Enhancing Student Learning Through #DigitalPowerups, “Pushed me to be Creative”: Student Discussions in Environmental Sociology Course
Bibliographic record
Abstract
The use of #digitalpowerups is a technique that involves associating keywords with prompts in online discussion forums, which enables students to have more choice and voice. These powerups not only help structure responses but also enrich discussions and develop academic skills necessary for online assignments. The approach leverages the social media interaction space of discussion forums by introducing hashtags that remind students of the prompt being addressed and indicate the level of Bloom's being engaged. By using the powerups, students can engage in mid-levels and higher-order levels of Bloom's, along with the lower levels that they typically engage in based on the design and facilitation of the discussion. Students typically participate in the lower levels of Bloom's taxonomy (#remember, #understand) due to the way the discussion is structured and facilitated. However, the use of #digitalpowerups encourages students to move beyond these levels and engage in mid-levels (#apply, #analyze, #evaluate) and higher-order levels (#create, #connect) during discussions.The powerups also scaffold or frame student responses with habits of mind skills. This article examines how the #digitalpowerups strategy supports learning in a virtual community for Environmental Concerns in the Environmental Sociology Course through content analysis of student discussion postings. The primary data (total of 375 postings) were collected from the Environmental Sociology Class throughout the following academic years: Fall 2020 (96 postings), Fall 2021 (67 postings), Spring 2022 (92 postings) and Spring 2023 (120 postings).
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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 | 0.020 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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; 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".