Emotional Agents in Educational Game Design
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
Evaluating the subjective playing experience and engagement in learning is important in the design of advanced learning technologies (ALTs) that respond to the learners' cognitive and emotional states. This article addresses students' attitudes toward an educational game, Heroes of Math Island, and their responses to the emotional agent, an animated monkey. Fifteen students (seven boys and eight girls) from grades six and seven participated in this quasi-experimental study (pretest, intervention, post-test, followed by post-questionnaire and interview). This research presents a detailed analysis of students' subjective reactions with respect to Heroes of Math Island and to the underlying mathematics content, their learning gains and emotions triggered during gameplay, and design issues resulting from the evaluation of the game and of its emotional agent. The findings from this study inform how ALTs and educational games can be designed in order to be effective and provide emotional engagement, enjoyment, and learning.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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