{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T13:43:06Z","timestamp":1743082986169,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031630279"},{"type":"electronic","value":"9783031630286"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-63028-6_9","type":"book-chapter","created":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T16:05:16Z","timestamp":1717171516000},"page":"104-116","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancement of Knowledge Concept Maps Using Deductive Reasoning with Educational Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5125-3524","authenticated-orcid":false,"given":"Hyunhee","family":"Choi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6313-5031","authenticated-orcid":false,"given":"Hayun","family":"Lee","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8921-6761","authenticated-orcid":false,"given":"Minjeong","family":"Lee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,1]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","unstructured":"Bashir, A., Bashir, S., Rana, K., Lambert, P., Vernallis, A.: Post-COVID-19 adaptations; the shifts towards online learning, hybrid course delivery and the implications for biosciences courses in the higher education setting. Front. Educ. (FIE), 310 (2021). https:\/\/doi.org\/10.3389\/feduc.2021.711619","DOI":"10.3389\/feduc.2021.711619"},{"issue":"11","key":"9_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3569576","volume":"55","author":"G Abdelrahman","year":"2023","unstructured":"Abdelrahman, G., Wang, Q., Nunes, B.: Knowledge tracing: a survey. ACM Comput. Surv. 55(11), 1\u201337 (2023). https:\/\/doi.org\/10.1145\/3569576","journal-title":"ACM Comput. Surv."},{"issue":"7","key":"9_CR3","doi-asserted-by":"publisher","first-page":"9205","DOI":"10.1007\/s10639-022-11015-6","volume":"27","author":"A Bessadok","year":"2022","unstructured":"Bessadok, A.: Analyzing student aspirations factors affecting e-learning system success using a structural equation model. Educ. Inf. Technol. 27(7), 9205\u20139230 (2022). https:\/\/doi.org\/10.1007\/s10639-022-11015-6","journal-title":"Educ. Inf. Technol."},{"key":"9_CR4","doi-asserted-by":"publisher","first-page":"31553","DOI":"10.1109\/ACCESS.2018.2839607","volume":"6","author":"P Chen","year":"2018","unstructured":"Chen, P., Lu, Y., Zheng, V.W., Chen, X., Yang, B.: KnowEdu: a system to construct knowledge graph for education. IEEE Access 6, 31553\u201331563 (2018)","journal-title":"IEEE Access"},{"key":"9_CR5","unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), San Francisco, CA, USA, pp. 282\u2013289 (2001)"},{"key":"9_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2020.100001","volume":"1","author":"GJ Hwang","year":"2020","unstructured":"Hwang, G.J., Xie, H., Wah, B.W., Ga\u0161evi\u0107, D.: Vision, challenges, roles and research issues of Artificial Intelligence in education. Comput. Educ. Artif. Intell. 1, 100001 (2020). https:\/\/doi.org\/10.1016\/j.caeai.2020.100001","journal-title":"Comput. Educ. Artif. Intell."},{"key":"9_CR7","doi-asserted-by":"publisher","unstructured":"Wang, S., et al.: Using prerequisites to extract concept maps from textbooks. In:\u00a0Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, Indianapolis, Indiana, USA, pp. 317\u2013326 (2016). https:\/\/doi.org\/10.1145\/2983323.2983725","DOI":"10.1145\/2983323.2983725"},{"key":"9_CR8","doi-asserted-by":"publisher","unstructured":"Liang, C., Wu, Z., Huang, W., Giles, C.L.: Measuring prerequisite relations among concepts. In:\u00a0Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal, pp. 1668\u20131674 (2015). https:\/\/doi.org\/10.18653\/v1\/D15-1193","DOI":"10.18653\/v1\/D15-1193"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Roy, S., Madhyastha, M., Lawrence, S., Rajan, V.: Inferring concept prerequisite relations from online educational resources. In:\u00a0Proceedings of the AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, USA, vol. 33, no. 01, pp. 9589\u20139594 (2019)","DOI":"10.1609\/aaai.v33i01.33019589"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Nallapati, R., Cohen, W.: Link-PLSA-LDA: a new unsupervised model for topics and influence of blogs. In:\u00a0Proceedings of the International AAAI Conference on Web and Social Media, Seattle, Washington, USA, vol. 2, no. 1, pp. 84\u201392 (2008)","DOI":"10.1609\/icwsm.v2i1.18621"},{"issue":"2","key":"9_CR11","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1080\/10986060701854425","volume":"10","author":"GJ Stylianides","year":"2008","unstructured":"Stylianides, G.J., Stylianides, A.J.: Proof in school mathematics: insights from psychological research into students\u2019 ability for deductive reasoning. Math. Think. Learn. 10(2), 103\u2013133 (2008). https:\/\/doi.org\/10.1080\/10986060701854425","journal-title":"Math. Think. Learn."},{"key":"9_CR12","doi-asserted-by":"publisher","unstructured":"Spooner, S.A.: Mathematical foundations of decision support systems. In: Berner, E.S. (ed.) Clinical Decision Support Systems. Health Informatics, pp. 23\u201343. Springer, New York (2007). https:\/\/doi.org\/10.1007\/978-0-387-38319-4_2","DOI":"10.1007\/978-0-387-38319-4_2"},{"key":"9_CR13","doi-asserted-by":"publisher","unstructured":"Giannotti, F., Manco, G., Pedreschi, D., Turini, F.: Experiences with a logic-based knowledge discovery support environment. In: Lamma, E., Mello, P. (eds.) AI*IA 1999. LNCS, vol. 1792, pp. 202\u2013213. Springer, Heidelberg (2000). https:\/\/doi.org\/10.1007\/3-540-46238-4_18","DOI":"10.1007\/3-540-46238-4_18"},{"issue":"2","key":"9_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/276305.276306","volume":"27","author":"D Tsur","year":"1998","unstructured":"Tsur, D., et al.: Query flocks: a generalization of association-rule mining. ACM SIGMOD Rec. 27(2), 1\u201312 (1998). https:\/\/doi.org\/10.1145\/276305.276306","journal-title":"ACM SIGMOD Rec."},{"key":"9_CR15","doi-asserted-by":"publisher","unstructured":"Muhammad, A., Zhou, Q., Beydoun, G., Xu, D., Shen, J.: Learning path adaptation in online learning systems. In: Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), Nanchang, China, pp. 421\u2013426. IEEE (2016). https:\/\/doi.org\/10.1109\/cscwd.2016.7566026","DOI":"10.1109\/cscwd.2016.7566026"},{"issue":"5","key":"9_CR16","first-page":"421","volume":"37","author":"A Murata","year":"2006","unstructured":"Murata, A., Fuson, K.: Teaching as assisting individual constructive paths within an interdependent class learning zone: Japanese first graders learning to add using 10. J. Res. Math. Educ. 37(5), 421\u2013456 (2006)","journal-title":"J. Res. Math. Educ."},{"issue":"2","key":"9_CR17","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1016\/j.compedu.2007.08.004","volume":"51","author":"CM Chen","year":"2008","unstructured":"Chen, C.M.: Intelligent web-based learning system with personalized learning path guidance. Comput. Educ. 51(2), 787\u2013814 (2008)","journal-title":"Comput. Educ."},{"issue":"3","key":"9_CR18","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1016\/j.tele.2017.05.007","volume":"35","author":"F Gasparetti","year":"2018","unstructured":"Gasparetti, F., De Medio, C., Limongelli, C., Sciarrone, F., Temperini, M.: Prerequisites between learning objects: automatic extraction based on a machine learning approach. Telemat. Inform. 35(3), 595\u2013610 (2018)","journal-title":"Telemat. Inform."},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Cai, D., Zhang, Y., Dai, B.: Learning path recommendation based on knowledge tracing model and reinforcement learning. In: Proceedings of the 2019 IEEE 5th International Conference on Computer and Communications (ICCC), Chengdu, China, pp. 1881\u20131885 (2019)","DOI":"10.1109\/ICCC47050.2019.9064104"},{"issue":"4","key":"9_CR20","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1109\/TLT.2022.3193751","volume":"15","author":"A Siren","year":"2022","unstructured":"Siren, A., Tzerpos, V.: Automatic learning path creation using OER: a systematic literature mapping. IEEE Trans. Learn. Technol. 15(4), 493\u2013507 (2022)","journal-title":"IEEE Trans. Learn. Technol."},{"issue":"10","key":"9_CR21","doi-asserted-by":"publisher","first-page":"1981","DOI":"10.9728\/dcs.2022.23.10.1981","volume":"23","author":"H Choi","year":"2022","unstructured":"Choi, H., Lee, M.: Analysis of prerequisite relation in knowledge graph using ElasticNet (LASSO)+ RF+ HMM: focusing on K-12 math. J. Digit. Contents Soc. 23(10), 1981\u20131990 (2022). https:\/\/doi.org\/10.9728\/dcs.2022.23.10.1981","journal-title":"J. Digit. Contents Soc."},{"issue":"1","key":"9_CR22","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani, R.: Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Ser. B Stat Methodol. 58(1), 267\u2013288 (1996)","journal-title":"J. R. Stat. Soc. Ser. B Stat Methodol."