Report on the Learning Experiences of Undergraduate Students in a Novel Aerospace Engineering Course Integrating Teaching and Research
Bibliographic record
Abstract
Abstract Assessment of the Learning Outcomes of Undergraduate Students in a Novel Undergraduate Aerospace Engineering Course Integrating Teaching and ResearchThis study concerns the learning experiences of undergraduate students in a novel undergraduateAerospace Engineering course that integrates teaching and research. The first one-third of thecourse is devoted to conventional lectures and laboratory exercises with computer interfaced dataacquisition systems. The latter two-thirds focus on design and research projects in AerospaceEngineering with a few lectures interspersed. The teaching method of the new course has someunique characteristics: i) Undergraduates gain a research experience by working in small groupsof two or three students supervised by a volunteer graduate student research mentor, ii) Theparticular research project is developed by the course instructors and the volunteer graduatestudent research mentor as one related to the graduate student’s thesis research, and iii) Theresearch projects integrate departmental facilities and capabilities for continued research indesign, fabrication, experimentation, and computation for future course offerings. The presentstudy analyzes the experiences of the undergraduate students by answering the followingresearch questions: 1) In what ways do undergraduate students benefit from the course’s teachingmethods?, 2) How did this experience affect undergraduate students’ interest or motivation forcontinued research in a particular area?, and 3) What are the particularly important aspects of theinstructors’ responsibilities that require attention in this teaching arrangement? Pre- and post-surveys along with interviews in focus groups were used for data collection. The benefits for theundergraduate students related to their future careers but also the difficulties encountered in thegroup dynamics, communication skills, and uneven time commitments are addressed in the fullpaper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".