A novel adaptive learning path method
Abstract
Finding an appropriate learning path and content is an important issue to achieve learning goal especially in e-learning systems. The main challenge of these systems is providing courses suitable to different learners with different knowledge background. Such systems should be efficient and adaptive. Furthermore, an optimal adaptive learning path can help the learners in reducing the cognitive overload and disorientation. In this paper, a novel two stages adaptive learning path algorithm, which is called ACO-Map is proposed. Discovering groups of learners according to their knowledge patterns is performed in first stage. Then in second stage ant colony optimization as a metaheuristic method is applied to find learning path based on Ausubel Meaningful Learning Theory. The output of this algorithm is a concept map for each group of learners according to their needs.
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In [27], ant colony optimization was used to optimize learning paths for groups of students based on their knowledge patterns.
“The ACO algorithm is used to optimize learning paths for different groups of students.The first stage involves grouping learners based on their knowledge patterns.The second stage then uses the ACO algorithm to determine the best learning path for each of these groups, with the end goal being a concept map tailored to the needs of each group.”
From Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review (2023) · cites this paper as [27]
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Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review
Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023) · Education Sciences · doi:10.3390/educsci13121216 · Cited by 980 · see citing works
Gonaygunta, H., Nadella, G. S., Pramod Pawar, P., & Kumar, D. (2024) · 2024 Systems and Information Engineering Design Symposium (SIEDS) · doi:10.1109/sieds61124.2024.10534661 · Cited by 39 · see citing works
- Authors
- Ahmad, K., Maryam, B. I., & Molood, A. E.
- Affiliations
- Amirkabir University of Technology (IR)
- Venue
- 4th International Conference on e-Learning and e-Teaching (ICELET 2013)
- Publisher
- IEEE
- Published
- 2013-02
- Pages
- 20-25
- OpenAlex
- W2046785027
- Cited by
- 15
- References
- 11
- Citations by year
- 2026: 1 · 2024: 2 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 2 · 2018: 1 · 2017: 1 · 2016: 1
- FWCI
- 0.22
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International and National Conference on E-Learning and E-Teaching (ICeLeT) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- adaptive learning paths, online learning, ant colony optimization, concept maps, student grouping, knowledge patterns, cognitive overload, metaheuristic optimization
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