The DOI matches its Crossref record; 44 of the 46 references it cites were found in a registry or an index.
E-Learning personalization based on hybrid recommendation strategy and learning style identification
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Learning styles (Çakıroğlu, 2014;Klašnja-Milićević et al., 2011;Latham, Crockett and McLean, 2014) have been among the broadly chosen components in previous studies as a reference for adapting learning.”
From A systematic literature review of personalized learning terms (2020) · cites this paper as Klašnja-Milićević et al., 2011
Citations
Cites
Adomavičius, G., & Tuzhilin, A. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.99 · Cited by 10,539
Evaluating collaborative filtering recommender systems
Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T. (2004) · ACM Transactions on Information Systems · doi:10.1145/963770.963772 · Cited by 5,798
Amazon.com recommendations: item-to-item collaborative filtering
Linden, G., Smith, B., & York, J. (2003) · IEEE Internet Computing · doi:10.1109/mic.2003.1167344 · Cited by 5,403
Agrawal, R., & Srikant, R. (2002) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.1995.380415 · Cited by 5,150
GroupLens: an open architecture for collaborative filtering of netnews
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., & Riedl, J. (1994) · Proceedings of the 1994 ACM conference on Computer supported cooperative work - CSCW '94 · doi:10.1145/192844.192905 · Cited by 5,058
Learning and Teaching Styles in Engineering Education.
Felder, R. M., & Silverman, L. K. (1988) · Cited by 3,475
LaVan, H., & Carley, C. (1984) · Simulation & Games · doi:10.1177/0037550084152005 · Cited by 3,151
Shardanand, U., & Maes, P. (1995) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/223904.223931 · Cited by 2,821
An Algorithmic Framework for Performing Collaborative Filtering
Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J. (2017) · ACM SIGIR Forum · doi:10.1145/3130348.3130372 · Cited by 2,512
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008) · Psychological Science in the Public Interest · doi:10.1111/j.1539-6053.2009.01038.x · Cited by 2,147
Flagged first, then by citations
2 of the 46 references couldn’t be matched to a known paper.
Research works printed but not linked: 4
- Dunn, 1984, Practical applications of the research: responding to students’ learning styles-step one, Illinois State Research and Development Journal, 21, 1
- Kristofic, A. (2005). Recommender system for adaptive hypermedia Applications. In Proceeding of Informatics and Information Technology Student Research Conference, Bratislava, 229–234.
- Peña, C.I., Marzo, J.L., & de la Rosa, J.L., (2002). Intelligent agents in a teaching and learning environment on the web. In: IEEE International Conference on Advanced Learning Technologies, 21–27.
- Vesin, 2009, Learning management system for programming in java, Sectio Computatorica, 31, 75
Cited by
Sorted by citations
Items 201–300 of 579
Recommender system for Web 2.0 supported eLearning
Dlab, M. H., & Hoić-Božić, N. (2014) · IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon.2014.6826214 · Cited by 17
Vedavathi, N., & Kumar, K. M. A. (2022) · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · doi:10.1142/s0218488522500192 · Cited by 17
Ranking semantic relationships between two entities using personalization in context specification
Viswanathan, V., & Ilango, K. (2012) · Information Sciences · doi:10.1016/j.ins.2012.04.024 · Cited by 17
An elective course suggestion system developed in computer engineering department using fuzzy logic
Adak, M. F., Yumuşak, N., & Taşkın, H. (2016) · International Conference on Industrial Informatics and Computer Systems (CIICS) · doi:10.1109/iccsii.2016.7462394 · Cited by 17
Personalized, Affect and Performance-driven Computer-based Learning
Athanasiadis, C., Hortal, E., Koutsoukos, D., Lens, C. Z., & Asteriadis, S. (2017) · International Conference on Computer Supported Education · doi:10.5220/0006331201320139 · Cited by 17
Education Data-Driven Online Course Optimization Mechanism for College Student
Wang, Z., & Yu, N. (2021) · Mobile Information Systems · doi:10.1155/2021/5545621 · Cited by 17
Educational crowdsourcing to support the learning of computer programming
Al‐Jumeily, D., Hussain, A. J., Alghamdi, M. S., Dobbins, C., & Lunn, J. (2015) · Research and Practice in Technology Enhanced Learning · doi:10.1186/s41039-015-0011-3 · Cited by 17
Smart Learning Environment: Paradigm Shift for Online Learning
Temdee, P. (2020) · IntechOpen eBooks · doi:10.5772/intechopen.85787 · Cited by 17
Martínez-Carrascal, J. A., Muñoz-Gama, J., & Sancho-Vinuesa, T. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3298035 · Cited by 12
A model to create a personalized online course based on the student’s learning styles
Nguyen, H.-H., Trung, K. D., Duc, L. N., Hoang, L. D., Ba, P. T., & Nguyen, V. A. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12287-2 · Cited by 16
Content's Personalized Recommendation for Implementing Ubiquitous Learning in Health 2.0
Neto, F. M. M., da Costa, A. A. L., Sombra, Ê. L., Moreira, J. D. C., Valentim, R. A. D. M., Samper, J. J., do Nascimento, R. P. C., & Flores, C. D. (2014) · IEEE Latin America Transactions · doi:10.1109/tla.2014.7014522 · Cited by 16
Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design
Hoiles, W., & van der Schaar, M. (2016) · International Conference on Machine Learning · Cited by 16
Using Ontology for Providing Content Recommendation Based on Learning Styles inside E-learning
Kusumawardani, S. S., Prakoso, R. S., & Santosa, P. I. (2014) · International Conference on Artificial Intelligence, Modelling and Simulation (AIMS) · doi:10.1109/aims.2014.40 · Cited by 16
MOOC-FRS: A new fusion recommender system for MOOCs
Li, Y., & Li, H. (2017) · IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) · doi:10.1109/iaeac.2017.8054260 · Cited by 16
On the Efficiency of Online Social Learning Networks
Brinton, C. G., Buccapatnam, S., Zheng, L., Cao, D., Lan, A., Wong, F. M. F., Ha, S., Chiang, M., & Poor, H. V. (2018) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2018.2859325 · Cited by 16
A multidimensional ELO model for matching learning objects
Prisco, A., Penna, R., Evandro, Botelho, S. S. D. C., Tonin, N. A., & Bez, J. L. (2018) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2018.8658847 · Cited by 16
Design and implementation of the multi-agent system in education
Hamal, O., Faddouli, N.-E. E., & Harouni, M. H. A. (2021) · World Journal on Educational Technology Current Issues · doi:10.18844/wjet.v13i4.6264 · Cited by 16
E-LEARNING PERSONALIZATION BASED ON COLLABORATIVE FILTERING AND LEARNER’S PREFERENCE
Bourkoukou, O., & Bachari, E. E. (2016) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 16
Abbas, Y., Martinetti, A., Nizamis, K., Spoolder, S., & van Dongen, L. A. M. (2021) · Interactive Learning Environments · doi:10.1080/10494820.2021.1940215 · Cited by 15
Paireekreng, W., & Prexawanprasut, T. (2015) · International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) · doi:10.1109/ecticon.2015.7206951 · Cited by 15
Design and evaluation of planning and mathematical models for generating learning paths
Nigenda, R. S., Maya-Padrón, C., Martínez-Salazar, I., & Torres‐Guerrero, F. (2017) · Computational Intelligence · doi:10.1111/coin.12134 · Cited by 15
Career Goal-based E-Learning Recommendation Using Enhanced Collaborative Filtering and PrefixSpan
Ma, X., & Ye, L. (2018) · International Journal of Mobile and Blended Learning · doi:10.4018/ijmbl.2018070103 · Cited by 15
Designing Personalized Learning Environments — The Role of Learning Analytics
Klašnja‐Milićević, A., Ivanović, M. D., & Stantić, B. (2020) · Vietnam Journal of Computer Science · doi:10.1142/s219688882050013x · Cited by 15
Self-citationA personalized programming exercise recommendation algorithm based on knowledge structure tree
Zheng, W., Du, Q., Fan, Y., Tan, L., Xia, C., & Yang, F. (2021) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-211499 · Cited by 15
Alfaro, L., Rivera, C., Luna-Urquizo, J., Castañeda, E., & Fialho, F. A. P. (2018) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2018.091202 · Cited by 15
Ismail, H., Belkhouche, B., & Harous, S. (2019) · IEEE Access · doi:10.1109/access.2019.2956284 · Cited by 15
Rule-Based Reasoning for Building Learner Model in Programming Tutoring System
Vesin, B., Ivanović, M. D., Klašnja‐Milićević, A., & Budimac, Z. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-25813-8_17 · Cited by 15
Self-citationLeveraging online behaviors for interpretable knowledge-aware patent recommendation
Du, W., Yan, Q., Zhang, W., & Ma, J. (2021) · Internet Research · doi:10.1108/intr-08-2020-0473 · Cited by 16
Evaluation study of eLGuide: A framework for adaptive e‐learning
Zafar, A., & Albidewi, I. (2015) · Computer Applications in Engineering Education · doi:10.1002/cae.21625 · Cited by 14
John, B., Jayakumar, J., Muthukumar, A., & Jeevanandam, P. K. (2016) · The Turkish Online Journal of Educational Technology · Cited by 14
Qehaja, A. B. (2025) · foresight · doi:10.1108/fs-04-2024-0079 · Cited by 29
Design and evaluation of an adaptive framework for virtual learning environments
Alshammari, M. T. (2020) · International Journal of ADVANCED AND APPLIED SCIENCES · doi:10.21833/ijaas.2020.05.006 · Cited by 13
Schöni, L., Carles, V., Strohmeier, M., Mayer, P. B., & Zimmermann, V. (2024) · European Symposium on Usable Security (EuroUSEC) · doi:10.1145/3688459.3688460 · Cited by 13
A New Web-Based Personalized Learning System Improves Student Learning Outcomes
Sancenón, V., Wijaya, K., Wen, X. Y. S., Utama, D. A., Ashworth, M. J., Ng, K. H., Cheong, A., & Neo, Z. (2022) · International Journal of Virtual and Personal Learning Environments · doi:10.4018/ijvple.295306 · Cited by 13
Chrysafiadi, K., Virvou, M. K., & Sakkopoulos, E. (2019) · Intelligent systems reference library · doi:10.1007/978-3-030-13743-4_11 · Cited by 13
Sung, H., Hwang, G., Hung, C., & Huang, I. (2012) · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI) · doi:10.1109/iiai-aai.2012.59 · Cited by 13
Yi, X., Sun, J., & Wu, X. (2024) · Mathematics · doi:10.3390/math12101455 · Cited by 12
Advising Approach to Enhance Students' Performance Level in Higher Education Environments
Mostafa, A. M., Khedr, A. E., & Abdo, A. (2017) · Journal of Computer Science · doi:10.3844/jcssp.2017.130.139 · Cited by 12
Hybrid Filtering Recommendation System in an Educational Context
Baidada, M., Mansouri, K., & Poirier, F. (2021) · International Journal of Web-Based Learning and Teaching Technologies · doi:10.4018/ijwltt.294573 · Cited by 12
Participatory Learner Modelling Design: A methodology for iterative learner models development
Cocea, M., & Magoulas, G. D. (2015) · Information Sciences · doi:10.1016/j.ins.2015.05.032 · Cited by 14
Learning How to Program in C Using Adaptive Hypermedia System
Anthony, P., Joseph, N. E., & Ligadu, C. P. (2013) · International Journal of Information and Education Technology · doi:10.7763/ijiet.2013.v3.254 · Cited by 12
ONTOLOGY-BASED MODEL FOR E-LEARNING MANAGEMENT SYSTEM (O-BMEMS)
Tunde, F., & Sunday, A. O. (2015) · Cited by 12
Online Learning Style Modeling for Course Recommendation
Li, R., Yin, C., Zhang, X., & David, B. T. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-981-10-8944-2_120 · Cited by 12
Alghabban, W. G., & Hendley, R. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60128-7_39 · Cited by 12
An Efficient Data Mining Approach to Concept Map Generation for Adaptive Learning
Huang, X., Yang, K. H., & Lawrence, V. B. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-20910-4_18 · Cited by 12
A Big-Data Oriented Recommendation Method in E-learning Environment
Bourkoukou, O., & Bachari, E. E. (2022) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v17i10.27861 · Cited by 11
Personalized Learning in the Online Learning from 2011 to 2021: A Bibliometric Analysis
Nguyen, H.-H., & Nguyen, V. A. (2023) · International Journal of Information and Education Technology · doi:10.18178/ijiet.2023.13.8.1928 · Cited by 11
August, T., Lo, K., Smith, N. A., & Reinecke, K. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642289 · Cited by 12
Personalized Learning in Science Recommendation System based on Learners’ Preferences
Cheong, N. (2022) · International Conference on Education Development and Studies (ICEDS) · doi:10.1145/3528137.3528161 · Cited by 11
A Systematic Literature Review Enhanced Felder Silverman Learning Style Models (FSLSM)
Supangat, S., & Saringat, M. Z. (2022) · International Conference on Informatics and Computing (ICIC) · doi:10.1109/icic56845.2022.10006958 · Cited by 11
Big Log Analysis for E-Learning Ecosystem
Zheng, Q., He, H., Ma, T., Ni, X., Li, B., & Dong, B. (2014) · IEEE International Conference on e-Business Engineering (ICEBE) · doi:10.1109/icebe.2014.51 · Cited by 11
Valaski, J., Malucelli, A., & Reinehr, S. (2011) · Cited by 11
Using information technology for personalizing the computer science teaching
Prisco, A., dos Santos, R., Botelho, S. S. D. C., Tonin, N. A., & Bez, J. L. (2017) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2017.8190727 · Cited by 11
Alshaigy, B., Kamal, S., Mitchell, F., Martin, C. E., & Aldea, A. (2015) · Workshop in Primary and Secondary Computing Education · doi:10.1145/2818314.2818319 · Cited by 11
James, L. A. (2014) · Figshare · doi:10.71889/5fylantbak.29860067 · Cited by 11
A Parallel Education Based Intelligent Tutoring Systems Framework
Jing, S., Tang, Y. G., Liu, X., Gong, X., Cui, W., & Liang, J. (2020) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc48988.2020.9238052 · Cited by 10
An adaptive e-learning framework
Faisal, M. H., AlAmeeri, A. W., & Alsumait, A. A. (2015) · International Conference on Information Integration and Web-based Applications & Services (iiWAS) · doi:10.1145/2837185.2837249 · Cited by 10
FUSE: A Fuzzy-Semantic Framework for Personalizing Learning Recommendations
Nguyễn, Đ. H., Arch‐int, N., & Arch‐int, S. (2018) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622018500220 · Cited by 10
Qodad, A., Benyoussef, A., Kenz, A. E., & Yadari, M. E. (2020) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v15i08.10574 · Cited by 10
Bachiri, Y.-A., & Mouncif, H. (2022) · Lecture notes in business information processing · doi:10.1007/978-3-031-06458-6_11 · Cited by 10
Oscar: An Intelligent Adaptive Conversational Agent Tutoring System
Latham, A., Crockett, K., McLean, D., & Edmonds, B. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-22000-5_58 · Cited by 10
Students' Satisfaction in Learning Style-Based Adaptation
Alshammari, M. T., Anane, R., & Hendley, R. (2015) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2015.56 · Cited by 10
Finding relevant semantic association paths using semantic ant colony optimization algorithm
Viswanathan, V., & Krishnamurthi, I. (2014) · Soft Computing · doi:10.1007/s00500-014-1247-3 · Cited by 10
dos Santos, H. L., Cechinel, C., Araújo, R., & Sicilia, M. (2015) · Communications in computer and information science · doi:10.1007/978-3-319-24129-6_16 · Cited by 10
Intelligent Personal Assistant for Educational Material Recommendation Based on CBR
Méndez, N. D. D., Marín, P. A. R., & Carranza, D. A. O. (2017) · Intelligent systems reference library · doi:10.1007/978-3-319-62530-0_7 · Cited by 10
The Integrated Environment for Learning Objects Design and Storing in Semantic Web
Dagienė, V., Gudonienė, D., & Bartkutė, R. (2018) · International Journal of Computers Communications & Control · doi:10.15837/ijccc.2018.1.3074 · Cited by 10
A Novel Algorithm for Dynamic Student Profile Adaptation Based on Learning Styles
Nafea, S. M., Siewe, F., & He, Y. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-29516-5_4 · Cited by 14
Interleaved Design for E-Learning: Theory, Design, and Empirical Findings
Li, A. T., De, L., Xu, S. X., & Cheng, Y. (2024) · MIS Quarterly · doi:10.25300/misq/2023/17206 · Cited by 14
A Comparative Study on Various Vocabulary Knowledge Scales for Predicting Vocabulary Pre-Knowledge
Zou, D., Xie, H., Rao, Y., Wong, T.-L., Wang, F. L., & Wu, Q. (2016) · International Journal of Distance Education Technologies · doi:10.4018/ijdet.2017010105 · Cited by 9
Attribute-based recommender system for learning resource by learner preference tree
Salehi, M., & Kmalabadi, I. N. (2012) · International Conference on Computer and Knowledge Engineering · doi:10.1109/iccke.2012.6395366 · Cited by 9
A Framework for Collaborative Multi-Institution MOOC Environment
Azhan, M. H. B. N., Saman, M. Y. M., & Man, M. B. (2016) · International Conference on Internet of Things, Data and Cloud Computing (ICC) · doi:10.1145/2896387.2896421 · Cited by 9
Learning and Performance Support - Personalization Through Personal Assistant Technology
Lapointe, J., Molyneaux, H., Kondratova, I., & Viejo, A. F. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-39483-1_21 · Cited by 9
Integration of Eye Tracking Technologies and Methods in an E-learning System
Ivanović, M. D., Klašnja‐Milićević, A., Ivković, J., & Porta, M. (2017) · Balkan Conference in Informatics · doi:10.1145/3136273.3136278 · Cited by 9
Self-citationAl-Abri, A. B., Al-Khanjari, Z. A. S., Jamoussi, Y., & Kraïem, N. (2018) · doi:10.1109/csit.2018.8486169 · Cited by 9
DEMİR, Ü. (2019) · Pedagogies An International Journal · doi:10.1080/1554480x.2019.1706522 · Cited by 9
Research on Online Learning Resource Recommendation Method Based on Wide & Deep and Elmo Model
Liu, J., Zhang, H., & Liu, Z. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1437/1/012015 · Cited by 9
Yang, C. C. Y., Chen, I. Y. L., Akçapınar, G., Flanagan, B., & Ogata, H. (2021) · Institutional Repositories DataBase (IRDB) · Cited by 9
Sabine Graf, A., Chang, T., Kersebaum, A., Rath, T., & Kurcz, J. (2014) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2014.41 · Cited by 9
Semantic Web Technologies for e-Learning: Models and Implementation
Dagienė, V., Gudonienė, D., & Burbaitė, R. (2015) · Informatica · doi:10.15388/informatica.2015.46 · Cited by 9
Comparison of E-Learning Personalization Systems: Protus and PLeMSys
Blazheska-Tabakovska, N., Ivanović, M. D., Klašnja‐Milićević, A., & Ivković, J. (2017) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v12i01.6085 · Cited by 9
Self-citationOntology-based learner modelling for supporting personalised e-Learning
Yarandi, M., Tawil, A. H., Jahankhani, H., & Hosseini, S. A. (2012) · International Conference on Interactive Mobile Communication, Technologies and Learning · doi:10.1109/imcl.2012.6396461 · Cited by 9
Alhalalmeh, Z. R., Fouda, Y. M., Rushdi, M. A., & El-Mikkawy, M. E. A. (2023) · Sustainability · doi:10.3390/su151914234 · Cited by 8
Personalized Learning Resource Recommendation Based on Course Ontology and Cognitive Ability
Diao, X., Zeng, Q., Duan, H., Song, Z., & Zhou, C. (2021) · Cited by 8
Knowledge-based Recommender System of Conceptual Learning in Science
Cheong, N. (2021) · International Conference on Education and E-Learning (ICEEL) · doi:10.1145/3502434.3502443 · Cited by 8
Classification-Based Approach to Concept Map Generation in Adaptive Learning
