{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T17:21:08Z","timestamp":1765041668871,"version":"3.44.0"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031984648"},{"type":"electronic","value":"9783031984655"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-98465-5_7","type":"book-chapter","created":{"date-parts":[[2025,7,19]],"date-time":"2025-07-19T01:47:30Z","timestamp":1752889650000},"page":"52-59","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Can Open Source LLMs Generate Math Questions at\u00a0Graduate Level Courses? An Empirical Study of\u00a0Linear Algebra Course"],"prefix":"10.1007","author":[{"given":"Alka","family":"Bhushan","sequence":"first","affiliation":[]},{"given":"Nirav","family":"Bhatt","sequence":"additional","affiliation":[]},{"given":"Anik","family":"Bhowmick","sequence":"additional","affiliation":[]},{"given":"Patrick Vincent","family":"Ndowo","sequence":"additional","affiliation":[]},{"given":"Sukanya Tukaram","family":"Naik","sequence":"additional","affiliation":[]},{"given":"Ramadhan Mwinyi","family":"Pembe","sequence":"additional","affiliation":[]},{"given":"Adhil Ahmed P. M.","family":"Shums","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,20]]},"reference":[{"key":"7_CR1","unstructured":"Azerbayev, Z., et al.: Llemma: an open language model for mathematics. In: The Twelfth International Conference on Learning Representations (2024)"},{"key":"7_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2024.100284","volume":"7","author":"S Bhandari","year":"2024","unstructured":"Bhandari, S., Liu, Y., Kwak, Y., Pardos, Z.A.: Evaluating the psychometric properties of chatGPT-generated questions. Comput. Educ. Artif. Intell. 7, 100284 (2024)","journal-title":"Comput. Educ. Artif. Intell."},{"key":"7_CR3","unstructured":"Brown, T.B., et al.: Language models are few-shot learners (2020). https:\/\/arxiv.org\/abs\/2005.14165"},{"key":"7_CR4","unstructured":"Chen, M., et al.: Evaluating large language models trained on code (2021). https:\/\/arxiv.org\/abs\/2107.03374"},{"key":"7_CR5","unstructured":"Didolkar, A., et al.: Metacognitive capabilities of LLMs: an exploration in mathematical problem solving. arXiv preprint arXiv:2405.12205 (2024)"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Drori, I., et al.: A dataset for learning university stem courses at scale and generating questions at a human level. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 15921\u201315929 (2024)","DOI":"10.1609\/aaai.v37i13.27091"},{"issue":"13","key":"7_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10639-024-12537-x","volume":"29","author":"WY Hwang","year":"2024","unstructured":"Hwang, W.Y., Utami, I.Q.: Using GPT and authentic contextual recognition to generate math word problems with difficulty levels. Educ. Inf. Technol. 29(13), 1\u201329 (2024)","journal-title":"Educ. Inf. Technol."},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Khurdi, G., Leo, J., Parsia, B., Sattler, U., AL-Emari, S.: A systematic review of automatic question generation for educational purposes. Int. J., Artif. Intell. Educ. 30, 121\u2013204 (2020)","DOI":"10.1007\/s40593-019-00186-y"},{"key":"7_CR9","unstructured":"Kojima, T., Gu, S.S., Reid, M., Matsuo, Y., Iwasawa, Y.: Large language models are zero-shot reasoners. In: Proceedings of the 36th International Conference on Neural Information Processing Systems, NIPS 2022. Curran Associates Inc., Red Hook (2022)"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Li, Y.: A practical survey on zero-shot prompt design for in-context learning. In: Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Processings, pp. 641\u2013647. INCOMA Ltd., Shoumen (2023)","DOI":"10.26615\/978-954-452-092-2_069"},{"key":"7_CR11","unstructured":"Lin, Z., et al.: Rho-1: not all tokens are what you need (2025). https:\/\/arxiv.org\/abs\/2404.07965"},{"key":"7_CR12","doi-asserted-by":"publisher","unstructured":"Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., Neubig, G.: Pre-train, prompt, and predict: a systematic survey of prompting methods in natural language processing. ACM Comput. Surv. 55(9) (2023). https:\/\/doi.org\/10.1145\/3560815","DOI":"10.1145\/3560815"},{"key":"7_CR13","unstructured":"Long, P.P.V., Vu, D.A., Hoang, N.M., Do, X.L., Luu, A.T.: ChatGPT as a math questioner? Evaluating chatGPT on generating pre-university math questions (2024). https:\/\/arxiv.org\/abs\/2312.01661"},{"key":"7_CR14","unstructured":"Mistral AI Team: Mathstral 7B (2024). https:\/\/mistral.ai\/news\/mathstral. Accessed 19 Feb 2025"},{"key":"7_CR15","unstructured":"Opedal, A., Stoehr, N., Saparov, A., Sachan, M.: World models for math story problems (2025). https:\/\/arxiv.org\/abs\/2306.04347"},{"key":"7_CR16","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21(1) (2020)"},{"key":"7_CR17","doi-asserted-by":"publisher","unstructured":"Reynolds, L., McDonell, K.: Prompt programming for large language models: beyond the few-shot paradigm. In: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA 2021. Association for Computing Machinery, New York (2021). https:\/\/doi.org\/10.1145\/3411763.3451760","DOI":"10.1145\/3411763.3451760"},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Scaria, N., Dharani\u00a0Chenna, S., Subramani, D.: Automated educational question generation at different bloom\u2019s skill levels using large language models: strategies and evaluation. In: International Conference on Artificial Intelligence in Education, pp. 165\u2013179. Springer (2024)","DOI":"10.1007\/978-3-031-64299-9_12"},{"key":"7_CR19","unstructured":"Shah, V., et al.: AI-Assisted generation of difficult math questions (2025). https:\/\/arxiv.org\/abs\/2407.21009"},{"key":"7_CR20","unstructured":"Shao, Z., et al.: Deepseekmath: pushing the limits of mathematical reasoning in open language models (2024). https:\/\/arxiv.org\/abs\/2402.03300"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Shridhar, K., Macina, J., El-Assady, M., Sinha, T., Kapur, M., Sachan, M.: Automatic generation of socratic subquestions for teaching math word problems. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 4136\u20134149 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.277"},{"key":"7_CR22","unstructured":"Wang, K., et al.: Mathcoder: seamless code integration in LLMs for enhanced mathematical reasoning (2023). https:\/\/arxiv.org\/abs\/2310.03731"},{"key":"7_CR23","first-page":"24824","volume":"35","author":"J Wei","year":"2022","unstructured":"Wei, J., et al.: Chain-of-thought prompting elicits reasoning in large language models. Adv. Neural. Inf. Process. Syst. 35, 24824\u201324837 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"7_CR24","unstructured":"Yu, L., et al.: Metamath: Bootstrap your own mathematical questions for large language models (2024). https:\/\/arxiv.org\/abs\/2309.12284"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Zhou, Z., et al.: Learning by analogy: diverse questions generation in math word problem (2023). https:\/\/arxiv.org\/abs\/2306.09064","DOI":"10.18653\/v1\/2023.findings-acl.705"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Education"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-98465-5_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T14:40:18Z","timestamp":1757256018000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-98465-5_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031984648","9783031984655"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-98465-5_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"20 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIED","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence in Education","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Palermo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aied2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aied2025.itd.cnr.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}