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Приложение C. Сопоставления студентов технологического и нетехнологического профилей / Appendix C. Comparison of Students from Technological and Non-Technological Profiles

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

Приложение С содержит результаты проверки гипотезы 3 о наличии различий в психологическом благополучии между студентами IT- и не-IT-профилей с учётом контроля пола. В таблице С1 представлены результаты двухфакторного ANOVA (главный эффект профиля с контролем пола) для 17 шкал благополучия (Рифф, PERMA, а также шкалы одиночества, негативных эмоций и доверия к ИИ). Показано, что после контроля пола ни одна шкала благополучия не показала значимого эффекта профиля (все p > 0,05). Единственное исключение — доверие к ИИ: студенты IT-профиля демонстрируют более высокий уровень доверия (F(1,149) = 4,18, p = 0,043, η²p = 0,027). В таблице С2 представлены результаты того же анализа для главного эффекта пола (с контролем профиля): девушки значимо превосходят юношей по большинству шкал благополучия (PERMA, Рифф, одиночество, позитивные отношения, управление средой, личностный рост, цели в жизни, самопринятие, позитивные эмоции, взаимоотношения, смысл, достижения, счастье). В таблице С3 приведены результаты анализа простых эффектов (Simple Main Effects) для негативных эмоций, где взаимодействие «пол × профиль» оказалось значимым (p = 0,047). Эффект пола значим только в не-IT-группе (F(1,53) = 5,00, p = 0,027), тогда как в IT-группе он не достигает порога (F(1,96) = 0,05, p = 0,832). Полученные результаты свидетельствуют о том, что различия в благополучии между IT- и не-IT-студентами объясняются смешением с полом; единственное сохранившееся профильное различие — более высокое доверие к ИИ у IT-студентов. Appendix C presents the results of testing Hypothesis 3 regarding differences in psychological well-being between IT and non-IT students while controlling for gender. Table C1 shows two-way ANOVA results (main effect of profile controlling for gender) for 17 well-being scales (Ryff, PERMA, plus loneliness, negative emotions, and trust in AI). After controlling for gender, no well-being scale showed a significant profile effect (all p > 0.05). The only exception was trust in AI: IT students reported higher trust (F(1,149) = 4.18, p = 0.043, η²p = 0.027). Table C2 presents the same analysis for the main effect of gender (controlling for profile): females significantly outperformed males on most well-being scales (PERMA, Ryff, loneliness, positive relations, environmental mastery, personal growth, purpose in life, self-acceptance, positive emotions, relationships, meaning, achievement, happiness). Table C3 shows Simple Main Effects results for negative emotions, where the interaction "gender × profile" was significant (p = 0.047). The gender effect was significant only in the non-IT group (F(1,53) = 5.00, p = 0.027), whereas in the IT group it was not (F(1,96) = 0.05, p = 0.832). The results indicate that differences in well-being between IT and non-IT students are explained by confounding with gender; the only remaining profile difference is higher trust in AI among IT students.

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