research paper on edtech industry in india

Factors impacting acceptance of e-learning in India: learners' perspective

Asian Association of Open Universities Journal

ISSN : 2414-6994

Article publication date: 21 July 2022

Issue publication date: 5 October 2022

This study aims to identify the most significant factors that influence acceptance of e-learning in India. As e-learning has gained popularity in the wake of the COVID-19 pandemic and continues to be one of the most sustainable methods of education, it is pertinent to examine learners' perception towards its acceptance. There is limited literature available on this subject in India, especially factoring in impact of the pandemic.

Design/methodology/approach

This study empirically analyses data of 331 adult e-learners in India, who have enrolled for one of the following e-learning formats: higher education, private coaching, test preparation, re-skilling and online certifications, corporate training and hobby and language-related learning. Their perception is examined on the basis of a model developed using the Unified Theory of Acceptance and Use of Technology model. Data are analysed through structural equation modelling using SPSS and AMOS statistical tools.

The result of the study shows that Infrastructure Dependability, Effectiveness of Design and Content of Courses and Student's Competency with Computers are the top three factors impacting e-learning acceptance in India.

Research limitations/implications

This study makes several theoretical contributions. Additionally, research findings and recommendations will facilitate education providers, corporates in the education industry and policymakers to focus on the significant areas for enhancing the acceptance of e-learning.

Originality/value

This study identifies and confirms important factors that influence e-learning acceptance and suggests opportunities for further in-depth research and analysis.

• Acceptance of e-learning
• Factors influencing acceptance of e-learning
• Factors impacting acceptance of e-learning
• E-Learning acceptance
• Acceptance of online learning

Duggal, S. (2022), "Factors impacting acceptance of e-learning in India: learners' perspective", Asian Association of Open Universities Journal , Vol. 17 No. 2, pp. 101-119. https://doi.org/10.1108/AAOUJ-01-2022-0010

Emerald Publishing Limited

Copyright © 2022, Sanya Duggal

Published in the Asian Association of Open Universities Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/ legalcode

1. Introduction

Education is a US$6 tn industry worldwide, as per Barclays Research and HolonIQ, an education intelligence provider. It is expected to grow to $7.3 tn by 2025 and to $10 tn by 2030 ( Barclays and HolonIQ, 2020 ). The segment of the education industry enabled by technology is called “education technology” or “EdTech” ( Barclays and HolonIQ, 2020 ).

Technology enables various services and solutions across levels in the education space. It encompasses learning, teaching, assessment, credentialing and certification, student data management and research management ( HolonIQ, 2021 ). However, only 3.1% of the total education expenditure worldwide is currently on digital aspects, which is expected to grow to 5.5% by the year 2025 ( HolonIQ, 2020 ). HolonIQ also estimates EdTech to become a US $404 Bn market by 2025 from US$183 bn in 2019 worldwide ( HolonIQ, 2020 ).

As of 2020, education in India is a US$117 Bn market with 360 Mn learners ( PGA Labs, 2020 ). It is expected to grow 2x to US$225 Bn by 2025 ( PGA Labs, 2020 ). The adoption of technology has been on a consistent rise in India's education sector in the last 10 years ( KPMG, 2017 ). Inc42 DataLabs estimated the Indian EdTech market to reach US$2.8 Bn in 2020. Aided by strong COVID-19 tailwinds, the report estimates its growth to be US$10.4 Bn by 2025 ( Inc42 Data Labs, 2020 ).

Online learning or e-learning is the largest segment of EdTech, attracting its maximum paid customers ( Nasscom, 2018 ). E-learning refers to learning provided via electronic means. It enables the availability of the learning process and educational curriculum outside the traditional classrooms (HolonIQ, 2021) . E-learning offers many benefits such as convenience, saving of time and costs, timely updates, flexibility and easy monitoring of learners' progress. Further, the online learning audience is vast and varied, ranging from school children to retired or working professionals ( KPMG, 2017 ).

E-learning promotes self-education, and with the availability of small and smart schools, it works well. Students are not restricted to gain knowledge within their domestic boundaries; they can now attend sessions across the nation with the help of the Internet. E-learning ensures many benefits such as the following: (1) Irrespective of the distance, it ensures communication between the parties with the help of a dialogues room, digital classroom and emails. (2) 24-h availability of the resources leads to no fixed time frame as teachers are available even after working hours. (3) Even after personal responsibilities, as per the time availability, everyone can learn ( Abed, 2019 ).

There is a change in sense of equality as well; earlier in traditional classrooms, it was observed that weak students hesitated in asking questions and did not share their opinions, but in e-learning, they have a platform where they can send their queries via email and can discuss one-to-one as well ( Sharp, 2000 ). Education is the basic and very strong beam behind the success of any nation ( Baiyere and Li, 2016 ). After COVID-19, the education sector suffered a lot because of the closing and suspension of schools. The sudden suspension left no choice for the education industry and made it vulnerable too. In these times, teachers and educators started trying and using various e-platforms to educate everyone. In this situation, information and communication technology offered edge over the traditional methods with e-learning and virtual universities ( Alsoud and Harasis, 2021 ). COVID-19 created a crisis in the education system and left it with a number of challenges. Challenge of one-to-one education, challenge of virtual education and many more challenges were faced by the world ( Edelhauser and Lupu-Dima, 2020 ).

The e-learning space in India hit an inflection point as the COVID-19 pandemic set in during H1 of 2020 ( Inc42 Data Labs, 2020 ). The pandemic compelled educational institutes and learners to use e-learning for continuing education. In this prevailing situation, it becomes more important to understand the perception of learners towards acceptance of e-learning and evaluate factors that can influence its acceptance positively. There is limited literature on this topic, especially research that (1) factors in the impact of the pandemic and (2) is greater in audience scope and includes adult learners.

Therefore, there is a need to identify the significant factors that affect the acceptance of e-learning systems and consequentially prioritise their effectiveness to improve the overall e-learning outcomes. In India, there are a few research papers on similar topics, especially on e-learning carried out by universities, but it is necessary to increase the scope to include other adult learners and thus support the success of the e-learning ecosystem. This study aims to evaluate factors that affect acceptance of e-learning and is targeted to users in the higher education space, test preparers over the age of 20 years, working professionals investing in re-skilling and online certifications and corporate training and users over the age of 20 years for hobby and language-related learning.

To summarise, the main objectives of this research are to (1) identify the impact of factors that influence the acceptance of e-learning systems in India for adult learners and (2) suggest ways to improve students' e-learning acceptance in India. This paper is structured as follows: Section 2 introduces the concepts and covers the extant literature, Section 3 has the research model and lays the hypothesis, Section 4 covers the research method, Section 5 provides the results of this research, Section 6 shares the discussion and Section 7 provides conclusions.

2. Relevant studies

This section examines the meaning of e-learning and past studies on the subject. It also explores the factors that affect the acceptance of e-learning. Based on these findings, a research model and hypotheses are developed in Section 3 .

2.1 E-learning

E-learning is a training or learning procedure that is created, managed and delivered using different information technology (IT) tools which can be local or global ( Masie, 2016 ). E-learning is defined as a learning methodology that is dependent on Internet communications and facilitates interaction between students and lecturers through suitably designed content and resources ( Resta and Patru, 2010 ).

Along the lines of Nguyen et al. (2014) , this research takes e-learning to be a learning method based on the Internet that is conducted through a formal educational program and is managed by a learning management system (LMS). It is meant to ensure collaboration and interaction and thus satisfy the learning demands of any learners irrespective of time and place. Pham and Huynh (2017) noted that there is a difference in e-learning in developed and developing countries. In developing countries like India, e-learning has been applied in the recent few years and proper technology infrastructure to support education is still underway.

The outbreak of COVID-19 has emphasised the change in learning from traditional teaching to online teaching. Now, most schools and universities have provided a hybrid system of teaching so that those who can’t come to school because of physical disabilities can now attend schools and higher education. In many governments of foreign countries like Georgia, the Education Ministry of Georgia has provided Microsoft Teams to all the public schools and also started TV schools (The Government of Georgia, 2020) .

2.2 Past studies on e-learning

The National Center for Education Statistics has reported an increment in the requirement for e-learning due to the COVID-19 pandemic. As per Biswas et al. (2020) , there has been a surge in the research on understanding students' perceptions and expectations of e-learning. Studies also reveal that learners' perceptions and acceptance are affected by a number of factors.

However, there are very limited studies that focus on the factors affecting acceptance of e-learning in India during the COVID-19 timeframe, especially the ones that cover adult learners, i.e., learners over the age of 18 years.

