The Analysis of Learning Plan conditions for General Courses (MKU) at Tidar University Based on E-Learning

Hari Wahyono, Dzikrina Dian Cahyani, Delfiyan Widiyanto


This study aimed to review the condition of e-learning-based general course (MKU) learning planning at Tidar University and its conformity with the vision and mission of Tidar University. Learning planning is an important aspect as a reference for implementation and reflection of learning. The type of this research is evaluation. Evaluation research is a research with systematic analysis using a five-step discrepancy model. A qualitative research approach was applied to analyze the data. Data were collected through interviews, observation, and documentation. The research subject is a lecturer at MKU at Tidar University, while the object of research is RPS MKU. The research took place at Tidar University from January 2021-December 2021. The results showed that the e-learning-based general course learning planning at Tidar University had been prepared by the majority of course lecturers where the percentage of lecturers who compiled RPS was 97%, and the rest by 3% no. In general, the preparation of learning plans has been categorized as good, namely the preparation of lecture materials, preparation of final skills, study materials for each meeting, learning methods, time allocation, student learning experiences, and the use of case study learning methods and team problem base learning. Weaknesses in learning planning were found at the stage of compiling graduate learning outcomes and subject learning outcomes that did not refer to the higher education curriculum in the era of the industrial revolution 4.0 and the standard of the Tidar University learning process. In addition, another drawback is that the preparation of the final capabilities of each meeting has not been formulated in accordance with the provisions. The preparation of assessment criteria and assessment indicators has not been systematically arranged where case study learning and team problem base learning have not been fully measured

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