Learning Analytics methods, Benefits, and challenges in Higher education: A systematic Literature Review
Higher education for the 21st century continues to promote discoveries in the field through learning analytics (LA). The problem is rapid embracing of LA in higher education diverts educators’ attention from clearly identifying requirements and implications of using LA in higher education. LA is a promising emerging field, yet higher education stakeholders need to become further familiar with issues related to using LA in higher education. Few studies have synthesized previous studies and provide a combined overview of LA issues in higher education. To address the problem, a systemic literature review was conducted to provide an overview of methods, benefits, and challenges of using LA in higher education. The literature review revealed that LA uses various methods including visual data analysis techniques, social network analysis, semantic, and educational data mining including prediction, clustering, relationship mining, discovery with models, and separation of data for human judgment to analyze data. The benefits include targeted course offerings, curriculum development, student learning outcomes, behavior and process, personalized learning, improved instructor performance, post-educational employment opportunities, and enhanced research in the field of education. Challenges include issues related to data tracking, collection, evaluation, analysis, lack of connection to learning sciences and optimizing learning environments, ethical and privacy issues. Such a comprehensive overview is useful as it provides an integrative report for faculty, course developers, and administrators about methods, benefits, and challenges of LA so that they may apply LA more effectively to improve teaching and learning in higher education.
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