Nasir Abdul Jalil
ABSTRACT
The report's purpose is to discover whether individual differences are connected with student expectations for learning analytics. The aim was to evaluate if the Big Five personality traits are connected to student predictions about learning analytics. Learning analytics is well-positioned to greatly improve student learning. There are many unanswered questions that are intertwined in that belief, which deals with learning analytics as a whole. Students' learning processes can be better supported and understood by using learning analytics. The goal of this investigation is to examine students' ideas about learning analytics tools' attributes and their interest in applying these features for education. In a first-stage investigation, researchers interviewed 364 university students. Smart PLS was used to carry out data analysis. Research that involves exploratory research will benefit from using partial least squares (PLS). The equal engagement of all stakeholders, from external organisations to individual students, is a challenge faced by each university given the global interest in learning analytics. Student expectations of learning analytics elements were discovered, and students are looking for support with planning and organising their learning processes, tools for self-assessment, delivery of adaptive recommendations, and personal evaluations of their learning.
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Index Terms
- Learning Analytics in Higher Education: The Student Expectations of Learning Analytics
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