewing 15 students who are attending online classes. Findings and results were drawn on the themes created by the researchers. It can be seen that majority of the students find online classes ineffective and only cater the privileged. Furthermore, lessons and discussions are difficult to digest using the current mode of learning. These findings signify a need to improve the mode of learning in order to provide a quality and effective education to students despite the current crisis faced by the country. Keywords: distance learning, online learning, online classes

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Understanding students' experiences towards online learning can help in devising innovative pedagogical approaches and creating effective online learning spaces. This study aimed to solicit the perception of 80 undergraduate students in one of the leading private institutions in the Philippines towards the compulsory shift from a blended to fully online learning modality amidst the novel coronavirus (COVID-19) pandemic. The study used a descriptive research design involving online surveys which contained Likert scale items and open-ended questions assessing one's capacity for and the challenges to online learning, as well as the proposed recommendations for enhancing the overall online class experience. Descriptive statistics was used to group data across different subsets. Likewise, a content analysis of qualitative variables of the actual experiences of online classes using the school's learning management system was prepared. Results indicate four self-perceived challenges in online learning: technological and infrastructural difficulties, individual readiness, instructional struggles, and domestic barriers. The study recommends re-evaluation and modification of current online learning guidelines to address the aforesaid challenges and build a genuinely resilient model for technology-driven and care-centered education based on student recommendations and challenges experienced.

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In light of the learning continuity challenges experienced by educational institutions in the Philippines amidst the onset of the Covid-19 health crisis, the research serves to assess the conduct of emergency response online classes in a Philippine city schools division. It utilized a researcher-made instrument which assessed the profile of the respondents; their level of competence and confidence in conducting and supervising online classes; the level of preparedness of the schools; the levels of difficulty in lesson delivery and instructional supervision; and perceived advantages, disadvantages, and suggestions for improvement of online classes. Through purposive sampling, the respondents comprised 91 teachers and 24 instructional supervisors from 18 schools. Results of the study revealed that teachers and instructional supervisors needed experience and training to be able to efficiently and effectively perform their tasks in online classes; and that there were students and teachers who were not able to regularly participate in online classes due to lack of resources. Respondents also said that online classes were flexible in terms of schedule and choice of strategies, able to ensure learning continuity, were convenient, and efficient in terms of saving time, money, and effort. However, they also said that online classes had decreased participation rate, were ineffective, and had limited interaction and socialization. Conduct of training/orientation and regular practice on online classes, and ensuring needed infrastructure and resources are in place and available, respectively; as well as further research on the topic were suggested.

Education and Information Technologies

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rimba hamid

This study aims to obtain an in-depth overview of (1) the distribution of students at the Department of PGSD FKIP UHO based on domicile in implementing online learning during the Covid-19 period; (2) infrastructure support for the effectiveness of online learning in the Covid-19 period; and (3) students' perceptions about online learning conducted by lecturers of the Department of PGSD FKIP UHO during Covid-19. This research was conducted in May 2020, which was included in the descriptive study, by conducting a survey of students at the Department of PGSD FKIP UHO, which was spread across all districts/cities in Southeast Sulawesi and other regions. Data collection techniques using open and closed questionnaires, with the research subjects of the class of 2017, 2018 and 2019 students who filled 316 questionnaires online from the link sent. Data obtained from students in the form of qualitative and quantitative raw data collected online and converted in Excel format. The data was...

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The Corona virus (Covid-19) pandemic out broken at the late 2019 was reported as a cluster of cases in December at Wuhan, China by The World Health Organization. The pandemic has been lasting about a year claimed more than 55 million cases and 1.5 million of death globally. This has brought into drastic changes in the normal lifestyle of people worldwide, especially into the routine of education field creating many changes into their policies and practices. The Pandemic has disrupted the cl assroom education system and paved a new normal way to online education system. The Information Communication Technologies have provided a rescue hand to bring back the student and teacher communication through online classes to persist the education. The study involves in analyzing the new normal practices at education sector in providing their classes online and the precautionary measures in enhancing the effectiveness of online classes.

Kimkong Heng

Afraseyab khattak

Afraseyab Khattak , sayyed Shah

Background: The spread of COVID-19 triggered a range of health sector responses. As a response to minimize the spread,e-learning schemes are employed in many countries including Pakistan. It is playing an important role during this outbreak; however, there are technical, educational, financial, infrastructural, and socioeconomic barriers that exist in the developing countries like Pakistan. These barriers have huge impact on the e-learning process in the country on both students and teachers. Purpose: This study tends to investigate the impact of online classes on students learning process and teachers fulfilling their responsibilities at university level, particularly during the lockdown of the third wave of COVID-19. Methods: For the data collection, a descriptive cross-sectional online and self-administrated survey has been conducted. The study sample has been made from eight different private and public sector universities of Khyber Pakhtunkhwa, Pakistan. Results: The results of the study have presented interesting facts which are not common is developed countries. Around 47.5% of teachers have reported their anxiousness about their online class cause of electrical problems and also 30.5% of the Internet connectivity issues. More than half of the students i.e., 58.5% have faced disturbance due to power shortage (load shedding) and around 56.7% have highlighted the Internet issue including availability and signal strength.The study has also shown that only 59% of the students have fully access their online

Journal ijmr.net.in(UGC Approved)

Corona virus disease (COVID-19) is an infectious disease caused by newly discovered corona virus. It is slowing down the world economy. Each and every sector whether working or non-working has been totally affected by it. Educational issues have grown up to a very large extent due to the pandemic. Educational issues are one of major issues among those topics which need to be taken into consideration now days. Internet has changed the things that how we communicate nowadays, Online teaching during this pandemic Covid-19 has proved to be another perk of technology. Teachers are efficiently taking online classes but the questions arise the consideration and challenges that students and teachers are facing. Study is to throw light on some of the major concerns regarding it.

Shivani Sawhney

The lockdown has compelled many educational institutions to cancel their classes, examinations etc. and to choose the online modes. In this regard, E-learning tools have played decisive role during this pandemic, helping educational institute to facilitate students learning. The use of suitable and relevant pedagogy for online education may depend on the expertise and exposure to information technology for both educators and the students. The present study assesses the challenges faced by students and its impact on their studies due to online classes during Covid-19. A total of 140 respondents were participated in survey that was pursuing their graduation. The research instrument used for survey was Google form and link was created and sends to the students by WhatsApp mode. The results reveal that the low connectivity issue was the one of the hurdle students were facing. Results also indicate that online learning has reduced the quality of education.

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Original research article, teaching and learning continuity amid and beyond the pandemic.

• Office of the University President, Palompon - Office of the Vice-President for Academic Affairs, Garcia-Center for Research and Development, Olvido - Office of the Board and University Secretary, Cebu, Philippines

The study explored the challenges and issues in teaching and learning continuity of public higher education in the Philippines as a result of the COVID-19 pandemic. The study employed the exploratory mixed-method triangulation design and analyzed the data gathered from 3, 989 respondents composed of students and faculty members. It was found out that during school lockdowns, the teachers made adjustments in teaching and learning designs guided by the policies implemented by the institution. Most of the students had difficulty complying with the learning activities and requirements due to limited or no internet connectivity. Emerging themes were identified from the qualitative responses to include the trajectory for flexible learning delivery, the role of technology, the teaching and learning environment, and the prioritization of safety and security. Scenario analysis provided the contextual basis for strategic actions amid and beyond the pandemic. To ensure teaching and learning continuity, it is concluded that higher education institutions have to migrate to flexible teaching and learning modality recalibrate the curriculum, capacitate the faculty, upgrade the infrastructure, implement a strategic plan and assess all aspects of the plan.

Introduction

The COVID-19 pandemic has created unprecedented challenges economically, socially, and politically across the globe. More than just a health crisis, it has resulted in an educational crisis. During lockdowns and quarantines, 87% of the world’s student population was affected and 1.52 billion learners were out of school and related educational institutions ( UNESCO Learning Portal, 2020 ). The suddenness, uncertainty, and volatility of COVID-19 left the education system in a rush of addressing the changing learning landscape.

