CFP last date
20 December 2024
Reseach Article

Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention

by Abdulkadir Karaci, Halil Ibrahim Akyuz, Goksal Bilgici, Nursal Arici
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 16
Year of Publication: 2018
Authors: Abdulkadir Karaci, Halil Ibrahim Akyuz, Goksal Bilgici, Nursal Arici
10.5120/ijca2018917806

Abdulkadir Karaci, Halil Ibrahim Akyuz, Goksal Bilgici, Nursal Arici . Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention. International Journal of Computer Applications. 181, 16 ( Sep 2018), 35-41. DOI=10.5120/ijca2018917806

@article{ 10.5120/ijca2018917806,
author = { Abdulkadir Karaci, Halil Ibrahim Akyuz, Goksal Bilgici, Nursal Arici },
title = { Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2018 },
volume = { 181 },
number = { 16 },
month = { Sep },
year = { 2018 },
issn = { 0975-8887 },
pages = { 35-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number16/29908-2018917806/ },
doi = { 10.5120/ijca2018917806 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:10.703149+05:30
%A Abdulkadir Karaci
%A Halil Ibrahim Akyuz
%A Goksal Bilgici
%A Nursal Arici
%T Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 16
%P 35-41
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This study examines the effect of web-based intelligent tutoring systems (ITS) on academic achievement and retention. The ITS developed by Arıcı and Karacı (2013) was adapted for instruction on electronic spreadsheet software, and an experimental study was conducted with 80 undergraduate students. The experimental design involved quantitative research using a pre- and post-tests with a control group. The control and experimental groups consisted of 42 and 38 students, respectively. To measure academic achievement and retention, the researchers developed an achievement test that consisted of 27 questions. After a four-week implementation period, students that used the ITS showed higher levels of academic achievement than the control group. However, the ITS did not significantly influence retention levels.

