Student personal and educational characteristics (gender, age, grade, GPA, courses taken, SAE type) were descriptively profiled for the 102 participants in the two groups¶
Claim · All claims
Evidence · 1 study · causalr2·q2
Currency · newest study 2014 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2017: local conditions change quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? The counterfactual group comprised 25 males (52.1%) and 21 females (43.8%), while the treatment group comprised 37 males (68.5%) and 16 females (29.6%), with most students in grades 10-12. → Bunch 2014
Evidence¶
Bunch 2014¶
Bunch, J. C., Robinson, J. S., Edwards, M. C., & Antonenko, P. D. (2014). How a Serious Digital Game Affected Students' Animal Science and Mathematical Competence in Agricultural Education. Journal of Agricultural Education, 55(3), 57-71. https://doi.org/10.5032/jae.2014.03057
q2 · i? · causal · r2
Descriptive statistics (frequencies and percentages) from research question one, based on 102 students completing the personal and educational characteristics questionnaire (48 counterfactual, 54 treatment). The counterfactual group was "25 males (52.1%) and 21 females (43.8%)"; the treatment group was 37 males (68.5%) and 16 females (29.6%).
"The counterfactual group students consisted of 25 males (52.1%) and 21 females (43.8%)."
Discussion¶
Related Claims¶
- Demographic characteristics (gender, age, race, major) showed no significant association with lower digital distraction in the rule-mining profiles — related
- Change in anxiety across the semester is negatively correlated with course grade and GPA for male students but not female students — related
- No GPA difference between male and female older learners, or across faculties — related
- Female gender, higher autonomous motivation, lower prior knowledge, and higher final course grades each predict more frequent voluntary StatBot use among graduate statistics students — related
- Female participants tended to outperform male participants in online SRL, while no substantial age differences were found — related
- Gender predicted SRL profile membership, with male students more likely in lower SRL profiles; major, prior experience, and time commitment did not predict membership — related
- Teachers' SRL competence profiles do not differ by gender, age, or teaching experience — related
- Female students had higher math course grades than male students, with no interactions between gender, math anxiety, and intervention group — related
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