The disruption of COVID-19 in the educational system is of great magnitude that universities have to cope with at the soonest possible time. The call is for higher education institutions to develop a resilient learning system using evidence-based and needs-based information so that responsive and proactive measures can be instituted. Coping with the effects of COVID-19 in higher education institutions demands a variety of perspectives among stakeholders. Consultation needs to include the administration who supports the teaching-learning processes, the students who are the core of the system, the faculty members or teachers who perform various academic roles, parents, and guardians who share the responsibility of learning continuity, the community, and the external partners who contribute to the completion of the educational requirements of the students. These complicated identities show that an institution of higher learning has a large number of stakeholders ( Illanes et al., 2020 ; Smalley, 2020 ). In the context of the pandemic, universities have to start understanding and identifying medium-term and long-term implications of this phenomenon on teaching, learning, student experience, infrastructure, operation, and staff. Scenario analysis and understanding of the context of each university are necessary to the current challenges they are confronted with (Frankki et al., 2020). Universities have to be resilient in times of crisis. Resiliency in the educational system is the ability to overcome challenges of all kinds–trauma, tragedy, crises, and bounce back stronger, wiser, and more personally powerful ( Henderson, 2012 ). The educational system must prepare to develop plans to move forward and address the new normal after the crisis. To be resilient, higher education needs to address teaching and learning continuity amid and beyond the pandemic.

Teaching and Learning in Times of Crisis

The teaching and learning process assumes a different shape in times of crisis. When disasters and crises (man-made and natural) occur, schools and colleges need to be resilient and find new ways to continue the teaching–learning activities ( Chang-Richards et al., 2013 ). One emerging reality as a result of the world health crisis is the migration to online learning modalities to mitigate the risk of face-to-face interaction. Universities are forced to migrate from face-to-face delivery to online modality as a result of the pandemic. In the Philippines, most universities including Cebu Normal University have resorted to online learning during school lockdowns. However, this sudden shift has resulted in problems especially for learners without access to technology. When online learning modality is used as a result of the pandemic, the gap between those who have connectivity and those without widened. The continuing academic engagement has been a challenge for teachers and students due to access and internet connectivity.

Considering the limitation on connectivity, the concept of flexible learning emerged as an option for online learning especially in higher institutions in the Philippines. Flexible learning focuses on giving students choice in the pace, place, and mode of students’ learning which can be promoted through appropriate pedagogical practice ( Gordon, 2014 ). The learners are provided with the option on how he/she will continue with his/her studies, where and when he/she can proceed, and in what ways can the learners comply with the requirements and show evidences of learning outcomes. Flexible learning and teaching span a multitude of approaches that can meet the varied needs of diverse learners. These include “independence in terms of time and location of learning, and the availability of some degree of choice in the curriculum (including content, learning strategies, and assessment) and the use of contemporary information and communication technologies to support a range of learning strategies” ( Alexander, 2010 ).

One key component in migrating to flexible modality is to consider how flexibility is integrated into the key dimensions of teaching and learning. One major consideration is leveraging flexibility in the curriculum. The curriculum encompasses the recommended, written, taught or implemented, assessed, and learned curriculum ( Glatthorn, 2000 ). Curriculum pertains to the curricular programs, the teaching, and learning design, learning resources as assessment, and teaching and learning environment. Adjustment on the types of assessment measures is a major factor amid the pandemic. There is a need to limit requirements and focus on the major essential projects that measure the enduring learning outcomes like case scenarios, problem-based activities, and capstone projects. Authentic assessments have to be intensified to ensure that competencies are acquired by the learners. In the process of modifying the curriculum amid the pandemic, it must be remembered that initiatives and evaluation tasks must be anchored on what the learners need including their safety and well-being.

Curriculum recalibration is not just about the content of what is to be learned and taught but how it is to be learned, taught, and assessed in the context of the challenges brought about by the pandemic. A flexible curriculum design should be learner-centered; take into account the demographic profile and circumstances of learners–such as access to technology, technological literacies, different learning styles and capabilities, different knowledge backgrounds and experiences - and ensure varied and flexible forms of assessment ( Ryan and Tilbury, 2013 ; Gachago et al., 2018 ). The challenge during the pandemic is how to create a balance between relevant basic competencies for the students to acquire and the teachers’ desire to achieve the intended outcomes of the curriculum.

The learners’ engagement in the teaching-learning process needs to be taken into consideration in the context of flexibility. This is about the design and development of productive learning experiences so that each learner is exposed to most of the learning opportunities. Considering that face-to-face modality is not feasible during the pandemic, teachers may consider flexible distant learning options like correspondence teaching, module-based learning, project-based, and television broadcast. For learners with internet connectivity, computer-assisted instruction, synchronous online learning, asynchronous online learning, collaborative e-learning may be considered.

The Role of Technology in Learning Continuity

Technology provides innovative and resilient solutions in times of crisis to combat disruption and helps people to communicate and even work virtually without the need for face-to-face interaction. This leads to many system changes in organizations as they adopt new technology for interacting and working ( Mark and Semaan, 2008 ). However, technological challenges like internet connectivity especially for places without signals can be the greatest obstacle in teaching and learning continuity especially for academic institutions who have opted for online learning as a teaching modality. Thus, the alternative models of learning during the pandemic should be supported by a well-designed technical and logistical implementation plan ( Edizon, 2020 ).

The nationwide closure of educational institutions in an attempt to contain the spread of the virus has impacted 90% of the world’s student population ( UNESCO, 2020 ). It is the intent of this study to look into the challenges in teaching and learning continuity amidst the pandemic. The need to mitigate the immediate impact of school closures on the continuity of learning among learners from their perspectives is an important consideration ( Edizon, 2020 ; Hijazi, 2020 ; UNESCO, 2020 ). Moreover, the teachers' perspectives are equally as important as the learners since they are the ones providing and sustaining the learning process. Teachers should effectively approach these current challenges to facilitate learning among learners, learner differentiation, and learner-centeredness and be ready to assume the role of facilitators on the remote learning platforms ( Chi-Kin Lee, 2020 ; Edizon, 2020 ; Hijazi, 2020 ).

Statement of Objective

This study explores the issues and challenges in teaching and learning amid the pandemic from the lenses of the faculty members and students of a public university in the Philippines as the basis for the development of strategic actions for teaching and learning continuity. Specifically, this study aimed to:

a.1. Preferred flexible learning activities.

a.2. Problems completing Requirements due to ICT Limitation

a.3. Provision of alternative/additional requirement.

a.4. Receipt of learning feedback.

a.5. Learning environment.

Objective 2: determine the profile of faculty and students in terms of online capacity as categorized into:

b.1. Access to Information Technology.

b.2. Access to Internet/Wi-fi.

b.3. Stability of internet connection.

Objective 3: develop emerging themes from the experiences and challenges of teaching and learning amidst the pandemic.

Methodology

The design used in the study is an exploratory mixed-method triangulation design. It was utilized to obtain different information but complementary data on a common topic or intent of the study, bringing together the differing strengths non-overlapping weaknesses of quantitative methods with those of qualitative methods ( Creswell, 2006 ). The use of the mixed method provided the data used as a basis for the analysis and planning perspective of the study.

This study was conducted in the context of a state university funded by the Philippine government whose location was once identified as having one of the highest COVID19 cases in the country. With this incidence, the sudden suspension of classes and the immediate need to shift the learning platform responsive to the needs of the learners lend a significant consideration in this study. This explored the perspectives of the learners in terms of their current capacity and its implications in the learning continuity using online learning. These were explored based on the availability of gadgets, internet connectivity, and their learning experiences with their teachers. These perspectives were also explored on the part of the teachers as they were the ones who provided learning inputs to the students. These are necessary information to identify strategic actions for the teaching and learning continuity plan of the university.

After getting the quantitative and qualitative findings, these data were reviewed to provide a clear understanding of teachers’ and learners’ context and their experiences. From this information, a scenario analysis through scenario building was conducted which led to the development of the strategic actions for teaching and learning continuity. Scenario analysis is a method used in predicting the possible occurrences of consequences of a situation assuming the phenomenon will be continued in the future ( Kishita et al., 2016 ). This approach is considered a useful way for exploring plausible events that may or may not happen in the future ( Bekessy and Selinske, 2017 ). This approach was used to analyze the behavior of both teachers and students as part of the whole system in response to an unexpected event such as the pandemic which creates a theoretical scenario of best -case (optimistic) or worse case (pessimistic) scenario to enable the university to develop a holistic strategic plan for the teaching and learning continuity ( Balaman, 2019 ).

