Gamification and motivation: Impact on delay discounting performance
Bibliographic record
Abstract
Delay discounting is a phenomenon strongly associated with impulsivity. However, in order for a measured discounting rate in an experiment to meaningfully generalize to choices made elsewhere in life, participants must provide thoughtful, engaged answers during the assessment. Classic discounting tasks may not optimize intrinsic motivation or enjoyment, and a participant who is disengaged from the task is likely to behave in a way that provides a biased estimate of their discounting function. We assessed degree of delay discounting in a task intended to vary level of participant motivation. This was accomplished by introducing varying levels of gamification, the application of game design principles to a non-game context. Experiment 1 compared three versions of the delay discounting task with differing degrees of gamification and compared performance and task enjoyment across those variations, while Experiment 2 used two conditions (one gamified, one not). Participants found more gamified versions of the task more enjoyable than the other conditions, without producing substantial between-group differences in most cases. Thus, more polished task gameplay can provide a more enjoyable experience for participants without undermining delay discounting effects commonly reported in the literature. We also found that in all experimental conditions, higher levels of interest in or enjoyment of the task tended to be associated with more rapid discounting. This may suggest that low task motivation may result in less impulsive choice and suggests that participants who find delay discounting experiments sufficiently boring may bias assessments of value across delays.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".