2.3 Factors affecting acceptance of e-learning

E-learning is essentially an information system; thus, the acceptance of e-learning can be measured just like the acceptance of any other information system or technology. Acceptance of a technology system can also be factored as the success of that system, and thus, this study will consider all factors that contribute to the acceptance or success of a technology system.

According to Seddon (1997) , there are three aspects that evaluate an information system's success. These are (1) quality of a system as measured by timeliness, relevance and accuracy; (2) perceptual measurements such as user satisfaction and perceived usefulness and (3) perceived benefits that can range from organisational to individual to social.

DeLone and McLean (2003) added service quality as an additional contributing factor of the information system success model to the above-listed factors.

Pham and Huynh (2017) measured the success of an e-learning system through independent variables covering perceived usefulness, computer self-efficacy, email interaction, face-to-face interaction, ease of use and social presence.

There are two more models that can be used to understand the acceptance of a technology system: Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). Davis et al. (1989) developed the TAM using Fishbein and Ajzen’s (1975) Theory of Reasoned Action (TRA). The TAM explains that there are two main factors affecting the acceptance of information systems: perceived easiness in use and perceived usefulness. This was further explained by Venkatesh and Davis (2000) who suggested the Technology Acceptance Model (TAM2), an extension to explore the determinants of perceived easiness of use and perceived usefulness.

Venkatesh et al. (2003) proposed the UTAUT to reason the factors affecting user behaviour towards acceptance of information systems. The UTAUT proposes that four factors affect acceptance: effort expectancy, performance expectancy, facilitating conditions and social influence. Venkatesh et al. (2012) developed UTAUT2 by adding three new factors to these four: exchange value, convenience and habit.

Over the years, the UTAUT has been used as the foundational theory to explore the acceptance attributes of e-learning. Incorporating the context of e-learning systems, the UTAUT focuses on the following four factors:

2.3.1 Performance expectancy

Acceptance of e-learning is influenced by the design and content of the courses and the collaboration of students, as per Laily et al. (2013) and Selim (2007) . These could be considered as the two factors within performance expectancy.

2.3.2 Effort expectancy

This factor can be interpreted as the ease of use of e-learning systems by e-learners. As per Laily et al. (2013) , the computer competency of students affects acceptance of e-learning systems.

2.3.3 Social influence

As per Selim (2007) , lecturers/teachers play an important role in the acceptance of e-learning as they are in the capacity of advising students, implementing tests, organising events online and engaging students. This is representative of the factor of social influence.

2.3.4 Facilitating conditions

Conditions such as dependable infrastructure, platform/provider/university support and accessibility of Internet affect e-learning, as per Selim (2007) . These crucial factors can be considered as facilitating conditions for e-learning acceptance.

3. Research model and hypotheses

3.1 research model.

On the basis of the discussion mentioned earlier, the UTAUT model is selected as the foundational theory for this study as the UTAUT covers a majority of factors that affect the acceptance of e-learning. The UTAUT is the “unified theory of acceptance and use of technology” model that was formulated by Venkatesh et al. in "User acceptance of information technology: Toward a unified view” (2003). This model aims to explain a user's intentions and dependencies to use an information system and the ensuing usage behaviour. It is based on four key constructs, first being performance expectancy, second effort expectancy, third social influence and fourth facilitating conditions (see Figure 1 ).

For the proposed research model, seven constructs, being directly based on these 4 dimensions of the UTAUT model, are drawn in this study. The seven defined constructs are as follows: Effectiveness of Instructor or Lecturer, Student's Competency with Computers, Student's Collaboration Interests, Effectiveness of Design and Content of Courses, Accessibility of Essential Resources, Infrastructure Dependability and Provider Support Received.

It can be observed, as mentioned in Section 2 , that constructs “Student's Collaboration Interests” and “Effectiveness of Design and Content of Courses” can be associated to performance expectancy; construct “Student's Competency with Computers” is related to effort expectancy; “Effectiveness of Instructor or Lecturer” is associated to social influence and “Accessibility of Essential Resources”, “Infrastructure Dependability” and “Provider Support Received” tie into facilitating conditions (see Figure 2 ).

3.2 Hypothesis statements

The seven hypothesis statements are developed from the seven factors obtained through the review and analysis so far.

3.2.1 Instructor

There is a significant impact of the instructor on e-learning acceptance of students.

3.2.2 Computer competency

There is a significant impact of computer competency on e-learning acceptance of students.

3.2.3 Collaboration interests

There is a significant impact of collaboration of students on the e-learning acceptance of students.

3.2.4 Design and content of courses

There is a significant impact of content and design of the courses on the e-learning acceptance of students.

3.2.5 Accessibility of essential resources

There is a significant impact of accessibility of essential resources on the e-learning acceptance of students.

3.2.6 Infrastructure dependability

There is a significant impact of infrastructure dependability on the e-learning acceptance of students.

3.2.7 Platform/provider/institution support

There is a significant impact of platform/provider support on the e-learning acceptance of students.

4.1 Methodology

Step 1 : Preliminary Quantitative Research. The first version of the questionnaire was circulated to 40 participants who had prior experience with e-learning. These data were collected, and reliability was tested using Cronbach's alpha test and exploratory factor analysis. On the basis of the discrepancies observed in this set, minor modifications were made to the survey questionnaire. The final survey was then circulated to students and working professionals to capture responses.

Step 2 : Final Quantitative Research. The final questionnaire was sent to students at higher education institutes and to the professionals across different age groups, domains and industries. The only requirement was that the survey participant must have undertaken an e-learning course in the last one year. The data collected were analysed through Cronbach's alpha analysis, exploratory factor analysis, confirmatory factor analysis (CFA) and structural equation modelling (SEM).

4.2 Measurement scales

A 5-point Likert scale was used to solicit responses from the participants to gather their inputs to each variable. The variables rolled up to 8 constructs – 7 were factors impacting e-learning acceptance, and the 8th construct gauged the acceptance of e-learning by participants. The first construct, Effectiveness of Instructor, had 6 variables developed from Soong et al. (2001) and Volery and Lord (2000) . The second construct, Student's Competency with Computers, drew 5 variables from Soong et al. (2001) . The third construct, Student's Collaboration Interests, had 5 variables again from Soong et al. (2001) . The fourth construct, Effectiveness of Design and Content of Courses, had 5 scales from Soong et al. (2001) . The fifth construct, Accessibility of Essential Resources, had 6 items from Volery and Lord (2000) . The sixth construct, Infrastructure Dependability, developed 4 items from Volery and Lord (2000) . The seventh construct, Provider Support Received, had 6 items based on Selim (2007) . The eight construct, What Do You Feel About E-Learning, measured e-learning acceptance and was developed on 7 items from Selim (2007) and Nehari and Bender (1978) .

Here are the variables used for each construct (see Table 1 ).

4.3 Data gathering and analysis

According to the research by Hoang and Chu (2008) , the minimum sample size for analysis of data must be higher than 5 times the observed variables. In this study, 44 variables were observed, developed from 8 underlying factors. Thus, the minimum sample size requirement was 220 (44 × 5). In order to get sufficient data, the survey was shared with over 1,000 participants and the aim was to collect about 300 responses.

5. Results and observations

After the data were collected, it was analysed with the help of Cronbach's alpha analysis, exploratory factor analysis, CFA and SEM. To this effect, the statistical tools IBM SPSS and IBM SPSS AMOS were used.

5.1 Overview of data collected

Data for this research were collected through the random sampling method. The survey questionnaire was circulated via email, social networking websites and university forums and in person also. A total of 388 responses were received from the survey. Out of these, there were 331 valid responses. Invalid responses comprised of respondents who had not taken any e-learning course, who gave the same answer to every question, etc.

The following is a demographic overview of the data received ( N  = 331) (see Table 2 ).

5.2 Cronbach's alpha analysis

Cronbach’s alpha measures the reliability of a set of data. It determines the internal consistency by checking how closely items are related to a construct. A scale can be considered reliable if its Cronbach’s alpha coefficient ( α ) is greater than 0.6. Also, as Nguyen and Nguyen (2011) defined, the item correlation within a group must be greater than 0.3 and if it is not so, the item must be removed.

On analysing the results from this survey, it was found that the Cronbach’s alpha of all constructs was greater than 0.6. However, there were 4 items that had to be removed owing to correlations lesser than 0.3. Here is a summary (see Table 3 ).

5.3 Exploratory factor analysis

Exploratory factor analysis is a multivariate technique that is used to identify underlying relationships between a set of data variables. The first step within this is the Kaiser–Meyer–Olkin (KMO) and Bartlett test, which indicates the suitability of data for purposes of structure detection. The KMO coefficient in these data was 0.930, indicating that exploratory factor analysis could be used since the coefficient was >0.5.

It showed that hypothesis of correlation within the variables must be rejected as Sig. = 0.000. Further, with Eigenvalue ≥ 1, with the “principal component analysis” method, using “Promax” rotation along with Kaiser normalisation, there were 7 factors extracted from the 40 measured variables. There were no variables with low loading (<0.3) factor coefficients, and thus, no variables had to be removed at this stage. This output could be used next for CFA (see Figures 3 and 4 ).

5.4 Confirmatory factor analysis

CMIN – Chi-square

CMIN/df – Chi-square/degree of freedom

GFI – Goodness of fit index

CFI – Comparative fit index

TLI – Tucker–Lewis Index

RMSEA – Root mean square error approximation

According to Nguyen (2013) , for a model to be considered fit as per market data, the values of TLI, GFI and CFI must be ≥ 0.9, RMSEA ≤ 0.08 and CMIN/df ≤ 3.

Initially as the estimates are calculated, TLI = 0.861, GFI = 0.758, CFI = 0.872, RMSEA = 0.073 and CMIN/df = 2.771, which clearly did not meet the criteria. In the next iterations, variables are removed one by one based on variables with low weights as per the standardized regression weights table. In this order, the following variables were removed: AER4, AER6, Outcome 6, SCC1, Outcome 7, ELI2, Outcome 3, ID3, ELI1, ELI6, AER2, PSR1, PSR2, PSR6 and ECD1. Finally, the following values were estimated: CMIN = 430.083, CMIN/df = 1.741, GFI = 0.905, CFI = 0.965, TLI = 0.958 and RMSEA = 0.047.

This determined that the model could be fit to the survey data. The final CFA result, as created in AMOS software, was as follows (see Figure 5 ).

5.5 Structural equation model analysis

SEM is a multivariate statistical technique that is used to determine structural relationships between latent constructs and measured variables. SEM analysis is based on CFA. As the determined model was fit for survey data, the next step here was to build the structural relationship between the variables.

Here is the finalised SEM result, as presented in AMOS (see Figure 6 ).

Analysing the text output of this diagram, the following values are noted that are to be used to accept/reject the hypothesis of this study.

The P -value is considered to be a piece of evidence against the null hypothesis, and a p -value less than 0.05 (ideally ≤0.05) is statistically significant, leading to the null hypothesis being rejected. To that effect, only one hypothesis from the observed 7 is rejected (H07-PSR, rest 6 are accepted) (see Table 4 ).

6. Discussion

This analysis showed that Infrastructure Dependability (0.217), the Effectiveness of Design and Content of Courses (0.159), Student's Competency with Computers (0.059), Student's Collaboration Interests (0.057) and Effectiveness of Instructor (0.008) had a significant impact on the e-learning acceptance of students, in that order. Accessibility of essential resources (−0.035) had insignificant impact on e-learning acceptance. Provider/platform/university technical support has no impact on the acceptance of e-learning by students.

These results are quite similar to prior research by Selim (2007) and Laily et al. (2013) which had the collaboration of students, course content and IT infrastructure as the top three impact factors. However, in this study, two of these factors are the same, and collaboration of students is the differentiating factor as this study has student's competency with computers instead. From the research by Pham and Huynh (2018) , competency with computers, social presence and student collaboration was drawn as the top three factors. Again, computer competency is common in the top three factors in the current study.

E-learning in India is still at a nascent stage, and the results of this study can be explained in that context. Infrastructure dependability refers to the core technology (computer/laptop) and communications network (Internet connectivity) required for e-learning to function. Many parts of India have undependable Internet connectivity, and poor networks now and then are common in most areas of the country. Thus, dependable infrastructure is the first and foremost requirement for e-learning acceptance. Secondly, the quality and learning outcome of e-learning is driven by the content of the courses offered and the way that they are designed. Perceived good-quality content and user-friendly structuring tend to lead to higher acceptance of e-learning. Thirdly, as noted in the earlier part of the study, a vast majority of e-learning is currently driven by re-skilling and certification courses. EdTech in India has been popularised only in the last 8–10 years; thus, this re-skilling and certification learning audience is mid/late technology adopters and not digital natives. Their competency in using computers is workable and might not be extremely proficient. This explains why computer competency criteria rank in the top third.

Moving to the other two criteria, students' collaboration interests rank very close to the computer competency criteria. Students enjoy collaborating with instructors and peers over online learning, and this enhances their acceptability of the e-learning format. This coalesces with the proven fact that students have lesser inhibitions or fears when participating online vs participating in traditional formats. The last factor, the effectiveness of the instructor, points to the collaboration encouraged by the facilitator by asking questions, involving students in discussions and encouraging acceptance of e-learning. This factor ranking last could be majorly attributed to the fact that most of the e-learning designed in India presently is in recorded formats vs being live teaching. The majority of re-skilling and certification courses are pre-recorded and leave hardly any room for live discussions. The test preparation category and higher education tend to have live interactions with teachers, but the quantum of this category in overall e-learning is low.

Accessibility of essential resources has an insignificant impact on e-learning acceptance. These resources include good connectivity, satisfactory browsing speed, no bandwidth problems when browsing, easy-to-use e-learning websites, etc. These can be understood as convenience factors as opposed to necessity factors. In India, the first technology requirement is core hardware and software and a dependable network (infrastructure dependability factor), and convenience comes as secondary or not a priority. This explains why accessibility falls in the insignificant impact category.

Lastly, provider/platform/university technical support has no impact on the acceptance of e-learning by students. This factor is not at all influencing in e-learning acceptance as it is least expected/required by students. E-learning acceptance is not dependent on this criterion at all.

7. Conclusion

7.1 conclusions.

This study has reviewed past literature on the acceptance of e-learning and created a model to test the factors affecting acceptance of e-learning in India. The model used in this study was based on the UTAUT model and comprised of 7 factors covering 44 variables developed from past research.

Data were collected to understand users' behaviours regarding e-learning acceptance. From a total of 388 responses received, 331 could be analysed for the study. The data analysis was conducted with the help of Cronbach analysis, exploratory factor analysis, CFA and SEM. This was carried out with the help of tools like SPSS and AMOS.

The results of the study showed that infrastructure dependability, effectiveness of design and content of courses and students’ competency with computers were the top three factors impacting e-learning acceptance in India. Students’ collaboration interests and effectiveness of instructor also had a significant impact on the e-learning acceptance of Indian students.

7.2 Recommendations

Infrastructure Dependability . On a micro-level, different organisations can take active steps to improve the infrastructure required by their e-learners. For example, for online corporate training, companies can ensure that their employees have well-functioning laptops and proper network connectivity. In case of higher education, universities can provide laptops/tablets or other devices to students as part of the onboarding resources. Further, Shuja et al. (2019) showed that mobile platforms contribute to students’ improved academic performance. This insight can be utilised by test preparation organisations and other institutes to ensure that their e-learning content is mobile-friendly.

Effectiveness of Design and Content of Courses . Learning online is different from learning in traditional formats and requires understanding behaviours and drivers of learners. To that effect, design and content of e-courses must be updated and revised regularly. E-learning content must also be broken into smaller pieces, infused with more effective methods like videos, whiteboarding and live interactions and structured in easily consumable ways. More innovative techniques like gamification can also be introduced to improve content design effectiveness.

Student's Competency with Computers . Platforms, organisations and institutes can equip students with learning resources to improve their computer competency. They can provide the option to learn both basic and advanced computer features and skills. One example to do this could be to include a 5-min optional introduction to a new user upon enrolling in a platform. Another example could be a short virtual training to higher education students during on-boarding procedures.

Student's Collaboration Interests . Different online activities and games can be included in course content to have students interact and collaborate more. Virtual workshops can encourage group participation and presentation. An information portal or collaboration tool such as Microsoft Teams or Google Meet can be provided to students for effective participation. These activities can be scored and measured for enhanced effect.

Effectiveness of Instructor . An instructor can improve effectiveness by involving students more in classes. Instructors can encourage students to speak and participate, ask questions, conduct activities, etc. They can also improvise on the format and structure of classes to change from simply sharing presentations online to include videos, app-based games, quick quizzes, etc.

These recommendations are indicative and not exhaustive; however, their implementation can help in improving the acceptance of e-learning.

7.3 Contributions

This study makes several theoretical contributions to academia. It adds new and current dimensions to previous research on the subject, including the impact on COVID-19. The findings discovered herein can be used as premises for further research.

Additionally, this study brings out results for industry use. Research findings and recommendations covered herein will facilitate education providers, corporates in the education industry and policymakers to focus on the significant areas for enhancing the acceptance of e-learning in India.