Both quantitative and qualitative approaches were used simultaneously. In this study, objectives 1 and 2 require data on the profile of the teachers and learners which can best be acquired using a descriptive quantitative design. This was done through an online structured survey was conducted to identify the challenges in teaching and learning using google forms. Choices were provided in the Google form which the respondents can choose from. The surveys were done by the Cebu Normal University - Center for Research and Development and Federation of Supreme Student Council.

The qualitative approach was utilized to answer objective number 3 which looked into the experiences and challenges of the teachers and the learners. The narratives which the respondents submitted were done through online open-ended questions to allow them to share their experiences and challenges. These were analyzed using a thematic approach to best provide a clear description of the experiences and challenges.

After the analysis of the quantitative and qualitative data, the team of researchers developed the possible scenarios that will take place as the basis for the flexible strategic actions that the university will adapt depending on the classification of community quarantine and the health situation of the locale where the university is located. In the analysis of the current status of Cebu Normal University, parameters are reviewed and outcomes are utilized through scenario building. Scenario building provides the contextual basis for the development of the new normal in the university. Scenario building as explained by Wilkinson (1995) is a good strategy to use on how current observations play their role in future situations. Each scenario is constructed about the future, modeling a distinct, plausible world. Scenarios are plausible alternative futures of what might happen under particular assumptions by focusing on key drivers, complex interactions, and irreducible uncertainties ( Polcyznski, 2009 ).

The prospective scenarios created are the best, probable scenarios, and worse scenarios. Current or existing situations/conditions of CNU served as the probable scenario, while the ideal case situation served as the best scenario. From the scenario built, key problems and challenges are developed as a basis for the model developed ( Imperial, 2020 ). This provided the strategic long-term and short-term strategies for CNU’s academic operations. The best scenario is based on the perspective that the university allows limited face-to-face classes in the remaining months of the semester. The probable scenario is with the current enhanced community quarantine (ECQ) status of the city or province where the university is located, at least six (6) months, after, face-to-face interactions will be allowed with the opening of the new school year will. Worse Scenario happens when the locale is placed under sustained community quarantine and face-to-face classes will never be allowed at the start of the new school year. The strategic actions of the university are inclusive of the three (3) scenarios to allow flexibility of the responses of the university in this pandemic.

There were 3,646 student respondents (85% of the student population) and 252 (97% of the teaching personnel) teaching personnel who responded to the survey. To determine accessibility and reach of communication transmission related to the teaching-learning process, the location of the respondents was also identified. The majority of the student respondents (67%) are located in Cebu province; 17% in Cebu City, and 12% in other provinces. The 63% or 157 faculty members are residing in Cebu province while 32% or 81 of them reside in Cebu City; other provinces 5%. Qualitative feedback was also gathered to explore further the challenges experienced and clarify information about open-ended online messaging. Data was gathered from March-April 2020 in a state-funded university in the Philippines with the campus located in the center of the city. To comply with the ethical guidelines, strict adherence to data privacy protocols and data use restrictions were followed. The data were analyzed and were considered in identifying emerging themes scenarios in teaching and learning.

The data gathered were reviewed and analyzed by looking into the challenges that need to be addressed and the ideal perspectives that should have been implemented to generate different scenarios. Scenario building provides the contextual basis for the development of the new normal in the university. Scenario building as explained by Wilkinson (1995) is a good strategy to use on how current observations play their role in future situations. Each scenario is constructed about the future modeling a distinct, plausible world. Scenarios are plausible alternative futures of what might happen under particular assumptions by focusing on key drivers, complex interactions, and irreducible uncertainties ( Polcyznski, 2009 ). The prospective scenarios created are the best and probable scenarios. Current or existing situations/conditions of the university served as the probable scenario, while the ideal case situation served as the best scenario. From the scenario built, key problems and challenges are developed as a basis for the model developed ( Imperial, 2020 ). The model will provide the strategic long-term and short-term strategies for the university’s academic operations Figure 1 .

FIGURE 1 . Schematic diagram of the conceptual analysis.

Results and Discussion

Challenges on teaching and learning amid the pandemic.

In the quantitative data gathered through an online survey, the students reported their concerns related to their learning experiences during the suspension of physical classes. Most of the student respondents reported that adjustments were made by the teachers in terms of course outcomes and syllabi. However, most of them claimed that the learning activities were not flexible enough to be done either offline or online as they could not as shown in Table 1 comply with the requirements within the expected schedule.

TABLE 1 . The profile of flexibility of the learning activities for offline or online learning among students (n = 1,689).

Moreover, as shown in Table 2 , students reported that the majority of them were unable to accomplish the tasks assigned by the teachers due to their inability to access the internet or use suitable gadgets to finish the tasks.

TABLE 2 . Number of students who reported if they have problems. Completing requirements due to ICT limitation (n = 1952).

Part of the survey for students focused on how students reacted to home-based tasks assigned to them to complete the learning competencies of the course. Teachers provided alternative tasks online through electronic mails and an online portal Table 3 .

TABLE 3 . Provision of alternative/additional requirement (n=1952).

Students confirmed that some online classes and additional requirements were still provided to them by the faculty ( Table 4 ) The majority of the students responded that the alternative tasks were adequate. The nature and content of the alternative tasks provided were suited to the remaining concepts to be addressed in their coursework ( Table 4 ). Despite that, several students still reported that these alternative tasks are not sufficient to enable them to acquire the remaining competencies required of them at the end of the semester.

TABLE 4 . Adequacy of alternative tasks for learning attainment (n=74).

Students in one college were surveyed on the receipt of feedback from their respective teachers. A comparable response from students claimed they received and didn’t receive immediate feedback as to whether what they submitted to the professors is okay or what aspect they still need to improve more. As teaching continuity was made possible through online modality and other home-based tasks, they still had difficulty complying with the requirements of the course. The survey included the type of home environment the students have to assess factors that influence their difficulty. Students were asked whether their home learning environment is conducive to learning or not.

Data in Table 5 show that learners believed that their home environment is not conducive for learning when schools were closed and physical contact was discontinued as there were many disruptions including internet connectivity. On the part of the faculty, there were challenges met as evidenced by the feedbacks of the students. The teaching-learning process requires an active engagement of the faculty. They are the drivers of the learning process and the success of the learning outcomes would partially depend on their extent of active participation as facilitators, mentors, or coaches to the learners.

TABLE 5 . Students learning environment.

In the teaching-learning process, students need feedback on the progress of their outputs and whether they did well in their tasks. As shown in Table 6 , the majority of the students reported receiving no feedback from their teachers on the online module while a majority hope to get immediate feedback. Further exploration is required to determine why teachers are unable to provide immediate feedback for students.

TABLE 6 . Feedback from teachers (n = 154).

Faculty and Students’ Access to Technology

One of the modalities in teaching and learning that gained popularity amid COVID-19 was online learning. When classes were suspended, universities migrated from the face to face interaction to the online modality. Hence, this survey was conducted to determine the capability of the students and teachers in terms of available information technology gadgets and connections.

The profile of both the faculty and students’ access to internet-based information showed that the majority can access this information ( Table 7 ). Moreover, the majority of the students (82.61%) and faculty (94.4%) have internet access Table 8 . However, most of them reported unstable internet connections which makes their home environment less conducive to sustain learning facilitated by the online readings and activities given Table 9 . The majority of the students used mobile phones for online learning which is not capable of addressing online tasks and submission of requirements. On top of this, concerns for limited internet access of students and faculty emanate from external service providers most especially when using cellular data in areas where satellite signals are limited.

TABLE 7 . Faculty and students’ access to information technology (n = 4,072).

TABLE 8 . Faculty, staff and students’ access to internet/Wi-fi.

TABLE 9 . Stability of internet connection (n = 1952).

Emerging Themes in Teaching and Learning

A qualitative survey was also conducted to substantiate the quantitative data gathered. The narrative comments of the respondents in the survey were analyzed and were grouped into emerging themes and scenarios of teaching and learning.

The Trajectory Towards Flexibility in Teaching Design, Delivery, and Assessment

The sudden cancellation of classes in the middle of the semester placed both faculty and students unprepared. Questions on how to continue their classes, the learning modality, the appropriate assessment, and access to learning materials were foremost in the mind of both teachers and students. The narratives of the respondents became the basis for identifying the emerging scenarios in teaching and learning amid and beyond the pandemic.

