{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T06:05:12Z","timestamp":1790057112915,"version":"4.0.1"},"reference-count":19,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The rapid integration of digital technologies and generative artificial intelligence (AI) into higher education has reshaped first-year students\u2019 learning experiences and self-reported psychological adjustment. Using a cross-sectional self-report design, this study examined the statistical associations among AI-enabled course development, AI proficiency, academic adjustment, and a composite indicator of self-reported psychological adjustment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross-sectional self-report survey was conducted among 551 first-year university students from a single institution. Descriptive statistics, Pearson correlations, multiple and hierarchical regressions, Bootstrap mediation analysis (PROCESS), moderated mediation analysis, and structural equation modeling (AMOS) were employed to examine the hypothesized associations. Causal inference is not warranted given the cross-sectional and self-report nature of the data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Students reported high satisfaction with AI-enabled course development and strong acceptance of AI learning tools, with over 80% recognizing AI\u2019s learning efficiency and actively using AI for study. However, self-reported indicators of psychological strain were endorsed by more than two-thirds of the sample; these items are descriptive self-report indicators and do not constitute clinical diagnoses. Regression analyses showed that course development satisfaction and AI proficiency were statistically and positively associated with emotional management, stress coping, and academic adjustment. Hierarchical regression demonstrated that these variables substantially improved model explanatory power, with the highest explained variance observed for academic adjustment (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u202f=\u202f0.240). Mediation analysis indicated that AI proficiency partially mediated the association between course development satisfaction and self-reported psychological adjustment (indirect effect\u202f=\u202f0.124, 95% CI [0.076, 0.181]). Moderation analysis revealed that AI-related usage pressure attenuated the positive association between AI proficiency and self-reported psychological adjustment (moderation index\u202f=\u202f\u22120.051, 95% CI [\u22120.095, \u22120.017]). Structural equation modeling showed acceptable model fit (\n                      <jats:italic>\u03c7<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \/df\u202f=\u202f2.31, CFI\u202f=\u202f0.956, TLI\u202f=\u202f0.941, RMSEA\u202f=\u202f0.049, SRMR\u202f=\u202f0.041).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In this cross-sectional sample, AI-enabled course development was statistically and positively associated with first-year students\u2019 self-reported psychological adjustment, both directly and indirectly through self-reported AI proficiency. Excessive self-reported AI-related stress attenuated these positive associations. Because the design is cross-sectional and self-report-based, these findings should be interpreted as statistical associations rather than causal effects. Universities may consider strengthening AI literacy training, optimizing course design, managing technology-related workload, and providing psychological support to maximize the potential benefits of AI-integrated education; future longitudinal and multi-institution studies are needed to test these associations more rigorously.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpsyg.2026.1909803","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T05:40:02Z","timestamp":1790055602000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A study on AI-enabled course development, AI proficiency, and first-year students\u2019 academic and psychological adjustment"],"prefix":"10.3389","volume":"17","author":[{"given":"Jun","family":"Zhang","sequence":"first","affiliation":[{"name":"Yangzhou Polytechnic Institute","place":["Yangzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yushi","family":"Yin","sequence":"additional","affiliation":[{"name":"Yangzhou Polytechnic Institute","place":["Yangzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1738774","DOI":"10.3389\/frai.2026.1738774","article-title":"Exploring the role of agentic AI in fostering self-efficacy, autonomy support, and self-learning motivation in higher education","volume":"9","author":"Alqurni","year":"2026","journal-title":"Front. Artif. Intell."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"7991","DOI":"10.1007\/s12144-025-07433-7","article-title":"Generative artificial intelligence acceptance and artificial intelligence anxiety among university students: the sequential mediating role of attitudes toward artificial intelligence and literacy","volume":"44","author":"Cengiz","year":"2025","journal-title":"Curr. Psychol."},{"key":"ref3","doi-asserted-by":"publisher","first-page":"105979","DOI":"10.1016\/j.actpsy.2025.105979","article-title":"Prevention of AI learning anxiety: the chain mediation role of technophilia and AI self-efficacy under the context of teacher support","volume":"261","author":"Chai","year":"2025","journal-title":"Acta Psychol."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"3162","DOI":"10.1080\/10494820.2024.2440877","article-title":"From anxiety to action: exploring the impact of artificial intelligence anxiety and artificial intelligence self-efficacy on motivated learning of undergraduate students","volume":"33","author":"Chen","year":"2024","journal-title":"Interact. Learn. Environ."},{"key":"ref5","doi-asserted-by":"publisher","first-page":"045","DOI":"10.28945\/5689","article-title":"Linking AI literacy, self-efficacy, attitudes, and achievement: a mixed-methods study on the moderating role of AI usage and study year","volume":"24","author":"Dang Thu","year":"2025","journal-title":"J. Inf. Technol. Educ. Res."},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/10705519909540118","article-title":"Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives","volume":"6","author":"Hu","year":"1999","journal-title":"Struct. Equ. Model. Multidiscip. J."},{"key":"ref7","doi-asserted-by":"publisher","first-page":"961","DOI":"10.1080\/15391523.2025.2478424","article-title":"The AI motivation scale (AIMS): a self-determination theory perspective","volume":"58","author":"Li","year":"2025","journal-title":"J. Res. Technol. Educ."},{"key":"ref8","doi-asserted-by":"publisher","first-page":"100485","DOI":"10.1016\/j.caeai.2025.100485","article-title":"Objective measurement of AI literacy: development and validation of the AI competency objective scale (AICOS)","volume":"9","author":"Markus","year":"2025","journal-title":"Comput. Educ.: Artif. Intell."},{"key":"ref9","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/s44163-026-01293-1","article-title":"Self-efficacy and instructor support as determinants of ChatGPT effectiveness in student learning","volume":"6","author":"Mohamud","year":"2026","journal-title":"Discov. Artif. Intell."},{"key":"ref10","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/s10648-006-9029-9","article-title":"The control-value theory of achievement emotions: assumptions, corollaries, and implications for educational research and practice","volume":"18","author":"Pekrun","year":"2006","journal-title":"Educ. Psychol. Rev."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"879","DOI":"10.3758\/BRM.40.3.879","article-title":"Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models","volume":"40","author":"Preacher","year":"2008","journal-title":"Behav. Res. Methods"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1037\/0003-066X.55.1.68","article-title":"Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being","volume":"55","author":"Ryan","year":"2000","journal-title":"Am. Psychol."},{"key":"ref13","doi-asserted-by":"publisher","first-page":"102537","DOI":"10.1016\/j.techsoc.2024.102537","article-title":"Comprehension, apprehension, and acceptance: understanding the influence of literacy and anxiety on acceptance of artificial intelligence","volume":"77","author":"Schiavo","year":"2024","journal-title":"Technol. Soc."},{"key":"ref14","doi-asserted-by":"publisher","first-page":"3247","DOI":"10.1080\/10494820.2025.2564739","article-title":"AI literacy as a key driver of user experience in AI-powered assessment: insights from Socratic mind","volume":"34","author":"Soylu","year":"2025","journal-title":"Interact. Learn. Environ."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1001\/archinte.166.10.1092","article-title":"A brief measure for assessing generalized anxiety disorder","volume":"166","author":"Spitzer","year":"2006","journal-title":"Arch. Intern. Med."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"101227","DOI":"10.1016\/j.jslw.2025.101227","article-title":"The development and validation of a scale on student AI literacy in L2 writing: a domain-specific perspective","volume":"69","author":"Xu","year":"2025","journal-title":"J. Second. Lang. Writ."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1007\/s12144-025-08937-y","article-title":"Bridging individual and contextual influences: exploring the multilevel pathways of generative AI in shaping academic self-efficacy","volume":"45","author":"Yu","year":"2026","journal-title":"Curr. Psychol."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/10494820.2025.2570493","article-title":"The influence of generative artificial intelligence support on learning anxiety and academic expectation stress: the mediating role of self-efficacy","volume":"34","author":"Zhang","year":"2025","journal-title":"Interact. Learn. Environ."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"e0313314","DOI":"10.1371\/journal.pone.0313314","article-title":"How do personal attributes shape AI dependency in Chinese higher education context? 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