{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:35:35Z","timestamp":1757619335422,"version":"3.44.0"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031992605"},{"type":"electronic","value":"9783031992612"}],"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\/978-3-031-99261-2_14","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T04:13:53Z","timestamp":1753244033000},"page":"147-157","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Systematic Control of\u00a0Multiple-Choice Item Difficulty Through LLM-Based Distractor Generation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8123-1059","authenticated-orcid":false,"given":"Haruki","family":"Oka","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0003-445X","authenticated-orcid":false,"given":"Yoshito","family":"Tan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0267-5653","authenticated-orcid":false,"given":"Tsunenori","family":"Ishioka","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1663-5812","authenticated-orcid":false,"given":"Kensuke","family":"Okada","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,21]]},"reference":[{"key":"14_CR1","doi-asserted-by":"publisher","unstructured":"Alhazmi, E., Sheng, Q.Z., Zhang, W.E., Zaib, M., Alhazmi, A.: Distractor generation in multiple-choice tasks: a survey of methods, datasets, and evaluation. In: Al-Onaizan, Y., Bansal, M., Chen, Y.N. (eds.) Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 14437\u201314458. Association for Computational Linguistics, Miami (2024). https:\/\/doi.org\/10.18653\/v1\/2024.emnlp-main.799","DOI":"10.18653\/v1\/2024.emnlp-main.799"},{"key":"14_CR2","doi-asserted-by":"publisher","unstructured":"Bitew, S.K., Deleu, J., Develder, C., Demeester, T.: Distractor generation for multiple-choice questions with predictive prompting and large language models (2023). https:\/\/doi.org\/10.48550\/arXiv.2307.16338","DOI":"10.48550\/arXiv.2307.16338"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Cheng, Y., et al.: Guiding the growth: difficulty-controllable question generation through step-by-step rewriting. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 5968\u20135978. ACL, Stroudsburg (2021)","DOI":"10.18653\/v1\/2021.acl-long.465"},{"key":"14_CR4","doi-asserted-by":"publisher","unstructured":"Chiang, S.H., Wang, S.C., Fan, Y.C.: CDGP: automatic cloze distractor generation based on pre-trained language model. In: Findings of the Association for Computational Linguistics: EMNLP 2022, pp. 5835\u20135840. ACL, Abu Dhabi (2022). https:\/\/doi.org\/10.18653\/v1\/2022.findings-emnlp.429","DOI":"10.18653\/v1\/2022.findings-emnlp.429"},{"issue":"21\u201323","key":"14_CR5","doi-asserted-by":"publisher","first-page":"31907","DOI":"10.1007\/s11042-021-11222-2","volume":"80","author":"B Das","year":"2021","unstructured":"Das, B., Majumder, M., Phadikar, S., Sekh, A.A.: Multiple-choice question generation with auto-generated distractors for computer-assisted educational assessment. Multimed. Tools Appl. 80(21\u201323), 31907\u201331925 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"14_CR6","unstructured":"Dave, N., Bakes, R., Pursel, B., Giles, C.L.: Math multiple choice question solving and distractor generation with attentional GRU networks. Int. Educ. Data Min. Soc. (2021)"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Feng, W., et al.: Exploring automated distractor generation for math multiple-choice questions via large language models. In: Duh, K., Gomez, H., Bethard, S. (eds.) Findings of the Association for Computational Linguistics: NAACL 2024, pp. 3067\u20133082. ACL, Mexico City (2024)","DOI":"10.18653\/v1\/2024.findings-naacl.193"},{"key":"14_CR8","doi-asserted-by":"publisher","unstructured":"Fernandez, N., Scarlatos, A., Feng, W., Woodhead, S., Lan, A.: DiVERT: distractor generation with variational errors represented as text for math multiple-choice questions. In: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 9063\u20139081. ACL, Miami (2024). https:\/\/doi.org\/10.18653\/v1\/2024.emnlp-main.512","DOI":"10.18653\/v1\/2024.emnlp-main.512"},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A., Rubin, D.B.: Bayesian Data Analysis, 3rd edn. Chapman & Hall\/CRC Texts in Statistical Science. Chapman & Hall\/CRC, Philadelphia (2013)","DOI":"10.1201\/b16018"},{"key":"14_CR10","doi-asserted-by":"publisher","unstructured":"Haladyna, T.M.: Developing and Validating Multiple-Choice Test Items, 3rd edn. Routledge (2004). https:\/\/doi.org\/10.4324\/9780203825945","DOI":"10.4324\/9780203825945"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Hwang, K., Wang, K., Alomair, M., Choa, F.S., Chen, L.K.: Towards automated multiple choice question generation and evaluation: aligning with bloom\u2019s taxonomy. In: Artificial Intelligence in Education, pp. 389\u2013396. Springer (2024)","DOI":"10.1007\/978-3-031-64299-9_35"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Jiao, Y., Shridhar, K., Cui, P., Zhou, W., Sachan, M.: Automatic educational question generation with difficulty level controls. In: Artificial Intelligence in Education: 24th International Conference, AIED 2023, Tokyo, Japan, 3\u20137 July 2023, Proceedings, pp. 476\u2013488. Springer, Heidelberg (2023)","DOI":"10.1007\/978-3-031-36272-9_39"},{"key":"14_CR13","unstructured":"Kutner, M.H., Nachtsheim, C.J., Neter, J., Li, W.: Applied Linear Statistical Models, 5 edn. McGraw\u2013Hill, Boston (2005)"},{"key":"14_CR14","doi-asserted-by":"publisher","unstructured":"Lee, Y., Kim, S., Jo, Y.: Generating plausible distractors for multiple-choice questions via student choice prediction (2025). https:\/\/doi.org\/10.48550\/arXiv.2501.13125","DOI":"10.48550\/arXiv.2501.13125"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Liang, C., Yang, X., Dave, N., Wham, D., Pursel, B., Giles, C.L.: Distractor generation for multiple choice questions using learning to rank. In: Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pp. 284\u2013290. Association for Computational Linguistics, Stroudsburg (2018)","DOI":"10.18653\/v1\/W18-0533"},{"key":"14_CR16","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.jrp.2013.09.008","volume":"48","author":"MR Maniaci","year":"2014","unstructured":"Maniaci, M.R., Rogge, R.D.: Caring about carelessness: participant inattention and its effects on research. J. Res. Pers. 48, 61\u201383 (2014)","journal-title":"J. Res. Pers."