Investigating Engineering Student Problem Solving Skill Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In school, students often familiarize themselves with structured, closed-ended problems. Meanwhile, engineering work tends to revolve around complex, open-ended problems, which creates a gap in engineering education. The aim of this study is to investigate engineering student perceptions of problem solving and how they gain these skills within their education. This study focuses on the student part of the study. A Qualtrics survey was distributed to undergraduate engineering students. Through the survey, students self-assessed their confidence in solving problems. Students also provided insight on their process when solving open-ended problems as well as how they are assessed within the engineering curriculum. There were 134 survey responses, representing all years of undergraduate study. Students are generally confident in their problem-solving skills but find complex, open-ended, problems difficult. Students found that individual assessments helped gain critical thinking and analysis skills while group assessments allowed them to see new perspectives. The limitations to solving open-ended problems were identified, demonstrating the need for more exposure to open-ended problems and teaching activities to help students interpret these problems in a setting where grades are not heavily affected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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