Bibliographic record
Abstract
A story in the June 2017 issue of Physics Today recently caught my eye. An Issues and Events story by Toni Feder (page 28) stated that project-based learning is gaining popularity. I am a retired industrial physicist with my PhD in atomic theory. I’d like to share a related story.I think it was my junior year, 1966–67, at Colorado State University. I was taking a course on modern physics; the class had two parts. The lecture part was traditional and worth five credits, if memory serves me, and the laboratory part would now be called project-based learning. It was worth two credits.On the first day of lab class, the professor took us to the basement of the physics wing, unlocked the doors of three rooms, and said, “You may use any materials in this room, the next one, and the one at the end of the hall. You are to design and execute five experiments in modern physics, record the data, and make a report on each. The notebooks and reports will be turned in at the end of the quarter and will determine your grade for the class.” He then went back upstairs to his office. He was always available, but few needed to consult him.We were teamed up into groups of two. In addition to choosing from several “canned” experiments, each group took on at least one original experiment. My partner and I chose to measure the stopping potential of the photoelectron. We found a regulated DC power supply with shielding, a student spectroscope, and a few odds and ends, and we cobbled together a credible experiment. The result was within 20% of the accepted value, a quite good result for the equipment available to us.That class served me well throughout my career. It taught me to read what others had done, adapt their work, and solve problems with the equipment at hand, and it developed in me a passion for the projects I encountered. I had an exciting career that involved topics from reprogramming a direct-reading spectrograph for analytical chemistry to studying iron aluminides. The work was an equal mix of the theoretical and the experimental and was highly interdisciplinary. For example, one summer I was a student hire at Aerojet General to work on Project NERVA, an effort to develop nuclear propulsion for spacecraft.Among other things, the project-based lab fostered a can-do attitude in me. I strongly applaud the efforts described in Feder’s story. Section:ChooseTop of page <<© 2019 American Institute of Physics.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.030 | 0.013 |
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".