Intelligent Tutoring System Using Bayesian Network for Vocational High Schools in Indonesia

Muhammad Ikhwan Burhan; Eko Sediyono; Kusworo Adi

doi:10.1051/e3sconf/202131705027

All issues

Volume 317 (2021)

E3S Web Conf., 317 (2021) 05027

References

Open Access

Issue		E3S Web Conf. Volume 317, 2021 The 6^th International Conference on Energy, Environment, Epidemiology, and Information System (ICENIS 2021)


Article Number		05027
Number of page(s)		10
Section		Information System Management and Environment
DOI		https://doi.org/10.1051/e3sconf/202131705027
Published online		05 November 2021

Direktorat Jenderal Pendidikan Dasar dan Menengah (Ditjen Dikdasmen), Grand Design Pengembangan Teaching Factory dan Technopark di SMK (Ditjen Dikdasmen, Jakarta, 2016) [Google Scholar]
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N.W.A. Majid, T. Ridwan,, A. Fauzi, R. Hikmawan, Integrating of E-learning to Improve Students Competence in Vocational School, in proc. of Int. Conf. on Technical and Vocational Education and Training, ICTVET, Feb. 2019, Bandung, Indonesia(2019) [Google Scholar]
A. Keleş, R. Ocak, A. Keleş, A. Gülcü, ZOSMAT: Web-based Intelligent Tutoring System for Teaching–Learning Process, Expert Systems with Applications, 36, 1229-1239 (2009) [Google Scholar]
A. Ramírez-Noriega, R. Juárez-Ramírez, Y. Martínez-Ramírez, Evaluation module based on Bayesian Networks to Intelligent Tutoring Systems, Int. J. of Information Management, 37, 1488-1498 (2017) [Google Scholar]
J.A. Kulik, J.D. Fletcher, Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic Review, Review of Educational Research, 86, 42–78 (2016) [Google Scholar]
J. Han, W. Zhao, Q. Jiang, M. Oubibi, X. Hu, Intelligent Tutoring System Trends 2006–2018: A Literature Review, in Proceedings of 8th Int. Conf. on Educational Innovation through Technology, EITT, 27–31 Oct. 2019, Mississippi, USA (2019) [Google Scholar]
Y. He, S.C. Hui, T.T. Quan, Automatic Summary Assessment for Intelligent Tutoring Systems, Computers & Education, 53, 890-899, (2009) [Google Scholar]
K. VanLehn, The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems, Educational Psychologist, 46, 197–221, (2011) [Google Scholar]
K. Kularbphettong, P. Kedsiribut, P. Roonrakwit, Developing an Adaptive Web-based Intelligent Tutoring System Using Mastery Learning Technique, Procedia - Social and Behavioral Sciences, 191, 686-691 (2015) [Google Scholar]
A. Karaci, H.I. Akyuz, G. Bilgici, Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention, Int. J. of Computer Applications, 181, 36-41 (2018) [Google Scholar]
S.D. de Carvalho, F.R. de Melo, E.L. Flôres, S.R. Pires, L.F.B. Loja, Intelligent tutoring system using expert knowledge and Kohonen maps with automated training, Neural Comput. & Appl, 32, 13577–13589 (2020) [Google Scholar]
A. Gelman, J.B. Carlin, H.S. Stern, D.B. Dunson, A. Vehtari, D.B. Rubin, Bayesian data analysis: third edition (CRC Press Taylor & Francis Group, Florida, 2013) [Google Scholar]
B.G. Marcot, T.D. Penman, Advances in Bayesian network modelling: Integration of modelling technologies, Environmental Modelling & Software, 111, 386-393 (2019) [Google Scholar]
M.A. Javidian, Z. Wang, L. Lu, M. Valtorta, On a hypergraph probabilistic graphical model, Annals of Mathematics and Artificial Intelligence, 88, 1003–1033 (2020) [Google Scholar]
L. Huang, G. Cai, H. Yuan, J. Chen, A hybrid approach for identifying the structure of a Bayesian network model, Expert Systems with Applications, 131, 308-320 (2019) [Google Scholar]
B.G. Marcot, A.M. Hanea, What is an optimal value of k in k-fold cross-validation in discrete Bayesian network analysis?, Computational Statistics, 1-23 (2020) [Google Scholar]
J. Xu, Y. Zhang, D. Miao, Three-way confusion matrix for classification: A measure driven view, Information Sciences, 507, 772-794 (2020) [Google Scholar]
R.R. Hake, Interactive engagement vs traditional methods: six-thousand student survey of mechanics test data for introductory physics courses, American Journal of Physics, 66, 64–74 (1998) [Google Scholar]

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[1] Direktorat Jenderal Pendidikan Dasar dan Menengah (Ditjen Dikdasmen), Grand Design Pengembangan Teaching Factory dan Technopark di SMK (Ditjen Dikdasmen, Jakarta, 2016) [Google Scholar]

[2] Baharuddin, J. Dalle, Interactive courseware for supporting learners competency in practical skills, Turkish Online J. of Edu.Tech, 16, 88-99, (2017) [Google Scholar]

[3] N.W.A. Majid, T. Ridwan,, A. Fauzi, R. Hikmawan, Integrating of E-learning to Improve Students Competence in Vocational School, in proc. of Int. Conf. on Technical and Vocational Education and Training, ICTVET, Feb. 2019, Bandung, Indonesia(2019) [Google Scholar]

[4] A. Keleş, R. Ocak, A. Keleş, A. Gülcü, ZOSMAT: Web-based Intelligent Tutoring System for Teaching–Learning Process, Expert Systems with Applications, 36, 1229-1239 (2009) [Google Scholar]

[5] A. Ramírez-Noriega, R. Juárez-Ramírez, Y. Martínez-Ramírez, Evaluation module based on Bayesian Networks to Intelligent Tutoring Systems, Int. J. of Information Management, 37, 1488-1498 (2017) [Google Scholar]

[6] J.A. Kulik, J.D. Fletcher, Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic Review, Review of Educational Research, 86, 42–78 (2016) [Google Scholar]

[7] J. Han, W. Zhao, Q. Jiang, M. Oubibi, X. Hu, Intelligent Tutoring System Trends 2006–2018: A Literature Review, in Proceedings of 8th Int. Conf. on Educational Innovation through Technology, EITT, 27–31 Oct. 2019, Mississippi, USA (2019) [Google Scholar]

[8] Y. He, S.C. Hui, T.T. Quan, Automatic Summary Assessment for Intelligent Tutoring Systems, Computers & Education, 53, 890-899, (2009) [Google Scholar]

[9] K. VanLehn, The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems, Educational Psychologist, 46, 197–221, (2011) [Google Scholar]

[10] K. Kularbphettong, P. Kedsiribut, P. Roonrakwit, Developing an Adaptive Web-based Intelligent Tutoring System Using Mastery Learning Technique, Procedia - Social and Behavioral Sciences, 191, 686-691 (2015) [Google Scholar]

[11] A. Karaci, H.I. Akyuz, G. Bilgici, Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention, Int. J. of Computer Applications, 181, 36-41 (2018) [Google Scholar]

[12] S.D. de Carvalho, F.R. de Melo, E.L. Flôres, S.R. Pires, L.F.B. Loja, Intelligent tutoring system using expert knowledge and Kohonen maps with automated training, Neural Comput. & Appl, 32, 13577–13589 (2020) [Google Scholar]

[13] A. Gelman, J.B. Carlin, H.S. Stern, D.B. Dunson, A. Vehtari, D.B. Rubin, Bayesian data analysis: third edition (CRC Press Taylor & Francis Group, Florida, 2013) [Google Scholar]

[14] B.G. Marcot, T.D. Penman, Advances in Bayesian network modelling: Integration of modelling technologies, Environmental Modelling & Software, 111, 386-393 (2019) [Google Scholar]

[15] M.A. Javidian, Z. Wang, L. Lu, M. Valtorta, On a hypergraph probabilistic graphical model, Annals of Mathematics and Artificial Intelligence, 88, 1003–1033 (2020) [Google Scholar]

[16] L. Huang, G. Cai, H. Yuan, J. Chen, A hybrid approach for identifying the structure of a Bayesian network model, Expert Systems with Applications, 131, 308-320 (2019) [Google Scholar]

[17] B.G. Marcot, A.M. Hanea, What is an optimal value of k in k-fold cross-validation in discrete Bayesian network analysis?, Computational Statistics, 1-23 (2020) [Google Scholar]

[18] J. Xu, Y. Zhang, D. Miao, Three-way confusion matrix for classification: A measure driven view, Information Sciences, 507, 772-794 (2020) [Google Scholar]

[19] R.R. Hake, Interactive engagement vs traditional methods: six-thousand student survey of mechanics test data for introductory physics courses, American Journal of Physics, 66, 64–74 (1998) [Google Scholar]