Journals / Turkish Online Journal of Distance Education / 2018 / Cilt: 19 - Sayı: 1

Mobile Learning According to Students of Computer Engineering and Computer Education: A Comparison of Attitudes

Pages
4–17
Publication Date
2018-01-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

An important implication from the findings, among others, is supplementing Computer Engineering curriculum with elective courses on the fundamentals of mobile learning, and/or the design and development of m-learning software, so as to create, in the long run, more specialized and complementary teams comprised of trained CENG and CEIT graduates in m-learning sector.

📌 3 Key Takeaways

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Objective & Hypothesis:Mobile learning has started to perform an increasingly significant role in improving learning outcomes in education.
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Key Findings & Data:Using a correlational survey method, a Mobile Learning Attitude Scale (MLAS) was administered to 531 students, analysis of which revealed a positive attitude to m-learning in general.
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Conclusion & Impact:An important implication from the findings, among others, is supplementing Computer Engineering curriculum with elective courses on the fundamentals of mobile learning, and/or the design and development of m-learning software, so as to create, in the long run, more specialized and complementary teams comprised of trained CENG and CEIT graduates in m-learning sector.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:M-learning · education · attitude

Abstract

Mobile learning has started to perform an increasingly significant role in improving learning outcomes in education. Successful and efficient implementation of m-learning in higher education, as with all educational levels, depends on users’ acceptance of this technology. This study focuses on investigating the attitudes of undergraduate students of Computer Engineering (CENG) and Computer Education and Instructional Technology (CEIT) departments in a Turkish public university towards m-learning from three perspectives; gender, area of study, and mobile device ownership. Using a correlational survey method, a Mobile Learning Attitude Scale (MLAS) was administered to 531 students, analysis of which revealed a positive attitude to m-learning in general. A further investigation of the aforementioned three variables showed a more positive attitude for female students in terms of usability, for CEIT students in terms of advantages, usability and independence, and for those owning a mobile device in terms of usability. An important implication from the findings, among others, is supplementing Computer Engineering curriculum with elective courses on the fundamentals of mobile learning, and/or the design and development of m-learning software, so as to create, in the long run, more specialized and complementary teams comprised of trained CENG and CEIT graduates in m-learning sector.

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Cite This Article

GEZGİN, D. M., ADNAN, M., GUVENDIR, M. A. (2018). Mobile Learning According to Students of Computer Engineering and Computer Education: A Comparison of Attitudes. Turkish Online Journal of Distance Education, Cilt: 19 - Sayı: 1, 4–17. https://ajindex.com/articles/140141

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References (11)

  1. Albert, L. J., & Johnson, C. S. (2011). Socioeconomic Status – and Gender-Based Differences in Students’ Perceptions of E-Learning Systems. Decision Sciences Journal of Innovative Education, 9(3), 421-436.
  2. Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93-102.
  3. Al-Fahad, F. N. (2009). Students’ attitudes and perceptions towards the effectiveness of mobile learning in King Saud University, Saudi Arabia. The Turkish Online Journal of Educational Technology, 8(2), 111-119.
  4. Ally, M. (2004). Using learning theories to design instruction for mobile learning devices. Proceedings of the Mobile Learning 2004
  5. International Conference, Rome. Ally, M. (2007). Guest Editorial-Mobile Learning. The International Review of Research in Open and Distributed Learning, 8(2) Alshalabi, I., & Elleithy, K. (2012). Effective M-learning design Strategies for computer science and Engineering courses. International Journal of Mobile Network Communications & Telematics (IJMNCT), 2(1). Retrieved from http://arxiv.org/abs/1203.1897.
  6. Alwraikat, M. A., & Al Tokhaim, H. (2014). Exploring the Potential of Mobile Learning Use among Faculty Members. International Journal of Interactive Mobile Technologies (iJIM), 8(3), 4-10. Baya’a, N. F., & Daher, W. M. (2009). Learning Mathematics in an Authentic Mobile Environment: The Perceptions of Students.iJIM, 3(SI), 6-14.
  7. Buyukozturk, S., Cakmak, E. K., Akgun, O. E., Karadeniz, S., & Demirel, F. (2008).Bilimsel arastırma yontemleri [Scientific Research Methods].Ankara, Turkey: Pegem Academy Publishing. Cavus N. (2011). Investigating mobile devices and LMS integration in higher education: student perspectives. Procedia Computer Science, 3, 1469-1474.
  8. Cavus, N., & Uzunboylu, H. (2009). Improving critical thinking skills in mobile learning. Procedia-Social and Behavioral Sciences, 1(1), 434-438.
  9. Chen, B., & Denoyelles, A. (2013). Exploring Students’ Mobile Learning Practices in Higher Education. Educause Review Online. Retrieved from http://www.educause.edu/ero/article/exploringstudents-mobile-learningpractices-higher-education.
  10. Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054-1064.
  11. Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative