Constructing a Bayesian belief network to generate learning path in adaptive hypermedia system.

Abstract

There are many methods and techniques which have been promoted to develop adaptive hypermedia systems [1]. Our model approach [2], generating adaptive courses based on learner's profile which learner's includes background, skills, style...etc. One of important steps in our model is to generate learning path adaptive for each learner. In this paper, we promote an algorithm based on shortest path search algorithm to evaluate learning object (LO) based on its attributes [3] and constructed a Bayesian Belief Network (BBN) to generate learning path for each learner. Tóm tȃt. Nhiề u phu . o . ng pháp cũng nhu . kỹ thuâ . t du . o . . c dề xuất dê ' phát triê ' n các hê . thống ho . c thích nghi. Mô hình cu 'a chúng tôi phát triê ' n nhȃ ' m ta . o ra các khóa ho . c thích nghi du . . a trên các thông tin về ngu .ò. i ho . c nhu . kiến thú . c, kỹ nȃng, so . ' thích v..v. Mô . t trong nhũ . ng bu .ó. c quan tro . ng cu 'a mô hình là ta . o ra các tiến trình ho . c thích nghi cho tù . ng ngu .ò. i ho . c. Bài báo này chúng tôi trình bày thuâ . t toán du . . a trên thuâ . t toán tìm du .ò. ng di ngȃn nhất dê ' lu . . a cho . n các dối tu . o . . ng ho . c du . . a vào thuô . c tính cu 'a chúng và xây du . . ng ma . ng xác suất Bayesian Belief dê ' ta . o ra các tiến trình ho . c phù ho . . p vó . i nhu cầ u ngu .ò. i ho . c.

Learning content design and learner adaptation for adaptive e-learning environment: a survey

“…The statistical approach Bayesian probability theory is used for finding the adaptive learning path (individual sequencing) (Anh et al 2008). Here firstly a node probability table (prior) based on Bayesian probability theory is created.…”

Automated Adaptive Mobile Learning System using Shortest Path Algorithm and Learning Style

“…A directed graph represents an accurate picture of course descriptions for online courses through computer-based implementation of various educational systems [12]. E-learning and m-learning systems are modeled as a weighted directed graph where each node represents a course unit [13].…”

A Heuristic Method for Learning Path Sequencing for Intelligent Tutoring System (ITS) in E-learning

“…Nguyen Viet (2008) assigned the weight directly to the courseware (learning object) Norsham et al (2009) have used three weights (1.0, 0.5,0) to the concepts respectively, depending upon the concept if it is very significant and described particularly, slightly described or if the concept is not relevant. The Self organizing map is used to cluster the collection of learning object based on concept similarity.…”

“…Instead of forcing an instructor designer to manually define the set of selection rules, an artificial intelligence (AI) technique has been widely used in E-leaning systems to find the adaptive course sequencing. A Bayesian belief network has been constructed to generate the course sequencing based on learner's profile and courseware difficulty level (Nguyen Viet, 2008). Artificial Neural Network method has been used to discover the connection between the domain concepts contained in the learning object and the learner's learning need by identifying a group of similar learning objects to select the suitable group for a particular student (Norsham et al, 2009).The concept relation matrix between the course-wares has been developed with help of TF-IDF (Term frequency-inverse document frequency), in which matrix values are used for fitness function in genetic Algorithm to construct an optimal learning path for each learner (Huang, Huang, & Chen, 2007).…”