Gender, age and English proficiency show nuanced group differences in chatbot attitudes and concerns¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r1 · q3
Currency · newest study 2026 · checked against its sources 2026-10-16 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q3 i? ANOVA revealed gender differences in attitude toward chatbots (males more likely to agree than females per Tukey's HSD) and in whether chatbots improve study grades; intermediate and advanced English-proficiency students agreed more that chatbot use was common among peers. → Stephen Colbran 2026 q3 i? Older age groups (26–30, 31–35, over 45) were more concerned than younger groups about being accused of breaching academic integrity. → Stephen Colbran 2026 (2)

Evidence¶

Stephen Colbran 2026¶

Stephen Colbran, Meena Jha and Caitlin Schiavone. (2026). Understanding student perspectives on generative AI chatbots: a human-centred mixed-methods study in higher education. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00605-w

q3 · i? · associational · r1

ANOVA results in the RQ1 section: attitude difference by gender (F = 3.44, Sig = .035, df = 2) with "males were more likely to agree than females"; grades item F = 4.31, Sig = .016; English-proficiency ANOVA on peer usage F = 3.88, Sig = .011, df = 3, with intermediate and advanced respondents more likely to agree.

"ANOVA revealed significant differences existed between group means on the issue of having a positive attitude towards the use of chatbots in education (F = 3.44, Sig = .035, df = 2). Tukey's HSD (Honestly Significant Difference) pairwise comparisons revealed that males were more likely to agree than females."

Stephen Colbran 2026 (2)¶

Stephen Colbran, Meena Jha and Caitlin Schiavone. (2026). Understanding student perspectives on generative AI chatbots: a human-centred mixed-methods study in higher education. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00605-w

q3 · i? · associational · r1

Age ANOVA on concern about being accused of breaching academic integrity (F = 2.59, Sig = .026, df = 6): "the age groups 26–30, 31–35 and over 45 were more concerned about, this issue than the groups 18–20, 21–25 and 41–45".

"Tukey's HSD pairwise comparisons revealed that the age groups 26–30, 31–35 and over 45 were more concerned about, this issue than the groups 18–20, 21–25 and 41–45."

Discussion¶

Learner Variables¶

• Age and Developmental Stage — predictor: learners who differ on it differ in outcomes
• English-Learner Status — predictor: learners who differ on it differ in outcomes
• Gender — predictor: outcomes differ by group: a gap reflecting circumstances and treatment, not a cause

Related Claims¶

• Chatbot users held more positive attitudes and reported greater perceived knowledge gains than non-users — related
• Students hold generally positive attitudes toward educational chatbots and agree the chatbots they used improved their knowledge and understanding — related
• Male students are significantly more work-avoidant than female students in the project-based course, with no gender differences on the other measures — related
• Gender effects on self-regulated learning are mediated by culture, discipline, and age, with mixed direction across samples — related
• Low- and intermediate-proficiency students report higher perceived usefulness, ease of use, and satisfaction for AI-assisted English tools than high-proficiency students — related
• Female students show stronger academic self-confidence, more positive attitudes, higher achievement, and fewer absences, but this advantage diminishes almost completely under mastery learning — related
• Gender differences in AI perception scores appear only in the overall score and attitudes dimension, with males scoring higher — related
• Prior chatbot exposure rather than general technological literacy is associated with willingness to use chatbots — related
• Female students are significantly more likely than male students to use AI for schoolwork and to seek advice from AI tools — related
• Gender is associated with small differences in GenAI use, literacy, and monitoring, while educational level shows no significant differences — related
• Gender differences in GenAI usage clusters are minimal, confined to a male-dominated Zero usage cluster — related
• Self-perceived TPACK-21 domain scores do not differ significantly by faculty age group or appointment type — related
• Students in secondary mathematics report high acceptance of the domain-specific AI chatbot ADA across all Technology Acceptance Model dimensions — related
• Chatbot design carries a documented female-by-default gender bias — related
• LLM learners are younger, more likely male, and score higher on technology affinity than non-learners — related
• No statistically significant gender differences in perceived learning outcomes across any dimension among higher vocational students — related
• Male and female students used ChatGPT differently: females used it more frequently and for questions, males more sporadically and to check answers — related
• AI applications in STEM education foster positive affective perception, including attitude, interest, and motivation — related
• Persistence behaviors in the face of challenge differed significantly by age and gender — related
• Students perceived ChatGPT as a valuable learning tool for asking questions, getting explanations, and clarifying understanding — related
• Male respondents were significantly more likely than non-male respondents to have no concern about their labour being used for military purposes — related
• Humanities students report higher perceived usefulness, ease of use, and behavioral intention for AI-assisted English tools than STEM students, with small effect sizes — related
• Gender and ability/skills are the most investigated moderators/mediators of peer assessment — related