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ERIC Number: EJ1140553
Record Type: Journal
Publication Date: 2017-May
Pages: 21
Abstractor: As Provided
ISSN: ISSN-1360-2357
Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization
Rastegarmoghadam, Mahin; Ziarati, Koorush
Education and Information Technologies, v22 n3 p1067-1087 May 2017
Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is personalized based on learning and solving problem styles. The purposed algorithm, based on ACO, generates the adaptive optimal learning path. The algorithm describes an architecture which supports the recording, processing and presentation of collective learner behavior designed to create a feedback loop informing learners of successful paths towards the attainment of learning goals. The algorithm parameters are tuned dynamically to conform to the actual pedagogical process. The article includes the results of implementation and experiment represent this algorithm is able to provide its main purpose which is finding optimal learning paths based on learning styles and improved performance of previous adaptive tutoring systems.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Myers Briggs Type Indicator
Grant or Contract Numbers: N/A