教学代理语言风格及AI生成方式对不同认知风格小学生视频学习的影响

doi:10.12139/j.1672-0628.2026.03.013

摘要/Abstract

摘要： 技术的进步提高了教学代理的语言能力，也使创建AI生成教学代理成为可能。但不同认知风格学生适合何种语言风格教学代理尚不清晰，其AI生成教学代理是否有效也有待探究。为此，实验1考察了会话和正式风格教学代理对不同认知风格小学生视频学习的影响。结果发现，场独立学生在两种条件下的社会临场感、认知负荷和测验成绩均无显著差异；场依存学生在会话风格条件下的社会临场感和测验成绩更高，且场依存学生的社会临场感在教学代理语言风格和测验成绩间起完全中介作用。实验2进一步探究了相较于真人会话风格教学代理，采用AI生成语音、AI生成语音及仿真形象和AI生成语音及卡通形象方式创建的会话风格教学代理对场依存学生是否同样有效。结果发现，AI生成语音及卡通形象的会话风格教学代理进一步提高了场依存学生的测验成绩。上述结果表明，会话风格教学代理对场依存学生更有效，AI生成语音及卡通形象的会话风格教学代理能进一步提高其学习效果。

关键词: 教学代理, 语言风格, 认知风格, AI生成教学代理, 小学生

Abstract: Technological advances have improved the language capabilities of pedagogical agents, enabling the creation of AI-generated pedagogical agents. However, it is unclear which language style of pedagogical agent is appropriate for students with different cognitive styles, and further exploration is needed into the effectiveness of their AI-generated pedagogical agents. Therefore, Experiment 1 examined the effects of conversational and formal style pedagogical agents on video learning among pupils with different cognitive styles. The results indicated no significant differences in social presence, cognitive load, or test scores between the two conditions for field-independent students. However, field-dependent students exhibited higher social presence and test scores in the conversational style condition than in the formal style condition; the social presence in field-dependent students fully mediated the relationship between language style and test scores. Experiment 2 further examined whether the conversational style pedagogical agents created using AI-generated voice, AI-generated voice and human-like appearance, or AI-generated voice and cartoon appearance were equally effective for field-dependent students, compared to real-human conversational style pedagogical agents. The results indicated that only the conversational style pedagogical agents created using AI-generated voice and cartoon appearance further improved the test scores of field-dependent students. These findings suggest that conversational style pedagogical agents are more effective for field-dependent students, and their effectiveness can be further enhanced when they are created using AI-generated voice and cartoon appearance.

Key words: pedagogical agent, language style, cognitive styles, AI-generated pedagogical agents, pupils

中图分类号:

B849

杜雪娇, 孟子凡, 李瑶, 王楚雯, 董颖红. 教学代理语言风格及AI生成方式对不同认知风格小学生视频学习的影响[J]. 心理与行为研究, 2026, 24(3): 384-392.

DU Xuejiao, MENG Zifan, LI Yao, WANG Chuwen, DONG Yinghong. Effects of Pedagogical Agents’ Language Styles and Their AI-Generated Approach on the Video Learning for Pupils with Different Cognitive Styles[J]. Studies of Psychology and Behavior, 2026, 24(3): 384-392.