For many years, students have been exposed to traditional, face-to-face classroom-based teaching. Outcomes-based education has been integrated into the curriculum and its implementation, but the learning delivery is still under the actual supervision of teachers. Due to ECQ students have to shift to independent learning through the home-based tasks assigned to them by their teachers. Ordinarily, many students have trouble making the transition to the more independent learning required at university compared with their secondary years .

“It’s very difficult for me to learn on my own in the confines of my home, but I don’t have a choice ,” narrated one student.

This shows that this pandemic has created a new platform in teaching and learning delivery that students are compelled to accept. In this situation, students have to take responsibility for their learning, be more self-directed, make decisions about what they will focus on how much time they will spend on learning outside the classroom ( The Higher Education Academy, 2014 ; Camacho and Legare, 2016 ). In the new setting, students are expected to read, understand and comply with the tasks without the guidance of the teachers. They are forced to assume self-directed independent learning.

The teachers on the other hand affirmed that the use of face-to-face delivery would not work anymore in the new learning environment.

“ One thing that I have learned is to adjust my materials to ensure that learners can still acquire the competencies without the face-to-face interaction with my students ” narrated one teacher.

With the concerns on access to online services, faculty members considered the use of a non-online approach and explored the necessary modifications that can be applied in the future. Hence, in the narrative, several faculty members said they have prepared modules as an option for pure online learning delivery.

Assessment of student learning outcomes is very important. A concern on how to assess learning outcomes and how to answer assessment tasks emerged as a major concern as reflected in the narratives of the teacher and student respondents. The assessment measures are essential as an assurance that learners have attained various knowledge and skills and that they are ready for employment or further study ( Coates, 2015 ). There is a need to address the teachers’ concern on how to conduct off-classroom performance evaluation and the bulk of submissions that they have to evaluate which are submitted online or offline. The design and planning are important factors to consider not only in the assessment per se but also in the parameters on how students will be graded ( Osborn, 2015 ). For the teachers, the following concerns emerged,

“Difficulty assessing performance-based tasks (RLE) , ” “Difficulty tracking, checking of students’ outputs” and “Concerns on failing due to non-submission of requirements online and low midterm Performance”

In the assessment of learning, the teacher respondents agreed that they have to think of innovative ways of assessing students in the context of their situation and home environment so the outcomes expected of the course will be manifested by the students.

One of the challenges of online or distance learning is the difficulty in participating in groupwork activities. The challenge is how the schedule or availability of group members be accommodated within the group ( Gillett-Swan, 2017 ; Kebritchi, Lipschuetz, and Santiague, 2017 ). More particularly when online assessments are done with certain deadlines or time limits.

“Difficulty complying group activities”

“Time-based online exams”

The challenges seen in this phase are to determine the flexible learning system most applicable for CNU learners, the readiness of the students and faculty to handle the tasks to assign and to be complied by the students, the appropriateness of the learning delivery vis-à-vis learning outcome, and the preparation of the learning materials fit for self-directed independent learning.

In times of disaster, the educational system takes on a different route for effective learning continuity. The learning curriculum requires it to be more responsive to the current needs of the learners and the teachers.

“ Concerns in completing OJT”

“Dissertation/Thesis defense scheduled”

“Concerns on when the academic year ends”

The flexibility that the curriculum has to adopt requires the offering of choices on the current reality of the educational environment and customizing a given course to meet the needs of the learners. It is therefore crucial in considering the provision of the possibility of making learning choices to learners. These learning choices can cover class times, course content, instructional ( Huang et al., n.d. ).

It is a challenge for the university to consider the restructuring of the curriculum to address the gaps in the learning outcomes left when classes were suspended and the re-scheduling of the mid-semester On-the-Job Training of some programs. Amidst this crisis, flexibility in the next academic calendar has to be considered while it is uncertain when the COVID-19 crisis will be contained.

The Role of Technology

In the overall narratives concerning teaching-learning delivery and assessment, the role of information technology particularly on internet connection has been repetitively mentioned by both teachers and students. In the crisis scenario, faculty and students could eventually bounce forward to the usual teaching-learning activities outside the classrooms had this concern been made available to all. Per survey results, most of the students and some faculty members are residing outside the city and are experiencing unstable if no internet connection at all.

“ No internet connectivity/unstable connectivity”

“Occasional power interruptions”

In designing for online or distance learning, there is a need to understand the role of technology to attain the success of the engagement ( Kerka, 2020 ). Internet is not the only factor to consider but also the equipment that is needed for the teachers and the learners to engage effectively. If these are not available, there is a need to evaluate the approach used in the teacher-learner interaction.

“Limited gadgets (one laptop shared with other siblings/no laptop or PC only phone)”

“No printer for completion of a requirement to be submitted”

With the current health crisis with the shifting of learning delivery, the challenge would be on how to provide an inclusive IT infrastructure to provide quality education for all learners ( Internet access and education: Key considerations for policy makers, 2017 ).

The Learner’s and the Teacher’s Learning Environment

In an attempt to address the disruption of classes and promote continuity of learning, teachers immediately resort to online learning as the most workable way of delivery of the lessons. In this new learning setup, students are forced to stay at home and transfer their classrooms to the same location. In most cases, it is often overlooked that learners come from different home settings and have different home arrangements.

“Not appropriate learning environment (congested home setting)”

“Lack of support from parents (assigning home tasks when a student is supposed to be work on learning tasks)”

“Overlapping of home activities and academic activities”

In most cases, families frequently engaged their children in learning activities, however, different patterns were observed across different social groups. Families in low socio-economic position households, and those living in disadvantaged neighborhoods provided fewer learning experiences. This may in part be due to the challenges that families living in socially and economically disadvantaged circumstances face in accessing the financial and social resources needed to provide a rich early home learning environment for learning. The findings reveal that education is still pursued in economically challenging settings but with more challenges. A home learning environment has a positive “direct association” with a child’s academic performance ( Australian Institute of Family Studies, 2015 ). The findings require a three-helix platform in education that is the partnership between academe, industry, and the stakeholders.

Maslow Before Bloom Orientation: Safety and Security

Prevailing sentiments among employees and students are their concern for their safety and security. The basic needs of humans according to Maslow’s Hierarchy of needs are foremost in the minds of the university’s clients and workers. As reported by the students and employees, their foremost concern is safety and the psychological manifestations of the anxiety of being infected.

“Foremost concern is safety and security even after ECQ is lifted”

“Fear of being infected with COVID”

“With PUI/PUM family members or the students themselves”

“Psychological and emotional reactions (anxiety, panic, fear, loneliness, a feeling of helplessness, mood swings, anger)”

The second category of concerns is on security and the possibility of sustaining their education due to loss of jobs, loss of family members, and the uncertainty of traveling to the university.

“Family financial crisis–no budget to buy loads, sustain needs”

“Unable to go home”

“Transportation concerns”

The concerns raised by the participants of the study require the university to provide access to considerable support to deal with the struggles, challenges, and even trauma because of the pandemic. There is a need to help manage mental health, self-esteem, and relationships after the quarantine which left some of the students isolated for quite a time ( Sweeney, 2020 ). Mental health programs have to be in place in formal learning settings. Because of the unprecedented challenges that students and teachers experienced in the pandemic, the ability to successfully hurdle through formal learning may be limited if the overall well-being is compromised.

Strategic Scenario Analysis

This section presents the analysis of the possible scenarios that might take place in the university based on the following components: the planned curriculum, instruction (teaching-learning process), assessment, student engagement, and technology and infrastructure. The probable scenario is the current enhanced community quarantine (ECQ) status of the City or province where the university is located. During ECQ, no face-to-face interaction is allowed and province-wide lockdowns are implemented. The best scenario allows the limited face-to-face class and the worse scenario happens when the locale is under ECQ and placed on a lockdown due to the increasing COVID-19 cases.

In the area of curriculum and instruction, the action points revolved around the identification of courses that can be flexibly offered, rescheduling offerings when health measures permit it and providing interventions for competencies that were not met. The additional action points would refer to the creation of materials that would meet the needs of the students in the different scenarios and the provision of access to all resources that aid learning. Lastly, plans for assessment delivery are laid out to ensure the validity of means and with consideration to quarantine measures. Laying down the scenarios provide options for the educational institution to be able to meet the demands of the changes enforced by the pandemic to the delivery of learning to students. Reviewing these options reveal that the differences in the plan of action for this area of concern are a matter of granting access to students for resources needed for learning continuity.

The next area of concern is student engagement which reveals the different levels of engagement of parents and guardians, the means of communication with students, and an investment in the capability-building of faculty members to facilitate the teaching-learning process amid the pandemic. The focus on the trainings for the faculty members in the area implies that flexible learning in this health crisis requires a particular skill set to heighten student engagement without diminishing the role of support systems in the students’ homes and the need for appropriate technology to facilitate the needed interactions. This leads to the last area of concern on technology and infrastructure. The University has to take into account and facilitate the provision of needed equipment, materials, systems, software, and physical structures to support flexible learning. The complete scenario matrix is reflected in Table 10 .

TABLE 10 . Scenario matrix.

Migrating to Flexible Teaching and Learning: The University’s Strategic Response for Academic Continuity

After exploring the perspectives of the respondents and the analysis of the emerging scenarios in teaching and learning, the University implemented the proactive response to ensure academic continuity in times of crisis. It is evident that for universities to thrive and lead, the flexible teaching-learning modality needs to be adopted taking into consideration the best and worst-case scenarios. Migrating to flexi learning means recalibrating the written curriculum, capacitating the faculty, and upgrading technological infrastructure to respond to the changing scenarios amid and beyond the pandemic. Outlined in the paragraphs that follow were the ways forward pursued by the university as a response for academic continuity.

Recalibrate the Curriculum

To address the competencies which were left at the time of the class suspension, discipline-based course mapping was conducted. A series of cluster meetings by faculty members teaching similar courses teaching load were done for the revision of the unified syllabus, integration of the outcomes-based teaching and learning strategies using flexible learning platforms such as distance and online learning options, and the learning assessment strategies suitable for individual student needs. A syllabi repurposing is conducted and the revisiting of the syllabi focusing on the essential course outcomes. This strategy enables the faculty to revise the activities/course work/tasks/experiences that can be delivered through blended learning. This also enabled them in designing the instructional strategies, activities, and assessments that will achieve the learning objectives. The modification of the syllabi incorporated the development of modules, assessment tasks that can be delivered using differentiated instruction/in class or off class.

A program-based curriculum review was also conducted to identify courses that would need to be re-scheduled in its offering due to its nature and requirement such as swimming courses. Moreover, On-the- Job (OJT) which was supposedly offered during summer or mid-year was transferred to a later semester as industry partners are limiting its personnel at the height of the pandemic.

Reconfiguring the OJT, practice teaching and Related Learning Experience based on simulation set-up with scenario-based activities with assigned equivalency hours was also developed. The Practice teaching using blended learning or online approach, Nursing used alternative Related learning simulation.

The strategic actions included short-term plans of possible limited physical classes and long-term plans of pure online classes. Embedded in the plans are the in-class and off-class mode, re-structuring and retrofitting requirement for limited face-to-face classes, and the upgrading of internet-based facilities for pure online classes. On top of this, they need to cater to learners who have no access to the internet includes the translation of online learning modules to printed modules.

Capacitate the Faculty

Flexible learning capacitation of faculty was also addressed as online learning was new to the university. The university conducted an upskilling and rewiring through series of online trainings on module development for flexible learning distance education and the use of an online learning management system for faculty members. Reskilling and reconfiguring of faculty through webinar series on laboratory teaching using simulation learning for teachers handling laboratory, RLE, OJT. And a cross-skilling and reimagining using series of online webinars on developing counseling skills of faculty members concerning the COVID crisis. The university initiated the Higher Education Connect webinar series by discipline which served as an avenue of sharing and exchanging best practices during the pandemic-induced suspension of physical classes. The series of online for and webinars provided the teachers’ professional development including information sharing platform, Online learning platform, Hands-on training platform, Repository of web tools, and Laboratory for data analytics.

Safe learning infrastructure for Reframing Teaching and Learning was addressed through Telecounseling Services with mobile hotline numbers to cater to the needs of the clients and Student Communication Center with hotline numbers accessible by phone or online to cater to the academic concerns of the students. The university also initiated the Adopt-a-Student program for stranded students during the Enhanced Community Quarantine and assisted in the process of going back to their provinces.

Upgrade the Infrastructure

The university’s priority is to ensure that technology is sustainable and feasible. The ICT focal persons of the university were mobilized to Determine basic computer configuration and minimum Operating System requirements and provide alternative solutions to learners with technological/location-related challenges. For example, provide small learning activity packages for learners with slow internet connections. Ensure changes to the learning activity that can be made with internal resources. Determine the characteristics, possibilities, and limitations of the learning management system (LMS) to be used and ensure consistency of access across platforms (if applicable).

An Organizational Structures as a support system was also created which was the Center for Innovative Flexible Learning to provide assistance and monitoring so that the existing Information Technology Office of the university will not be overwhelmed.

It is also strategic to develop collaboration with stakeholders (Local Government Units (LGU), Alumni, Partner agencies). The forging of partnerships with LGU provides avenues where students during off-class students will go to the learning hub in the LGU complete with internet connectivity for students to work on their tasks in case they don’t have connectivity at home, so students will not go to the internet café and pay. This will also provide opportunities for resource sharing for the benefit of the students.

ICT Infrastructure in teaching and learning and student services was also addressed through Online enrollment, full utilization of Google Classroom as the learning management system, and the fully online delivery of classes. The university also changed its internet subscription to higher bandwidth and subscription to zoom for online meetings and conferences. Internet Connectivity of faculty members has assisted a monthly internet allowance. Gadget on loan for students in coordination with Student Supreme Council. Library online services through Document Delivery Services (DDS) and Modern Information Assistant in the New Normal Innovative Education.

Implementation and On-Going Assessment of the Strategic Response

The implementation of the strategic response entails the collaborative engagement of all stakeholders in the university. The process requires the involvement of the administration, faculty, staff, students, parents, and other stakeholders that enables the institution to move forward, managing and mitigating risks successfully. Hence, the university is implementing the continuous process of consultation, feedbacking, and intensive monitoring as important ingredients for the plans to be successfully implemented. The regular conduct of dialogues and discussions among stakeholders, capacity building of students and faculty, open communication through hotline centers, and continuous quality assurance monitoring mechanisms enable the university to enhance and implement successfully the strategic programs and activities amid the pandemic.

Anchored on the initial success of the evidenced-based strategic plans, the university at present has institutionalized the flexible learning system with the establishment of the Center for Flexible Learning that manages, capacitates, and assists the students and the faculty members in the continuing implementation of the flexible learning modality. Technology support has been provided by increasing the internet bandwidth to ensure uninterrupted connectivity in the campus and providing internet allowance to the faculty. Students with limited or no connectivity are given printed modules as instructional resources. In anticipation of the limited face-to-face classes as safety and health protocols may allow, the curricular offerings, teaching-learning processes, and assessment tools have been enhanced by applying best practices that maximize quality teaching and learning. On-going trainings and webinars for the faculty, students, and stakeholders to thrive in the new educational landscape have been conducted. The university has also established professional learning communities which become avenues for the sharing of resources and practices that continuously support and enhance teaching and learning continuity amid and beyond the pandemic.

Teaching and learning continuity amid the pandemic requires an analysis of the parameters by which the university operates from the perspective of the stakeholders to include the students, faculty, curriculum, and external stakeholders. Grounded on data, higher education institutions have to conduct strategic scenario analysis for best, possible and worse scenarios in the areas of curriculum and instruction, student engagement, and technology and infrastructure. To ensure teaching and learning continuity amid and beyond the pandemic, higher education institutions need to migrate to flexible teaching and learning modality by recalibrating the curriculum, capacitating the faculty, and upgrading the infrastructure. These strategic actions have to be continuously assessed, modified, and enhanced to respond to the volatile, uncertain, and changing scenarios in times of crisis.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

FD, DP, LG, and MO contributed to the conception and design of the study. DP and LG organized the data and facilitated the initial analysis. FD and DP wrote the first draft of the manuscript. All authors wrote sections of the manuscript and contributed to the manuscript revision. MO ran the final plagiarism test and grammar check prior to submission.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Kerka, S. (2020). Distance Learning, the Internet, and the World Wide Web . Retrieved from ericdigest: https://www.ericdigests.org/1997-1/distance.html .

Kishita, Y., Hara, K., Uwasu, M., and Umeda, Y. (2016). Research Needs and Challenges Faced in Supporting Scenario Design in Sustainability Science: A Literature Review. Sustainability Sci. 11 (2), 331–347. doi:10.1007/s11625-015-0340-6

Mark, G., and Semaan, B. (2008). Resilience in Collaboration: Technology as a Resource for New Patterns of Action,” in Proceedings of the 2008 ACM conference on computer supported cooperative work , San Diego, CA , November 8–12, 2008 ( CSCW08: Computer Supported Cooperative Work ), pp. 137–146. https://doi.org/10.1145/1460563.1460585

Osborn, L. (2015). Performance Assessment in Online Learning. In 19th Annual Conference on Distance Teaching and Learning , Madison, Wisconsin , August 14–16, 2002 ( University of Wisconsin System ). Available at: https://files.eric.ed.gov/fulltext/ED471207.pdf

Polcyznski, M. (2009). Scenario Planning . Retrieved from https://www.flca.net/images/ScenarioPlanning.pdf .

Ryan, A., and Tilbury, D. (2013). Flexible Pedagogies: New Pedagogical Ideas . London: Higher Education Academy .

Smalley, A. (2020). “Higher Education Responses to Coronavirus (COVID-19),” in National Conference of State Legislatures . Available at: https://www.ncsl.org/research/education/higher-education-responses-to-coronavirus-covid-19.aspx .

Sweeney, N. (2020). When the Covid-19 Crisis Finally Ends, Schools Must Never Return to normal . United Kingdom: The Guardian . Available at: https://www.theguardian.com/education/2020/apr/07/when-the-covid-19-crisis-finally-ends-uk-schools-must-never-return-to-normal .doi:10.1158/1557-3265.covid-19-po-009

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UNESCO Learning Portal (2020). Brief 3: Learning and Teaching Materials Paris .

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Keywords: teaching and learning continuity, flexible learning, pandemic, higher education, scenario–analysis

Citation: Dayagbil FT, Palompon DR, Garcia LL and Olvido MMJ (2021) Teaching and Learning Continuity Amid and Beyond the Pandemic. Front. Educ. 6:678692. doi: 10.3389/feduc.2021.678692

Received: 10 March 2021; Accepted: 06 July 2021; Published: 23 July 2021.

Reviewed by:

Copyright © 2021 Dayagbil, Palompon, Garcia and Olvido. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Michelle Mae J. Olvido, [email protected]

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Distance learning in the Philippines: A year of hits and misses

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This is AI generated summarization, which may have errors. For context, always refer to the full article.

REMOTE EDUCATION. Parents and students return the modules to teachers at the Araullo High School in Manila on Tuesday, July 13, as the school year came to a close.

Every morning, Adelaide Dolar would ask a favor: could she charge her mobile phone at her neighbor’s house? She didn’t have electricity at home, and her children needed her gadget for online class work. She did this for the whole duration of the school year 2020-2021. 

The pandemic made it difficult for financially struggling families like hers to fulfill their children’s needs for distance learning, the 43-year-old vendor from Batangas province told Rappler in an interview on Sunday, July 18.

Despite this, she made sure that her children would not miss school the past year, when the government enforced a remote setup due to pandemic lockdowns.

Her three children – all basic education students – were enrolled under the modular learning system. The eldest, who was in Grade 10, needed to occasionally attend online classes. The younger ones, however, couldn’t just answer the modules distributed by the school; they also needed to watch video lessons uploaded on YouTube or do research for their classes.

With a meager income of P300 ($5.91) a day from selling afternoon snacks to her neighbors, Dolar had to budget this amount between their meals and an allotment of mobile data   for her children’s online classes.

“If they have online classes, I need to have P200 for internet ‘load.’ If my eldest son needs to attend a Google meet, I need to buy internet load worth P50 per hour. Of course, there’s also research that needs to be done, so the P50 load won’t be enough – that’s why we’re spending P200 for it. It will be registered for three days,” she said.

To make a living, Dolar and her husband sell snacks every afternoon in their neighborhood. Her husband has been diagnosed with bipolar disorder, so he cannot help that much with household finances. Dolar also does laundry services just to get by.

Not good for mental health

Aside from the financial burden brought by remote education, Dolar said that her children’s mental health had been affected. Without teachers explaining the lessons to students, she had to change her morning routine so she could guide and motivate her children to answer their learning modules. That delayed her preparation of food she would sell in the afternoon.

“They’re looking for the [in-person] school. They said in-person classes are better. They miss their interaction with their classmates. They are unmotivated to study. What will happen next school year? Will we be in this kind of situation again?” Dolar asked.

“They were culture-shocked. They are not used to this kind of situation. They’re hoping to interact with their teachers and their classmates,” she added.

In a recent video interview released by the Ateneo School of Government, Professor Carmel Abao said that aside from the issue of accessibility, remote learning also had an impact on students’ mental health.

“There’s an issue on the impact of this kind of learning on mental health. I still think that this is not advisable. Our kids are not made for this kind of isolation. Even if you do perform well in online learning, it’s different if you’re able to see, feel, and talk with your classmates,” she said.

Students didn’t learn as much

In a Rappler Talk interview on Friday, July 16, senior high school graduate Cheska Avenido said she found the remote learning setup really difficult.

“Besides the adjustment under the new modes of learning, sometimes we ask ourselves if studying during a pandemic is still worth it, because there are a lot of uncertainties,” she said.

Dolar shared that sentiment, saying her children didn’t learn that much in the remote setup, as she could not teach them properly. Though Dolar graduated with a degree in computer science, she wasn’t able to practice any related profession.

“I think they’re learning, but learning with teachers is far way better. Sometimes, I find it really hard to understand their lessons. Face-to-face classes is still the best way to go,” Dolar said.

Aside from the school system being unprepared for the shift, remote education also posed a major challenge for students who did not have anyone to facilitate learning at home, or whose parents were not capable of guiding them due to lack of knowledge. (READ:  Parents bear the brunt of distance learning as classes shift online )

Dolar said that, most times, she was the one attending her children’s online classes, especially in mathematics, so she could explain the concepts to them when answering their modules.

An online survey conducted by the multisectoral group Movement for Safe, Equitable, Quality and Relevant Education (SEQuRE) found that 86.7% of students under modular learning, 66% under online learning, and 74% under blended learning said they “learned less” under the alternative modes of learning compared with the traditional face-to-face setup.

The survey also found that only 5.4% under the blended learning, 5.7% under modular learning, and 9.1% under online learning “learned more.”

The survey was conducted from June 25 to July 12 among 1,278 teachers, 1,299 Grades 4 to 12 students, and 3,172 parents.

Teachers’ Dignity Coalition chairperson Benjo Basas said in a Rappler interview that, while the teachers would always do their best to teach students under any circumstance, they didn’t have any control on how students would respond.

“Either of those modalities, whether online or modular, it was difficult to learn. It’s difficult for the students. It’s also difficult for the teachers because we’re not trained for this system,” he said.

In March, senators questioned a report from the Department of Education (DepEd) that said 99% of public school students obtained a passing grade in the first quarter of the school year (October-December 2020).

The lawmakers were baffled by the high passing rate because many students struggled with distance learning. They cited instances when it was the parents or household members who ended up answering the exercises in the learning modules.

In remote learning, some students pay someone else to do their classwork

Education Undersecretary Diosdado San Antonio said it was likely that teachers were being considerate and therefore gave students high passing rates.

When pandemic is over, Basas said, teachers would have a tougher job because the students will need to catch up on the level of learning that corresponds to their grade or class.

“We have a lot of catching up to do because we’re promoting students to the next level even though we’re unsure if they do actually learn. But then we cannot do something about it because we’re asked to be considerate since we’re in a pandemic,” he said.

Erroneous modules, not enough gadgets

Education advocates have said that the pandemic highlighted the gaps in the Philippine education system. This was evident in the erroneous learning modules distributed to public school students during the pandemic.

“Painful” grammatical errors ,  wrong math equations , and depictions of  gender stereotypes  alarmed a public already worried over the quality of education that over 24 million students were receiving during the pandemic.

