Toward a Tripartite Model of Intrinsic Motivation
Bibliographic record
Abstract
Intrinsic motivation (IM) refers to engaging in an activity for the pleasure inherent in the activity. The present article presents a tripartite model of IM consisting of IM to know (i.e., engaging in an activity to experience pleasure while learning and trying to understand something new), IM toward accomplishment (i.e., engaging in an activity for the pleasure experienced when attempting task mastery), and IM to experience stimulation (i.e., engaging in an activity for feelings of sensory pleasure). The tripartite model of IM posits that each type of IM can result from task, situational, and personality determinants and can lead to specific types of cognitive, affective, and behavioral outcomes. The purpose of this research was to test some predictions derived from this model. Across 4 studies (Study 1: N = 331; Study 2: N = 113; Study 3: N = 58; Study 4: N = 135), the 3 types of IM as well as potential determinants and consequences were assessed. Results revealed that experiencing one type of IM over the others depends in part on people's personality styles. Also, each type of IM was found to predict specific outcomes (i.e., affective states and behavioral choices). The implications of the tripartite model of IM for motivation research are discussed.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| 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".