Sep 2026· Artificial Intelligence and Education· Vol 1· 0 citations
Abstract
This study investigated how college students’ use of ChatGPT has evolved from a tool for simply getting answers to one that supports motivation and learning engagement. Using a novel survey instrument based on Self-Determination Theory, we measured six types of motivation, three intrinsic, two extrinsic, and amotivation, across two cohorts of students (2023 and 2025). Results revealed statistically significant increases in both intrinsic and extrinsic motivation over time. While early use of ChatGPT focused on convenience and task completion, students increasingly reported using it to overcome mental blocks, build momentum, and stay engaged with their academic work. Follow-up analyses of repeat participants and comparisons by class standing suggest these trends reflect broader shifts in student engagement, not just cohort or experience differences. Cluster analysis revealed distinct motivational profiles, highlighting variation in how students incorporate ChatGPT into their academic routines. These findings suggest that as generative artificial intelligence becomes more familiar, accessible, and sophisticated, students are integrating it more deeply into their learning processes, not just for answers, but for sustained motivation and support.
The increasing integration of artificial intelligence (AI) tools in higher education has transformed students’ learning experiences and academic practices. Among these tools, ChatGPT has gained considerable attention for its ability to support academic tasks, enhance learning efficiency, and facilitate student engagement. Guided by McClelland’s Theory of Needs, this study examines university students’ motivation for using ChatGPT in learning, with particular emphasis on the need for achievement, need for power, and need for affiliation. A quantitative research design was employed using a survey questionnaire administered to 123 university students enrolled in Mandarin language courses at a university branch campus. The instrument consisted of six sections measuring critical thinking, learner agency, academic performance, ChatGPT usage, student engagement, and motivational needs. Data were analyzed using descriptive statistics, independent samples t-tests, and Pearson correlation analysis. The findings indicate that students perceive ChatGPT as a useful learning tool that supports assignment completion, enhances learning efficiency, and contributes positively to academic performance. The results further revealed no significant differences in motivational needs based on gender or academic clusters. However, significant positive relationships were identified among the three motivational needs proposed by McClelland’s theory. The study also highlights that despite the increasing role of AI-assisted learning tools, instructor support and human interaction remain important in sustaining student engagement and meaningful learning experiences. The findings suggest that educators should integrate ChatGPT into educational practices in a balanced and pedagogically guided manner to support students’ motivation and learning outcomes in the digital learning environment.
Lee Chai Chuen, Teo Ai Min, L. Yui et al.· International journal of res...· 0 citations
It is concluded that ChatGPT has significant potential to complement traditional learning methods, provided it is used responsibly, and offers valuable implications for educators and policymakers in integrating AI tools effectively into educational settings.
H. Ibrahim, Dr. Rudresh Pandey, Nureen Waheda binti Mohd Nazdir et al.· Asian Pacific Journal of Man...· 0 citations
Generative AI is increasingly used in L2 writing, yet little is known about its use by beginners and learners of languages other than English. This study examined how four beginner learners of Japanese engaged affectively, cognitively, and behaviorally with ChatGPT feedback while writing. Data were collected through interviews, stimulated recalls, screen recordings, and reflective journals. The data analysis also included error types, prompt types, and the accuracy of ChatGPT output. Affectively, participants valued English translations but reported negative emotions due to inconsistent, self‐contradictory explanations, low trust, and feedback beyond their proficiency. Cognitively, orthographic accessibility reduced attention to feedback, though learners still evaluated suggestions critically. Behaviorally, participants frequently verified ChatGPT output with external resources and used ChatGPT mainly for proofreading and word lookup. Findings highlight how proficiency and orthography shape engagement with AI feedback. This study underscores the importance of teaching AI‐use strategies to elicit level‐appropriate feedback for beginner learners.
Jun Takahashi, Yoshie Kadowaki· Foreign language annals· 0 citations
This study investigated how chatbots, designed with distinct personality traits (more engaging vs. less engaging) and feedback features (basic vs. enhanced) influenced L2 learners’ affective variables, such as anxiety, enjoyment, curiosity, and boredom, during their conversational interactions. Although second language acquisition research, including AI-based chatbot studies, has examined how learners’ emotions are shaped during L2 tasks, there has been insufficient focus on how variations in chatbot characteristics affect learners’ emotional experiences. To address this gap, we conducted a mixed-methods study of undergraduate EFL students, examining their interactions with three conversational agents, each featuring distinct combinations of personality traits and feedback features. Participants engaged in conventional tasks and completed a questionnaire to assess affective variables, which was supplemented with open-ended questions to gain further insights. Our findings revealed how L2 learners’ emotional experiences differ depending on the conversational agents’ characteristics. Based on these insights, we propose the pedagogical implications for the design and implementation of chatbots for L2 learning.
J. Lee, Hansol Lee, Kyungmin Kim· Language Learning & Tech...· 0 citations
Growing use of generative AI technologies like ChatGPT has changed online learning and increased student motivation. This study explores online learning motivation and ChatGPT using Self-Determination Theory (SDT) to examine competence, autonomy, and relatedness in online learners. 189 academics from various fields participated in a quantitative survey. A five-point Likert scale-based 52-item questionnaire was derived from Ryan and Deci (2000), Fowler (2018), and Youssef et al. (2024). Competence, autonomy, and relatedness were not gender-specific across academic groupings. In the descriptive study, students rated the AI system's function in critical thinking, academic accomplishment, engagement, and learning motivation positively. The greatest competency item was students' practice of cross-checking ChatGPT knowledge with independent study (M = 4.06), whereas the most autonomous item was achieving good grades (M = 4.59). Relatedness was strong in social engagement and teacher support. They liked class discussions (M = 4.00) and found course materials meaningful (M = 4.28). Positive correlations were found between competence, autonomy (r =.550, p <.001), and competence and relatedness (r =.551, p <.001). The results support the Self-Determination Theory as a valid framework for online learning motivation and show that ChatGPT can promote learners' competence, autonomy, and relatedness if responsibly integrated into online learning settings. The work has major theoretical, pedagogical, and practical consequences for higher education AI-assisted learning.
E. S. Mohandas, Aini Faridah Azizul Hassan, Nor Azyyati Md Saad et al.· International journal of res...· 0 citations
The rise of ChatGPT as a popular tool among EFL learners has become a subject in recent studies. Preliminary classroom observations reveal that many students use ChatGPT to scan texts to retrieve immediate answers to grammar-related tasks rather than engaging in analytical and reflective practice. Moreover, while scholarship mainly explores the impacts of ChatGPT on writing and vocabulary learning of English majors, there are limited studies on how ChatGPT is actually used by non-English-major students in grammar learning. To fill this gap, this study investigates how students perceive and actually use ChatGPT as a scaffolding for understanding or a shortcut for task completion. Drawing upon the Technology Acceptance Model (TAM) and social constructivism (Vygotsky, 1978), a questionnaire was delivered to 239 non-major university students. Cronbach’s alpha, descriptive statistics, and regression analyses were used to analyze data. Findings indicate that students hold a positive perception of ChatGPT's ease of use and usefulness. Perceived usefulness predicts not only students’ intention to use ChatGPT and their tendency to engage with explanations and learning support, but also students’ reliance on ChatGPT for obtaining quick answers and completing tasks. These findings reveal that ChatGPT has dual impacts on students’ constructive and convenience-driven learning. Pedagogical guidance is needed to foster critical and reflective engagement with ChatGPT.
