A LEARNING ANALYTICS-BASED EVALUATION MODEL TO IMPROVE LEARNING EFFECTIVENESS IN THE LEARNING OUTCOME EVALUATION COURSE Abdul Hasan Saragih (a*), Harun Sitompul (b), Muslim (c)
a,b,c) Universitas Negeri Medan, North Sumatera, Indonesia
Abstract
This study aims to develop a Learning Analytics-based evaluation model to improve the learning effectiveness of the Learning Outcome Evaluation course for students of the Mechanical Engineering Education Study Program. The approach used is Research and Development (R&D) with the ADDIE development model, which includes the stages of analysis, design, development, implementation, and evaluation. Learning Analytics is applied to digitally collect, measure, and analyze student learning activity data to provide targeted feedback and support instructional decision-making. The research instruments included an expert validation questionnaire, learning activity observations, and student learning log data. Validation results indicate that the developed evaluation model is highly feasible to use. Practicality testing indicates that the model is easy to use by lecturers and students. The effectiveness test results showed significant improvements in learning outcomes, active student participation, and self-reflection skills. This model is recommended as an adaptive and responsive evaluation innovation to the needs of 21st-century learning, particularly in vocational engineering education.