7.4 Limitations and future research

There are a few limitations of this study, enumerated as hereunder: (1) The sample size of 331 is small and limited. (2) The data sample might be limited to urbanised populations and might not reflect the acceptance factors in rural areas or students belonging to very-low- or very-high-income groups. (3) The seven factors included for consideration in the study might not be exhaustive, and there could be potential factors (more current or innovative) not included in the study.

Thus, as with all research, there is scope for further work from this study. The small size can be expanded to allow for wider coverage of geographical area, even beyond India, or to rural populations, within India. It would be helpful to introduce other potentially impacting variables to this research for further findings. Further, each of the top impacting factors can be explored in greater detail to find potential areas of the highest impact.

The UTAUT model, adapted from Venkatesh et al . (2003)

The proposed research model

KMO and Barlett's test result

Exploratory factor analysis result

Final standardised CFA result

Final standardised structural equation model analysis result

Scale adaptation variables used in the constructs

Demographic data of survey participants

Cronbach’s alpha analysis results

Hypothesis testing results

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Is India ready to accept an EdTech-intensive system in post pandemic times? A strategic analysis of India’s “readiness” in terms of basic infrastructural support

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The pandemic situation has forced most of the countries to plummet toward a virtual, distant learning format in recent years since 2020. While there are certain undeniable benefits of a virtual, technology-infused setup, it essentially calls for a complete paradigm shift for a country like India which has otherwise been a practitioner of traditional classroom teaching. Despite that, the recent boom in the EdTech market in India coupled with recent government policies indicate that India is going for that paradigm shift. The key thing to note here is that an EdTech-intensive setup is not as primitive as the traditional one. Its feasibility demands more rigorous infrastructural support. This paper looks into the very basic infrastructural requirements of the system in light of a very straightforward strategic analysis model—Objective and Key Results. Under this setup, India’s readiness is measured in terms of the availability of electricity, internet, and digital equipment with the intention of making an accessible, affordable and inclusive EdTech-driven education system. Moving one step further, this paper also tallies the recent policies with the specific shortcomings of the existing system to determine whether or not India is moving on the right path to progress. In a nutshell, it is found that there is ample room for improvement in the current arrangement for implementing a large-scale EdTech-enabled system, but the progress is most certainly happening in the right direction. Recent policies make quite an argument in favor of doing away with the digital divide and building an effective and inclusive EdTech-powered education system for the future generations of citizens.

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In March 2020, after WHO declared the COVID-19 to be a global pandemic, the majority of the countries imposed a “lockdown” to control the spread of this virus, putting an immediate halt to all sorts of economic and social activities. This frozen state of the economies directly impacted all sectors including the education sector as well. A compulsion to find an alternative mode of operation became the burning necessity. In this situation, most of the countries adopted remotely operated distant learning as their key technique to continue the functioning of their respective education sectors. This is where it is to be vehemently pointed out that this adoption was a compulsion and this has impacted the education sector and its stakeholders in various ways depending on several preparedness and acceptance parameters. In other words, a sudden paradigm shift is expected to impact different cohorts of stakeholders differently due to the difference in their ability to accept and manage the so-called “new normal”. Therefore, at the beginning of 2022, while the world moves toward a post-COVID-19 situation, it is increasingly important to discuss the impact of these modifications on the stakeholders. In recent days, the global education scenario has leaned toward technology-infused teaching and learning which includes components of distant learning and remote operations. Specifically, after the pandemic, the world has acknowledged not only the benefits but the sheer necessity of a virtual platform in the education sector. So, instead of a temporary solution to mobilize an otherwise frozen economy, technology-infused operation is being widely thought as the future face of the global education industry.

This is where both the context and the intent of this particular paper come from. Switching to a more technology-infused system is not a minor modification, it is a gigantic leap to a completely different paradigm. Therefore, the prerequisites of this jump are expected to be different than the existing traditional classroom system which has been operating for centuries now. But in the modern setup, the method of teaching and learning is operated through Information and Communication Technology (ICT). Therefore, if ICT being the driving force of the education industry becomes the norm, the prerequisites are to be taken care of to ensure smooth and inclusive operation for optimum yield. In other words, the “readiness” factor is to be considered with utmost importance in order to make this transition a successful and productive one. This particular paper specifically focuses on the situation in India to assess its readiness in taking on an ICT-powered education system. Put differently, this paper scrolls through India’s recent moves to embrace ICT-powered education, the challenges that come with it, and policies to cater to those challenges.

Evolution of educational technology in India

In a world that is espousing ICT-powered education, India is certainly not falling behind. While it is true that India’s education sector is primarily reliant on traditional classroom teaching approach, recent developments in the Indian education sector show clear inclination toward Educational Technology (EdTech). EdTech offers a certain range of major benefits over the traditional setup. Firstly, EdTech allows customization and personalization of the curricula based on individual specific requirements and abilities. Secondly, the involvement of ICT provides ease of access to educational content for both learners and instructors. Lastly, EdTech enables distant learning and remote operations, as discussed previously, removing geographical constraints of learning (Zhang and Aslan 2021). In short, it can be said that EdTech provides a structural easement and thus accelerates the very process of delivering education. This in turn translates into economic growth through increased labor productivity, technological innovation, and implementation of newer technology (Hanushek and Woessmann 2010 ). This is where the social and economic interest begins to grow for any country to implement EdTech.

India is home to the largest population of learners belonging to the K-12 system with a reported enrollment rate (2017–2018) of approximately 250 million learners in 1.5 million schools across the nation (Statista survey data). Therefore, augmenting the education system to reap the benefits of EdTech and ICT-driven learning will surely contribute to the overall human capital formation and subsequent increment in productivity along with technological innovations in India translating into higher economic growth. Incentivized by this motive, the Indian education sector has become the cultivation ground of budding EdTech ventures in recent years. Both private sector and public sector initiatives have been seen to be growing in order to make EdTech more mainstream and an integrated part of the Indian education system.

The stepping stone of the Indian EdTech ecosystem is the launch of the EDUSAT satellite. In September 2004, a project of INR 5.5 billion was conducted by the Indian Space Research Organization (ISRO) in order to launch this satellite which was designed to cater exclusively to the educational requirements of the country. In specific, the satellite was used to create virtual classrooms in remote areas of India to deliver education through visualization offered by video programs telecast by the satellite (Nagaratinam 2015 ). In 2008, private players came into the field and e-learning platforms like Extramarks and Khan Academy became popular in India. With this, gradually EdTech started providing successful business models to startups in the Indian market with a vast user base. This gradual increment came to its peak and turned into an EdTech boom in 2015–2016. According to the reports published in The Economic Times and estimations done by Nasscom, in 2015 alone, nearly a thousand EdTech startups came forward to join the EdTech venture in India with an estimated funding of USD 125 million. At the same time, Indian students started joining other internationally recognized platforms as well. According to a MyStory report, in 2015, more than 1.5 million learners joined online courses on the popular US-based platform Coursera.

This rapid growth has only seen an upward trajectory in terms of consumption over time. Parallel to the great potential of the Indian market, the Indian education industry has become the breeding ground of many blooming and booming EdTech startups. Currently, there are approximately 4530 EdTech startups in India of which more than 400 were founded after 2019. Very recently, Indian EdTech startups have attracted nearly $4 billion worth of investments in the past two years, of which $2.2 billion was invested in 2020 alone right after the nationwide lockdown had frozen the education sector of the country. An additional $1.9 billion investment done in 2021 has added 3 more Indian names to the list of global EdTech unicorns (valued at over $1 billion). The Indian name Byju’s, existing in the world EdTech unicorns list since 2017, has now become a decacorn with a valuation of $21 billion (HolonIQ 2022 ). Unacademy, Emeritus, and upGrad are three more Indian EdTech startups that have been included in the list in August 2021, followed by Vedantu in September of that year. Very recently, another Indian startup, Lead School made it to the list in January 2022 (HolonIQ 2022 ). It is to be noted here that Byju’s is currently the world’s largest EdTech startup catering to more than 100 million registered users. These figures make it evident that India is a very lucrative market for EdTech. Additionally, the company has reported that its average user engagement time has gone up by 30% during the pandemic, average daily engagement time has gone up from 71 to 100 min (Economic Times, February 2021).

