Using a Motivational Typology to Understand and Respond to Disruptive Behaviour
Bibliographic record
Abstract
This case study is about understanding disruptive students who are motivated by a psychological need to invoke change in a learning space. Marczewski’s User Types Test, a typol- ogy for classifying both intrinsic and extrinsic motivational tendencies, and based on Self-Determination Theory, was ad- ministered to 14 participants, aged 9 through 15, to determine their User Type profile; one participant emerged as a Disrup- tor. The semiotic signs created by the Disruptor in an online learning platform were collected and analyzed to determine the unique behaviour patterns of a Disruptor, in contrast with Marczewski’s other User Types, including Philanthropist, Achiever, Socializer, Free Spirit, and Explorer. Implications for online instructors include understanding why Disruptors interrupt, interrogate, and intimidate, and possible strategies for responding, including nudging toward positive disruption, designing for Disruptors, and acknowledging and celebrating disruption in cases where it may facilitate (and not hinder) learning.
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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 | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".