2018 ASEE Annual Conference & Exposition

Fundamental engineering courses serve as the foundation for advanced discipline-specific courses and are commonly required across multiple engineering programs. Students often take several of these courses concurrently based on their curriculum, during a period in their academic careers marked by personal, social, and academic challenges. Examples of these courses in mechanical engineering curricula are Dynamics, Heat Transfer, and Thermodynamics.
Literature that explore these courses often describe low rates of student success and educational environments that conflict with the learning experience students value and expect; they are often taught in large classes with little faculty interaction. In fact, a critical factor that shapes the student learning experience is interaction with instructors as socializers in the academic environment. We focus on this notion to provide context for the learning experience in fundamental engineering courses, an important step before designing strategies to facilitate effective learning environments. Guided by Eccles’ expectancy value model of academic motivation, we explored faculty perspectives on facilitating learning in concept-heavy mechanical engineering courses. We used the role of instructors as socializers as embedded within Eccles’ model to guide our analysis.
For this paper, we analyzed 3 purposefully-selected transcripts of semi-structured interviews, chosen from a dataset consisting of interview transcripts with 41 instructors of concept-heavy engineering courses from multiple disciplines and institutions across the United States, collected as part of a larger NSF-funded project. We chose mechanical engineering professors, who represented majority (44%) of the participants in the larger study. To account for variability of experiences within the discipline, we chose one professor each from the top two courses taught by participants (Thermodynamics, 29%; Heat Transfer, 24%) and the course taught by the least number of participants (Dynamics, 8%). We also ensured variability in class size (20-30, 24-39, 65-75) and institution type; participants included in the analysis taught in a R1, R2, and Baccalaureate College (arts & sciences focus), based on the Carnegie Classifications.
Emergent themes include instructor beliefs about student interests, attitudes, values, and barriers that prevent students from making the most out of the learning process. We identified instructor values, aspirations, and the strategies that instructors employ to facilitate learning in fundamental engineering courses. From this sample, we found similarities in strategies (e.g., use of cognitive modeling) across participants. There were differences, however, in perceptions about student values and motivation between the instructor who taught a larger class in a larger institution and the instructor who taught in a smaller, specialized institution.
Our descriptions of variations in the teaching experience according to class size and institution type may inform analysis of remaining transcript data using case study as research design. The codes and themes define the boundaries of teaching foundational engineering courses for a class size and institution type, representing a case. The case descriptions for other contexts generated by this future work may identify barriers to effective learning environments and inform the design of strategies to overcome challenges faced by instructors of fundamental engineering courses.