Evaluating effectiveness of active learning in computer science using metacognition

Active learning refers to instruction where the learners play an active role in learning and has been found to increase student retention, improve acquisition of higher order thinking and reasoning skills, and improve performance in STEM courses. Two main active learning techniques: student response systems (aka. clickers) and flipped classroom assignments, were incorporated in University of Michigan-Flint computer science (CS) courses. This paper describes how clickers have been incorporated in CS courses and their impact on student learning. There are several ways of evaluating student learning, and tests have traditionally been considered an incomplete and limited reflection of the students´ knowledge. In our prior work [11], students´ metacognitive knowledge has been used as an effective measure of students´ learning. Metacognitive knowledge can be considered to include knowledge of the person, the task, and the available strategies. In this work, we want our students to be aware of their level of understanding of the topics in a course. A student can use this knowledge along with knowledge of the task and available strategies to achieve the cognitive goals. This paper studies how clickers participation impacts student learning as measured by metacognitive knowledge.