{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T01:03:23Z","timestamp":1769821403903,"version":"3.49.0"},"reference-count":17,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,2,2]]},"abstract":"<jats:p>Personalized exercise recommendation is an important research project in the field of online learning, which can explore students\u2019 strengths and weaknesses and tailor exercises for them. However, programming exercises differs from other disciplines or types of exercises due to the comprehensive of the exercises and the specificity of program debugging. In order to assist students in learning programming, this paper proposes a programming exercise recommendation algorithm based on knowledge structure tree (KSTER). Firstly, the algorithm provides a calculation method for quantifying students\u2019 cognitive level to obtain their knowledge needs through individual learning-related data. Secondly, a knowledge structure tree is constructed based on the association relationship of knowledge points, and a learning objective prediction method is proposed by combining the knowledge needs and the knowledge structure tree to represent and update the learning objective. Finally, KSTER imports a matching operator that calculates cognitive level and exercise difficulty based on learning objectives, and makes top-\u03b7 recommendation for exercises. Experiments show that the proposed algorithm significantly outperforms the other algorithms in both precision and recall. The comparison experiments with real-world data demonstrate that KSTER effectively improves students\u2019 learning efficiency.<\/jats:p>","DOI":"10.3233\/jifs-211499","type":"journal-article","created":{"date-parts":[[2021,12,28]],"date-time":"2021-12-28T12:26:05Z","timestamp":1640694365000},"page":"2169-2180","source":"Crossref","is-referenced-by-count":10,"title":["A personalized programming exercise recommendation algorithm based on knowledge structure tree"],"prefix":"10.1177","volume":"42","author":[{"given":"Wei","family":"Zheng","sequence":"first","affiliation":[{"name":"School of Software, Nanchang Hangkong University, Nanchang, China"},{"name":"Software Testing and Evaluation Center, Nanchang Hangkong University, Nanchang, China"}]},{"given":"Qing","family":"Du","sequence":"additional","affiliation":[{"name":"School of Software, Nanchang Hangkong University, Nanchang, China"},{"name":"Software Testing and Evaluation Center, Nanchang Hangkong University, Nanchang, China"}]},{"given":"Yongjian","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Software, Nanchang Hangkong University, Nanchang, China"},{"name":"Software Testing and Evaluation Center, Nanchang Hangkong University, Nanchang, China"}]},{"given":"Lijuan","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Software, Nanchang Hangkong University, Nanchang, China"},{"name":"Software Testing and Evaluation Center, Nanchang Hangkong University, Nanchang, China"}]},{"given":"Chuanlin","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Software, Nanchang Hangkong University, Nanchang, China"},{"name":"Software Testing and Evaluation Center, Nanchang Hangkong University, Nanchang, China"}]},{"given":"Fengyu","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Software, Nanchang Hangkong University, Nanchang, China"},{"name":"Software Testing and Evaluation Center, Nanchang Hangkong University, Nanchang, China"}]}],"member":"179","reference":[{"issue":"3","key":"10.3233\/JIFS-211499_ref2","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1016\/j.compedu.2010.11.001","article-title":"E-learning personalization based on hybrid recommendation strategyand learning style identification","volume":"56","author":"Kla\u0161nja-Mili\u0107evi\u0107","year":"2011","journal-title":"Computers & Education"},{"issue":"1","key":"10.3233\/JIFS-211499_ref3","first-page":"176","article-title":"Cognitive diagnosis based personalized question recommendation[J]","volume":"40","author":"Zhu","year":"2017","journal-title":"Chinese Journal of Computers"},{"key":"10.3233\/JIFS-211499_ref4","first-page":"53","article-title":"Utilizing knowledge graph and student testing behavior data for personalized exercise recommendation[C]\/\/","volume":"2018","author":"Lv","journal-title":"Proceedings of