Supporting productive exploration in invention activities: are simulations too challenging?
Bibliographic record
Abstract
Studies show that invention activities, where students invent a general rule from provided resources before receiving direct instruction on the target topic, are particularly beneficial for learning outcomes. For most common implementations of invention activities, students are provided with instructor-designed contrasting cases with which to invent their rule. Alternatively, students could use an interactive simulation where they then have the agency to explore and collect observations on their own. While this provides a promising opportunity for developing more robust inquiry skills, it also introduces substantial challenges for the students that, in addition to learning about the domain, need to learn about expert ways of doing science. In this work, we compare different support structures that seek to mitigate these issues. Specifically, we incorporate a collaborative support structure and further provide students with either a short list of general rules to disprove or a list of important features that students are prompted to incorporate in their rule. We show that these support structures are not sufficient to make the exploration of students in our simulation-based invention activities as productive as with using contrasting cases.
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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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".