Beyond Acceptance: Introducing Linguistic-Cognitive Accessibility Friction in the DURA Model of Digital Resource Utilisation in Indian Higher Education

Abstract

Indian higher education has acquired a large digital library footprint over the past decade. The National Digital Library of India reports over 8.25 crore content items in more than 70 languages, with an NDLI Club network covering more than 5,800 institutions and roughly 1.7 million registered members (NDLI, 2024); e-ShodhSindhu reports access to over 10,000 full-text journals and 164,300 e-books for member institutions (INFLIBNET, 2024); and Shodhganga had received theses from 739 universities by December 2023 (INFLIBNET, 2023). These figures are provider self-reports of registrations and holdings, and are treated in this paper as indicators of the scale of provision only, not as evidence of use. The empirical record from Indian universities tells a more uneven story: studies repeatedly find that quality of access, infrastructure, and language barriers depress actual usage well below what the headline numbers might suggest (Bhatt & Rana, 2011; Lwoga, 2014; Siwach & Malik, 2019; Pandey, 2024). The dominant frameworks used to explain technology use, the Technology Acceptance Model (Davis, 1989), the Unified Theory of Acceptance and Use of Technology 2 (Venkatesh, Thong, & Xu, 2012), and the DeLone–McLean Information Systems Success Model (DeLone & McLean, 2003), were built mainly in well-resourced, English-medium settings. This paper is offered explicitly as a conceptual, theory-building contribution (MacInnis, 2011; Jaakkola, 2020) and makes two contributions. The first is the Digital Usage and Resource Accessibility (DURA) Model, built through a narrative integrative review (Whittemore & Knafl, 2005) of the literature on digital resource utilisation in Indian higher education, with supporting evidence from comparable contexts. DURA has four interdependent components: Digital Infrastructure Accessibility (D), User Digital Competency (U), Resource Relevance and Quality (R), and Awareness and Motivational Factors (A). The second contribution is a new construct, Linguistic-Cognitive Accessibility Friction (LCAF), grounded in Cognitive Load Theory (Sweller, 2011) and accompanied by a proposed measurement strategy that adapts established cognitive-load instruments (Paas, Tuovinen, Tabbers, & Van Gerven, 2003; Hart & Staveland, 1988). LCAF captures the extra cognitive cost a non-English-medium learner pays when working with predominantly English-language scholarly content, and it is theorised to act as a non-linear moderator on usage. Ten falsifiable propositions are advanced, including two explicitly conjectural boundary-condition predictions, and a staged validation roadmap covering expert content validation, pilot instrument development, and confirmatory testing is specified. The model's claims are scoped to Indian higher education; extension to other developing-nation contexts is framed as a hypothesis for comparative research rather than an assumption.