While on the one hand, the above discussion elaborates privately pursued EdTech ventures in India, like the initiative of EDUSAT, recent government policies also have a keen focus on EdTech. The National Education Policy (NEP) 2020 is the government’s newest arrow in the quiver to achieve Sustainable Development Goal (SDG) 4 (to provide quality education to its citizens) which inherits the very concept of EdTech in the day to day educational operations. As already discussed, EdTech has three main components through which it enhances the educational outcomes: customizability of content, accessibility of content, and remote operations. NEP caters to all three of these components. In order to identify and acknowledge student-specific characteristics and infuse them in the learning process, NEP proposes detailed renovation and reintroduction of the e-learning platforms, e.g., SWAYAM and DIKSHA; this will make the system more “student-centered”. Providing e-content and QR code energized textbooks across the entire country through these platforms will give ease of access to educational content. Additionally, keeping in mind the paucity of digital resources, NEP also proposes to use standardized multimedia platforms i.e. radio and television to deliver educational content to the general populace. Apart from this, the top one hundred universities across the country are permitted to start online courses from 30 May 2020 itself which allows students to access courses according to their requirement and preferences without worrying about geographical barriers and the hustles of relocating.

Considering the overall scenario, it is safe to say that EdTech in India is not just an alternative for an otherwise frozen system. The gigantic growth and immaculate presence of EdTech in the veins of the current educational practice in India put forth a clear signal that EdTech is ready to become an integral part of the next generation Indian education system. This brings forth the motivation to discuss different preparedness parameters in the Indian socioeconomic framework to ensure a fruitful and inclusive operation of EdTech in the country.

In the economics of education literature, it is well established that EdTech appreciably widens the horizon of possibilities in the education sector. Most importantly, it accepts the heterogeneity among students to provide a more engaging and well-suited experience of learning (Al Hadwer et al. 2019) which was otherwise missing in the traditional “one-size-fits-all” system. Simultaneously, it is also undeniable that the infrastructural requirement of a majorly EdTech-driven system is not as primitive as the traditional classroom teaching setup. The most critical divisive factor between the two is the requirement for digital infrastructure as EdTech systems highly rely on ICT. This raises the concern to study the “readiness” factor of any country prior to implementing a large-scale EdTech transfiguration (Adam et al. 2021 ).

It is very important to note here that the readiness factor primarily consists of infrastructural preparedness and access to digital resources which in turn depend on the socioeconomic condition and governance of a particular country. These factors are very country-specific and contain irregularity. Conclusions drawn on the basis of parameters observed in one country, cannot be relevant in the case of another. Therefore, because of the irregularity of the domain, the literature is unable to come to a generalized opinion about the readiness (or feasibility in other words) of a full-scale adoption of an EdTech driven system. This question has to be answered on a country level. Specifically, in a developing country like India, the question of readiness is of utmost importance, because within-the-country variations are also to be considered in a large country like India with such a vast population. These within-the-country variations can put barriers among the population and hinder the inclusivity of the venture in totality. This paper attempts to strategically analyze the situation and assess the very basic readiness factors in the way of embracing an EdTech-intensive system in India.

Research question and methodology

With the compulsive switch to the virtual platform along with the push of NEP 2020, a permanent paradigm shift in the Indian education sector is imminent. This paper attempts to assess whether or not India is ready for that shift. The main problem with such a discussion is the subjectivity of the term “readiness” itself. Therefore, it is of utmost importance to have a precise definition of the term “readiness” in order to clearly establish the territory of the upcoming discussion as well as map the procedure of analysis step by step.

With that purpose in hand, one of the most straightforward strategic planning models, Objective and Key Results (OKR) is considered here (Grove 2015 ). OKR is all about setting a specific achievement, also known as the “objective”, and deploying a few measurable quantitative parameters of progress, also known as “key results”, which are then tracked to know how close or how far one is from their respective objective. This particular framework can be adopted quite suitably here. The first step is to identify the objective at hand. Obviously, the objective is to make India ready for an EdTech-intensive education system in post-pandemic times .

The next step is to find out the measurable quantitative parameters (i.e. the key results) to reflect the progress toward the said objective. In order to set up the key results, an approach known as the Key Performance Indicators (KPI) is used. It essentially states that there are a few crucial (measurable) performance parameters that are responsible for the overall effectiveness of the system. Here, studying the literature, one can easily say the first and foremost parameter which is responsible for making an EdTech driven system successful is the availability of the internet along with digital devices. ICT being the building block of EdTech, without internet and digital devices it is simply not possible for any EdTech system to function. The necessity for these is well documented in the literature. However, if one moves one step further, there is a more rudimentary factor to be considered—electricity! Without electricity, it is once again impossible to power up the equipment.

Therefore, electricity, internet, and availability of digital devices can be considered three primary factors which affect the performance of the EdTech system. These are quantifiable parameters as well. Simply by considering the penetration rate, a picture of progress toward the desired “readiness” can be painted. Hence, the research question boils down to the following,

Is India ready to accept an EdTech-intensive system in post-pandemic times , where readiness is measured in terms of

availability of electricity

availability of internet connectivity

availability of digital resources.

In other words, the fields of electricity, internet connectivity, and digital resource availability will be reviewed in detail to figure out how far or how close India is to attaining the desired readiness to have an effective EdTech transfiguration of the education system in the country. In this context, within-the-country variations are also pointed out to render the picture of inclusivity in the system. Additionally, this paper will also take a quick glance at the recent government policies to see if the policies are at par with the measures necessary to address any shortcomings of the current arrangement.

Implication of the key performance indicators

While the data clearly reflects a flourishing business for the EdTech hubs in India, it is important to ensure its inclusivity while discussing a nationwide application. In fact, the transition to a new paradigm affects different cohorts in different ways in conformity with their distinctive values of readiness. Therefore, it is important to include all the stakeholders across all geographic, cultural, and socioeconomic backgrounds while deciding on the future footsteps of the Indian education system. Notwithstanding the individual preferences and capabilities and their respective effects, infrastructural constraints are to be widely discussed in this regard as well in the context of a developing country like India. This is where the aforementioned “key results” are going to come into play. To understand this wide-ranging diversity across the country, and how that affects the readiness under consideration, the situation is reviewed on the basis of those predetermined parameters: electricity, internet, and access to digital resources.

Key performance indicators

Availability of electricity.

In reference to infrastructural preparedness, the most primary technical requirement of an ICT-driven system has to be electricity. According to the World Bank Global Electrification Database, in 2019, more than 97% of Indian households have electricity added to the list of their available basic amenities. This is undoubtedly a remarkable leap forward from 88% in 2015 and 89.5% in 2016. However, the vast land of India is not so uniform to be treated as a single entity. A very basic division would tell that among the 1.2 billion population, more than 833 million reside in rural areas whereas only 377 million are urban residents (Indian Census 2011). While the situations in rural and urban India are not quite similar, on average the disparity is not that pronounced. In fact, since 2015, the electrification process in rural India has been quite successful according to the data given by the Council of Energy, Environment, and Water (CEEW) (Agrawal et al.  2020 ). The average daily supply of electricity to an urban household is 22 h compared to their rural counterparts, lagging behind only by a minuscule 2 h with an average daily supply of 20 h. However, a further division with respect to states can take one deeper into the scenario. On the one hand, despite the very successful rural electrification project, 2.4 percent of households (mostly rural) still have no electricity in their houses due to the affordability factor. This 2.4 percent of households majorly belong to the states of Uttar Pradesh, Madhya Pradesh, Rajasthan, and Bihar. Three of these states, Uttar Pradesh, Madhya Pradesh, and Bihar have been part of the ACCESS program (The Access to Clean Cooking Energy and Electricity—Survey of States) and have shown steep increment in electrification in the rural areas along with Jharkhand, Odisha, and West Bengal. Despite that, there are still people in these states who can not afford electricity. Compared to only 12.5 h daily in 2015, the average electricity availability has significantly increased to 18.5 h daily in 2020. In 2020, 73 percent of rural consumers have reported to be satisfied with the facilities related to the availability of electricity in their households which is a significant increase from only 23 percent in 2015 and 55 percent in 2018. Therefore, despite some hindrance, the overall situation in terms of availability of electricity in rural India has significantly improved after 2015. However, specific states, e.g., Uttar Pradesh, Haryana, Jharkhand, and Bihar are still behind (Indian Residential Energy Survey 2020) with less than 18 h of supply in rural areas and about 20 h in urban areas which lie quite below the average line for India as a whole. In sum, it indicates that while there is some lack of consistency across all states and demographic variations of the country, the holistic picture of the entire country shows a significant improvement over the past few years. But there is definitely room for improvement. For instance, two-third of rural households and two-fifth of urban households still face abrupt power disconnection at least once a day as reported by CEEW. In a nutshell, a significant trend of improvement is evident with some space for refinement in the way of building a sustainable system.