},{"key":"14_CR17","unstructured":"OpenAI: GPT-4o. ChatGPT (May 13 Version) (2024). https:\/\/chat.openai.com\/. Accessed 02 Nov 2024"},{"key":"14_CR18","doi-asserted-by":"crossref","unstructured":"Palma\u00a0Gomez, F., Panda, S., Flor, M., Rozovskaya, A.: Using neural machine translation for generating diverse challenging exercises for language learner. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 6115\u20136129. Association for Computational Linguistics, Stroudsburg (2023)","DOI":"10.18653\/v1\/2023.acl-long.337"},{"key":"14_CR19","unstructured":"R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2022). https:\/\/www.R-project.org\/"},{"key":"14_CR20","unstructured":"Scarlatos, A., Feng, W., Smith, D., Woodhead, S., Lan, A.: Improving automated distractor generation for math multiple-choice questions with overgenerate-and-rank. In: Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024), pp. 222\u2013231. Association for Computational Linguistics, Mexico City (2024)"},{"key":"14_CR21","doi-asserted-by":"publisher","first-page":"825","DOI":"10.3389\/fpsyg.2019.00825","volume":"10","author":"J Shin","year":"2019","unstructured":"Shin, J., Guo, Q., Gierl, M.J.: Multiple-choice item distractor development using topic modeling approaches. Front. Psychol. 10, 825 (2019)","journal-title":"Front. Psychol."},{"issue":"2","key":"14_CR22","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1177\/014662168300700208","volume":"7","author":"ML Stocking","year":"1983","unstructured":"Stocking, M.L., Lord, F.M.: Developing a common metric in item response theory. Appl. Psychol. Meas. 7(2), 201\u2013210 (1983)","journal-title":"Appl. Psychol. Meas."},{"issue":"1","key":"14_CR23","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s41039-018-0082-z","volume":"13","author":"Y Susanti","year":"2018","unstructured":"Susanti, Y., Tokunaga, T., Nishikawa, H., Obari, H.: Automatic distractor generation for multiple-choice English vocabulary questions. Res. Pract. Technol. Enhanc. Learn. 13(1), 15 (2018)","journal-title":"Res. Pract. Technol. Enhanc. Learn."},{"key":"14_CR24","unstructured":"Taslimipoor, S., Benedetto, L., Felice, M., Buttery, P.: Distractor generation using generative and discriminative capabilities of transformer-based models. In: Calzolari, N., Kan, M.Y., Hoste, V., Lenci, A., Sakti, S., Xue, N. (eds.) Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC\u2013COLING 2024), pp. 5052\u20135063. ELRA and ICCL, Torino (2024)"},{"key":"14_CR25","doi-asserted-by":"publisher","first-page":"2186","DOI":"10.1109\/TLT.2024.3491801","volume":"17","author":"Y Tomikawa","year":"2024","unstructured":"Tomikawa, Y., Suzuki, A., Uto, M.: Adaptive question-answer generation with difficulty control using item response theory and pretrained transformer models. IEEE Trans. Learn. Technol. 17, 2186\u20132198 (2024)","journal-title":"IEEE Trans. Learn. Technol."},{"key":"14_CR26","doi-asserted-by":"crossref","unstructured":"Uto, M., Tomikawa, Y., Suzuki, A.: Difficulty-controllable neural question generation for reading comprehension using item response theory. In: Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), pp. 119\u2013129. Association for Computational Linguistics, Toronto (2023)","DOI":"10.18653\/v1\/2023.bea-1.10"},{"issue":"12","key":"14_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v035.i12","volume":"35","author":"JP Weeks","year":"2010","unstructured":"Weeks, J.P.: Plink: an R Package for linking mixed-format tests using IRT-based methods. J. Stat. Softw. 35(12), 1\u201333 (2010)","journal-title":"J. Stat. Softw."},{"issue":"4","key":"14_CR28","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1177\/014662168200600408","volume":"6","author":"DJ Weiss","year":"1982","unstructured":"Weiss, D.J.: Improving measurement quality and efficiency with adaptive testing. Appl. Psychol. Meas. 6(4), 473\u2013492 (1982)","journal-title":"Appl. Psychol. Meas."},{"key":"14_CR29","doi-asserted-by":"crossref","unstructured":"Yoshimi, N., Kajiwara, T., Uchida, S., Arase, Y., Ninomiya, T.: Distractor generation for fill-in-the-blank exercises by question type. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pp. 276\u2013281. Association for Computational Linguistics, Stroudsburg (2023)","DOI":"10.18653\/v1\/2023.acl-srw.38"}],"container-title":["Communications in Computer and Information Science","Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-99261-2_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T18:25:53Z","timestamp":1757269553000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-99261-2_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031992605","9783031992612"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-99261-2_14","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"21 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"}}]}}