In large classes with hundreds of students enrolled, it is difficult to gauge the knowledge level of the students on a regular basis until the exams where it is almost too late to correct and supplement competency deficiencies. Complementing weekly lectures with an online learning platform coupled with a direct competency model for e-learning and e-assessment can provide real-time feedback on student knowledge and deficiencies for the instructors and help the students better prepare for their exams and increase their core knowledge. A case study of a large Chemistry for Mechanical Engineering course (~400-500 students) at a German technical university utilized an online platform to develop a direct competency model to assess students' knowledge of core chemistry competencies. These competencies were based on the learning outcomes of the course. This model consisted of short review questions (2-3 per topic) that tested students' understanding of the concept as well as pre and post self-assessments of these core competencies. Students that scored higher on the direct competency questions showed higher mastery of the subject topic through achieving higher scores on correlated exam tasks and subtasks. Also the pre and post selfassessment showed that students assessed themselves to have made significant gains in core knowledge. This validation of the competency model allows it to be used in real-time in an online learning platform to discern how well students understand the material and allows the instructor to correct deficiencies shortly after the material is presented and before the next exam.
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