Availability of internet

In the queue, the next is access to the internet. After the introduction of the “Digital India” programme in 2015, several steps were taken in the way of revolutionizing the telecom industry in India and it has significantly increased access to the internet through mobile networks. One of the major contributions came from Jio telecom services introduced by the Reliance group in 2016. In 2021, the world’s second-largest online market (behind China) India had over 560 million internet users with a projected number of 650 million in 2023 (Statista, August 2021). It is true that this constitutes only around half of the existing population in the country. In other words, the internet penetration is only 47% in India (Keelery 2021 ). However, here as well, it is to be noted that this number was only 27% in 2015 (and about 4% in 2007), therefore, it can be thought of as quite a leap forward in the past few years. However, it is important to mention here that while the disparity among the number of internet users in rural and urban India is relatively low, there is a significant gender bias when it comes to the rural population where 58% of the users are male and the rest 42% are female (Statista 2021). Similar to electricity, a disparity is observed from state to state. While the average penetration rate in India is 40 percent, it is 68 percent in Delhi followed by Kerala at 56%. Odisha, Andhra Pradesh, Telangana, Madhya Pradesh, and West Bengal belong to the bottom of the list with a slightly above 30 percent penetration rate (Statista, March 2022).

Availability of digital equipment

Availability of digital equipment has been seen to be the epicenter of the quibble in many cases during the COVID-19 lockdown in the country. In fact, many students have reportedly committed suicide after being deprived of the privilege to join online lectures due to the lack of a smartphone or similar device. Including the incidents that happened in Mysuru, Karnataka (August 2020); Satara, Maharashtra (September 2020), and Punjab (June 2020), scarcity of digital resources has surely been a major contributing factor in the loss of nearly 12,500 lives of students in 2020 alone as reported by Times of India in November 2021 (Kumar 2021 ). The data shows that the number of smartphone users in India is nearly 748 million in 2020 (Statista, September 2021) which is around 57% of the entire population. More importantly, it is to be noted here, that usually, young students do not own their own devices. For instance, a student studying in kindergarten is not expected to have his or her own device. Moreover, as per world bank reports, the per capita income of an Indian individual is USD 1927 which if calculated, turns out to be USD 160 per month. The average price of a smartphone is recorded to be USD 196 in 2020–2021 (Statista, December 2021). Therefore, affordability becomes an issue in this case, specifically for low-income groups. This establishes the fact that in terms of access to digital equipment, there is a serious disparity among people belonging to different socioeconomic backgrounds when it comes to the availability of digital resources. This is one of the major problems dreading the EdTech-driven system. Inclusivity is expected to be hindered in this case.

Recent policies: direction and effects

In a survey conducted by KPMG and Google in 2017, it was vociferously advocated that in order to spread EdTech in the country, it is very important for the citizens to have access to cheap internet and digital equipment (Pandit and Agrawal 2021 ), as well as have the necessary government support in framing “digital-friendly” policies. Therefore, this discussion cannot end without taking a glance at the policies at hand to promote EdTech in the country.

The above discussion carries a subtle essence that disparity in availability and affordability can create a “digital divide” in the country which hampers the fundamental motto of education as a part of SDG—inclusivity (Bonini  2020 )! Therefore, on the one hand, government policies are to be focused on systematic modifications to the structure in terms of making suitable curricula and so on; on the other hand, ensuring equity to every learner irrespective of their demographic position is also of utmost importance.

As mentioned earlier, NEP 2020 is the current milestone of Indian policies with a target to give the Indian education system a detailed overhaul. Keeping NEP at its heart, the National Digital Education Architecture (NDEAR) is deployed to translate the vision of NEP into reality. In NDEAR, a number of issues that plague the Indian education system have been raised and answered. The core essence of NDEAR is to build a decentralized, accessible, enriched, and inclusive system to deliver education to the learners. The foundational idea is to strengthen the ground for all stakeholders in the system including students, teachers, and school administration as well. The NDEAR articulates its objectives to include 170 million learners in the country belonging to the age group of 3–23 in the pool of school-going individuals and parallelly, address the issue of school dropouts. As discussed in the very beginning, NEP is designed to improve the accessibility of educational content. Although the discussion in the previous sections has raised a concern of affordability becoming an obstacle to accessibility, NDEAR offers ample access to both learners and instructors. While giving access to study material such as books, video lessons, virtual laboratories, etc. is a beneficial initiative for students under NDEAR, it also caters to the needs of the instructors by helping them to design better lesson plans, online referral content, and evaluation tools. A moment’s digression is to be done here to understand the importance of catering to both the demand (student) and the supply (instructor) side of the system. The recent literature carries significant evidence that instructors habituated to the traditional system often struggle to make the content engaging yet flexible to cater to different sorts of learners’ requirements and abilities. Another factor that contributes to this hurdle is the low feedback of virtual platforms. Since the interaction is not one-to-one, often it is difficult for the instructors to understand whether the content is suitable enough for the class (Bwire et al. 2020 ). This is why giving adequate support to the instructors is definitely an indispensable part of any digital teaching–learning system.

Strengthening the overall administration is also a part of NDEAR’s motto. The most interesting proposition made in NDEAR is introducing a “coherent multi-channel multimodal learning continuum”, i.e., to help the stakeholders to interact with each other on various platforms including television, radio, etc. as well as web portal, mobile application, and interactive voice response (IVR) with the motto of “anyone can learn” and “anyone can help learn”. Including the initiative of DIKSHA (and other e-learning apps) that has been mentioned earlier, NDEAR also features a unified application program interface (API) for personalized adaptive learning experience for students as well as teacher training, school management, and other content enhancing and managerial purposes.

Now, this policy discussion has to be connected to the primary intent of this paper. The most significant grievances which came up by reviewing the “key results” under reference here are in terms of accessibility and affordability. The discussion about NEP and NDEAR that took place in this paper so far, shows a glimmer of hope that the policies have the potential to make education accessible for everyone. The usage of generic multimedia platforms like radio, television, and IVR which can go beyond the internet availability constraint and deliver educational content to everyone addresses one of the concerns raised here. The rest of the propositions, the e-learning platform, and its features are still expected to be delivered through the internet. Therefore, the internet connectivity issue is still a relevant constraint in the way of implementing an EdTech fueled system nationwide. However, in terms of affordability and availability of digital equipment, very recently, the Uttar Pradesh government has announced to give away 10 million smartphones and tablets to students for free. The first phase of this scheme has been rolled out on 25 December 2021. Similar initiatives have been seen in other states as well which include Haryana, Delhi, Karnataka, West Bengal, and Jharkhand (The Telegraph, November 2021). A similar scheme has been seen in Gujarat in the name of Namo Tablet Yojana 2022 where students will be given tablets at a subsidized price of INR 1000. Therefore, measures are taken to address the lack of digital equipment among students while keeping an eye on the affordability constraint. Hence, the major problems discussed before, as the hurdles toward adopting a more EdTech-intensive system, are being gradually addressed by the recent government policies.

Limitations of this approach

It is evident that India has come a long way to stand where it stands today. While there is still wide space for improvement, the major issues are well addressed by policies in recent times and this can be thought of as a big step forward in making the digital dream come true. It will not be unjust on the basis of the existing discussion in this paper that a worthwhile implementation of the newly designated policy framework can make India stand shoulder to shoulder with the first world EdTech giants like China and USA. However, the strategic framework used in this paper to organize the arguments tends to assume a linear relationship between availability and functionality. In other words, it assumes that if digital equipment is available, it serves the purpose. This is not always the case. There remain two major questions of compatibility and digital literacy along with other minor concerns. Even if a piece of equipment is physically present, it might not be in a suitable condition to be operated in a way one wants to. On the other hand, a particular person, be that a learner or an instructor, might not have sound knowledge about how to operate the equipment. These additional concerns are discussed in the following paragraph with reference to an empirical exercise conducted in 2020.

Since the lockdown happened in the country, and in order to unfreeze the frozen education scenario everyone jumped into the puddle of familiarizing themselves with a virtual setup, a number of things have come forward. While the numbers look very promising in terms of infrastructural penetration, a survey conducted in 2020 that asked the stakeholders about the quality of service they are getting, specified that 80% of the sample population believed that the quality of service can be a limitation for expansion of online education, 70% of the sample population reported that they have faced difficulty in downloading videos from the internet for online education purposes (Wadhwa and Khatak 2020 ). The same study has also pointed out that 62% of the respondents were skeptical with security concerns regarding these online platforms e.g. Google Meet, Zoom, etc. The mishap of Gnosticplyers where 932 million user records were stolen from 44 companies in China (Tong, Zheng, and Wan 2019, December) reminds us that there is always a potential data security threat when it comes to such systems. It is also to be noted that most pre-school learners do not possess a smartphone or a tablet. Giving away devices by a particular state government is undoubtedly a noble initiative. However, if the actual numbers are considered, catering to approximately 250 million learners in the K-12 system alone, is an expensive and highly time-consuming task for the government. As just mentioned, digital literacy has to be taken into account in this regard. Acquiring a digital device alone is not sufficient, it is also important that the individual using it has at least a basic knowledge of how to operate it. Therefore, the availability of resources alone is, once again, not the only challenge being talked about here.

