USER ADOPTION READINESS OF AN ARTIFICIAL INTELLIGENCE-BASED LEARNING MANAGEMENT SYSTEM (LMS) IN HIGHER EDUCATION: A CASE STUDY AT TELKOM UNIVERSITY

Caca Sukma Saeful Hidayat Hidayat; Imanuddin Hasbi; Uruqul Nadhif Dzakiy

doi:10.62567/micjo.v3i3.2838

Authors

Caca Sukma Saeful Hidayat Hidayat Universitas Telkom
Imanuddin Hasbi Universitas Telkom
Uruqul Nadhif Dzakiy Universitas Telkom

DOI:

https://doi.org/10.62567/micjo.v3i3.2838

Keywords:

AI-Based LMS, User Adoption Readiness, Perceived Usefulness, Perceived Ease of Use, Trust in AI, Higher Education

Abstract

The development of Artificial Intelligence (AI)-based Learning Management Systems (LMS) offers significant potential to enhance the effectiveness of higher education through learning personalization, learning analytics, and the automation of academic processes. However, the successful implementation of AI-based LMS is not solely determined by technological sophistication, but also by users’ readiness to adopt the technology. This study aims to analyze the user adoption readiness of students and lecturers toward AI-based LMS and to examine the effects of perceived usefulness, perceived ease of use, and trust in AIon such readiness. This study employs a mixed-method approach with a sequential explanatory design. The quantitative phase was conducted through a survey of students and lecturers in higher education institutions using a Likert-scale questionnaire, and the data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Subsequently, the qualitative phase involved in-depth interviews to further explain and enrich the quantitative findings, which were analyzed using thematic analysis.This study hypothesizes that perceived usefulness, perceived ease of use, and trust in AIhave a positive influence on user adoption readiness in the use of Artificial Intelligence-based Learning Management Systems (LMS). This study is expected to contribute theoretically to the literature on AI-based educational technology adoption and practically to higher education institutions in developing more effective AI-based LMS implementation strategies that are aligned with users’ readiness.

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