Self-Regulated Learning in Video Game Environments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Video games engage players in rapid and complex interactions of self-regulatory processes. The way individuals regulate their cognitive, affective, and behavioral process while playing electronic games, relates to their ability to cope with the onslaught of information that electronic games require for their mastery. The psychological factors that produce self-regulated learning are explored as they relate to a player’s intentionality, interest, aptitude, motivation, goal-setting, and affect while playing games. A discussion of video games as authentic learning environments looks at the roles of student initiated learning in authentic contexts and specific design strategies are outlined. Practical learning strategies that promote SRL are presented to facilitate the use of conscious self-regulatory skills that students can implement in these authentic learning environments. This chapter opens the discussion of the role of self-regulated learning in video game environments and its impact in the field of educational gaming.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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