Assessing the Readiness of Students in Adopting Learning Analytics in Higher Education

Abstract

Purpose: Getting students involved in developing learning analytics (LA) services is a major challenge in the academic world. Despite calls for more stakeholder involvement, research into students' views and expectations of learning analytics services is scant. Improving end-user buy-in and resource planning is possible by addressing these concerns and learning about student expectations before rolling out LA.Methodology: An extensive literature review is included, with a focus on previous research into the value, existing models, and difficulties of implementing LA. To fill this void, we used the SHIELA approach to survey students' beliefs and expectations concerning LA adoption. Factor loading, construct validity, and discriminant validity tests are performed in SmartPLS 4 to ensure the accuracy and credibility of the data. A structural equation model further verified the relationship between students' anticipations and their actual acceptance of LA.Findings: Our research confirms that the effectiveness of LA adoption is highly influenced by the three highlighted constructs: privacy and ethics and organizational and meaningful expectations. The research also showed that the student considered creating a detailed learning profile for each module to be the best application of LA. They believed LA would give them feedback on their learning and help them make better decisions. They think institutions have a moral and legal responsibility to act, which means they should also include, promote, and empower students. Institutions must take the necessary precautions to reduce risks, even though teaching staff should share the load.Originality and Value: The research supplies university officials with data for improving their LA adoption tactics while also informing students of new ways in which LA might inform their own educational choices. This paradigm shift and the higher education sector's sustained, productive interest in learning analytics will lead to better results for students, universities, and society. Based on the findings, the study also suggests several avenues and topics for future research.