Exploring barriers affecting eLearning usage intentions: an NLP-based multi-method approach

With online-learning becoming the new mode of learning, providers need to understand the barriers that learners face. The objective of this study is to utilise a multi-method approach to examine the barriers that affect learner’s intention to use e-Learning services. The multi-method approach consists of qualitative semi-structured interviews of 8 participants, topic-modelling on 3227 reviews from Coursera dataset and 463 responses from an online survey for quantitative analysis. The interviews revealed themes like ‘rigid-course-structure’, ‘complexity’, ‘quality-of-facilitator’, and ‘value-addition’. The topic-modelling approach extracted themes like, ‘technique-of-teaching’, ‘language-of-speaker’, ‘course-content’, ‘privacy’, ‘payment-issues’, etc. The empirical study revealed that value [course-content (‘course-content’, ‘value-addition’) and facilitator-issues (‘quality-of-facilitator’, ‘handling-of-queries’)], tradition [trust (‘privacy concerns’, ‘authenticity’, ‘reliability’)] and risk [payment issues (‘payment-failures’, ‘refund issues’)] barriers have a notable negative impact on usage-intention. The originality of this works lies in the fact that it explores payment-failure, facilitator-quality, and course-value affecting the acceptance of e-Learning services from the innovation-resistance-theory stance utilising data from various sources (qualitative data from interviews and online reviews and quantitative survey-based data). This work has also discussed different limitations in this study and scope for future research.