Shroomroot: An Action-Based Digital Game to Enhance Postsecondary Teaching and Learning about Mycorrhizae
Bibliographic record
Abstract
The majority of terrestrial plants associate with fungi in symbiotic resource-exchange relationships called mycorrhizae. Because of the importance of these mycorrhizal systems to ecosystem functioning, it is crucial that future resource managers and scientists have a solid understanding of mycorrhizal ecology. Limited interest of postsecondary students in plants and fungi compared with animals, combined with difficulties visualizing below-ground processes, present challenges for learning mycorrhizal concepts. To address this, we created the digital, plant-ecology-centric, action-based game Shroomroot for use in a second year, postsecondary Introduction to Soil Science course. We then assessed effects of Shroomroot on students’ knowledge acquisition and engagement with the topic of mycorrhizal ecology using a pre- and post-test evaluation. Students’ knowledge of mycorrhizal ecology increased significantly after playing Shroomroot, and tended to increase more for items related to Shroomroot gameplay than in rewards-based game content. Student engagement with mycorrhizal content tended to increase after gameplay. These results suggest positive potential for action-based, plant-ecology-oriented digital games in a postsecondary science curriculum. Furthermore, greater understanding of mycorrhizae has the potential to improve our multifaceted relationships with the ecosystems upon which we depend.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".