{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T16:50:26Z","timestamp":1773939026883,"version":"3.50.1"},"reference-count":46,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DUE-1761178"],"award-info":[{"award-number":["DUE-1761178"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DRL-2112635"],"award-info":[{"award-number":["DRL-2112635"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Artif Intell Educ"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s40593-024-00421-1","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T13:02:01Z","timestamp":1721221321000},"page":"533-558","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["LLM-Based Student Plan Generation for Adaptive Scaffolding in Game-Based Learning Environments"],"prefix":"10.1016","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-4128-4898","authenticated-orcid":false,"given":"Alex","family":"Goslen","sequence":"first","affiliation":[]},{"given":"Yeo Jin","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Jonathan","family":"Rowe","sequence":"additional","affiliation":[]},{"given":"James","family":"Lester","sequence":"additional","affiliation":[]}],"member":"78","published-online":{"date-parts":[[2024,7,17]]},"reference":[{"key":"421_CR1","unstructured":"Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F.L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., et al. (2023). Gpt-4 technical report. arXiv preprint arXiv:2303.08774."},{"key":"421_CR2","doi-asserted-by":"crossref","unstructured":"Azevedo, R., Martin, S. A., Taub, M., Mudrick, N. V., Millar, G. C., & Grafsgaard, J. F. (2016). Are pedagogical agents\u2019 external regulation effective in fostering learning with intelligent tutoring systems? In: Intelligent Tutoring Systems: 13th International Conference, ITS 2016, Zagreb, Croatia, June 7-10, 2016. Proceedings 13, pp. 197\u2013207. Springer","DOI":"10.1007\/978-3-319-39583-8_19"},{"key":"421_CR3","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.813632","volume":"13","author":"R Azevedo","year":"2022","unstructured":"Azevedo, R., Bouchet, F., Duffy, M., Harley, J., Taub, M., Trevors, G., Cloude, E., Dever, D., Wiedbusch, M., Wortha, F., et al. (2022). Lessons learned and future directions of metatutor: Leveraging multichannel data to scaffold self-regulated learning with an intelligent tutoring system. Frontiers in Psychology., 13, 813632.","journal-title":"Frontiers in Psychology."},{"key":"421_CR4","first-page":"99","volume":"18","author":"R Bart\u00e1k","year":"2021","unstructured":"Bart\u00e1k, R., Ondr\u010dkov\u00e1, S., Behnke, G., & Bercher, P. (2021). Correcting hierarchical plans by action deletion. Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning, 18, 99\u2013109.","journal-title":"Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning"},{"key":"421_CR5","doi-asserted-by":"crossref","unstructured":"Bercher, P., Alford, R., & H\u00f6ller, D. (2019). A survey on hierarchical planning-one abstract idea, many concrete realizations. In: IJCAI, pp. 6267\u20136275.","DOI":"10.24963\/ijcai.2019\/875"},{"issue":"1\u20132","key":"421_CR6","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/S0004-3702(96)00047-1","volume":"90","author":"AL Blum","year":"1997","unstructured":"Blum, A. L., & Furst, M. L. (1997). Fast planning through planning graph analysis. Artificial intelligence., 90(1\u20132), 281\u2013300.","journal-title":"Artificial intelligence."},{"key":"421_CR7","first-page":"90","volume-title":"Handbook of Educational Psychology","author":"M Boekaerts","year":"2015","unstructured":"Boekaerts, M., & Pekrun, R. (2015). Emotions and emotion regulation in academic settings. Handbook of Educational Psychology (pp. 90\u2013104). New York, NY: Routledge."},{"key":"421_CR8","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020). Language models are few-shot learners. Advances in neural information processing systems., 33, 1877\u20131901.","journal-title":"Advances in neural information processing systems."},{"key":"421_CR9","doi-asserted-by":"crossref","unstructured":"Bulathwela, S., Muse, H., & Yilmaz, E. (2023). Scalable educational question generation with pre-trained language models. In: International Conference on Artificial Intelligence in Education, pp. 327\u2013339. Springer","DOI":"10.1007\/978-3-031-36272-9_27"},{"key":"421_CR10","unstructured":"Chen, M., Tworek, J., Jun, H., et al. (2021). Evaluating large language models trained on code. CoRR. arXiv:2107.03374"},{"key":"421_CR11","doi-asserted-by":"crossref","unstructured":"Cloude, E. B., Taub, M., Lester, J., & Azevedo, R. (2019). The role of achievement goal orientation on metacognitive process use in game-based learning. In: Artificial Intelligence in Education: 20th International Conference, AIED 2019, Chicago, IL, USA, June 25-29, 2019, Proceedings, Part II 20, pp. 36\u201340 . Springer","DOI":"10.1007\/978-3-030-23207-8_7"},{"key":"421_CR12","doi-asserted-by":"crossref","unstructured":"Cochran, K., Cohn, C., Rouet, J. F., & Hastings, P. (2023). Improving automated evaluation of student text responses using gpt-3.5 for text data augmentation. In: International Conference on Artificial Intelligence in Education, pp. 217\u2013228. Springer","DOI":"10.1007\/978-3-031-36272-9_18"},{"key":"421_CR13","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.813677","volume":"13","author":"DA Dever","year":"2022","unstructured":"Dever, D. A., Amon, M. J., Vrzakova, H., Wiedbusch, M. D., Cloude, E. B., & Azevedo, R. (2022). Capturing sequences of learners\u2019 self-regulatory interactions with instructional material during game-based learning using auto-recurrence quantification analysis. Frontiers in Psychology., 13, 813677.","journal-title":"Frontiers in Psychology."},{"key":"421_CR14","volume-title":"Automated Planning: Theory and Practice","author":"M Ghallab","year":"2004","unstructured":"Ghallab, M., Nau, D., & Traverso, P. (2004). Automated Planning: Theory and Practice. Amsterdam: Elsevier."},{"key":"421_CR15","doi-asserted-by":"crossref","unstructured":"Goslen, A., Carpenter, D., Rowe, J., Azevedo, R., & Lester, J. (2022). Robust Player Plan Recognition in Digital Games with Multi-Task Multi-Label Learning. In: Proceedings of the 18th AAAI Conference on AIIDE, pp. 105\u2013112. AAAI Press, Pomona, CA, USA.","DOI":"10.1609\/aiide.v18i1.21953"},{"key":"421_CR16","doi-asserted-by":"crossref","unstructured":"Goslen, A., Carpenter, D., Rowe, J., Henderson, N., Azevedo, R., & Lester, J. (2022). Leveraging Student Goal Setting for Real-Time Plan Recognition in Game-Based Learning. In: Proceedings of the Twenty-Third International Conference on Artificial Intelligence in Education (AIED-22), pp. 78\u201389. Springer, Durham, UK.","DOI":"10.1007\/978-3-031-11644-5_7"},{"key":"421_CR17","doi-asserted-by":"crossref","unstructured":"Goslen, A., Taub, M., Carpenter, D., Azevedo, R., Rowe, J., & Lester, J. (2024). Leveraging student planning in game-based learning environments for self-regulated learning analytics. Journal of Educational Psychology.","DOI":"10.1037\/edu0000901"},{"key":"421_CR18","unstructured":"Hello GPT-4o. https:\/\/openai.com\/index\/hello-gpt-4o\/"},{"issue":"1","key":"421_CR19","first-page":"253","volume":"14","author":"J Hoffmann","year":"2001","unstructured":"Hoffmann, J., & Nebel, B. (2001). The ff planning system: Fast plan generation through heuristic search. J. Artif. Int. Res., 14(1), 253\u2013302.","journal-title":"J. Artif. Int. Res."},{"key":"421_CR20","doi-asserted-by":"crossref","unstructured":"Jiao, Y., Shridhar, K., Cui, P., Zhou, W., & Sachan, M. (2023). Automatic educational question generation with difficulty level controls. In: International Conference on Artificial Intelligence in Education, pp. 476\u2013488. Springer","DOI":"10.1007\/978-3-031-36272-9_39"},{"key":"421_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.lindif.2023.102274","volume":"103","author":"E Kasneci","year":"2023","unstructured":"Kasneci, E., Se\u00dfler, K., K\u00fcchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., G\u00fcnnemann, S., H\u00fcllermeier, E., et al. (2023). Chatgpt for good? on opportunities and challenges of large language models for education. Learning and Individual Differences., 103, 102274.","journal-title":"Learning and Individual Differences."},{"key":"421_CR22","doi-asserted-by":"crossref","unstructured":"Kim, Y.J., Goslen, A., Rowe, J., Mott, B., & Lester, J. (2023). Language model-based player goal recognition in open world digital games. In: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-23).","DOI":"10.1609\/aiide.v19i1.27503"},{"key":"421_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2022.104694","volume":"194","author":"A Koskinen","year":"2023","unstructured":"Koskinen, A., McMullen, J., Hannula-Sormunen, M., Ninaus, M., & Kiili, K. (2023). The strength and direction of the difficulty adaptation affect situational interest in game-based learning. Computers & Education., 194, 104694.","journal-title":"Computers & Education."},{"key":"421_CR24","doi-asserted-by":"crossref","unstructured":"Kumaran, V., Carpenter, D., Rowe, J., Mott, B., & Lester, J. (2024). Procedural level generation in educational games from natural language instruction. IEEE Transactions on Games.","DOI":"10.1109\/TG.2024.3392670"},{"key":"421_CR25","doi-asserted-by":"crossref","unstructured":"Leung, E. W. C., & Li, Q. (2003). A dynamic conceptual network mechanism for personalized study plan generation. In: Advances in Web-Based Learning-ICWL 2003: Second International Conference, Melbourne, Australia, August 18-20, 2003. Proceedings 2, pp. 69\u201380. Springer","DOI":"10.1007\/978-3-540-45200-3_8"},{"key":"421_CR26","doi-asserted-by":"publisher","unstructured":"Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2020). BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 7871\u20137880. Association for Computational Linguistics, Online. https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.703 . https:\/\/aclanthology.org\/2020.acl-main.703","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"421_CR27","doi-asserted-by":"crossref","unstructured":"MacNeil, S., Tran, A., Mogil, D., Bernstein, S., Ross, E., & Huang, Z. (2022). Generating diverse code explanations using the gpt-3 large language model. In: Proceedings of the 2022 ACM Conference on International Computing Education Research-Volume 2, pp. 37\u201339.","DOI":"10.1145\/3501709.3544280"},{"key":"421_CR28","unstructured":"Min, W., Mott, B., Rowe, J., Liu, B., & Lester, J. (2016). Player Goal Recognition in Open-World Digital Games with Long Short-Term Memory Networks. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence(IJCAI-16), pp. 2590\u20132596. , New York."},{"key":"421_CR29","doi-asserted-by":"publisher","unstructured":"Min, W., Mott, B., Rowe, J., Taylor, R., Wiebe, E., Boyer, K., & Lester, J. (2017). Multimodal goal recognition in open-world digital games. In: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-17), pp. 80\u201386. https:\/\/doi.org\/10.1609\/aiide.v13i1.12939","DOI":"10.1609\/aiide.v13i1.12939"},{"key":"421_CR30","doi-asserted-by":"crossref","unstructured":"Pande, J., Min, W., Spain, R. D., Saville, J. D., & Lester, J. (2023). Robust team communication analytics with transformer-based dialogue modeling. In: International Conference on Artificial Intelligence in Education, pp. 639\u2013650. Springer","DOI":"10.1007\/978-3-031-36272-9_52"},{"key":"421_CR31","doi-asserted-by":"crossref","unstructured":"Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In: Handbook of Self-regulation, pp. 451\u2013502. Elsevier, ???.","DOI":"10.1016\/B978-012109890-2\/50043-3"},{"key":"421_CR32","unstructured":"Plass, J. L., Mayer, R. E., & Homer, B. D. (2020). Handbook of Game-based Learning. Mit Press, ???"},{"key":"421_CR33","doi-asserted-by":"crossref","unstructured":"Polceanu, M., Porteous, J., Lindsay, A., & Cavazza, M. (2021). Narrative Plan Generation with Self-Supervised Learning. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21), pp. 5984\u20135992. AAAI Press, Virtual.","DOI":"10.1609\/aaai.v35i7.16747"},{"key":"421_CR34","unstructured":"Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020). Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. JMLR, 4."},{"issue":"1\u20132","key":"421_CR35","first-page":"115","volume":"21","author":"JP Rowe","year":"2011","unstructured":"Rowe, J. P., Shores, L. R., Mott, B. W., & Lester, J. C. (2011). Integrating learning, problem solving, and engagement in narrative-centered learning environments. International Journal of Artificial Intelligence in Education., 21(1\u20132), 115\u2013133.","journal-title":"International Journal of Artificial Intelligence in Education."