Implementing Generative AI Agent Game to Support Reading of Classical Chinese Literature: A Needs Analysis
Abstract
This study investigated the challenges faced by middle school students when engaging with "Study with Confucius," a generative artificial intelligence (GenAI) agent game designed for learning classical Chinese reading. Utilizing the framework proposed by Groff and Mouza (2008), the research aimed to conduct a comprehensive needs analysis across three key dimensions: student-related, teacher-related, and technology-related aspects. Data were collected from 29 students in mainland China through video recordings of their gameplay. Challenges were defined based on their duration and students' responses that contradicted predefined correct answers, resulting in the identification of 29 challenges. Findings indicated that students encountered student-related challenges including linguistic misinterpretation, distraction, cognitive overload, student misbeliefs, and inappropriate attitudes; teacher-related challenges such as lack of support and inadequate access to teaching and technological resources; and technology-related challenges including external and internal malfunctions. These insights contribute to understanding the complexities as well as learning opportunities of integrating GenAI agent games into reading education.
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Studies addressed persistent challenges in traditional curricula, such as difficulties in understanding poetry, classical literature, or cultural symbolism, using AI to help students engage with texts more deeply through visual and multimodal support.
“These studies addressed persistent challenges in traditional curricula, such as difficulties in understanding poetry, classical literature, or cultural symbolism. AI was used to help students engage with texts more deeply through visual and multimodal support [70-74].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [73]
In science and outreach games, AI operates as a non-player character or assistant, providing stepwise hints, rule explanations, and plot advancement.
“In science and outreach games, AI operates as a non-player character or assistant, providing stepwise hints, rule explanations, and plot advancement.”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [73]
Readability issues, insufficient explanatory depth, and cognitive overload can further impede knowledge construction and amplify over-reliance risks.
“Readability issues [76], insufficient explanatory depth [91,92], and cognitive overload [73] can further impede knowledge construction and amplify over-reliance risks [94,119].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [73]
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Lin, X., & Tan, H. (2025) · Systems · doi:10.3390/systems13100840 · Cited by 22 · see citing works
- Authors
- Lin, H., Xiong, Z., Tang, H., Jiang, S., Wei, W., & Fang, K.
- Affiliations
- Macao Polytechnic University (MO)
- Tsinghua Shenzhen International Graduate School (CN)
- Venue
- 2024 4th International Conference on Educational Technology (ICET)
- Publisher
- IEEE
- Published
- 2024-09-13
- Pages
- 86-91
- OpenAlex
- W4407214735
- Cited by
- 2
- References
- 13
- Citations by year
- 2025: 2
- FWCI
- 3.07
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Educational Technology (ICET) (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- generative AI agents, game-based learning, Chinese classical literature, reading instruction, junior high school students, needs assessment, student challenges, teacher support, cognitive overload, technology integration in education
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