Towards a pragmatic modeling of learner's complex system by reflecting Boulding's typology at the affective computing space
Bibliographic record
Abstract
This work reflects Boulding's Typology (BT) of the learner's complex system at the space of affective computing. From this perspective, the learner's emotional state is interweaved with the structural elements of his/her learning functioning (both internal and external) when placed within an educational setting. The advent of new technological achievements in the accurate acquisition of the learner's affective state allows for the redesign of the ICT-based educational settings, taking into account a bilateral approach of the learner's system that involves both cognitive and emotional processes, as reflected in the Valence/Arousal space. Justification of the crucial role of learner's affective state in the design of an ICT-based educational setting is provided with the implications derived from an experimental case-study, referring to emotional responses to IADS-based sound stimuli presented to three age-dependent learner-groups. The proposed affective parameters define an enriched BT that could serve as a basis for structuring a new model, closer to the pragmatic nature of the learner's system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".