Huang, X., Yang, K. H., & Lawrence, V. B. (2015) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2015.149 · Cited by 8
Adaptive Recommendations to Students Based on Working Memory Capacity
Chang, T., Kurcz, J., El-Bishouty, M. M., Sabine Graf, A., & Kinshuk (2014) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2014.27 · Cited by 8
Towards Reading Session-Based Indicators in Educational Reading Analytics
Sadallah, M., Encelle, B., Maredj, A.-E., & Prié, Y. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24258-3_22 · Cited by 8
Método Híbrido de Recomendación Adaptativa de Objetos de Aprendizaje basado en Perfiles de Usuario
Marín, P. A. R., Duque, N., & Ovalle, D. A. (2016) · Formación universitaria · doi:10.4067/s0718-50062016000400010 · Cited by 8
Experiences in using educational recommender system ELARS to support e-learning
Dlab, M. H. (2017) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.23919/mipro.2017.7973508 · Cited by 8
Case-based Reasoning Intelligent Tutoring System
Masood, M., & Mokmin, N. A. M. (2017) · International Conference Big Data Research · doi:10.1145/3152723.3152735 · Cited by 8
Coma-Roselló, T., Aguelo, A., Álvarez, P., Sanz, C. V., & Baldassarri, S. (2018) · IEEE Revista Iberoamericana de Tecnologias del Aprendizaje · doi:10.1109/rita.2018.2879388 · Cited by 8
A process perspective on research and design issues in educational personalization
Beese, E. B. (2019) · Theory and Research in Education · doi:10.1177/1477878519893963 · Cited by 8
Machine Learning Based Improved Recommendation Model for E-learning
Ezaldeen, H., Misra, R., Alatrash, R., & Priyadarshini, R. (2019) · International Conference on Intelligent Computing and Remote Sensing (ICICRS) · doi:10.1109/icicrs46726.2019.9555866 · Cited by 8
Cooperative Learning on The Academic Achievement of Middle-School Students Based on Learning Style
Arifin, K. (2022) · ETDC Indonesian Journal of Research and Educational Review · doi:10.51574/ijrer.v1i2.175 · Cited by 8
Nganji, J. T., & Brayshaw, M. (2015) · International Journal of Information Retrieval Research · doi:10.4018/ijirr.2015070105 · Cited by 8
Rollande, R., & Grundspeņķis, J. (2012) · International Conference on Digital Information Processing and Communications · doi:10.1109/icdipc.2012.6257276 · Cited by 8
Automating the E-learning Personalization
Essalmi, F., Ayed, L. J. B., Jemni, M., Kinshuk, K., & Sabine Graf, A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39146-0_32 · Cited by 8
Using learning styles as a basis for creating adaptive open learning environments: an evaluation
Fasihuddin, H., Skinner, G., & Athauda, R. (2016) · International Journal of Learning Technology · doi:10.1504/ijlt.2016.079034 · Cited by 8
Cheng, L., Chu, H., & Shiue, B.-M. (2015) · International Journal of Distance Education Technologies · doi:10.4018/ijdet.2015100103 · Cited by 8
A Prevalence Trend of Characteristics of Intelligent and Adaptive Hypermedia E-Learning Systems
Marković, M. G., Jakupović, A., & Kovačić, B. (2014) · AEE Journal · Cited by 8
Metadata
- Authors
- Klašnja-Milićević, A., Vesin, B., Ivanović, M., & Budimac, Z.
- Affiliations
- University of Novi Sad (RS)
- Corresponding author
- Vesin, Boban
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 56
- Issue
- 3
- Pages
- 885-899
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W1994510396
- Cited by
- 580
- References
- 46
- Citations by year
- 2026: 11 · 2025: 23 · 2024: 25 · 2023: 27 · 2022: 41 · 2021: 47 · 2020: 53 · 2019: 56 · 2018: 41 · 2017: 50 · 2016: 52 · 2015: 54 · 2014: 37 · 2013: 29 · 2012: 19
- FWCI
- 56.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- personalized e-learning, learning style identification, hybrid recommendation, frequent sequence mining, learner preferences
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review