ACM Turing Celebration Conference-China"},{"key":"10.3233\/JIFS-211499_ref5","first-page":"106","article-title":"DBNCF: Personalized courses recommendation system based on DBN in MOOC environment[C]\/\/","volume":"2017","author":"Zhang","journal-title":"2017 International Symposium on Educational Technology (ISET). IEEE"},{"key":"10.3233\/JIFS-211499_ref6","first-page":"2053","article-title":"Multi-View Active Learning for Video Recommendation[C]\/\/","volume":"2019","author":"Cai","journal-title":"IJCAI"},{"key":"10.3233\/JIFS-211499_ref7","first-page":"1261","article-title":"Exploring multi-objective exercise recommendations in online education systems[C]\/\/","volume":"2019","author":"Huang","journal-title":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management"},{"key":"10.3233\/JIFS-211499_ref10","first-page":"1","article-title":"Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation [J]","volume":"2017","author":"Polato","journal-title":"Neurocomputing"},{"key":"10.3233\/JIFS-211499_ref11","unstructured":"Segal Z.K.A., Ya\u2019 akov (Kobi)Gal G.S. and Shapira B., EduRank: A Collaborative Filtering Approach to Personalization in E-learning. In Proceedings of the 7th International Conference on Educational Data Mining. International Educational Data Mining Society, London, UK, (2014), 68\u201375."},{"key":"10.3233\/JIFS-211499_ref12","first-page":"145","article-title":"Recommender System for Selection of the Right Study Program for Higher Education Students","volume":"10","author":"Vukicevic","year":"2013","journal-title":"Chapman and Hall Boston, MA, USA, Chapter"},{"issue":"3","key":"10.3233\/JIFS-211499_ref15","doi-asserted-by":"crossref","first-page":"2965","DOI":"10.3233\/JIFS-169652","article-title":"Personalized exercise recommendation algorithm combining learning objective and assignment feedback[J]","volume":"35","author":"Xia","year":"2018","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-211499_ref16","first-page":"436","article-title":"A study on exercise recommendation method using Knowledge Graph for computer network course[C]\/\/","volume":"2020","author":"Zhu","journal-title":"2020 International Conference on Networking and Network Applications (NaNA). IEEE"},{"issue":"20","key":"10.3233\/JIFS-211499_ref17","first-page":"7263","article-title":"Recommendation of Programming Problems in Online Judge Platform: An Experimental Research","volume":"11","author":"Li","year":"2015","journal-title":"Journal of Computational Information Systems"},{"issue":"2","key":"10.3233\/JIFS-211499_ref18","doi-asserted-by":"crossref","first-page":"51","DOI":"10.4018\/ijdet.2014040103","article-title":"An E-Learning Collaborative Filtering Approach to Suggest Problems to Solve in Programming Online Judges","volume":"12","author":"Mota","year":"2014","journal-title":"International Journal of Distance Education Technologies"},{"key":"10.3233\/JIFS-211499_ref19","unstructured":"Boting Q., Research of C Programming Exercises Recommendation based on Hierarchical Labels,\u201d Northwest University, (2014)."},{"key":"10.3233\/JIFS-211499_ref20","unstructured":"Wu Y.F., Online Question Recommendation System based on Hybrid Transfer Bagging\u2014-Taking C Programming Course as an Example, Northwest University (2013)."},{"issue":"2","key":"10.3233\/JIFS-211499_ref21","doi-asserted-by":"crossref","first-page":"2821","DOI":"10.1016\/j.procs.2010.08.007","article-title":"Exercises Recommending forLimited Time Learning","volume":"1","author":"Bielikov\u00e1","year":"2010","journal-title":"Procedia Computer Science"},{"key":"10.3233\/JIFS-211499_ref22","doi-asserted-by":"crossref","unstructured":"Fan J., Feng S., Zeng Q. and Zhao Z., Personalized Knowledge Acquisition through Interactive Data Analysis in E-Learning System, Journal of Computers 5(5) (2010).","DOI":"10.4304\/jcp.5.5.709-716"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-211499","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T12:52:15Z","timestamp":1769777535000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-211499"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,2]]},"references-count":17,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/jifs-211499","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,2]]}}}