The Influence of Age, Gender, and Cognitive Ability on the Susceptibility to Persuasive Strategies
Why this work is in the frame
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Bibliographic record
Abstract
The fact that individuals may react differently toward persuasive strategies gave birth to a shift in persuasive technology (PT) design from the one-size-fits-all traditional approach to the individualized approach which conforms to individuals’ preferences. Given that learners’ gender, age, and cognitive level can affect their response to different learning instructions, it is given primacy of place in persuasive educational technology (PET) design. However, the effect of gender, age, and cognitive ability on learners’ susceptibility to persuasive strategies did not receive the right attention in the extant literature. To close this gap, we carried out an empirical study among 461 participants to investigate whether learners’ gender, age, and cognitive ability significantly affect learners’ susceptibility to three key persuasive strategies (social learning, reward, and trustworthiness) in PETs. The results of a repeated measure analysis of variance (RM-ANOVA) revealed that people with high cognitive level are more likely to be susceptible to social learning, while people with low cognitive level are more likely to be susceptible to trustworthiness. Comparatively, our results revealed that males are more likely to be susceptible to social learning, while females are more likely to be susceptible to reward and trustworthiness. Furthermore, our results revealed that younger adults are more likely to be susceptible to social learning and reward, while older adults are more likely to be susceptible to trustworthiness. Our findings reveal potential persuasive strategies which designers can employ to personalize PTs to individual users in higher learning based on their susceptibility profile determined by age, gender, and cognitive level.
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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 | 0.000 | 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