University Students’ Sense of Achievement in GenAI-Assisted Academic Work
whose achievement is it?
Yuhao Lei · Shien Ye · Mubarak Almansoori · Saleh Faisal Saleh Abdulla Ahmed
what we’ve read so far ↓
Li et al. (2026)interviews
Hu (2026)interviews
Batista-Toledo & Gavilan (2026)*experiments
Su et al. (2026)*experiment
Wang et al. (2026)survey
Heil et al. (2025)survey
Alam et al. (2026)survey
Faiella et al. (2025)survey
Research Rationale
why study Sense of Achievement?
CONTEXT
GenAI is part of everyday study
Writing · coding · modelling
High-quality output in minutes
QUESTION
A good result — but is it my achievement?
What do students count as their own contribution?
WHY IT MATTERS
Sense of achievement is part of psychological well-being
Theme: the university student experience in the 21st century
We explore this openly — without assuming AI is harmful.
What We Have Read
eight studies so far
Li et al. (2026)interviews
Hu (2026)interviews
Su et al. (2026)*experiment
Batista-Toledo & Gavilan (2026)*experiments
Heil et al. (2025)survey
Alam et al. (2026)survey
Wang et al. (2026)survey
Faiella et al. (2025)survey
50 students, 10 staff · China
Outsourcing to AI goes with weaker ownership; reflective use keeps it
17 students · Hong Kong
Competence redefined as asking, judging and correcting
526 design students · China
With AI: less effort and ownership; high marks feel less earned
Social-science undergraduates · Spain
Delegating a task to AI, or using AI as support, changes ownership and impostor feelings
223 students · Australia, Germany, Italy
Students rate GenAI tools as helpful, for different goals
400 students · Saudi Arabia
AI use linked to self-reported learning outcomes
478 students · China
Reflective AI use goes with fewer impostor feelings; thoughtless use with more
273 adults · online panel
People feel less creative when using AI than in general
* abstract only so far — full text not yet read
Research Gap
what’s missing?
Learning, ownership & self-beliefs
Sense of Achievement
Quantitativehow much?
Qualitativehow does it feel?
Heil et al. (2025)survey
Alam et al. (2026)survey
Wang et al. (2026)survey
Batista-Toledo & Gavilan (2026)*experiments
Faiella et al. (2025)survey
Su et al. (2026)*experiment
Li et al. (2026)interviews
Hu (2026)interviews
?
Our studyinterviews about real tasks
Among the studies we reviewed, none explores sense of achievement through students’ own accounts.
* abstract only
Research Aim
what we want to understand
To explore how university students make sense of their personal contribution and sense of achievement in GenAI-assisted academic work.
EXPLORE, NOT TEST
Open to positive, negative or neutral experiences
IN THEIR OWN WORDS
Students’ meanings, not our definitions
REAL TASKS
Recent academic work completed with GenAI
Research Question
the one thing we ask
How do university students make sense of their personal contribution and sense of achievement when they use GenAI for academic work?
KEY TERM
Personal contribution
What students see as their own ideas, decisions and effort
KEY TERM
Sense of achievement
Satisfaction, pride or a feeling of progress
Proposed Method
how we’ll find out
DESIGN
Qualitative, semi-structured interviews
One recent, real task per participant
PARTICIPANTS
Monash College students
Details to be confirmed with our teacher
SAMPLE QUESTIONS
“Which parts feel most like yours? Why?”
“Tell me about a recent task you completed with AI.”
“How did you feel afterwards?”
ANALYSIS
Reflexive thematic analysis
Themes built from participants’ own words
Progress and Next Steps
DONE
✓Topic and focus agreed
✓Eight articles collected: seven kept, one set aside
✓Draft aim, question and interview ideas
NEXT
→One replacement article
→Full texts of Su et al. and Batista-Toledo & GavilanAbstracts only so far — we will ask for advice
→Team contract, consent form, interview guide
References
Alam, M. N., Islam, M. A., Babiker, M. O. A., Siddiqui, M. S., Amin, M. B., & Oláh, J. (2026). AI-assisted learning tools and student learning outcomes: A cognitive load theory perspective. Computers in Human Behavior Reports, 21, Article 100986. https://doi.org/10.1016/j.chbr.2026.100986
Batista-Toledo, S., & Gavilan, D. (2026). ¿Lo hice yo o lo hizo la inteligencia artificial? Impacto de la inteligencia artificial en la propiedad psicológica y el síndrome del impostor del alumnado en la educación superior [Did I do it or did artificial intelligence? Impact of artificial intelligence on psychological ownership and impostor syndrome among students in higher education]. Revista Tecnología, Ciencia y Educación, (33), 7–33. https://doi.org/10.51302/tce.2026.24625
Faiella, A., Zielińska, A., Karwowski, M., & Corazza, G. E. (2025). Am I still creative? The effect of artificial intelligence on creative self-beliefs. The Journal of Creative Behavior, 59(2), Article e70011. https://doi.org/10.1002/jocb.70011
Heil, J., Ifenthaler, D., Cooper, M., Mascia, M. L., Conti, R., & Penna, M. P. (2025). Students’ perceived impact of GenAI tools on learning and assessment in higher education: The role of individual AI competence. Smart Learning Environments, 12, Article 37. https://doi.org/10.1186/s40561-025-00395-0
Hu, W. W. (2026). University student perspectives on generative AI: Reconfiguring competence, fairness, and authorship in academic work. Studies in Higher Education, 51(10), 2337–2355. https://doi.org/10.1080/03075079.2026.2658738
Li, X., Xian, X., & Du, P. (2026). From AI dependence to reflective collaboration: Psychological ownership, competency anxiety, and perceived support in AI-assisted learning. Frontiers in Psychology, 17, Article 1903784. https://doi.org/10.3389/fpsyg.2026.1903784
Su, H., Wu, L., Yue, Z., Mei, W., Zhang, J., & Zhang, J. (2026). When high scores no longer feel earned: A vignette study of students’ psychological responses to AI-assisted design creation. International Journal of Educational Research, 140, Article 103083. https://doi.org/10.1016/j.ijer.2026.103083
Wang, Y., Mi, X., Tang, W., Tang, Y., & Gao, H. (2026). How generative AI use styles shape academic engagement: The roles of academic impostor syndrome and AI policy clarity. Behavioral Sciences, 16(6), Article 862. https://doi.org/10.3390/bs16060862
Su et al. (2026) and Batista-Toledo & Gavilan (2026): abstracts only so far