Concluding discussion

The primary question that has been explored in this paper is the readiness of India as an economy to plunge into a more ICT-driven, EdTech-intensive system post the COVID-19 pandemic. This readiness is measured in terms of the availability of (a) electricity, (b) internet, and (c) digital equipment. Obviously, an EdTech-driven system empowers the learners and opens up a new horizon of possibilities in front of them, but on the other hand, unlike the traditional setup, the infrastructural requirement of such a system is not so primitive. It is evident that India has significantly progressed in past few years in terms of infrastructural preparedness. The basic amenities of electricity and internet have a higher rate of availability among the citizens both in rural and urban areas. However, inter-state variation is at large in terms of electrification and internet penetration. For instance, Kerala has one of the best internet penetration and electrification rate in the entire country with 56% population having access to the internet and more than 23 h of daily average availability of electricity in both rural and urban areas. In contrast to that, Uttar Pradesh performs poorly in both cases with only 34 percent of the population having access to the internet and the rural electrification rate being the worst at a daily average of only 16 h. This disparity has to be addressed if digital divide is to be avoided. Although the government makes some promising cases in overlooking this digital divide and delivering educational content via more generic and more easily available multimedia platforms, e.g., television and radio and IVR phone calls and so on; to reap the benefit at its fullest potential, the availability of internet and electricity is to be improved. Programs like online textbooks through QR codes, e-learning platforms, and distant learning will not be effective if the accessibility of the internet is not ensured across the country. The availability of digital equipment has so far been the most crucial of all three points because of the affordability factor attached to it. Specifically for low-income groups, buying digital equipment like smartphones or tablets is beyond the range of affordability. This problem has also been handled quite well by the recent policies where students were given tablets and smartphones for free or at a very low, subsidized price. Altogether, it can be said that despite the enormous room for improvement in terms of infrastructural availability, the rapid growth of the components under reference, and rightly directed government policies to supplement that growth make a promising case in favor of EdTech. India might not be completely ready yet, but it is certainly on the right track to be ready to accept a more EdTech-intensive system in post-pandemic times.

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Nag, R.K. Is India ready to accept an EdTech-intensive system in post pandemic times? A strategic analysis of India’s “readiness” in terms of basic infrastructural support. Decision 49 , 253–261 (2022). https://doi.org/10.1007/s40622-022-00313-0

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RECENT POSTS

India to become the EdTech capital of the world

• Nov 26, 2021, 12:19

EdTech funding focused on start-ups

Indian EdTech start-ups raised more than US$ 1.43 billion across 100 deals in 2020. The COVID-19 pandemic disruptions and subsequent lockdowns compelled both parents and educational institutions to implement tech-enabled learning solutions, making EdTech the most funded sector in the country. Of the total funding raised, Byju’s leads with 57%, followed by Unacademy (10.5%) and Vedantu (9.5%).

Since 2020, India has seen four EdTech start-ups turn into unicorns (Unacademy, UpGrad, and Eruditus and Vedantu) and one into a decacorn (Byju’s). A unicorn is a company valued over US$ 1 billion and decacorn is valued >US$ 10 billion.

Gamification and rise of edutainment

Gamification has gained popularity among EdTech start-ups. Companies such as Toppr, PlayAblo, Cuemath and Byju’s have introduced learning through games and puzzles that make it easier and fun for students to understand concepts. Similarly, companies such as Kiddopia, Kutuki Kids Learning, TinyTapps, Enguru and Lido Learning have taken steps to make education more interesting with interactive videos and music. For instance, according to a study, over 70% students stated that gamified courses are more motivating than traditional ones.

A hybrid EdTech industry

According to experts, players in the EdTech segment are expected to adopt a hybrid channel approach in the future. Online players are trying to establish offline touchpoints for students. For instance, EdTech decacorn Byju’s has piloted Byju’s Learning Centre, a new hybrid model, allowing students to visit offline education centres for classes.

Key Drivers

Exponential growth of internet penetration in India

According to the IAMAI-Kantar ICUBE 2020 report, India had 622 million active internet users in 2020. This number is expected to increase by 45% to reach 900 million by 2025, due to higher adoption rates in rural India. Small towns in India account for two out of five active internet users in the country. Urban population comprises 67% of active internet users.

According to the Annual Status of Education Report (ASER) 2020, smartphone ownership among government school student families increased from 30% in 2018 to 56% in 2020, whereas smartphone ownership  among private school student families rose from 50% to 74%.  

Government initiatives driving the Indian EdTech industry

The Indian EdTech industry is expected to be more policy friendly in the upcoming years due to rising government interest. The National Education Policy 2020 emphasised the importance of leveraging technology in education solutions and supported creation of leaning content in regional languages, calling it a high priority.

K–12 category has potential to grow in the future

The EdTech industry in India is growing at a significant rate, with high interest in the K–12 segment as COVID-19 lockdowns have disrupted the activities of educational institutions. According to Tracxn, a data analytics company, Indian EdTech firms have raised US$ 5.77 billion in funding in 2021 so far. Of the total amount raised, US$ 99 million was raised by K–12 education specialists. Since 2018, more than 4,800 K–12 EdTech start-ups have been launched globally, with 1,782 start-ups in India alone. They offer courses in the form of subscription packages for a set of subjects to each class.

Adoption of advanced technologies such as artificial intelligence (AI), machine learning (ML), AR and VR will not replace teachers in the classroom, but will empower teachers with valuable tools and platforms to ensure effective in-class learning. Recent activities

The Road Ahead… Investors are interested in EdTech start-ups as they quickly adapt to advanced technologies and provide a high return on investment. The demand for EdTech firms among students and parents is increasing as the post-pandemic situation continues to boost the need for remote learning. The Government of India (GOI) has announced various plans and systematic changes to improve the EdTech industry and enhance the remote learning experience for students. For instance, in May 2020, the GOI announced PM e-VIDYA, allowing the top 100 universities in the country to start online courses. Thus, the National Education Policy 2020, accessibility to education and teachers, demand for upskilling and remote learning will accelerate growth of the Indian EdTech industry .  

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15 EdTech research papers that we share all the time

We hope you saw our recent blog post responding to questions we often get about interesting large-scale EdTech initiatives. Another question we are often asked is: “What EdTech research should I know about?” 

As Sara’s blog post explains, one of the Hub’s core spheres of work is research, so we ourselves are very interested in the answer to this question. Katy’s latest blog post explains how the Hub’s research programme is addressing this question through a literature review to create a foundation for further research.  While the literature review is in progress, we thought we would share an initial list of EdTech papers that we often reach for. At the Hub we are fortunate enough to have authors of several papers on this list as members of our team. 

All papers on this list are linked to a record in the EdTech Hub’s growing document library – where you will find the citation and source to the full text. This library is currently an alpha version. This means it’s the first version of the service and we’re testing how it works for you. If you have any feedback or find any issues with our evidence library, please get in touch.

Tablet use in schools: a critical review of the evidence for learning outcomes

This critical review by our own Bjӧrn Haßler, Sara Hennessy, and Louis Major has been cited over 200 times since it was published in 2016. It examines evidence from 23 studies on tablet use at the primary and secondary school levels. It discusses the fragmented nature of the knowledge base and limited rigorous evidence on tablet use in education. 

Haßler, B., Major, L., & Hennessy, S. (2016) Tablet use in schools: a critical review of the evidence for learning outcomes . Journal of Computer Assisted Learning, 32(2), 139-156.

The impact and reach of MOOCs: a developing countries’ perspective

This article challenges the narrative that Massive Open Online Courses (MOOCs) are a solution to low and middle-income countries’ (LMIC) lack of access to education, examining the features of MOOCs from their perspectives. It argues that a complicated set of conditions, including access, language, and computer literacy, among others, challenge the viability of MOOCs as a solution for populations in LMIC. 

Liyanagunawardena, T., Williams, S., & Adams, A. (2013) The impact and reach of MOOCs: a developing countries’ perspective. eLearning Papers , 33(33).

Technology and education – Why it’s crucial to be critical

A thought-provoking read, Selwyn’s book chapter argues that technology and education should continuously be viewed through a critical lens. It points to how the use of technology in education is entwined with issues of inequality, domination, and exploitation, and offers suggestions for how to grapple with these issues. 

