Putting Things into Context: Generative AI-Enabled Context Personalization for Vocabulary Learning Improves Learning Motivation
Joanne Leong, Pat Pataranutaporn, Valdemar Danry, Florian Perteneder, Yaoli Mao, Pattie Maes
Abstract
Fostering students’ interests in learning is considered to have many positive downstream effects. Large language models have opened up new horizons for generating content tuned to one’s interests, yet it is unclear in what ways and to what extent this customization could have positive effects on learning. To explore this novel dimension, we conducted a between-subjects online study (n=272) featuring different variations of a generative AI vocabulary learning app that enables users to personalize their learning examples. Participants were randomly assigned to control (sentence sourced from pre-existing text) or experimental conditions (generated sentence or short story based on users’ text input). While we did not observe a difference in learning performance between the conditions, the analysis revealed that generative AI-driven context personalization positively affected learning motivation. We discuss how these results relate to previous findings and underscore their significance for the emerging field of using generative AI for personalized learning.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 632d2d61-afa7-4c06-89cf-0c35c1c9e305Cited by top-tier papers11
- "Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in EducationEmma Harvey, Allison Koenecke, René F. KizilcecCHI 2025 · 63 citations
- How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About ItNanna Inie, Jeanette Falk, Raghavendra SelvanCHI 2025 · 33 citations
- Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI LiteratureShuning Zhang, Hui Wang, Xin YiCSCW 2025 · 31 citations
- Breaking Barriers or Building Dependency? Exploring Team-LLM Collaboration in AI-infused Classroom DebateZihan Zhang, Black Sun, Pengcheng AnCHI 2025 · 24 citations
- Social-RAG: Retrieving from Group Interactions to Socially Ground AI GenerationRuotong Wang, Xinyi Zhou, Lin Qiu, Joseph Chee Chang et al.CHI 2025 · 8 citations
Related papers
- Storyfier: Exploring Vocabulary Learning Support with Text Generation ModelsZhenhui Peng, Xingbo Wang, Qiushi Han, Junkai Zhu et al.UIST 2023 · 26 citations
- Characterizing LLM-Empowered Personalized Story Reading and Interaction for Children: Insights From Multi-Stakeholder PerspectivesJiaju Chen, Minglong Tang, Yuxuan Lu, Bingsheng Yao et al.CHI 2025 · 20 citations
- PAIGE: Examining Learning Outcomes and Experiences with Personalized AI-Generated Educational PodcastsTiffany D. Do, Usama Bin Shafqat, Elsie Ling, Nikhil SardaCHI 2025 · 28 citations
- Open Sesame? Open Salami! Personalizing Vocabulary Assessment-Intervention for Children via Pervasive Profiling and Bespoke Storybook GenerationJungeun Lee, Suwon Yoon, Kyoosik Lee, Eunae Jeong et al.CHI 2024 · 28 citations
- Exploring Multimodal Generative AI for Education through Co-design Workshops with StudentsPrajish Prasad, Rishabh Balse, Dhwani BalchandaniCHI 2025 · 12 citations
