Optimizing Adaptive Hypermedia Educational Systems: A Comparative Study of Frameworks

Authors

DOI:

https://doi.org/10.21015/vtcs.v12i2.2034

Abstract

The majority of online educational systems deliver the same content to all learners, disregarding their individual needs, goals, and educational backgrounds. This approach often makes the learning process challenging and unengaging. Adaptive hypermedia addresses this issue by enhancing these systems through personalization and customization. Adaptive hypermedia-based educational systems (AHES) create a learner profile, known as a learner model, and tailor the content based on the learner's preferences and prior educational history. However, developing AHES is a complex and time-consuming task, as it requires the integration of adaptive features alongside communication tools, digital libraries, and more. To simplify this process, various authoring tools and frameworks, such as AHA! Moodle, Open edX, InterBook, and COFALE, are available. This study provides an analysis and comparison of these frameworks, facilitating the selection of an appropriate framework for developing high-quality AHES.

References

M. Khan and K. Mustafa, "Modelling adaptive hypermedia instructional system: a framework," Multimedia Tools and Applications, vol. 78, pp. 14397–14424, 2019.

M. Khan and K. Mustafa, "Adaptive hypermedia instructional system (AHIS): A model," Education and Information Technologies, vol. 24, pp. 3329–3392, 2019.

M. Benfarha, M. Lamarti, and O. El Hichami, "Towards the development of a structure based on the learning styles of dynamic adaptive hypermedia for online teaching," in Fostering Pedagogical Innovation Through Effective Instructional Design, pp. 391–414, IGI Global, 2024.

S. Sarwar, Z. Qayyum, R. García-Castro, M. Safyan, and R. Munir, "Ontology based e-learning framework: A personalized, adaptive and context aware model," Multimedia Tools and Applications, vol. 78, no. 24, pp. 34745–34771, 2019.

S. Ardchir, M. Talhaoui, and M. Azzouazi, "Towards an adaptive learning framework for MOOCs," in International Conference on E Technologies, pp. 236–251, Springer International Publishing, 2019.

R. Khairanis, "Innovation in Arabic language learning methodology: Combining technology and interactive approaches," As-Sulthan Journal of Education, vol. 1, no. 2, pp. 281–293, 2024.

M. Benfarha and M. Lamarti, "The implementation of adaptation methods and techniques to build an individualized course," in E-Learning and Smart Engineering Systems (ELSES 2023), pp. 490–496, Atlantis Press, 2024.

A. Papadimitriou and G. Gyftodimos, "The role of learner characteristics in the adaptive educational hypermedia systems: the case of the mathema," IJ Modern Education and Computer Science (IJMECS), vol. 9, no. 10, pp. 55–68, 2019.

J. Carrera-Román, J. Guerrero-García, and E. Vera-Cervantes, "Design of an adaptive hypermedia system to strengthen algebra learning skills of high school students," Journal of Teaching and Educational Research, pp. 9–24, 2023.

S. Ennouamani and Z. Mahani, "An overview of adaptive e-learning systems," in 2017 eighth international conference on intelligent computing and information systems (ICICIS), pp. 342–347, IEEE, 2017.

A. Alameen and B. Dhupia, "Implementing adaptive e-learning conceptual model: A survey and comparison with open source LMS," International Journal of Emerging Technologies in Learning (iJET), vol. 14, no. 21, pp. 28–45, 2019.

S. Kumar, B. Singh, and M. Agarwal, "Course content and learner classification using fuzzy logic to enhance adaptive learning system," Library Progress International, vol. 44, no. 3, pp. 17205–17218, 2024.

M. Gavriushenko, On personalized adaptation of learning environments, PhD thesis, University of Jyväskylä, 2017.

D. Hariyanto, "An adaptive e-learning system based on student’s learning styles and knowledge level," Advanced Information Systems, vol. 8, no. 4, pp. 103–117, 2020.

H. Makogon, T. Lavrut, M. Chornyi, B. Matuzko, and W. Załoga, "Information technology of the acquiring professional competencies process in the e-learning management system environment by constructing an educational trajectory," Advanced Information Systems, vol. 8, pp. 103–117, 2024.

J. Mamcenko, "Comparative analysis of personalization approaches and tools to improve learning used in different learning systems," in INTED2018 Proceedings, pp. 4674–4684, IATED, 2018.

M. Maravanyika, N. Dlodlo, and N. Jere, "An adaptive recommender-system based framework for personalised teaching and learning on e-learning platforms," in 2017 IST-Africa Week Conference (IST-Africa), pp. 1–9, IEEE, 2017.

I. Adeniyi, N. Al Hamad, O. Adewusi, C. Unachukwu, B. Osawaru, C. Onyebuchi, S. Omolawal, A. Aliu, and I. David, "E-learning platforms in higher education: A comparative review of the USA and Africa," International Journal of Science and Research Archive, vol. 11, no. 1, pp. 1686–1697, 2024.

R. Maaliw III, "Adaptive virtual learning environment based on learning styles for personalizing e-learning system: Design and implementation," Online Submission, vol. 8, no. 6, pp. 3398–3406, 2020.

H. Xie, D. Zou, R. Zhang, M. Wang, and R. Kwan, "Personalized word learning for university students: A profile-based method for e-learning systems," Journal of Computing in Higher Education, vol. 31, pp. 273–289, 2019.

E. Aeiad, A framework for an adaptable and personalised e-learning system based on free web resources, PhD thesis, University of Salford, 2017.

M. Venkatesh and S. Sathyalakshmi, "Smart learning using personalised recommendations in web-based learning systems using artificial bee colony algorithm to improve learning performance," Electronic Government, an International Journal, vol. 16, no. 1-2, pp. 101–117, 2020.

N. Alqahtani, "Adaptation in the e-learning systems," Technium Soc. Sci. J., vol. 23, p. 296, 2021.

E. Kurilovas, "Comparative analysis of applying learning analytics tools to create personalised learners' profiles: Artificial neural networks vs case-based reasoning and bayesian networks," in Edulearn18 Proceedings, pp. 3392–3401, 2018.

A. Mavroudi, M. Giannakos, and J. Krogstie, "Supporting adaptive learning pathways through the use of learning analytics: Developments, challenges and future opportunities," Interactive Learning Environments, vol. 26, no. 2, pp. 206–220, 2018.

K. Amit, S. Ninni, and A. Jyothi, "Learning styles based adaptive intelligent tutoring systems: Document analysis of articles published between 2001 and 2016," International Journal of Cognitive Research in Science, Engineering and Education, vol. 5, no. 2, p. 83, 2017.

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Published

2024-12-31

How to Cite

Muhammad Kamran, Raza, B., Shahzad, F., Kareem, M. S., & Naz, K. (2024). Optimizing Adaptive Hypermedia Educational Systems: A Comparative Study of Frameworks. VAWKUM Transactions on Computer Sciences, 12(2), 326–339. https://doi.org/10.21015/vtcs.v12i2.2034