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: admin : Tue, 7 September 2021, 10:06 AM

Trends and Main Issues of Learning Analytics for the Higher Education
[장상현]
KERIS Director


*Introduction


TBA



[Sunkyeong Jeong]
University Innovation Center, Seoul National University Senior Researcher


*Introduction


In the university, it is necessary to establish a use case and a learning analysis system construction strategy for the learning experience of students. Self-Regulated Learning, identification of learning difficulties and customized learning support, optimized education programs and design, creating a learning environment for learners' growth, utilizing three-dimensional learning experience data and securing a reasonable evaluation system, Educational effectiveness through educational support, learning participation and interaction between learners should be considered.
Learning Analytics is a technology that measures, collects, analyzes, and reports data related to learners and their contexts to understand and optimize learning and learning environments. A data-driven approach is driving fresh and dynamic changes in education and learning. This is because we can track learning activities that are much more extended than before, collect vast amounts of data generated in the process, and analyze them in depth to derive three-dimensional insights into learners individuals. Based on this, we can provide optimized learning support to professors and learners and contribute to realizing personalized learning.
A case study of learning analysis in the field of higher education consists of the following contents. To all stakeholders related to the purpose of learning analysis and the project, it is suggested to secure the rationale for learning analysis and the justification for the introduction of learning analysis, secure the budget for the introduction of the learning analysis solution, and secure professional manpower for processing, interpretation, and visualization of learning data. .Learning analysis continuously monitors the progress of introduction and use, evaluates suitability for the purpose of 'learning analysis', rechecks the entire process, and presents security procedures. Since the purpose of learning analysis is to accumulate a vast amount of learner's learning experience as data, and to realize personalized learning based on this, a proposal for a predictive model for this is required. We present the potential of learning analysis and suggest changes in the perspective of universities for this purpose.




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