Instructional performance benefits and adoption of learning management systems using task-technology fit theory

Brenda Benosa, Jayvee Niel Sias

Abstract


The COVID-19 pandemic propelled the virtualization of traditional classrooms in higher education, prompting institutions to adopt or develop learning management systems (LMS) to sustain academic functions. Although considerable research focused on commercial LMS platforms, the performance and adoption of in-house systems remain underexplored, particularly in resource-constrained settings. In response, this study examined the deployment of Camarines Sur Polytechnic Colleges’ (CSPC) in-house LMS, the CSPC-Learning Online Space (CSPC-LeOnS), specifically, to determine its adoption rate, evaluate the influence of task-technology fit (TTF), and LMS adoption on instructional performance benefits (PB), and generate recommendations for system improvement and information and communications technology (ICT) policy. Implementing a multimethod approach, partial least squares-structural equation modeling (PLS-SEM) analyzed the quantitative survey data from 60 faculty members and thematic analysis to explore qualitative insights. The findings revealed a low adoption rate (0%-33%), except for the College of Computer Studies (88%). The structural model uncovered the strong influence of TTF on PB (β=0.765); however, it revealed a weak positive correlation between LMS adoption and PB (β=0.230). This suggests that while adoption is significant, alignment between system features and instructional tasks is critical to achieve better instructional outcomes. Moreover, the study also recommended improvements for LMS design, organizational technology acquisition, and deployment policy.

Keywords


Higher education; Instructional performance; LMS adoption; PLS-SEM; TTF theory

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DOI: https://doi.org/10.11591/edulearn.v20i4.24451

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Journal of Education and Learning (EduLearn)
p-ISSN: 2089-9823; e-ISSN: 2302-9277
Published by Intelektual Pustaka Media Utama (IPMU) in collaboration with the Institute of Advanced Engineering and Science (IAES).

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