Aside from learning module blunders, Ateneo’s Abao said the pandemic exposed the “cracks” in the country’s education system.

“If the problem before the pandemic was the lack of classrooms, the problem now is the lack of computers. We have a problem with the quantity and quality which were magnified by the pandemic,” she said.

Better than academic freeze

Still, there were those who appreciated that the Department of Education (DepEd) and the Commission on Higher Education were able to go ahead with the school year amid the pandemic.

Dolar said that, even though the implementation was flawed, distance learning was still better than having an academic break. (READ: School time out during a pandemic? Pros and cons of an academic break )

“They have nothing to do at home, that’s why it’s okay to have distance learning. But we hope that they can improve the implementation and provide support to parents, teachers, and students,” she said.

Professor Jayeel Cornelio, director of Ateneo de Manila University’s development studies program, said that while remote education provided an opportunity for those in the academe to be creative, it would not be as effective if not all had equal access to the tools needed for the digital shift.

“As a professor, [remote education for me] is a good. We take advantage of every platform available, but the question is – who is winning and losing here? The reality is that if you come from an elite private school, you can easily cope with it. But we cannot say that flexible learning is the way to go for small private schools and state universities,” he said.

Students and teachers remain safe from the virus while they continue learning from their homes. Despite the challenges brought by remote learning, senior high school graduate Avenido said she still felt unsafe to return to face-to-face classes.

“I’d be comfortable to return to face-to-face classes if the government finds better solutions to our pandemic problems. If they can find ways to contain virus spread and ramp up vaccination, it’s the only way I will feel safe to join face-to-face classes,” she said.

Over a year into the pandemic, the Philippines is still struggling to contain the deadly virus that has so far infected more than 1.5 million and has killed over 26,000 of its population. The country is bracing for a possible surge in infections, as the threat of a more virulent Delta variant looms.

Finding local solutions

Regina Sibal, lead convenor of education advocacy group Aral Pilipinas, said that, aside from the slow response, the government’s top-down approach in its policy making was another barrier in the reopening of schools. She said that the government should not be implementing a “blanket rule” across the country.

“Our remote learning now is for all schools and no provision is given to other areas that are able to do face-to-face classes. Disparity in education access has been more pronounced now, especially in marginalized areas that lack resources,” she said.

Sibal said that what government should be doing now is to provide local communities with guidelines on finding solutions specific to their areas and situations. (READ: Empower LGUs to make decisions on school opening – advocacy group )

President Rodrigo Duterte turned down several times calls for face-to-face classes due to the threat of the pandemic.

Education Secretary Leonor Briones, however, was hopeful the DepEd would get the go signal to start limited face-to-face classes in some 100 schools it had identified. She was banking on the vaccination of teachers and the planned inoculation of students.

Are PH schools ready for face-to-face classes during pandemic?

The DepEd had said that it was preparing for “the delivery of quality education no matter what the circumstances will be in the coming months.”

Public schools in the country will start classes for school year 2021-2022 on September 13 , while private schools can start as early as June since they closed the past school year earlier.

“Enhanced”  blended distance learning will continue to be implemented. But will the government make it right for millions of students this time around? – Rappler.com

Editors’ Note: All Filipino quotes were translated into English .

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RECOMMENDED READS

• 5 Steps to Getting Started with Llama 2
• The Llama Ecosystem: Past, Present, and Future
• Introducing Code Llama, a state-of-the-art large language model for coding
• Meta and Microsoft Introduce the Next Generation of Llama
• Today, we’re introducing Meta Llama 3, the next generation of our state-of-the-art open source large language model.
• Llama 3 models will soon be available on AWS, Databricks, Google Cloud, Hugging Face, Kaggle, IBM WatsonX, Microsoft Azure, NVIDIA NIM, and Snowflake, and with support from hardware platforms offered by AMD, AWS, Dell, Intel, NVIDIA, and Qualcomm.
• We’re dedicated to developing Llama 3 in a responsible way, and we’re offering various resources to help others use it responsibly as well. This includes introducing new trust and safety tools with Llama Guard 2, Code Shield, and CyberSec Eval 2.
• In the coming months, we expect to introduce new capabilities, longer context windows, additional model sizes, and enhanced performance, and we’ll share the Llama 3 research paper.
• Meta AI, built with Llama 3 technology, is now one of the world’s leading AI assistants that can boost your intelligence and lighten your load—helping you learn, get things done, create content, and connect to make the most out of every moment. You can try Meta AI here .

Today, we’re excited to share the first two models of the next generation of Llama, Meta Llama 3, available for broad use. This release features pretrained and instruction-fine-tuned language models with 8B and 70B parameters that can support a broad range of use cases. This next generation of Llama demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning. We believe these are the best open source models of their class, period. In support of our longstanding open approach, we’re putting Llama 3 in the hands of the community. We want to kickstart the next wave of innovation in AI across the stack—from applications to developer tools to evals to inference optimizations and more. We can’t wait to see what you build and look forward to your feedback.

Our goals for Llama 3

With Llama 3, we set out to build the best open models that are on par with the best proprietary models available today. We wanted to address developer feedback to increase the overall helpfulness of Llama 3 and are doing so while continuing to play a leading role on responsible use and deployment of LLMs. We are embracing the open source ethos of releasing early and often to enable the community to get access to these models while they are still in development. The text-based models we are releasing today are the first in the Llama 3 collection of models. Our goal in the near future is to make Llama 3 multilingual and multimodal, have longer context, and continue to improve overall performance across core LLM capabilities such as reasoning and coding.

State-of-the-art performance

Our new 8B and 70B parameter Llama 3 models are a major leap over Llama 2 and establish a new state-of-the-art for LLM models at those scales. Thanks to improvements in pretraining and post-training, our pretrained and instruction-fine-tuned models are the best models existing today at the 8B and 70B parameter scale. Improvements in our post-training procedures substantially reduced false refusal rates, improved alignment, and increased diversity in model responses. We also saw greatly improved capabilities like reasoning, code generation, and instruction following making Llama 3 more steerable.

*Please see evaluation details for setting and parameters with which these evaluations are calculated.

In the development of Llama 3, we looked at model performance on standard benchmarks and also sought to optimize for performance for real-world scenarios. To this end, we developed a new high-quality human evaluation set. This evaluation set contains 1,800 prompts that cover 12 key use cases: asking for advice, brainstorming, classification, closed question answering, coding, creative writing, extraction, inhabiting a character/persona, open question answering, reasoning, rewriting, and summarization. To prevent accidental overfitting of our models on this evaluation set, even our own modeling teams do not have access to it. The chart below shows aggregated results of our human evaluations across of these categories and prompts against Claude Sonnet, Mistral Medium, and GPT-3.5.

Preference rankings by human annotators based on this evaluation set highlight the strong performance of our 70B instruction-following model compared to competing models of comparable size in real-world scenarios.

Our pretrained model also establishes a new state-of-the-art for LLM models at those scales.

To develop a great language model, we believe it’s important to innovate, scale, and optimize for simplicity. We adopted this design philosophy throughout the Llama 3 project with a focus on four key ingredients: the model architecture, the pretraining data, scaling up pretraining, and instruction fine-tuning.

Model architecture

In line with our design philosophy, we opted for a relatively standard decoder-only transformer architecture in Llama 3. Compared to Llama 2, we made several key improvements. Llama 3 uses a tokenizer with a vocabulary of 128K tokens that encodes language much more efficiently, which leads to substantially improved model performance. To improve the inference efficiency of Llama 3 models, we’ve adopted grouped query attention (GQA) across both the 8B and 70B sizes. We trained the models on sequences of 8,192 tokens, using a mask to ensure self-attention does not cross document boundaries.

Training data

To train the best language model, the curation of a large, high-quality training dataset is paramount. In line with our design principles, we invested heavily in pretraining data. Llama 3 is pretrained on over 15T tokens that were all collected from publicly available sources. Our training dataset is seven times larger than that used for Llama 2, and it includes four times more code. To prepare for upcoming multilingual use cases, over 5% of the Llama 3 pretraining dataset consists of high-quality non-English data that covers over 30 languages. However, we do not expect the same level of performance in these languages as in English.

