Evolution of Student Attitudes Toward Teamwork in a Project-based, Team-based First-Year Introductory Engineering Course
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Bibliographic record
Abstract
Abstract Evolution of Student Attitudes Toward Teamwork in a Project- based, Team-based First Year Introductory Engineering CourseFor the past decade, engineering schools have developed a variety of models for introducingfirst-year students to their chosen field. One common model is a project-based course, in whichstudents work together on teams to design (and often build and test) something. Through thisprocess, students develop professional and teamwork skills and often also practice technicalcommunication in the context of a real design project. Such courses have been found to increasestudent persistence1 and self-efficacy, though in the latter case project-based learning appears tobe more beneficial for male students than for females2. More research is needed, however, intostudent attitudes toward teamwork and the characteristics of team experiences that lead toimprovements in student attitudes toward working in teams.This study is an exploratory investigation of student attitudes toward teamwork at three timepoints during a first-year team-based design course: before students have begun working inteams, after they have completed an initial small-scale design project in a 4- or 5-person team,and after they have completed a larger-scale design project with a different, similarly-sized team.In this presentation, the authors will explain how teamwork is managed in this first-yearengineering course through our methods of grouping students into teams of 4-5 as well as ourefforts to facilitate successful teams. These efforts include: ● a fun, engaging “ice breaking” exercise to encourage students to consider their team’s communication style as well as to get to know each other ● class discussion of the characteristics of effective teams ● peer mentors (alumni of the course) paired with each student team ● a skit about teamwork prepared by the Educational Theatre Company at our institution ● incorporation of real-stakes team member evaluations in which team members evaluate each other and receive peer feedbackWe will then report the results of a survey, administered this fall at the three time pointsdescribed above (n= about 55). The survey includes quantitative information regarding studentperspectives of the teamwork experience and the fun, frustration, and learning that occurred andqualitative information on the students’ perceived positive and negative characteristics ofteamwork. By administering the same survey at three time points during the semester, we canchart the evolution of those perspectives and assess our teaching methods. 1 Knight, D. W., Carlson, L. E., & Sullivan, J. F. (2007, June). Improving engineering student retentionthrough hands-on, team based, first-year design projects. 31st International Conference on Research inEngineering Education, Honolulu, HI.2 Kilgore, D., Sheppard, S., Atman, C. J., & Chachra, D. (2011, June). Motivation makes a difference, butare there differences in motivation? What inspires women and men to study engineering? 118th ASEEAnnual Conference & Exposition, Vancouver, BC, Canada. The largest contribution of this project may be the qualitative information gathered via thesurveys, which will help us better understand what aspects of teamwork experiences studentsbelieve most impact their perceptions of teamwork. For example, we may learn that groupcharacteristics such as gender balance or group size are most important in student attitude towardteamwork. This qualitative data will be used to further develop research questions that could beinvestigated quantitatively with a follow-up survey in future semesters.The data will be collected in September, October, and early December 2013, and is not availablefor this initial abstract. If accepted, a paper written up on this project will of course include thedata and an analysis of it. Our teaching schedule would allow us to conduct a new survey with anew cohort of students in the semester beginning in January 2014, and that data would beavailable for presentation at the conference (but not for inclusion in the paper).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it