Metacognition Approaches to Enhance Student Learning in Mechanical Engineering Classroom

It is conceivable that over the next decade, all students will have access to some form of internet-based device while attending classes. The work presented in this paper investigated how web-based metacognition tools influence student capacity to self-assess their understanding (learning), student regulation of their learning (confidence level), class dynamics (reaction) and instructor methods. Student self assessment associated with specific lecture slides were collected and compared with content-specific questions later in the examination. A set of online questions were used to evaluate student understanding on specific materials presented in the slides. Students were also asked to self-assess their confidence level in their answers. A web-based metacognition tool "LectureTools" was used to collect student responses. Correlation of correct answers with the self-assessment is presented to reflect on what the student thought they understood versus the outcome of their exam scores. The study evaluates how students may regulate their own learning and improve their ability to self-assess their understanding more critically. The ultimate goal is to empower students to become a better learner by self-assessment and evaluation of their own knowledge.