Motivation profiles: understanding interplay of persuasive strategies and self-determination theory
Why this work is in the frame
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Bibliographic record
Abstract
Persuasive strategies play a crucial role in designing systems that influence behaviour. Understanding how students respond to the strategies is essential for developing tailored motivational interventions that will enhance student motivation, engagement, and academic success. Grounded in Self-Determination Theory (SDT), our research explored how persuasive strategies – Self-monitoring, Commitment & Consistency, Social Comparison, and Competition – impact student learning. We conducted a study with 185 university students to investigate their receptiveness to the strategies, explore gender differences and interactions with SDT constructs. Results of statistical analysis, structural equation modelling, and cluster analysis revealed that: (1) the four strategies can be employed in the design of persuasive education systems/interventions – self-monitoring and commitment & consistency were effective for all participants, while social comparison and competition were only effective when aligned with individual preferences. (2) There were no significant gender differences in motivation, engagement, and strategies receptiveness. (3) Self-monitoring, commitment & consistency, and competition were positively linked to intrinsic motivation. (4) Clustering results identified two distinct motivational profiles, each with unique patterns of receptiveness to the strategies. Based on our findings, we propose guidelines for designing more motivational education systems. These insights can help to develop and personalise persuasive educational systems and interventions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it