BibTex RIS Kaynak Göster

Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model

Yıl 2015, , 249 - 251, 31.12.2015
https://doi.org/10.18100/ijamec.12490

Öz

 In recent years we have witnessed an increasingly heightened awareness of the potential benefits of adaptively in e-learning. This has been mainly driven by the realization that the ideal of individualized learning (i.e., learning tailored to the specific requirements and preferences of the individual) cannot be achieved, especially at a “massive” scale, using traditional approaches. In e-learning when the learning style of the student is not compatible with the teaching style of the teacher; difficulties in academic achievement can result. Therefore, knowing what is the preferred learning style supported by thinking style for individual can help in teaching and learning process. This paper presents an adaptive e-learning system (ALTENN) to improve e-learning environment.  Neural network technology has been used for implementing the model and extracts the appropriate learning style based on learner thinking style. The system structure and NN results are also presented in this paper.

Kaynakça

  • R. Costello (2013). Adaptive Intelligent Personalised Learning (AIPL) Environment A Thesis submitted to the University of Hull for the degree of Doctor of Philosophy.
  • Hanan. E. Dagez (2014), “E-learning Multi-Learning Style One Size Can Fit All”, Proceedings of the International conference on Computing Technology and Information Management, Dubai, UAE, 2014, P. 47-51.
  • Hanan. E. Dagez and K. Hashim, “Online Learning Style and e-Learning Approaches”, Published in IPSI-USA-2006, pp6; and published in NASA report, Volume 44, December 5, 2006.
  • E. Wagad (2015). Thinking Styles and their Relationship with Learning styles and Goal, 2008, University Female Students in the Holy City of Makkah AL-Mukarramah.
  • M. Tracey J. (2013). Automatic detection of learner-style for adaptive eLearning, ©2013, TraceyJ.Mehigan. http://creativecommons.org/licenses/by-nc-nd/3.0/
  • J. Turki, “Thinking style “In Light of Sternberg’s Theory” prevailing among the students of Tafila technical university and its relationship with some variables”, American International journal of contemporary research, Vol. 2 No.3, March 2012. Center for promoting ideas, USA
  • Hanan. E. Dagez, Mohamed. S. Baba “Applying Neural Network Technology in Qualitative Research for extracting Learning Style System to Improve E-learning Environment” published in proceeding of ITSIM’08, International Symposium on information technology, Volume 1, IEEE August 26, 2008.
  • Khirulddin. H, Hanan E. Dagez, “Adaptive Learning in An e-Learning Environment”, e-Learning National Seminar, organized by National University of Malaysia, Kuala Lumpur, December, 2006 – Plenary Presentation.
Yıl 2015, , 249 - 251, 31.12.2015
https://doi.org/10.18100/ijamec.12490

Öz

Kaynakça

  • R. Costello (2013). Adaptive Intelligent Personalised Learning (AIPL) Environment A Thesis submitted to the University of Hull for the degree of Doctor of Philosophy.
  • Hanan. E. Dagez (2014), “E-learning Multi-Learning Style One Size Can Fit All”, Proceedings of the International conference on Computing Technology and Information Management, Dubai, UAE, 2014, P. 47-51.
  • Hanan. E. Dagez and K. Hashim, “Online Learning Style and e-Learning Approaches”, Published in IPSI-USA-2006, pp6; and published in NASA report, Volume 44, December 5, 2006.
  • E. Wagad (2015). Thinking Styles and their Relationship with Learning styles and Goal, 2008, University Female Students in the Holy City of Makkah AL-Mukarramah.
  • M. Tracey J. (2013). Automatic detection of learner-style for adaptive eLearning, ©2013, TraceyJ.Mehigan. http://creativecommons.org/licenses/by-nc-nd/3.0/
  • J. Turki, “Thinking style “In Light of Sternberg’s Theory” prevailing among the students of Tafila technical university and its relationship with some variables”, American International journal of contemporary research, Vol. 2 No.3, March 2012. Center for promoting ideas, USA
  • Hanan. E. Dagez, Mohamed. S. Baba “Applying Neural Network Technology in Qualitative Research for extracting Learning Style System to Improve E-learning Environment” published in proceeding of ITSIM’08, International Symposium on information technology, Volume 1, IEEE August 26, 2008.
  • Khirulddin. H, Hanan E. Dagez, “Adaptive Learning in An e-Learning Environment”, e-Learning National Seminar, organized by National University of Malaysia, Kuala Lumpur, December, 2006 – Plenary Presentation.
Toplam 8 adet kaynakça vardır.

Ayrıntılar

Bölüm Research Article
Yazarlar

Hanan Ettaher Dagez

Ali Elghali Ambarka Bu kişi benim

Yayımlanma Tarihi 31 Aralık 2015
Yayımlandığı Sayı Yıl 2015

Kaynak Göster

APA Dagez, H. E., & Ambarka, A. E. (2015). Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model. International Journal of Applied Mathematics Electronics and Computers, 3(4), 249-251. https://doi.org/10.18100/ijamec.12490
AMA Dagez HE, Ambarka AE. Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model. International Journal of Applied Mathematics Electronics and Computers. Aralık 2015;3(4):249-251. doi:10.18100/ijamec.12490
Chicago Dagez, Hanan Ettaher, ve Ali Elghali Ambarka. “Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model”. International Journal of Applied Mathematics Electronics and Computers 3, sy. 4 (Aralık 2015): 249-51. https://doi.org/10.18100/ijamec.12490.
EndNote Dagez HE, Ambarka AE (01 Aralık 2015) Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model. International Journal of Applied Mathematics Electronics and Computers 3 4 249–251.
IEEE H. E. Dagez ve A. E. Ambarka, “Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model”, International Journal of Applied Mathematics Electronics and Computers, c. 3, sy. 4, ss. 249–251, 2015, doi: 10.18100/ijamec.12490.
ISNAD Dagez, Hanan Ettaher - Ambarka, Ali Elghali. “Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model”. International Journal of Applied Mathematics Electronics and Computers 3/4 (Aralık 2015), 249-251. https://doi.org/10.18100/ijamec.12490.
JAMA Dagez HE, Ambarka AE. Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model. International Journal of Applied Mathematics Electronics and Computers. 2015;3:249–251.
MLA Dagez, Hanan Ettaher ve Ali Elghali Ambarka. “Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model”. International Journal of Applied Mathematics Electronics and Computers, c. 3, sy. 4, 2015, ss. 249-51, doi:10.18100/ijamec.12490.
Vancouver Dagez HE, Ambarka AE. Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model. International Journal of Applied Mathematics Electronics and Computers. 2015;3(4):249-51.