Playing to the Strengths of Non-Major Students in Astro 101
Bibliographic record
Abstract
Astro 101 is a generic label for introductory survey courses for non-majors. A common struggle for instructors of Astro 101 is working with, or around, the students’ deficiencies in science and mathematical preparation. This paper describes an implementation of Astro 101, now in its eighth year, where the paradigm has been turned around to work with the strengths of the non-major students, rather than focusing on their deficiencies. \nKwantlen Polytechnic University (KPU) is an undergraduate university outside Vancouver, Canada, where all classes are limited to 35 students. The typical Astro 101 student at KPU is an arts major. Although the course carries a first-year number, students can be in years 1, 2, 3 or 4 of a four-year degree. When they enter the Astro 101 class, students typically bring with them skills and experiences exceeding those of typical science undergraduates, in areas such as paper writing, active group learning, public speaking and group presentations.\nIn this paper, one major course component, the term paper, is illustrated. The assignment comprises of four elements: proposal, written paper, abstract and participation in a panel discussion. With the small class size, the students have opportunities to work with the instructor on the proposal. Once the papers are complete, abstracts for the entire class are compiled into a booklet and circulated. The panel discussion provides a forum for students to share their new knowledge with the class, transforming what might have been a solitary exercise of the term paper into a culminating community experience.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.279 | 0.002 |
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; both teacher heads agree on what is shown here.
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".