Selwyn, N. (2015) Technology and education – Why it’s crucial to be critical. In S. Bulfin, N. F. Johnson & L. Rowan (Eds.), Critical Perspectives on Technology and Education (pp. 245-255). Basingstoke and St. Martins, New York: Palgrave Macmillan.

Moving beyond the predictable failure of Ed-Tech initiatives

This article argues that a narrow vision of digital technology, which ignores the complexity of education, is becoming an obstacle to improvement and transformation of education. Specifically, the authors critically reflect on common approaches to introducing digital technology in education under the guise of promoting equality and digital inclusion.

Sancho-Gil, J.M., Rivera-Vargas, P. & Miño-Puigcercós, R. (2019) Moving beyond the predictable failure of Ed-Tech initiatives. Learning, Media and Technology , early view. DOI: 10.1080/17439884.2019.1666873

Synergies Between the Principles for Digital Development and Four Case Studies

The REAL Centre’s report, which includes contributions from the Hub’s own ranks, is one of the few we’ve seen that provides an in-depth exploration of how the Principles for Digital Development apply to the education sector. It uses four case studies on the work of the Aga Khan Foundation, Camfed, the Punjab Education and Technology Board, and the Varkey Foundation. 

REAL Centre (2018). Synergies Between the Principles for Digital Development and Four Case Studies. Cambridge, UK: Research for Equitable Access and Learning (REAL) Centre, Faculty of Education, University of Cambridge .

Education technology map: guidance document

This report by the Hub’s Jigsaw colleagues accompanies a comprehensive map of 401 resources with evidence on the use of EdTech in low-resource environments. The evidence mapping reviews certain criteria of the resources from sources such as journal indices, online research, evaluation repositories, and resource centres and experts. The type of criteria it maps include: the geographical location of study, outcomes studied, and type of EdTech introduced.  While not inclusive of the latest EdTech research and evidence (from 2016 to the present), this mapping represents a strong starting point to understand what we know about EdTech as well as the characteristics of existing evidence.

Muyoya, C., Brugha, M., Hollow, D. (2016). Education technology map: guidance document. Jigsaw, United Kingdom.

Scaling Access & Impact: Realizing the Power of EdTech

Commissioned by Omidyar Network and written by RTI, this executive summary (with the full report expected soon) is a useful examination of the factors needed to enable, scale, and sustain equitable EdTech on a national basis. Four country reports on Chile, China, Indonesia, and the United States examine at-scale access and use of EdTech across a broad spectrum of students. It also provides a framework for an ecosystem that will allow EdTech to be equitable and able to be scaled.  

S caling Access & Impact: Realizing the Power of EdTech (Executive Summary). Omidyar Network.

Perspectives on Technology, Resources and Learning – Productive Classroom Practices, Effective Teacher Professional Development

If you are interested in how technology can be used in the classroom and to support teacher professional development, this report by the Hub’s Björn Haßler and members of the Faculty of Education at the University of Cambridge emphasizes the key point that technology should be seen as complementary to, rather than as a replacement for, teachers. As the authors put it, “the teacher and teacher education are central for the successful integration of digital technology into the classroom.” The report is also accompanied by a toolkit (linked below) with questions that can be used to interrogate EdTech interventions.

Haßler, B., Major, L., Warwick, P., Watson, S., Hennessy, S., & Nichol, B. (2016). Perspectives on Technology, Resources and Learning – Productive Classroom Practices, Effective Teacher Professional Development . Faculty of Education, University of Cambridge. DOI:10.5281/zenodo.2626440

Haßler, B., Major, L., Warwick, P., Watson, S., Hennessy, S., & Nichol, B. (2016). A short guide on the use of technology in learning: Perspectives and Toolkit for Discussion . Faculty of Education, University of Cambridge. DOI:10.5281/zenodo.2626660

Teacher Factors Influencing Classroom Use of ICT in Sub-Saharan Africa

In this paper, the Hub’s Sara Hennessy and co-authors synthesise literature on teachers’ use of ICT, with a focus on using ICT to improve the quality of teaching and learning. They find evidence to support the integration of ICT into subject learning, instead of treating it as a discrete subject, and to provide relevant preparation to teachers during pre- and in-service training to use ICT in classrooms. Although this evidence has been available for a decade, the implications of the paper’s findings are still not often reflected in practice.  

Hennessy, S., Harrison, D., & Wamakote, L. (2010). Teacher Factors Influencing Classroom Use of ICT in Sub-Saharan Africa. Itupale Online Journal of African Studies, 2, 39- 54.

Information and Communications Technologies in Secondary Education in Sub-Saharan Africa: Policies, Practices, Trends, and Recommendations

This landscape review by Burns and co-authors offers a useful descriptive starting point for understanding technology use in sub-Saharan Africa in secondary education, including the policy environment, key actors, promising practices, challenges, trends, and opportunities. The report includes four case studies on South Africa, Mauritius, Botswana, and Cape Verde. 

Burns, M., Santally, M. I., Halkhoree, R., Sungkur, K. R., Juggurnath, B., Rajabalee, Y. B. (2019) Information and Communications Technologies in Secondary Education in Sub-Saharan Africa: Policies, Practices, Trends, and Recommendations. Mastercard Foundation.

The influence of infrastructure, training, content and communication on the success of NEPAD’S pilot e-Schools in Kenya

This study examines the impact of training teachers to use ICT, on the success of NEPAD’S e-Schools. The e-Schools objectives were to impart ICT skills to students, enhance teachers’ capacities through the use of ICT in teaching, improve school management and increase access to education. Unlike other studies on the subject, Nyawoga, Ocholla, and Mutula crucially recognise that while teachers received technical ICT training, they did not receive training on pedagogies for integrating ICT in teaching and learning. 

Nyagowa, H. O., Ocholla, D. N., & Mutula, S. M. (2014). T he influence of infrastructure, training, content and communication on the success of NEPAD’S pilot e-Schools in Kenya . Information Development, 30(3), 235-246 .

Education in Conflict and Crisis: How Can Technology Make a Difference?

This landscape review identifies ICT projects supporting education in conflict and crisis settings. It finds that most of the projects operate in post-conflict settings and focus on the long-term development of such places. The report hones in on major thematic areas of professional development and student learning. It also presents directions for further research, including considerations of conflict sensitivity and inclusion in the use of ICT. 

Dahya, N. (2016) Education in Conflict and Crisis: How Can Technology Make a Difference? A Landscape Review . GIZ.

Does technology improve reading outcomes? Comparing the effectiveness and cost-effectiveness of ICT interventions for early-grade reading in Kenya

This randomized controlled trial contributes to the limited evidence base on the effects of different types of ICT investments on learning outcomes. All groups participated in the ‘base’ initiative which focused on training teachers and headteachers in literacy and numeracy, books for every student, teacher guides that matched closely with the content of the students’ book, and modest ICT intervention with tablets provided only for government-funded instructional supervisors. The RCT then compared outcomes from three interventions:  (1) base program plus e-readers for students, (2) base program plus tablets for teachers, and (3) the control group who were treated only with the base program. The paper finds that the classroom-level ICT investments do not improve literacy outcomes significantly more than the base program alone, and that cost considerations are crucial in selecting ICT investments in education.

Piper, B., Zuilkowski, S., Kwayumba, D., & Strigel, C. (2016). Does technology improve reading outcomes? Comparing the effectiveness and cost-effectiveness of ICT interventions for early-grade reading in Kenya. International Journal of Educational Development (49), 204-214.

[FORTHCOMING] Technology in education in low-income countries: Problem analysis and focus of the EdTech Hub’s work

Informed by the research cited in this list (and much more) – the Hub will soon publish a problem analysis. It will define our focus and the scope of our work. To give a taste of what is to come, the problem analysis will explain why we will prioritise teachers, marginalised groups, and use a systems lens. It will also explore emergent challenges in EdTech research, design, and implementation.

EdTech Hub. (2020). Technology in education in low-income countries: Problem analysis and focus of the Hub’s work (EdTech Hub Working Paper No. 5). London, UK. https://doi.org/10.5281/zenodo.3377829

It is important to note that we have included a mix of research types at varying levels of rigour, from landscape reviews and evidence maps, to critical reviews and case studies. Our list is not comprehensive and has some obvious limitations (they are all in English, for one). If you are interested in exploring more papers and evidence, don’t forget to check out the EdTech Hub’s growing document library , where you will find not just links to the full papers in this list but over 200 resources, with more being added each day.

What interesting EdTech research have you recently read, and what did you take away from it? Let us know in the comments section or on Twitter at @GlobalEdTechHub and use #EdTechHub

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