参考文献

李艳芬, 赵宁宁, 周铁民. (2017). 不同内隐学习任务在不同认知风格个体上的成绩差异. 心理与行为研究, 15(5), 606–612
吕馨, 刘景瑶, 魏柳青, 张学民. (2019). 目标数量与运动框架旋转角度对不同场认知风格个体多目标追踪表现的影响. 心理学报, 51(1), 24–35
宋合义. (1988). 认知方式图形测验的编制与修订说明. 见谢斯骏, 张厚粲 (编), 认知方式一个人格维度的实验研究 (pp. 261–276). 北京: 北京师范大学出版社.
宋淑娟, 刘华山. (2015). 数学-性别刻板印象对女生的威胁效应: 场认知风格的调节作用. 心理与行为研究, 13(3), 302–305, 319
王福兴, 李文静, 谢和平, 刘华山. (2017). 多媒体学习中教学代理有利于学习吗?——一项元分析研究. 心理科学进展, 25(1), 12–28
Almeida, L. M. C. G., Münzer, S., & Kühl, T. (2024). More personal, but not better: The personalization effect in learning neutral and aversive health information. Journal of Computer Assisted Learning, 40(5), 2248–2260
Bai, J., Cheng, X. L., Zhang, H., Qin, Y. H., Xu, T., & Zhou, Y. (2025). Can AI-generated pedagogical agents (AIPA) replace human teacher in picture book videos? The effects of appearance and voice of AIPA on children’s learning. Education and Information Technologies, 30(9), 12267–12287
Castro-Alonso, J. C., Wong, R. M., Adesope, O. O., & Paas, F. (2021). Effectiveness of multimedia pedagogical agents predicted by diverse theories: A meta-analysis. Educational Psychology Review, 33(3), 989–1015
Chen, C. M., Li, M. C., & Chen, Y. T. (2022). The effects of web-based inquiry learning mode with the support of collaborative digital reading annotation system on information literacy instruction. Computers & Education, 179, 104428
Du, X. J., Chen, C., & Lin, H. X. (2022). The impact of working memory capacity on collaborative learning in elementary school students. Frontiers in Psychology, 13, 1027523
Evans, C., Richardson, J. T. E., & Waring, M. (2013). Field independence: Reviewing the evidence. British Journal of Educational Psychology, 83(2), 210–224
Fynes-Clinton, S., Marstaller, L., & Burianová, H. (2019). Differentiation of functional networks during long-term memory retrieval in children and adolescents. NeuroImage, 191, 93–103
Ginns, P., Martin, A. J., & Marsh, H. W. (2013). Designing instructional text in a conversational style: A meta-analysis. Educational Psychology Review, 25(4), 445–472
Kühl, T., & Münzer, S. (2021). Learning about a serious disease: When a personalized message is harmful unless you are happy. Journal of Computer Assisted Learning, 37(5), 1312–1323
Li, H. Y., & Graesser, A. C. (2021). The impact of conversational agents’ language on summary writing. Journal of Research on Technology in Education, 53(1), 44–66
Li, J., Kizilcec, R., Bailenson, J., & Ju, W. (2016). Social robots and virtual agents as lecturers for video instruction. Computers in Human Behavior, 55, 1222–1230
Li, W. J., Wang, F. X., & Mayer, R. E. (2024). Increasing the realism of on-screen embodied instructors creates more looking but less learning. British Journal of Educational Psychology, 94(3), 759–776
Lin, L. J., Ginns, P., Wang, T. H., & Zhang, P. L. (2020). Using a pedagogical agent to deliver conversational style instruction: What benefits can you obtain? Computers & Education, 143, 103658
Lin, L. J., Lin, X., Zhang, X. F., & Ginns, P. (2024). The personalized learning by interest effect on interest, cognitive load, retention, and transfer: A meta-analysis. Educational Psychology Review, 36(3), 88
Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 92(4), 724–733
Netland, T., von Dzengelevski, O., Tesch, K., & Kwasnitschka, D. (2025). Comparing human-made and AI-generated teaching videos: An experimental study on learning effects. Computers & Education, 224, 105164
Nightingale, S. J., & Farid, H. (2022). AI-synthesized faces are indistinguishable from real faces and more trustworthy. Proceedings of the National Academy of Sciences of the United States of America, 119(8), e2120481119
Paas, F. G. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84(4), 429–434
Pataranutaporn, P., Danry, V., Leong, J., Punpongsanon, P., Novy, D., Maes, P. & Sra, M. (2021). AI-generated characters for supporting personalized learning and well-being. Nature Machine Intelligence, 3(12), 1013–1022
Pi, Z. L., Deng, L. X., Wang, X., Guo, P. R., Xu, T., & Zhou, Y. (2022). The influences of a virtual instructor’s voice and appearance on learning from video lectures. Journal of Computer Assisted Learning, 38(6), 1703–1713
Piaget, J. (1952). The origins of intelligence in children (M. Cook, Trans.). New York: W. W. Norton & Company.
Polat, H., Taş, N., Kaban, A., Kayaduman, H., & Battal, A. (2025). Human or humanoid animated pedagogical avatars in video lectures: The impact of the knowledge type on learning outcomes. International Journal of Human-Computer Interaction, 41(14), 8912–8927
Reichelt, M., Kämmerer, F., Niegemann, H. M., & Zander, S. (2014). Talk to me personally: Personalization of language style in computer-based learning. Computers in Human Behavior, 35, 199–210
Sikström, P., Valentini, C., Sivunen, A., & Kärkkäinen, T. (2022). How pedagogical agents communicate with students: A two-phase systematic review. Computers & Education, 188, 104564
Stiller, K. D., & Jedlicka, R. (2010). A kind of expertise reversal effect: Personalisation effect can depend on domain-specific prior knowledge. Australasian Journal of Educational Technology, 26(1), 133–149
Tinajero, C., Castelo, A. M., Guisande, M. A., & Páramo, M. F. (2010). Self-regulated learning in female students with different cognitive styles: An exploratory study. Perceptual and Motor Skills, 111(1), 31–44
Xu, T., Liu, Y., Jin, Y. R., Qu, Y. Y., Bai, J., Zhang, W. L., & Zhou, Y. (2025). From recorded to AI-generated instructional videos: A comparison of learning performance and experience. British Journal of Educational Technology, 56(4), 1463–1487
Zhao, F. Z. & Mayer, R. E. (2025). Improving multimedia learning with emotional design: Depicting key elements with positive features. Journal of Computer Assisted Learning, 41(3), e70028

