Volume 6, Issue 3 (10-2019)
Human Information Interaction 2019, 6(3): 55-71 |
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Khoeini S, Naghshineh N. Investigating the Adoption Rate of Students' Mental Model with the Structure of the Learning Management System of the University of Tehran by Card Sorting Method. Human Information Interaction 2019; 6 (3)
URL: http://hii.khu.ac.ir/article-1-2930-en.html
URL: http://hii.khu.ac.ir/article-1-2930-en.html
Associate Professor, Departmen University of Tehran
Abstract: (4213 Views)
Background and Aim: E-learning is an important topic in the educational settings and students are significant prerequisites of it, who have an essential role for the acceptance and effective use of e-learning management systems so that knowing their attitudes and mental models is essential for the successful implementation of such a method. Therefore, the aim of this study was to investigate the Adoption Rate of students' mental model with the structure of the learning management system of the University of Tehran using the card sorting method.
Methodology: Research had qualitative approach with card sorting and interview tools. Usabilitest software, descriptive statistics, distance matrix, and hierarchical clustering were used to analyze the data. Sample consisted of 15 postgraduate students at Tehran University (second semester of the academic year 2019-2020) that were interacting with the learning management system (Moodle).
Findings: Findings indicate that out of 42 cards examined, the status and classification of 36 cards (85%) in the learning management system were fully consistent with the participants' mental model and only in some cases such as "Help" and" Recent lessons referred" according to their mental model, users expected these sections to be placed in other categories. As well as labeling; 66% of users found the "settings" tag more appropriate than their "preferences" and the function of some, such as "medal management", "medal preferences" was unclear to them. Also, the categories presented in the three sections: "User Profile", "Quick Access" and "My Lessons" were approved by users.
Conclusion: The results show that the degree of adaptation of students' mental model to the structure of the learning management system of the University of Tehran is at a desirable level.
Methodology: Research had qualitative approach with card sorting and interview tools. Usabilitest software, descriptive statistics, distance matrix, and hierarchical clustering were used to analyze the data. Sample consisted of 15 postgraduate students at Tehran University (second semester of the academic year 2019-2020) that were interacting with the learning management system (Moodle).
Findings: Findings indicate that out of 42 cards examined, the status and classification of 36 cards (85%) in the learning management system were fully consistent with the participants' mental model and only in some cases such as "Help" and" Recent lessons referred" according to their mental model, users expected these sections to be placed in other categories. As well as labeling; 66% of users found the "settings" tag more appropriate than their "preferences" and the function of some, such as "medal management", "medal preferences" was unclear to them. Also, the categories presented in the three sections: "User Profile", "Quick Access" and "My Lessons" were approved by users.
Conclusion: The results show that the degree of adaptation of students' mental model to the structure of the learning management system of the University of Tehran is at a desirable level.
References
1. Berking, P., Gallagher, S., (2016). "Choosing a learning management system". Advanced Distributed Learning (ADL) Co-Laboratories, (2.4).
2. Elahian Firooz, S., Khazai, K., (2011). Extent of components of e-course development criteria in the educational content of virtual public universities in Iran, Information and Communication Technology in Educational Sciences, 2 (6), 141-162. (In Persian).
3. Gatsou, C., Politis, A., Zevgolis. D., (2012). The importance of mobile interface icons on user interaction, International Journal of Computer Science and Applications 9: 92-107.
4. Jamshidi Kia, S.; Fazelian, P.; Khoshneshin, Z. (2015). Evaluation of learning management system of e-learning center of Tehran University, Journal of Information and Communication Technology in Educational Sciences, 1 (21), 19-36. (In Persian).
5. Janice Jih, H., Charles Reeves, T., (1992). Mental Models: A Research Focus for Interactive Learning Systems, Educational Technology Research and Development, 40(3), 39-53. . Retrieved May 24, 2020. https://www.jstor.org/stable/30220012 [DOI:10.1007/BF02296841]
6. Jones, W., Pirolli, P., Card, S. K., Fidel, R., Gershon, N., Morville, P. ... & Russell, D. M., (2006). "It's about the information stupid!" why we need a separate field of human-information interaction. In CHI'06 extended abstracts on Human factors in computing systems (pp. 65-68). [DOI:10.1145/1125451.1125469]
7. Kazempour, Z., Nakhoda, M., Mirzabeigi, M.,, Naghshineh, N., (2017).The Relationship between the Post-Graduate Students of Isfahan University of Medical Sciences, Iran, Mental Models and Their Web Searching Behavior. Health Inf Manage, 14 (5), 217-223. (In Persian).
8. Khoshnood, F., Kiani Sarkaleh, M., Bani Ardalan, M., & Ebrahimi Atani, R., (2012). Study of learning management systems in e-learning and their comparison, The Second National Conference on Software Engineering, Lahijan Azad University, Lahijan. https://civilica.com/doc/184935/(In Persian).
