2025 ASEE Annual Conference & Exposition

This study presents findings from a National Science Foundation (NSF)-funded project aimed at exploring how students apply monitoring and evaluation (ME) processes in conjunction with their metacognitive knowledge of tasks (MKT). The research focused on problem-solving activities in engineering and mathematics courses, specifically Ordinary Differential Equations and Engineering Statics, which were chosen to represent different yet interconnected fields in the second-year engineering curriculum. Twenty undergraduate students (7 female, 13 male) from these courses participated. Data were collected through semi-structured, one-on-one interviews conducted before and after problem-solving sessions, with a think-aloud protocol employed during the sessions. Each student solved two problems of varying difficulty, resulting in a total of 80 qualitative data points.

The qualitative analysis of the semi-structured interview data provided insights into the students' understanding of tasks prior to engaging in problem-solving. Comparative Content Analysis (CCA) was used to systematically examine and compare qualitative data segments from the two courses, as well as the varying difficulty levels of the tasks. This approach enabled a detailed analysis of similarities, differences, and trends in students' metacognitive knowledge about the tasks. The Think-Aloud Protocol (TAP) data offered further insight into students' self-regulation in action during problem-solving. From this data, seven distinct problem-solving learning episodes were identified and categorized into four quadrants, each representing different interactions between students' metacognitive knowledge about the task and their self-regulation (monitoring/evaluation) during problem-solving activities.

In this paper, we focus on two learning episodes within the fourth quadrant (Routine Learning and Non-Adaptive Learning), where students possess adequate metacognitive knowledge about the task but do not employ sufficient monitoring and evaluation (M/E) strategies. This discrepancy leads to either successful or unsuccessful outcomes. In Routine Learning, participants demonstrate low levels of M/E strategies but high levels of metacognitive knowledge about tasks (MKT). They are familiar with the problem's context and have a strong understanding of it, allowing them to solve it successfully despite using fewer M/E strategies. In contrast, participants in Non-Adaptive Learning share similar characteristics but fail to solve the problem, even though they initially have a reasonably good understanding of it.

The study discussed how different episodes of problem-solving activities can shape students' perceptions of their task performance, either positively or negatively, and how these experiences influence their deeper understanding of the subject matter. It also examined the critical roles of metacognitive knowledge about tasks (MKT) and monitoring and evaluation in enhancing the teaching and learning processes within mathematics and engineering education, highlighting their impact on students' ability to navigate complex tasks and refine their problem-solving skills.