[1]	李玉华, 张宇祺, 韩靖雅, 李泉, 张李斌, 童廷婷, 张碧滢, 冯廷勇. 预期想象训练对小学生学业拖延的改善[J]. 心理与行为研究, 2026, 24(3): 327-334.
[2]	王娅珂, 张雨轩, 冯琳琳, 卡明芳, 梁菲菲. 小学三到五年级儿童阅读眼动模式的发展及其与阅读理解的关系[J]. 心理与行为研究, 2026, 24(2): 161-169.
[3]	刘泽琪, 李玉华, 高艳, 刘佳欣, 苏萌萌. 小学生家庭读写环境量表的编制及信效度检验[J]. 心理与行为研究, 2026, 24(1): 113-121.
[4]	崔佳歆, 左钰涵, 冯佳佳, 崔占玲. 表意文字和表音文字具有共同的认知基础：来自形状知觉的证据[J]. 心理与行为研究, 2025, 23(6): 766-773.
[5]	吴旻, 李双妍, 宋文琦, 郑天鹏. “双减”背景下小学生睡眠质量的潜在转变及情绪的影响[J]. 心理与行为研究, 2025, 23(1): 49-57.
[6]	贾宇晴, 高彤琪, 闫国利. 一年级小学生汉语默读和朗读差异的眼动研究[J]. 心理与行为研究, 2024, 22(5): 633-641.
[7]	梁菲菲, 向颖, 武浩, 韩洋. 汉语发展性阅读障碍小学生词边界划分的发展研究[J]. 心理与行为研究, 2021, 19(6): 757-763.
[8]	李赛男, 闫国利, 王亚丽, 刘敏, 赵淑萍. 一年级小学生阅读知觉广度的眼动研究[J]. 心理与行为研究, 2021, 19(5): 606-611.
[9]	邱晨, 牛美心, 周新林, 杨涛. 四、七年级学生分数数量表征与数学学业成就的关系：分数概念理解的中介作用[J]. 心理与行为研究, 2021, 19(5): 628-635.
[10]	张苏媛, 兰泽波, 张水, 孟珠, 闫国利. 无关言语对一年级小学生阅读影响的眼动研究[J]. 心理与行为研究, 2021, 19(4): 433-438,446.
[11]	郭筱琳, 秦欢, 罗良. 父母孝道信念与小学生孝道信念的关系：父母教育卷入的中介作用及家庭结构的差异[J]. 心理与行为研究, 2021, 19(2): 258-264.
[12]	刘文, 孟祥蕊, 车翰博, 张嘉琪, 沈漪. 小学生创造性人格教师评定问卷的编制及信效度检验[J]. 心理与行为研究, 2020, 18(5): 624-630.
[13]	刁春婷, 周文倩, 黄臻. 小学生成长型思维模式与学业成绩、生活满意度的关系：学业自我效能感的中介作用[J]. 心理与行为研究, 2020, 18(4): 524-529.
[14]	王立东, 李倩, 罗良. 父母家校沟通与小学生参与数学课外补习的关系研究[J]. 心理与行为研究, 2020, 18(1): 67-71.
[15]	王江洋, 肖青, 聂家昕, 高亚华. 孤儿小学生主观幸福感的积极心理教育干预[J]. 心理与行为研究, 2019, 17(5): 634-643.