Using Course Level Data Analytics to Evaluate Student Learning Outcomes & Engagement

ABSTRACT

This paper describes a process for evaluating student learning at the course-level. Course-level data is used to inform continuous improvement of program-level assessment. The sample consists of direct and indirect measures related to 101 students enrolled in a principles of financial accounting course. Direct measures indicate that most students meet or exceed learning expectations. Students scored higher on questions related to lower levels of Bloom's taxonomy (1956). Indirect measures indicate students perceive stronger than actual performance. Students not meeting the threshold of performance, cite student engagement as the reason. As engagement is paramount to success in COVID-19 learning environments, results are relevant for informing assessment interventions.