},{"key":"9_CR23","doi-asserted-by":"crossref","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","DOI":"10.1023\/A:1010933404324"},{"key":"9_CR24","doi-asserted-by":"publisher","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: Overview of supervised learning. In: Hastie, T., Tibshirani, R., Friedman, J. (eds.) The Elements of Statistical Learning. SSS, pp. 9\u201341. Springer, New York (2009). https:\/\/doi.org\/10.1007\/978-0-387-84858-7_2","DOI":"10.1007\/978-0-387-84858-7_2"},{"key":"9_CR25","doi-asserted-by":"crossref","unstructured":"Zucchini, W., MacDonald, I.L., Langrock, R.: Hidden Markov Models for Time Series: An Introduction Using R, 2nd edn. Chapman and Hall\/CRC, London (2016)","DOI":"10.1201\/b20790"},{"key":"9_CR26","doi-asserted-by":"crossref","unstructured":"Zhou, X., Li, Y., Yuan, L., Ma, G., Tan, X., Zhang, K., et al.: Learning path recommendation method based on knowledge map. In: Handbook of Research on Managerial Practices and Disruptive Innovation in Asia,\u00a0pp. 171\u2013184. IGI Global, Pennsylvania (2020)","DOI":"10.4018\/978-1-7998-0357-7.ch009"},{"key":"9_CR27","doi-asserted-by":"publisher","first-page":"249","DOI":"10.3758\/BF03194060","volume":"14","author":"S Ritter","year":"2007","unstructured":"Ritter, S., Anderson, J.R., Koedinger, K.R., Corbett, A.: Cognitive tutor: applied research in mathematics education. Psychon. Bull. Rev. 14, 249\u2013255 (2007)","journal-title":"Psychon. Bull. Rev."},{"issue":"5","key":"9_CR28","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1111\/j.1551-6709.2012.01245.x","volume":"36","author":"KR Koedinger","year":"2012","unstructured":"Koedinger, K.R., Corbett, A.T., Perfetti, C.: The Knowledge-Learning-Instruction framework: bridging the science-practice chasm to enhance robust student learning. Cogn. Sci. 36(5), 757\u2013798 (2012). https:\/\/doi.org\/10.1111\/j.1551-6709.2012.01245.x","journal-title":"Cogn. Sci."},{"key":"9_CR29","unstructured":"Osborne J., Overbay, A.: The power of outliers (and why researchers should ALWAYS check for them). Pract. Assess. Res. Eval. 9, Article no. 6 (2019)"},{"key":"9_CR30","first-page":"5105","volume":"33","author":"M Wojtas","year":"2020","unstructured":"Wojtas, M., Chen, K.: Feature importance ranking for deep learning. Adv. Neural. Inf. Process. Syst. 33, 5105\u20135114 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"9_CR31","doi-asserted-by":"publisher","unstructured":"Cohen, I., Huang, Y., Chen, J., Benesty, J., et al.: Pearson correlation coefficient. Noise Red. Speech Process., 1\u20134 (2009). https:\/\/doi.org\/10.1007\/978-3-642-00296-0_5","DOI":"10.1007\/978-3-642-00296-0_5"},{"key":"9_CR32","doi-asserted-by":"crossref","unstructured":"Schmid Jr., J.: The relationship between the coefficient of correlation and the angle included between regression lines. J. Educ. Res. 41(4), 311\u2013313 (1947)","DOI":"10.1080\/00220671.1947.10881608"},{"key":"9_CR33","doi-asserted-by":"publisher","unstructured":"Goutte, C., Gaussier, E.: A probabilistic interpretation of precision, recall and\u00a0F-score, with implication for evaluation. In: Losada, D.E., Fern\u00e1ndez-Luna, J.M. (eds.) ECIR 2005. LNCS, vol. 3408, pp. 345\u2013359. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/978-3-540-31865-1_25","DOI":"10.1007\/978-3-540-31865-1_25"},{"key":"9_CR34","doi-asserted-by":"publisher","first-page":"12855","DOI":"10.1007\/s10639-022-11120-6","volume":"27","author":"Y Jang","year":"2022","unstructured":"Jang, Y., Choi, S., Jung, H., et al.: Practical early prediction of students\u2019 performance using machine learning and eXplainable AI. Educ. Inf. Technol. 27, 12855\u201312889 (2022)","journal-title":"Educ. Inf. Technol."}],"container-title":["Lecture Notes in Computer Science","Generative Intelligence and Intelligent Tutoring Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-63028-6_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T16:06:22Z","timestamp":1717171582000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-63028-6_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031630279","9783031630286"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-63028-6_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"1 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ITS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Tutoring Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thessaloniki","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"its2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iis-international.org\/its2024-generative-intelligence-and-its\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}