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Bayesian Student Modeling in the AC&NL Tutor (CROSBI ID 695478)

Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija

Šarić-Grgić, Ines ; Grubišić, Ani ; Žitko, Branko ; Stankov, Slavomir ; Gašpar, Angelina ; Tomaš, Suzana ; Vasić, Daniel Bayesian Student Modeling in the AC&NL Tutor // Lecture notes in computer science / Sottilare, Robert A. ; Schwarz, Jessica (ur.). 2020. str. 245-257 doi: 10.1007/978-3-030-50788-6_18

Podaci o odgovornosti

Šarić-Grgić, Ines ; Grubišić, Ani ; Žitko, Branko ; Stankov, Slavomir ; Gašpar, Angelina ; Tomaš, Suzana ; Vasić, Daniel

engleski

Bayesian Student Modeling in the AC&NL Tutor

The reasoning process about the level of student’s knowledge can be challenging even for experienced human tutors. The Bayesian networks are a formalism for reasoning under uncertainty, which has been successfully used for various artificial intelligence applications, including student modeling. While Bayesian networks are a highly flexible graphical and probabilistic modeling framework, its main challenges are related to the structural design and the definition of “a priori” and conditional probabilities. Since the AC&NL Tutor’s authoring tool automatically generates tutoring elements of different linguistic complexity, the generated sentences and questions fall into three difficulty levels. Based on these levels, the probability- based Bayesian student model is proposed for mastery-based learning in intelligent tutoring system. The Bayesian network structure is defined by generated questions related to the node representing knowledge in a sentence. Also, there are relations between inverse questions at the same difficulty level. After the structure is defined, the process of assigning “a priori” and conditional probabilities is automated using several heuristic expert-based rules.

Intelligent tutoring systems ; Student modeling, Bayesian networks

Book Series: Lecture Notes in Computer Science, Volume: 12214

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Podaci o prilogu

245-257.

2020.

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objavljeno

10.1007/978-3-030-50788-6_18

Podaci o matičnoj publikaciji

Lecture notes in computer science

Sottilare, Robert A. ; Schwarz, Jessica

Cham: Springer

978-3-030-50787-9

0302-9743

1611-3349

Podaci o skupu

2nd Adaptive Instructional Systems (AIS 2020) ; 22nd International Conference on Human-Computer Interaction (HCII 2020)

predavanje

19.07.2020-24.07.2020

Kopenhagen, Danska

Povezanost rada

Računarstvo

Poveznice
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