Engineering Students' Epistemic Cognition in the Context of Problem Solving

Abstract

Background Students' beliefs about knowledge (epistemic beliefs) and their motivations toward processing information (epistemic motivation) have been suggested as influencing aspects of learning. Purpose This study investigated the relationship between engineering students' approach to solving an open‐ended homework problem and their epistemic motivation, engineering epistemic beliefs, and epistemic cognition. Methods The initial quantitative phase of this sequential explanatory mixed methods study employed a k‐means cluster analysis to identify homogenous subgroups of biomedical engineering students based on their epistemic beliefs and epistemic motivation measured using a survey (n = 50). Eighteen of these students were interviewed to explore their epistemic cognitions when solving an open‐ended homework problem. Transcripts were analyzed and results were overlaid with the clusters to investigate relationships between students' approaches to problem solving and their epistemic beliefs, motivation, and cognition. Results Three clusters of students were identified based on three constructs of epistemic beliefs and epistemic motivation: source of engineering knowledge, certainty of engineering knowledge, and closed‐mindedness. Students in the same cluster activated similar components of epistemic cognition, such as their desired outcomes for solving the problem. Additionally, we identified that the instructor's description of the problem and how the assignment was structured influenced how students approached solving the problem. Conclusions Comparison of clusters revealed that having more constructivist epistemic beliefs does not guarantee that students will set epistemic aims or make epistemic gains. Additionally, students' approaches to solving the open‐ended problem were influenced by their lack of desire to consider other ideas. The outcomes of this study provide a more complete understanding of students' epistemic cognitions and beliefs related to problem solving in the classroom.

Exemplars of Integration in Engineering Education’s Use of Mixed Methods Research

“…One publication made use of a methods flowcharts to illustrate their design and where mixing occurred. Faber and Benson's [32] work in the Journal of Engineering Education sought to explore the relationship between the approach an engineering student takes to solving an openended homework problem and different latent constructs: epistemic motivation, engineering epistemic beliefs, and epistemic cognition. They used a sequential explanatory mixed methods study to do so, which can be quickly gleaned from the flowchart in Figure 2.…”

“…While Shekar et al [50] showed how one could situate their study as a methodological contribution, a component of Faber and Benson [32] we would like to highlight is the idea of 'mixed methods data quality.' Because data analysis is often intertwined with a particular paradigmatic stance or set of assumptions, mixing data together and conducting analyses on the consolidated data carries additional considerations, which is often not acknowledged.…”

“…As one would expect references to support the quantitative and qualitative inquiry used in a study, the integration of the two merits literature to reference strategies or paradigmatic assumptions embedded in the process. We found two articles to have a particularly well-constructed methodological foundation: Faber and Benson [32] from the Journal of Engineering Education and Shekhar et al [50] from the European Journal of Engineering Education.…”

“…Trying to understand the structure of qualitative codes or themes through a quantitative perspective is not necessarily new either. EFA has been used to understand the relationships among qualitative themes [e.g., 31] and cluster analysis has been used in cases where the sample size is insufficient to conduct an EFA [e.g., 32,33]. Researchers can benefit from thinking about ways to represent their data in a different form and how to code for structure in their data rather than approaching the data thematically -as appropriate to their research question.…”

Board # 8 : Assessing Students’ Researcher Identity and Epistemic Cognition

“…A survey with 16 open-ended items pertaining to students' conceptualizations of research and their beliefs about themselves as researchers was developed 13 . This survey also included 45 closed items designed to measure students' engineering epistemic beliefs and need for cognitive closure [14][15][16][17][18][19] , and questions related to participant demographics (self-reported gender, race, ethnicity, year of study, etc.) were placed at the end of the survey.…”