Exploring Key Information Requirement for Effective Monitoring of Courses and Student Performance: a Qualitative Thematic Analysis
Year: 2025
Type: article
Abstract: Universities serve multiple stakeholders, including students, lecturers, parents, alumni, and regulatory bodies. Among these, students stand out as a primary focus, aligning with the university's core mission to educate. Achieving stakeholder satisfaction necessitates enhanced education quality, encompassing teaching methods, program delivery, and the relevance of course offerings. Students' success in gaining knowledge, skills, and competencies is critical to university effectiveness. In today’s dynamic educational landscape, digital technologies offer new avenues to enrich learning, with Learning Analytics (LA) emerging as a transformative field. The growth of big data has increased the volume and complexity of available educational data, requiring LA systems to evolve accordingly. With the universities maintaining more than one e-learning platform, LA presents a new challenge in integrating this heterogeneous e-learning data. To overcome this problem, graph databases and Resource Description Framework (RDF) ontologies have proven valuable for managing and analysing such extensive data. However, to build Web Ontology Language (OWL) frameworks that effectively support LA, researchers must first identify faculty administrators' and lecturers' specific data needs or key information, ensuring only essential information is taken to be integrated in LA. To gather the key information, interview sessions were conducted with six participants from two institutions, including an e-learning coordinator, lecturers, and faculty administrators as part of the case study. The interview result is crucial for identifying the essential information needed in LA pertaining to course performance and student performance.
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7117744946
FWCI:
Cites:
Cited by:
Related to: