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2004 International Journal of Uncertainty Fuzziness and Knowledge-Based Systems  
In this paper we discuss applications of Bayesian networks to educational testing. Namely, we deal with the diagnosis of person's skills.  ...  The experiments suggest that the test design can benefit from a Bayesian network that models relations between skills, not only in the case of an adaptive test but also when designing a fixed (nonadaptive  ...  There are theoretical problems related to the application of Bayesian networks to educational testing that were not studied in this paper.  ... 
doi:10.1142/s021848850400259x fatcat:qabh5xg35vhebnlqvai6h7tsl4

Using SVM to Combine Bayesian Networks for Educational Test Data Classification

Yen-Chun Tseng, Chih-Wei Yang, Bor-Chen Kuo
2016 International Journal of Innovative Computing, Information and Control  
There are five test data, and each has five different Bayesian networks designed by experts.  ...  The goal of this paper is trying to develop fusion methods for combining multiple Bayesian networks for modeling students' learning bugs and skills.  ...  ∆ 2 ), . . . , ψ(∆ m )] T , ψ(∆ i ) ∈ {0, 1} Sub = P (x|BN i ) ≥ ε (9) In the experiment of [14] , three Bayesian networks were generated based on one educational test data.  ... 
doi:10.24507/ijicic.12.05.1679 fatcat:vr52gapmonebzda4fsh5qd3xie

Bayesian Approach to Analyze Reading Comprehension: A Case Study in Elementary School Children in Mexico

Ernesto U. Rodriguez-Barrios, Roberto Angel Melendez-Armenta, Sandra G. Garcia-Aburto, Marieli Lavoignet-Ruiz, Luis Carlos Sandoval-Herazo, Antonio Molina-Navarro, Luis Alberto Morales-Rosales
2021 Sustainability  
The Bayesian network model allows for the determination of the language and communication level of achievement based on parameters such as learning style, learning pace, speed, and reading comprehension  ...  Hence, this article shows the usefulness of employing Bayesian techniques in the analysis of reading comprehension at elementary school.  ...  Since Bayesian networks have appeared, researchers have integrated them in modeling in the education domain to measure the technical and cognitive performance of a student.  ... 
doi:10.3390/su13084285 fatcat:2cvx6nde7zhdlbqgtziv2jzy2a

Development of an Intelligent Tutoring System Using Bayesian Networks and Fuzzy Logic for a Higher Student Academic Performance

Meltem Eryılmaz, Afaf Adabashi
2020 Applied Sciences  
the Bayesian network technique to adaptively support students in learning environments.  ...  In order to evaluate whether the academic performance of the students in different learning groups differs or not, analysis of covariance (ANCOVA) was used based on the students' pre-test and post-test  ...  the topic nodes in the Bayesian network.  ... 
doi:10.3390/app10196638 fatcat:uap47ywagzbmja5hgn4laff6ga

Predict Student Scores Using Bayesian Networks

Rafe Torabi, Parham Moradi, Ali Reza Khantaimoori
2012 Procedia - Social and Behavioral Sciences  
One can propose a model for predicting the student course scores based of the student's educational history. In this paper we propose a Bayesian Network model for prediction of student scores.  ...  We have tested our proposed model on 500 different students which has been studied in various Information technology university levels.  ...  Discrete process in Bayesian networks A simple bayesian network can be applied only on discrete data.  ... 
doi:10.1016/j.sbspro.2012.06.280 fatcat:foui5bgatba2bltk267umbluly

The initialization of the learner model combining the Bayesian networks and the stereotypes methods

Mouenis Anouar Tadlaoui, Rommel Novaes Carvalho, Mohamed Khaldi
2017 International Journal of Advanced Computer Research  
The structure of this paper consists of combining Bayesian networks with stereotypes method to initialize the learner model in adaptive hypermedia educational systems (AHES).  ...  Finally, and in order to disclose the validity of our hypothesis; we will present the experiments and the tests carried out.  ...  Figure 3 shows the Bayesian network of initial tests for the initialization of the learner model in an educational hypermedia system.  ... 
doi:10.19101/ijacr.2017.733024 fatcat:napfo7vv2zgqzky7vn4vgazaym

Research on Moral Education Function of Music Art in College Students Based on Bayesian Learning Algorithm

Meng Lu, Du Pengcheng, Song Yanfeng, Muhammad Arif
2022 Security and Communication Networks  
Bayesian network is a probabilistic graphical model that was developed in the 1980s. Therefore, it is urgent to establish the correct outlook on life and values of the motherland in the future.  ...  Based on Bayesian learning algorithm, this paper studies the moral education function of music art in college students.  ...  in the classroom. e Asia Network, CarTrouble-Shooter network, and Bayesian network in the Bayesian network standard test set are utilised in the simulation experiment to validate the algorithm's efficacy  ... 
doi:10.1155/2022/1809364 fatcat:vgdhaqxh3zdiflpugjvsmzcyza

