Relevance, Effort, and Perceived Quality: Language Learners’ Experiences with AI-Generated Contextually Personalized Learning Material

Draxler, Fiona ; Schmidt, Albrecht und Chuang, Lewis (2023): Relevance, Effort, and Perceived Quality: Language Learners’ Experiences with AI-Generated Contextually Personalized Learning Material. DIS '23: Designing Interactive Systems Conference, Pittsburgh PA USA, July 10 - 14, 2023. Byrne, Daragh; Martelaro, Nikolas; Boucher, Andy; Chatting, David J.; Alaoui, Sarah Fdili; Fox, Sarah Elizabeth; Nicenboim, Iohanna und MacArthur, Cayley (eds.) : In: Proceedings of the 2023 ACM Designing Interactive Systems Conference, New York, NY, United States: Association for Computing Machinery. 2249- 2262

Abstract

Artificial intelligence has enabled scalable auto-creation of context-aware personalized learning materials. However, it remains unclear how content personalization shapes the learners’ experience. We developed one personalized and two non-personalized, crowdsourced versions of a mobile language learning app: (1) with personalized auto-generated photo flashcards, (2) the same flashcards provided through crowdsourcing, and (3) manually generated flashcards based on the same photos. A two-week in-situ study (n = 64) showed that learners assessed the quality of the non-personalized auto-generated material to be on par with manually generated material, which means that auto-generation is viable. However, when the auto-generation was personalized, the learners’ quality rating was significantly lower. Further analyses suggest that aspects such as prior expectations and required efforts must be addressed before learners can actually benefit from context-aware personalization with auto-generated material. We discuss design implications and provide an outlook on the role of content personalization in AI-supported learning.

• Item Type: Conference or Workshop Item (Paper)
• Faculties: Mathematics, Computer Science and Statistics > Computer Science
• Subjects: 000 Computer science, information and general works > 004 Data processing computer science
• ISBN: 978-1-4503-9893-0
• Place of Publication: New York, NY, United States
• Language: English