IMPROVING PROBLEM SOLVING AND SOLUTION DESIGN SKILLS USING PROBLEM FLOW COACHES IN CAPSTONE PROJECTS
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
Engineers are known for their ability to solve problems and design solutions to those problems. There is an increasing concern that engineering education is failing to prepare students to properly address complex, ill-structured problems in the context of multi-disciplinary teams in order to produce innovative solutions and designs. Instructional solutions such as coaching, active learning, helping students develop metacognitive skills, and the direct teaching of creative problem solving skills have been proposed and will be discussed. This paper introduces a concept of “problem flow coaches,” who work closely with the capstone project teams. The problem flow coach, with expertise in systematic inventive problem solving methodologies, specifically OTSM (Russian language acronym for General Theory of Powerful Thinking) that is inclusive widely used problem solving methodology TRIZ, assists students in developing the cognitive and metacognitive skills needed to define, analyse and solve complex problems and develop innovative design concepts.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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