International Journal of Advanced Networking and Applications

Open Access Open Access  Restricted Access Subscription Access

Semantically Enchanced Personalised Adaptive E-Learning for General and Dyslexia Learners: An Ontology Based Approach


Affiliations
1 Department of Computer Science, Govt. Arts College, Melur, India
2 Department of CA & IT, Thiagarajar College, Madurai, India
 

E-learning plays an important role in providing required and well formed knowledge to a learner. The medium of e- learning has achieved advancement in various fields such as adaptive e-learning systems. The need for enhancing e-learning semantically can enhance the retrieval and adaptability of the learning curriculum. This paper provides a semantically enhanced module based e-learning for computer science programme on a learnercentric perspective. The learners are categorized based on their proficiency for providing personalized learning environment for users. Learning disorders on the platform of e-learning still require lots of research. Therefore, this paper also provides a personalized assessment theoretical model for alphabet learning with learning objects for children’s who face dyslexia.

Keywords

E-Learning, Personalized, Semantic, Ontology.
User
Notifications
Font Size

  • T. R. Gruber, “Toward Principles for the Design of Ontologies Used for Knowledge Sharing,” 1993.

  • C.-M. Chen, “Intelligent web-based learning system with personalized learning path guidance,” Comput. Educ., vol. 51, pp. 787–814, 2008.

  • T. R. Gruber, “A translation approach to portable ontology specifications,” Knowl. Acquis., vol. 5, no. 2, pp. 199–220, Jun. 1993.

  • J. Sarraipa, R. Jardim-Goncalves, and A. SteigerGarcao, “MENTOR: an enabler for interoperable intelligent systems,” Int. J. Gen. Syst., vol. 39, no. 5, pp. 557–573, Jul. 2010.

  • R. S. Smith, “GUIDELINES FOR AUTHORS OF LEARNING OBJECTS NMC: The New Media Con

  • W. Dick, “The Systematic Design of Instruction Chapter 1 Introduction to Instructional Design 2 The Dick and Carey Systems Approach Model for Designing Instruction 2.”

  • P. Malo, J. Sarraipa, R. Jardim-Goncalves, and A. Steiger-Garcao, “The CoSpaces Training System.”

  • X. Ochoa, “Learnometrics: Metrics for Learning Objects,” Proc. First Int. Conf. Learn. Anal. Knowl. LAK ’11, pp. 1–8, 2011.

  • S. Graf, T.-C. Liu, Kinshuk, N.-S. Chen, and S. J. H. Yang, “Learning styles and cognitive traits – Their relationship and its benefits in web-based educational systems,” Comput. Human Behav., vol. 25, no. 6, pp. 1280–1289, Nov. 2009.

  • M. Graff, “Cognitive Style and Attitudes towards Using Online Learning and Assessment Methods.,” Electron. J. e-Learning, vol. 1, no. 1, pp. 21–28, 2003.

  • J. T. Nganji, M. Brayshaw, and B. Tompsett, “Ontology-Based E-Learning Personalisation For Disabled Students in Higher Education,” Innov. Teach. Learn. Inf. Comput. Sci., vol. 10, no. 1, pp. 1–11, Feb. 2011.

  • M. Gross and C. Voegeli, “A multimedia framework for effective language training,” Comput. Graph., vol. 31, no. 5, pp. 761–777, Oct. 2007.

  • A. Alsobhi, N. Khan, and H. Rahanu, “An empirical approach to validate the Dyslexia Adaptive E-Learning (DAEL) framework,” in 2015 10th International Conference on Computer Science & Education (ICCSE), 2015, pp. 253–258.

  • A. Y. Alsobhi, N. Khan, and H. Rahanu, “DAEL Framework: A New Adaptive E-learning Framework for Students with Dyslexia,” Procedia Comput. Sci., vol. 51, pp. 1947–1956, Jan. 2015.

  • T. Ivanova, R. Andreev, and V. Terzieva, “Integration of Ontology with Development of Personalized ELearning Facilities for Dyslexics,” Springer, Berlin, Heidelberg, 2010, pp. 265–266.

  • A. Y. Alsobhi, N. Khan, and H. Rahanu, “Toward Linking Dyslexia Types and Symptoms to the Available Assistive Technologies,” in 2014 IEEE 14th International Conference on Advanced Learning Technologies, 2014, pp. 597–598.

  • A. Y. Alsobhi, N. Khan, and H. Rahanu, “Personalised Learning Materials Based on Dyslexia Types: Ontological Approach,” Procedia Comput. Sci., vol. 60, pp. 113–121, Jan. 2015.

  • M. Rani, R. Nayak, and O. P. Vyas, “An Ontologybased Adaptive Personalized E-learning System, Assisted by Software Agents on Cloud Storage,” Aug. 2017.

  • A. Y. Alsabawy, A. Cater-Steel, and J. Soar, “Determinants of perceived usefulness of e-learning systems,” Comput. Human Behav., vol. 64, pp. 843–858, Nov. 2016.

  • M. Masud, “Collaborative e-learning systems using semantic data interoperability,” Comput. Human Behav., vol. 61, pp. 127–135, Aug. 2016.

  • J. R. Kershner, “Network dynamics in dyslexia: Review and implications for remediation,” Res. Dev. Disabil., vol. 59, pp. 24–34, Dec. 2016.

  • W. G. Alghabban, R. M. Salama, and A. H. Altalhi, “Mobile cloud computing: An effective multimodal interface tool for students with dyslexia,” Comput. Human Behav., vol. 75, pp. 160–166, Oct. 2017.

  • S. S. A. Hamid, N. Admodisastro, A. Kamaruddin, N. Manshor, and A. A. A. Ghani, “Informing Design of an Adaptive Learning Model for student with Dyslexia,” in Proceedings of the 3rd International Conference on Human-Computer Interaction and User Experience in Indonesia - CHIuXiD ’17, 2017, pp. 67–75.

  • B. Srivastava and M. U. Haider, “knowledge based framework of personalized e- learning system for dyslexia,” 2017.


Abstract Views: 178

PDF Views: 0




  • Semantically Enchanced Personalised Adaptive E-Learning for General and Dyslexia Learners: An Ontology Based Approach

Abstract Views: 178  |  PDF Views: 0

Authors

K. Chitra
Department of Computer Science, Govt. Arts College, Melur, India
R. Umamaheswari
Department of CA & IT, Thiagarajar College, Madurai, India

Abstract


E-learning plays an important role in providing required and well formed knowledge to a learner. The medium of e- learning has achieved advancement in various fields such as adaptive e-learning systems. The need for enhancing e-learning semantically can enhance the retrieval and adaptability of the learning curriculum. This paper provides a semantically enhanced module based e-learning for computer science programme on a learnercentric perspective. The learners are categorized based on their proficiency for providing personalized learning environment for users. Learning disorders on the platform of e-learning still require lots of research. Therefore, this paper also provides a personalized assessment theoretical model for alphabet learning with learning objects for children’s who face dyslexia.

Keywords


E-Learning, Personalized, Semantic, Ontology.

References