To ensure Llama 3 is trained on data of the highest quality, we developed a series of data-filtering pipelines. These pipelines include using heuristic filters, NSFW filters, semantic deduplication approaches, and text classifiers to predict data quality. We found that previous generations of Llama are surprisingly good at identifying high-quality data, hence we used Llama 2 to generate the training data for the text-quality classifiers that are powering Llama 3.

We also performed extensive experiments to evaluate the best ways of mixing data from different sources in our final pretraining dataset. These experiments enabled us to select a data mix that ensures that Llama 3 performs well across use cases including trivia questions, STEM, coding, historical knowledge, etc.

Scaling up pretraining

To effectively leverage our pretraining data in Llama 3 models, we put substantial effort into scaling up pretraining. Specifically, we have developed a series of detailed scaling laws for downstream benchmark evaluations. These scaling laws enable us to select an optimal data mix and to make informed decisions on how to best use our training compute. Importantly, scaling laws allow us to predict the performance of our largest models on key tasks (for example, code generation as evaluated on the HumanEval benchmark—see above) before we actually train the models. This helps us ensure strong performance of our final models across a variety of use cases and capabilities.

We made several new observations on scaling behavior during the development of Llama 3. For example, while the Chinchilla-optimal amount of training compute for an 8B parameter model corresponds to ~200B tokens, we found that model performance continues to improve even after the model is trained on two orders of magnitude more data. Both our 8B and 70B parameter models continued to improve log-linearly after we trained them on up to 15T tokens. Larger models can match the performance of these smaller models with less training compute, but smaller models are generally preferred because they are much more efficient during inference.

To train our largest Llama 3 models, we combined three types of parallelization: data parallelization, model parallelization, and pipeline parallelization. Our most efficient implementation achieves a compute utilization of over 400 TFLOPS per GPU when trained on 16K GPUs simultaneously. We performed training runs on two custom-built 24K GPU clusters . To maximize GPU uptime, we developed an advanced new training stack that automates error detection, handling, and maintenance. We also greatly improved our hardware reliability and detection mechanisms for silent data corruption, and we developed new scalable storage systems that reduce overheads of checkpointing and rollback. Those improvements resulted in an overall effective training time of more than 95%. Combined, these improvements increased the efficiency of Llama 3 training by ~three times compared to Llama 2.

Instruction fine-tuning

To fully unlock the potential of our pretrained models in chat use cases, we innovated on our approach to instruction-tuning as well. Our approach to post-training is a combination of supervised fine-tuning (SFT), rejection sampling, proximal policy optimization (PPO), and direct preference optimization (DPO). The quality of the prompts that are used in SFT and the preference rankings that are used in PPO and DPO has an outsized influence on the performance of aligned models. Some of our biggest improvements in model quality came from carefully curating this data and performing multiple rounds of quality assurance on annotations provided by human annotators.

Learning from preference rankings via PPO and DPO also greatly improved the performance of Llama 3 on reasoning and coding tasks. We found that if you ask a model a reasoning question that it struggles to answer, the model will sometimes produce the right reasoning trace: The model knows how to produce the right answer, but it does not know how to select it. Training on preference rankings enables the model to learn how to select it.

Building with Llama 3

Our vision is to enable developers to customize Llama 3 to support relevant use cases and to make it easier to adopt best practices and improve the open ecosystem. With this release, we’re providing new trust and safety tools including updated components with both Llama Guard 2 and Cybersec Eval 2, and the introduction of Code Shield—an inference time guardrail for filtering insecure code produced by LLMs.

We’ve also co-developed Llama 3 with torchtune , the new PyTorch-native library for easily authoring, fine-tuning, and experimenting with LLMs. torchtune provides memory efficient and hackable training recipes written entirely in PyTorch. The library is integrated with popular platforms such as Hugging Face, Weights & Biases, and EleutherAI and even supports Executorch for enabling efficient inference to be run on a wide variety of mobile and edge devices. For everything from prompt engineering to using Llama 3 with LangChain we have a comprehensive getting started guide and takes you from downloading Llama 3 all the way to deployment at scale within your generative AI application.

A system-level approach to responsibility

We have designed Llama 3 models to be maximally helpful while ensuring an industry leading approach to responsibly deploying them. To achieve this, we have adopted a new, system-level approach to the responsible development and deployment of Llama. We envision Llama models as part of a broader system that puts the developer in the driver’s seat. Llama models will serve as a foundational piece of a system that developers design with their unique end goals in mind.

Instruction fine-tuning also plays a major role in ensuring the safety of our models. Our instruction-fine-tuned models have been red-teamed (tested) for safety through internal and external efforts. ​​Our red teaming approach leverages human experts and automation methods to generate adversarial prompts that try to elicit problematic responses. For instance, we apply comprehensive testing to assess risks of misuse related to Chemical, Biological, Cyber Security, and other risk areas. All of these efforts are iterative and used to inform safety fine-tuning of the models being released. You can read more about our efforts in the model card .

Llama Guard models are meant to be a foundation for prompt and response safety and can easily be fine-tuned to create a new taxonomy depending on application needs. As a starting point, the new Llama Guard 2 uses the recently announced MLCommons taxonomy, in an effort to support the emergence of industry standards in this important area. Additionally, CyberSecEval 2 expands on its predecessor by adding measures of an LLM’s propensity to allow for abuse of its code interpreter, offensive cybersecurity capabilities, and susceptibility to prompt injection attacks (learn more in our technical paper ). Finally, we’re introducing Code Shield which adds support for inference-time filtering of insecure code produced by LLMs. This offers mitigation of risks around insecure code suggestions, code interpreter abuse prevention, and secure command execution.

With the speed at which the generative AI space is moving, we believe an open approach is an important way to bring the ecosystem together and mitigate these potential harms. As part of that, we’re updating our Responsible Use Guide (RUG) that provides a comprehensive guide to responsible development with LLMs. As we outlined in the RUG, we recommend that all inputs and outputs be checked and filtered in accordance with content guidelines appropriate to the application. Additionally, many cloud service providers offer content moderation APIs and other tools for responsible deployment, and we encourage developers to also consider using these options.

Deploying Llama 3 at scale

Llama 3 will soon be available on all major platforms including cloud providers, model API providers, and much more. Llama 3 will be everywhere .

Our benchmarks show the tokenizer offers improved token efficiency, yielding up to 15% fewer tokens compared to Llama 2. Also, Group Query Attention (GQA) now has been added to Llama 3 8B as well. As a result, we observed that despite the model having 1B more parameters compared to Llama 2 7B, the improved tokenizer efficiency and GQA contribute to maintaining the inference efficiency on par with Llama 2 7B.

For examples of how to leverage all of these capabilities, check out Llama Recipes which contains all of our open source code that can be leveraged for everything from fine-tuning to deployment to model evaluation.

What’s next for Llama 3?

The Llama 3 8B and 70B models mark the beginning of what we plan to release for Llama 3. And there’s a lot more to come.

Our largest models are over 400B parameters and, while these models are still training, our team is excited about how they’re trending. Over the coming months, we’ll release multiple models with new capabilities including multimodality, the ability to converse in multiple languages, a much longer context window, and stronger overall capabilities. We will also publish a detailed research paper once we are done training Llama 3.

To give you a sneak preview for where these models are today as they continue training, we thought we could share some snapshots of how our largest LLM model is trending. Please note that this data is based on an early checkpoint of Llama 3 that is still training and these capabilities are not supported as part of the models released today.

We’re committed to the continued growth and development of an open AI ecosystem for releasing our models responsibly. We have long believed that openness leads to better, safer products, faster innovation, and a healthier overall market. This is good for Meta, and it is good for society. We’re taking a community-first approach with Llama 3, and starting today, these models are available on the leading cloud, hosting, and hardware platforms with many more to come.

Try Meta Llama 3 today

We’ve integrated our latest models into Meta AI, which we believe is the world’s leading AI assistant. It’s now built with Llama 3 technology and it’s available in more countries across our apps.

You can use Meta AI on Facebook, Instagram, WhatsApp, Messenger, and the web to get things done, learn, create, and connect with the things that matter to you. You can read more about the Meta AI experience here .

Visit the Llama 3 website to download the models and reference the Getting Started Guide for the latest list of all available platforms.

You’ll also soon be able to test multimodal Meta AI on our Ray-Ban Meta smart glasses.

As always, we look forward to seeing all the amazing products and experiences you will build with Meta Llama 3.

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