References
  1. Arıcı,N., Karacı, A. (2013). Türkçe Öğrenimi İçin Web Tabanlı Zeki Öğretim Sistemi (Türkzös) Ve Değerlendirmesi. Turkish Studies, 8(8), 65-87.
  2. Körez, A. (2009). Durum tabanlı öğrenci modeli ile zeki öğretim sistemi (ZÖS) tasarımı, Yayımlanmamış Yüksek Lisans Tezi, Marmara Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  3. Rishi, O. P., Govil, R., & Sinha, M. (2007). Distributed Case Based Reasoning for Intelligent Tutoring System : An Agent Based Student Modeling Paradigm. In Proceedings of World Academy of Science, Engineering and Technology (Vol. 23, pp. 273–276).
  4. Karacı, A., & Arıcı, N. (2014). Determining students’ level of page viewing in intelligent tutorial systems with artificial neural network. Neural Comput & Applic, 24, 675–684.
  5. Keleş, A., Ocak R., Keleş, A., Gülcü, A., (2009). “ZOSMAT: Web-based intelligent tutoring system for teaching-learning process”, Expert Systems with Applications, 36 (2): 1229-1239. doi: 10.1016/j.eswa.2007.11.064.
  6. Elbeh, H. M. A. (2012). A personalized emotional intelligent tutoring system based on AI planning, Unpublished Doctora’s Thesis, Ulm University, Artificial Intelligence Institute, Ulm.
  7. Doğan, B. (2006). Zeki öğretim sistemlerinde veri madenciliği kullanılması, Yayımlanmamış Doktora Tezi, Marmara Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  8. Graesser, A. C., Conley, M. W., & Olney, A. M. (2012). Intelligent tutoring systems. In S. Graham, & K. Harris (Eds.), APA Educational Psychology Handbook: Vol. 3. Applications to Learning and Teaching (pp. 451-473). Washington, DC: American Psychological Association.
  9. Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11, 87–110. doi:10.1023/A:1011143116306
  10. Korhan, G., Polat, R., Kurt, M. (2003). Analyzing Learning Concepts in Intelligent Tutoring Systems, The International Arab Journal of Information Technology, 13(2), 281-286, 2016.
  11. Weber, G., & Brusilovsky, P. (2001). ELM-ART : An Adaptive Versatile System for Web-based Instruction. International Journal of Artificial Intelligence in Education, 12, 351–384. doi:10.1.1.66.6245.
  12. Mitrovic, A. (2002). NORMIT: a Web-enabled tutor for database normalization. International Conference on Computers in Education, 2002. Proceedings. doi:10.1109/CIE.2002.1186210
  13. Mitrovic, A. (2003). An Intelligent SQL Tutor on the Web. International Journal of Artificial Intelligence in Education, 13, 173–197.
  14. Butz, C. J., Hua, S., & Maguire, R. B. (2004). A Web-based intelligent tutoring system for computer programming. In Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004 (pp. 159–165). doi:10.1109/WI.2004.10104
  15. Naser, S. S. A. (2008). Developing an intelligent tutoring system for students learning to program in C++. Information Technology Journal, 7, 1055–1060. doi:10.3923/itj.2008.1055.1060
  16. Abu-Naser, S., Ahmed, A., Al-Masri, N., Deeb, A., Moshtaha, E., & Abu Lamdy, M. (2011). An Intelligent Tutoring System for Learning Java Objects. International Journal of Artificial Intelligence & Applications, 2(2), 68-77. doi:10.5121/ijaia.2011.2205
  17. Virvou, M., & Moundridou, M. (2000). A web-based authoring tool for algebra-related intelligent tutoring systems. Educational Technology and Society, 3, 61–70.
  18. Günel, K., & Aşliyan, R. (2009). Determining difficulty of questions in intelligent tutoring systems. Turkish Online Journal of Educational Technology, 8, 14–21.
  19. Ben Ammar, M., Neji, M., Alimi, A. M., & Gouardères, G. (2010). The Affective Tutoring System. Expert Systems with Applications, 37, 3013–3023. doi:10.1016/j.eswa.2009.09.031
  20. Geng, X., Zhang, Z., Jiang, Y., & Yang, Y. (2010). An intelligent tutoring architecture for scenario-based flight training. In 2nd International Workshop on Education Technology and Computer Science, ETCS 2010 (Vol. 2, pp. 291–294). doi:10.1109/ETCS.2010.172
  21. Özek, M. B., Akpolat, Z. H., Orhan A. (2010). Web tabanlı akıllı öğretim sistemlerinde tip-2 bulanık mantık kullanarak öğrenci öğrenme stili modelleme. Fırat Üniv. Mühendislik Bilimleri Dergisi, 22 (1), 37-44.
  22. Cabada, R. Z., Barrón Estrada, M. L., & Reyes García, C. A. (2011). EDUCA: A web 2.0 authoring tool for developing adaptive and intelligent tutoring systems using a Kohonen network. Expert Systems with Applications, 38, 9522–9529. doi:10.1016/j.eswa.2011.01.145
  23. Mitrovic, A., Mayo, M., Suraweera, P., & Martin, B. (2001). Constraint-based tutors: a success story. Engineering of Intelligent Systems. doi:10.1007/3-540-45517-5_103
  24. Webb, N.L. (1997). Determining Alignment of Expectations and Assessments in Mathematics and Science Education. NISE Brief 1(2). Madison, WI: University of Wisconsin-Madison, National Institute for Science Education. Retrieved from http://facstaff.wceruw.org/normw/WEBBMonograph6criteria.pdf on July, 20, 2017
  25. Turgut, M.F. (1992). Eğitimde Ölçme ve Değerlendirme. Ankara: Saydam Matbaacılık.
  26. Tekin, H. (2000). Eğitimde Ölçme ve Değerlendirme. Ankara: Yargı Yayınları.
  27. Hsieh, S-J., Hsieh, P. Y., “Intelligent tutoring system authoring tool for manufacturing engineering education”, Int. J. Engng Ed., 17 (6): 569-579 (2001).
  28. Erdemir, M., Ingeç, K.Ş. (2015). The Influence of Web-based Intelligent Tutoring Systems on Academic Achievement and Permanence of Acquired Knowledge in Physics Education, US-China Education Review A, 5(1), 15-25.
  29. Christopher R. Wolfe, Valerie F. Reyna, Colin L. Widmer, Elizabeth M. Cedillos, Christopher R. Fisher, Priscila G. Brust-Renck, Audrey M. Weil. (2015). Efficacy of a Web-Based Intelligent Tutoring System for Communicating Genetic Risk of Breast Cancer: A Fuzzy-Trace Theory Approach, Medical Decision Making, 35(1), 46-59.
  30. Hooshyar, D., Ahmad, R.B., Yousefi, M., Yusop, F.D., Horng, S.-J. (2015). A flowchart-based intelligent tutoring system for improving problem-solving skills of novice programmers, Journal of Computer Assisted Learning, 31(4). 345–361
  31. Fossati, D., Eugenio, B. D., Ohlsson, S., Brown, C., Chen, L. (2015). Data driven automatic feedback generation in the iList intelligent tutoring system, Tech., Inst., Cognition and Learning, 10, 5–26.
  32. Keleş, A., Keleş, A. (2017). BİDEMAT - Zeki Öğretim Sistemi, Turkish Studies, 12(6), 547-564.
Index Terms

Computer Science
Information Sciences

Keywords

Intelligent tutoring system internet student model achievement retention.