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Exploring the acceptance for e-learning among higher education students in India: combining technology acceptance model with external variables

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Abstract

The concept of e-learning has now become fundamental in student learning process. This concept becomes even more relevant in situations of global crisis such as that arising from COVID-19. Since this pandemic there have been tectonic shifts in the education sector. Effective implementation of e-learning in higher education depends on students’ adoption of this technology. So, this study aimed to identify the factors influencing the behavioral intentions and actual usage of students in adopting e-learning. Additionally, it also examined the mediation effects among different latent constructs. Based on technology acceptance model (TAM), an explanatory structural model of technology acceptance was tested along with introduction of three external variables. To do this, a quantitative investigation was conducted using an online survey of higher education students in India, obtaining 570 responses. The structural model was examined through the partial least square structural equation modeling. Results obtained make it possible to validate the proposed model as findings explains the 56.2% variance of actual usage. In addition, it shows the direct and indirect effect of all three selected external variables of personal innovativeness, social factors and self-efficacy on the main constructs of TAM. The findings of this study are relevant for the higher education management, administration, e-learning system developers, marketers and researchers for improving the effective usage of e-learning by developing more focused and customized learning solutions.

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  1. Government College for Women, Gohana, Sonepat, India

    Jyoti Chahal

  2. Government College Narnaund, Hisar, India

    Neha Rani

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  1. Jyoti Chahal
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  2. Neha Rani
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Chahal, J., Rani, N. Exploring the acceptance for e-learning among higher education students in India: combining technology acceptance model with external variables. J Comput High Educ 34, 844–867 (2022). https://doi.org/10.1007/s12528-022-09327-0

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