},{"issue":"1","key":"421_CR36","doi-asserted-by":"publisher","first-page":"13","DOI":"10.18608\/jla.2015.21.3","volume":"2","author":"JR Segedy","year":"2015","unstructured":"Segedy, J. R., Kinnebrew, J. S., & Biswas, G. (2015). Using coherence analysis to characterize self-regulated learning behaviours in open-ended learning environments. Journal of Learning Analytics., 2(1), 13\u201348.","journal-title":"Journal of Learning Analytics."},{"key":"421_CR37","doi-asserted-by":"crossref","unstructured":"Shabrina, P., Mostafavi, B., Chi, M., & Barnes, T. (2023). Impact of learning a subgoal-directed problem-solving strategy within an intelligent logic tutor. In: International Conference on Artificial Intelligence in Education, pp. 389\u2013400. Springer","DOI":"10.1007\/978-3-031-36272-9_32"},{"key":"421_CR38","unstructured":"Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. CoRR. arXiv:1409.3215"},{"key":"421_CR39","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1007\/s40593-019-00191-1","volume":"30","author":"M Taub","year":"2020","unstructured":"Taub, M., Sawyer, R., Lester, J., & Azevedo, R. (2020). The impact of contextualized emotions on self-regulated learning and scientific reasoning during learning with a game-based learning environment. International Journal of Artificial Intelligence in Education., 30, 97\u2013120.","journal-title":"International Journal of Artificial Intelligence in Education."},{"key":"421_CR40","unstructured":"Thoppilan, R., Freitas, D.D., Hall, J., Shazeer, N., Kulshreshtha, A., Cheng, H., Jin, A., et al. (2022). Lamda: Language models for dialog applications. CoRR. arXiv:2201.08239"},{"key":"421_CR41","unstructured":"Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al. (2023). Llama 2: Open foundation and fine-tuned chat models. arXiv:2307.09288."},{"key":"421_CR42","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. In: Proceedings of the 31th Conference on Neural Information Processing SystemsNeurIPS"},{"key":"421_CR43","doi-asserted-by":"crossref","unstructured":"Winne, P., & Hadwin, A. (1998). Studying as self-regulated learning (pp. 291-318). Routledge","DOI":"10.4324\/9781410602350-19"},{"issue":"1","key":"421_CR44","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1111\/bjep.12173","volume":"88","author":"PH Winne","year":"2018","unstructured":"Winne, P. H. (2018). Theorizing and researching levels of processing in self-regulated learning. British Journal of Educational Psychology., 88(1), 9\u201320.","journal-title":"British Journal of Educational Psychology."},{"key":"421_CR45","volume-title":"Motivation and self-regulated learning: Theory, research, and application","author":"P Winne","year":"2008","unstructured":"Winne, P., & Hadwin, A. (2008). The weave of motivation and self-regulated learning. In D. H. Schunk & B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research, and application. New York, NY: Routledge."},{"issue":"3","key":"421_CR46","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1080\/00461520.2013.794676","volume":"48","author":"BJ Zimmerman","year":"2013","unstructured":"Zimmerman, B. J. (2013). From cognitive modeling to self-regulation: A social cognitive career path. Educational psychologist., 48(3), 135\u2013147.","journal-title":"Educational psychologist."}],"container-title":["International Journal of Artificial Intelligence in Education"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40593-024-00421-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40593-024-00421-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40593-024-00421-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T18:12:51Z","timestamp":1772647971000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40593-024-00421-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,17]]},"references-count":46,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["421"],"URL":"https:\/\/doi.org\/10.1007\/s40593-024-00421-1","relation":{},"ISSN":["1560-4292","1560-4306"],"issn-type":[{"value":"1560-4292","type":"print"},{"value":"1560-4306","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,17]]},"assertion":[{"value":"7 July 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No potential conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest\/Competing interests"}}]}}