R. G. Almond, R. J. Mislevy, L. Steinberg, D. Yan, and D. M. Williamson: Bayesian Networks in Educational Assessment

Fengfeng Ke
2016 Technology, Knowledge and Learning  
All authors are experts of educational assessment and well published in the fields of cognitive science, data mining, school and learning improvement.  ...  The book by Almond and his colleagues helps to address the aforementioned issues by explaining the potential of using graphical models, Bayesian network models in particular, to accumulate observed evidence  ...  It should be noted the book has tried to cater to varied needs and prior knowledge levels of potential users of Bayesian network in educational assessment.  ... 
doi:10.1007/s10758-016-9292-x fatcat:ressh6jxnbftxbnxc7jhdsy4r4

Student-at-risk detection by current learning performance indicators using Bayesian networks [article]

T. A. Kustitskaya, A. A. Kytmanov, M. V. Noskov
2020 arXiv   pre-print
We propose a concept for building a predictive model based on Bayesian networks for an academic course or module taught in a blended learning format.  ...  Our empirical studies confirm that the proposed approach is perspective for the development of an early warning system for various stakeholders of the educational process.  ...  The general design of a Bayesian network and a classifier, based on this network is presented in Section 3.  ... 
arXiv:2004.09774v1 fatcat:36dn7tjgxba3tdjfbv2m2wdr2a

Analysis of Students' Performance by Using Different Data Mining Classifiers

Hilal Almarabeh
2017 International Journal of Modern Education and Computer Science  
Data mining is becoming a very important field in educational sectors and it holds great potential for the schools and universities.  ...  The results shows that Bayesian Network classifier has the highest accuracy among the other classifiers.  ...  These metrics shows that Bayesian Network classifier performs better than other classifiers. IX.CONCLUSION Data mining has a significant importance in educational institutions.  ... 
doi:10.5815/ijmecs.2017.08.02 fatcat:n2wu322xbjed3pkkq2cyslxps4

An Automatic Optimal Course Recommendation Method for Online Math Education Platforms Based on Bayesian Model

Yongyan Fan, Jing Zhang, Dingli Zu, Hongyu Zhang
2021 International Journal of Emerging Technologies in Learning (iJET)  
To solve this problem, this paper designs an automatic recommendation method of optimal courses for online math education platforms based on Bayesian model.  ...  Online education platforms inject new vitality into the field of education, and greatly improves the accessibility to high-quality education resources.  ...  All nodes in the Bayesian inference network require a given condition probability table, since the nodes in the Bayesian network are divided into root nodes and non-root nodes, for nodes without a root  ... 
doi:10.3991/ijet.v16i13.24039 fatcat:io3i7zizavcp7exeszi5emuzey

A Traveling Salesman Learns Bayesian Networks [article]

Tuhin Sahai, Stefan Klus, Michael Dellnitz
2012 arXiv   pre-print
Structure learning of Bayesian networks is an important problem that arises in numerous machine learning applications.  ...  In this work, we present a novel approach for learning the structure of Bayesian networks using the solution of an appropriately constructed traveling salesman problem.  ...  To quantitatively test the prediction of the resulting Bayesian network we check the prediction of P (Salary|Education, Marital Status).  ... 
arXiv:1211.4888v1 fatcat:ew76dxgo6zc6zim4m7rzbgu3jq

Page 239 of Educational and Psychological Measurement Vol. 67, Issue 2 [page]

2007 Educational and Psychological Measurement  
Keywords: Bayesian network; Bayesian residual; DIC; item fit; Markov chain Monte Carlo Mas’ (1994) called for closer ties between cognitive science and measure- ment, producing a new class of psychometric  ...  This article suggests a number of graphics and statistics for diagnosing problems with cognitive diagnostic models expressed as Bayesian networks.  ... 

An Implementation of Parallel Bayesian Network Learning

Joseph S. Haddad, Timothy W. O'Neil, Anthony Deeter, Zhong-Hui Duan
2017 The Journal of Computational Science Education  
Bayesian networks may be utilized to infer genetic relations among genes. This has proven useful in providing information about how gene interactions influence life.  ...  The OpenMP and MPI accelerations are implemented in a single library and can be switched on or off. These accelerations are for computing multiple Bayesian networks simultaneously.  ...  Tests were run on dedicated machines utilizing 16 processors and computing 60 Bayesian networks per gene (600 total).  ... 
doi:10.22369/issn.2153-4136/8/2/4 fatcat:zumovcusrnf6pbyprpdlxprzgq

Decade review (1999-2009): progress of application of artificial intelligence tools in student diagnosis

Athanasios S. Drigas, Katerina Argyri, John Vrettaros
2009 International Journal of Social and Humanistic Computing  
This paper attempts to explore the research that has been conducted on the application of the most typical and popular soft computing techniques [fuzzy logic, neural networks, Bayesian networks, genetic  ...  programming and hybrid approaches such as neurofuzzy systems and genetic programming neural networks (GPNNs)] in student modelling over the decade 1999-2009.  ...  Vomlel (2003) gave an accurate description of how a Bayesian network model used in an adaptive test can be built.  ... 
doi:10.1504/ijshc.2009.031006 fatcat:wbrv7rsi2bgyhox2w7bdperda4
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