9. Kosak, L., Manning, D., Dobson, E., Rogerson, L., Cotnam, S., Colaric, S., & McFadden, C. (2004). Prepared to teach online? Perspectives of faculty in the University of North Carolina System, Online Journal of Distance Learning Administration, 7(3).
10. Mansoorian, Y., (2003). A Review of User Research in Web-Based Information Retrieval Studies, Library and Information Science, 6 (3), 1 - 22. (In Persian).
11. Najafi, E., Afrazeh, A., & Najafi, E., (2007). Investigating the causes of inefficiency of user guides in further adapting users' mental models to software produced according to IEEE-1063 standard, 4th International Conference on Information and Communication Technology Management, Tehran, Nedaye Eqtesad Bamdad
12. https://www.civilica.com/Paper-ICTM04-ICTM04_013.html (In Persian).
13. Nielsen, J., (2004). Card Sorting: How Many Users to Test,
14. https://www.nngroup.com/articles/card-sorting-how-many-users-to-test/?lm=card-sorting-definition&pt=article.
15. Rajabali Bigo, R., Fattahi, R., Parikh, M., (2016). Development and Evolution of the Concept of Mental Model in the Context of Information Systems: From a General Perspective to Performance Prediction, Journal of Library and Information Science Studies, 16, 1-18. (In Persian).
16. Rahmani, M., (2019). Study of the conformity of students' mental model with the e-learning system of Shahid Beheshti University of Tehran, Information Management, 5 (1), (In Persian).
17. Rahrovani, S., Mirzabeigi, M., Abbaspour, J., (2018). Investigating Factors Affecting on the Users' Mental Models of Icons in Digital Library Software, Journal of Information Processing and Management. 33 (2) :489-516. (In Persian).
18. Righi, C., James, J., Beasley, M., Day, D. L., Fox, J. E., Gieber, J., Ruby, L. (2013). Card sort analysis best practices. Journal of Usability Studies, 8(3), 69-89.
19. Rogers, E. M., (1995). Diffusion of innovations. New York: The Free Press.
20. Schmettow, M., & Sommer, J., (2016). Linking card sorting to browsing performance - are congruent municipal websites more efficient to use?, Behavior & Information Technology, 35:6, 452-470, DOI: 10.1080/0144929X.2016.1157207 [DOI:10.1080/0144929X.2016.1157207]
21. Sejzi, A. A., & Aris, B., (2013). Learning Management System (LMS) and Learning Content Management System (LCMS) at Virtual University. In 2nd International Seminar on Quality and Affordable Education (ISQAE), Johor, Malaysia. http://www. isqae. com.
22. Sherwin, K., (2018). Card Sorting: Uncover Users' Mental Models for Better Information Architecture. https://www.nngroup.com/articles/card-sorting-definition/
23. Spencer, D., (2009). Card Sorting: Designing Usable Categories. New York: Rosenfeld Media
24. Staggers, N., & Norcio, A. F., (1993). Mental models: concepts for human-computer interaction research, International Journal of Man-Machine Studies, 38(4), 299-305. [DOI:10.1006/imms.1993.1028]
25. Suaiman, M., Meadow, J., (1995). Icons and OPACs. New Library World. 96 (4): 11 - 14. [DOI:10.1108/03074809510146895]
26. Torrisi-Steele, G., Atkinson, T., (2020). Instructors and Students on the same page: Usability of Instructor Loaded resources in LMS sites. DOI: 10.21125/edulearn.2020.1726 [DOI:10.21125/edulearn.2020.1726]
27. Tullis, T., Wood, L., (2004). How Many Users Are Enough for a Card-Sorting Study? Usability Professionals Association (UPA) 2004 Conference, Minneapolis, MN, June 7-11, 2004.
28. Wentzela, J., Müllerb, F., Beerlage-de Jonga, N., van Gemert-Pijnen, J., (2016). Card sorting to evaluate the robustness of the information architecture of a protocol website. International Journal of Medical Informatics. 86, 71-81. [DOI:10.1016/j.ijmedinf.2015.12.003] [PMID]
29. Westbrook, L., (2006). Mental models: a theoretical overview and preliminary study. [DOI:10.1177/0165551506068134]
30. Journal of Information Science, 32 (2), 563-579. DOI: 10.1177/01655515068134
31. Xie, B., Zhou, J., Wang, H., (2017). How influential are mental models on interaction performance? Exploring the gap between users' and designers' mental models through a new quantitative method. Advances in Human-Computer Interaction, 2017. [DOI:10.1155/2017/3683546]
32. Zandi, S., Abedi, D., Yousefi, A. R., Changiz, T., Yamani, N., Kabiri, P., (2004). Familiarity with e-learning as a new educational technology and its integration in medical educational programs. Iranian Journal of Education in Medical Sciences, 11, 61-72. (In Persian).
33. Zareyi Zevaraki, E., (2010). Measuring and evaluating Elearning: case report of ELearning Course of Computer Engineering field. K. N. Toosi University of Technology. 6th National Conference and 3rd International Conference on Electronic Learning and Learning, Tehran University of Technology Electronic Education Center. (in Persian)
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