{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T16:04:00Z","timestamp":1774022640238,"version":"3.50.1"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031479939","type":"print"},{"value":"9783031479946","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-47994-6_38","type":"book-chapter","created":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T08:02:28Z","timestamp":1699344148000},"page":"437-450","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Automating Question Generation From\u00a0Educational Text"],"prefix":"10.1007","author":[{"given":"Ayan Kumar","family":"Bhowmick","sequence":"first","affiliation":[]},{"given":"Ashish","family":"Jagmohan","sequence":"additional","affiliation":[]},{"given":"Aditya","family":"Vempaty","sequence":"additional","affiliation":[]},{"given":"Prasenjit","family":"Dey","sequence":"additional","affiliation":[]},{"given":"Leigh","family":"Hall","sequence":"additional","affiliation":[]},{"given":"Jeremy","family":"Hartman","sequence":"additional","affiliation":[]},{"given":"Ravi","family":"Kokku","sequence":"additional","affiliation":[]},{"given":"Hema","family":"Maheshwari","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,8]]},"reference":[{"issue":"22","key":"38_CR1","doi-asserted-by":"publisher","first-page":"12902","DOI":"10.3390\/su132212902","volume":"13","author":"SF Ahmad","year":"2021","unstructured":"Ahmad, S.F., Rahmat, M.K., Mubarik, M.S., Alam, M.M., Hyder, S.I.: Artificial intelligence and its role in education. Sustainability 13(22), 12902 (2021)","journal-title":"Sustainability"},{"key":"38_CR2","doi-asserted-by":"crossref","unstructured":"Bethencourt-Aguilar, A., Castellanos-Nieves, D., Sosa-Alonso, J.J., Area-Moreira, M.: Use of generative adversarial networks (GANS) in educational technology research (2023)","DOI":"10.7821\/naer.2023.1.1231"},{"issue":"5","key":"38_CR3","first-page":"776","volume":"7","author":"B Bhat","year":"2019","unstructured":"Bhat, B., Bhat, G.: Formative and summative evaluation techniques for improvement of learning process. Eur. J. Bus. Soc. Sci. 7(5), 776\u2013785 (2019)","journal-title":"Eur. J. Bus. Soc. Sci."},{"key":"38_CR4","unstructured":"Chen, S.F., Beeferman, D., Rosenfeld, R.: Evaluation metrics for language models (1998)"},{"key":"38_CR5","doi-asserted-by":"crossref","unstructured":"Choi, E., et al.: QUAC: question answering in context. arXiv preprint arXiv:1808.07036 (2018)","DOI":"10.18653\/v1\/D18-1241"},{"key":"38_CR6","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"38_CR7","doi-asserted-by":"crossref","unstructured":"Ethayarajh, K.: How contextual are contextualized word representations? Comparing the geometry of BERT, ELMO, and GPT-2 embeddings. arXiv preprint arXiv:1909.00512 (2019)","DOI":"10.18653\/v1\/D19-1006"},{"key":"38_CR8","doi-asserted-by":"crossref","unstructured":"Faruqui, M., Das, D.: Identifying well-formed natural language questions. arXiv preprint arXiv:1808.09419 (2018)","DOI":"10.18653\/v1\/D18-1091"},{"key":"38_CR9","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1007\/s11023-020-09548-1","volume":"30","author":"L Floridi","year":"2020","unstructured":"Floridi, L., Chiriatti, M.: GPT-3: its nature, scope, limits, and consequences. Mind. Mach. 30, 681\u2013694 (2020)","journal-title":"Mind. Mach."},{"key":"38_CR10","unstructured":"Griffith, S., Subramanian, K., Scholz, J., Isbell, C.L., Thomaz, A.L.: Policy shaping: integrating human feedback with reinforcement learning. In: Advances in Neural Information Processing Systems, vol. 26 (2013)"},{"key":"38_CR11","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/978-981-16-0401-0_18","volume-title":"Advanced Computing","author":"K Grover","year":"2021","unstructured":"Grover, K., Kaur, K., Tiwari, K., Kumar, P.: Deep learning based question generation using t5 transformer. In: Garg, D., Wong, K., Sarangapani, J., Gupta, S.K. (eds.) IACC 2020. Communications in Computer and Information Science, vol. 1367, pp. 243\u2013255. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-16-0401-0_18"},{"key":"38_CR12","unstructured":"Huberman, A., et al.: Qualitative data analysis a methods sourcebook (2014)"},{"key":"38_CR13","unstructured":"Kriangchaivech, K., Wangperawong, A.: Question generation by transformers. arXiv preprint arXiv:1909.05017 (2019)"},{"key":"38_CR14","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1162\/tacl_a_00276","volume":"7","author":"T Kwiatkowski","year":"2019","unstructured":"Kwiatkowski, T., et al.: Natural questions: a benchmark for question answering research. Trans. Assoc. Comput. Linguist. 7, 453\u2013466 (2019)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"38_CR15","doi-asserted-by":"crossref","unstructured":"Lee, J., Wettig, A., Chen, D.: Phrase retrieval learns passage retrieval, too. arXiv preprint arXiv:2109.08133 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.297"},{"key":"38_CR16","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 (2018)","DOI":"10.18653\/v1\/W18-0533"},{"key":"38_CR17","unstructured":"Liu, Y., et al.: RoBERTa: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"38_CR18","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)"},{"key":"38_CR19","unstructured":"Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training (2018)"},{"key":"38_CR20","unstructured":"Salda\u00f1a, J.: The Coding Manual for Qualitative Researchers. Kindle e-reader Version (2016)"},{"key":"38_CR21","doi-asserted-by":"crossref","unstructured":"Schluter, N.: The limits of automatic summarisation according to rouge. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp. 41\u201345. Association for Computational Linguistics (2017)","DOI":"10.18653\/v1\/E17-2007"},{"issue":"1","key":"38_CR22","first-page":"1","volume":"3","author":"E Solas","year":"2018","unstructured":"Solas, E., Sutton, F.: Incorporating digital technology in the general education classroom. Res. Soc. Sci. Technol. 3(1), 1\u201315 (2018)","journal-title":"Res. Soc. Sci. Technol."},{"issue":"1","key":"38_CR23","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1111\/bjet.13288","volume":"54","author":"J Stanja","year":"2023","unstructured":"Stanja, J., Gritz, W., Krugel, J., Hoppe, A., Dannemann, S.: Formative assessment strategies for students\u2019 conceptions\u2013the potential of learning analytics. Br. J. Edu. Technol. 54(1), 58\u201375 (2023)","journal-title":"Br. J. Edu. Technol."},{"key":"38_CR24","unstructured":"Zhang, C., et al.: A complete survey on generative AI (AIGC): Is chatGPT from GPT-4 to GPT-5 all you need? arXiv preprint arXiv:2303.11717 (2023)"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence XL"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-47994-6_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T08:08:45Z","timestamp":1699344525000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-47994-6_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031479939","9783031479946"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-47994-6_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"8 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SGAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Innovative Techniques and Applications of Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambridge","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"43","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sgai2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/bcs-sgai.org\/ai2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"ConferenceExpert","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"67","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"27","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2 or 3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"A total of 76 reviewers plus two \u2018executive program committees\u2019 (one for each stream)","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}