Serious Game Leverages Productive Negativity to Facilitate Conceptual Change in Undergraduate Molecular Biology
Why this work is in the frame
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Bibliographic record
Abstract
We designed a serious game, MolWorlds, to facilitate conceptual change about molecular emergence by using game mechanics (resource management, immersed 3rd person character, sequential level progression, and 3-star scoring system) to encourage cycles of productive negativity. We tested the value-added effect of game design by comparing and correlating pre- and post-test misconceptions, interaction statistics, and engagement in the game with an interactive simulation that used the same graphics and simulation system but lacked gaming elements. We tested first-, second-, and third-year biology students' misconceptions at the beginning and end of the semester (n = 526), a subset of whom played either the game (n = 20) or control (n = 20) for 30 minutes prior to the post-test. A 3x3 mixed model ANOVA revealed that, while educational level (first-, second-, or third-year biology) did not influence misconceptions from pre-test to post-test, the intervention type (no intervention, simulation, or game) did (p<.001). Pairwise comparisons showed that participants exposed to the interactive simulation (p = .007), as well as those exposed to the game (p<.001), lost significantly more misconceptions in comparison to those who did not receive any intervention, while adjusting for educational level. A trending difference was found between the simulation group and the gaming group (p = .084), with the gaming group resolving more misconceptions. Quantitative analysis of click-stream data revealed the greater exploratory freedom of the control simulation, with greater accessibility to individuals who do not play games on a regular basis. However, qualitative analysis of gameplay data showed that MolWorlds-players experienced significantly more instances of productive negativity than control-users (p<.001) and that a trending relationship exists between the quality of productively negative events and lower post-test misconceptions (p = .066).
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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