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The digital age: is this the future of medical education? A cross-sectional study to assess medical students’ opinions about e-learning in psychiatry undergraduate medical education

Published online by Cambridge University Press:  19 May 2014

D. Mullins ,
F. Jabbar ,
N. Fenlon  and
K. C. Murphy
D. Mullins*
Affiliation:
Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin 9, Ireland
F. Jabbar
Affiliation:
University of Northern British Columbia, British Columbia, Canada
N. Fenlon
Affiliation:
Irish College of General Practitioners, Lincoln Place, Dublin 2, Ireland
K. C. Murphy
Affiliation:
Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin 9, Ireland
*
*Address for correspondence: D. Mullins, Senior Clinical Lecturer in Psychiatry, Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin 9, Ireland. (Email: dianetmullins@rcsi.ie)
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Abstract

Objectives

The main objectives were to assess medical students’ opinions about e-learning in psychiatry undergraduate medical education, and to investigate a possible relationship between learning styles and preferences for learning modalities.

Method

During the academic year 2009/2010, all 231 senior Royal College of Surgeons in Ireland (RCSI) medical students in their penultimate year of study were invited to answer a questionnaire that was posted online on Moodle, the RCSI virtual learning environment.

Results

In all, 186 students responded to the questionnaire, a response rate of 80%. Significantly more students stated a preference for live psychiatry tutorials over e-learning lectures. Students considered flexible learning, having the option of viewing material again and the ability to learn at one’s own pace with e-learning lectures, to be more valuable than having faster and easier information retrieval.

Conclusion

Students prefer traditional in-class studying, even when they are offered a rich e-learning environment. Understanding students’ learning styles has been identified as an important element for e-learning development, delivery and instruction, which can lead to improved student performance.

Keywords

e-learninglearning stylesmedical education
Type
Original Research
Information
Irish Journal of Psychological Medicine , Volume 31 , Issue 2 , June 2014 , pp. 89 - 96
Copyright
© College of Psychiatrists of Ireland 2014 

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References

Arbaugh, JB, Duray, R (2002). Technology and structural characteristics, student learning and satisfaction with web-based courses. Management Learning 33, 331–347.CrossRefGoogle Scholar
Bell, D, Mangione, C (2000). Design and analysis of a web-based guideline tutorial system that emphasizes clinical trial evidence. Proceedings of the AMIA Symposium 56–60.Google ScholarPubMed
Bissell, V, McKerlie, RA, Kinane, DF, McHugh, S (2003). Teaching periodontal pocket charting to dental students: a comparison of computer assisted learning and traditional tutorials. British Dental Journal 195, 333–336.CrossRefGoogle ScholarPubMed
Chew, FS, Smirniotopoulos, JG (1995). Teaching skeletal radiology with use of computer-assisted instruction with interactive videodisc. Journal of Bone and Joint Surgery America 77, 1080–1086.Google Scholar
Clark, R (1985). Confounding in educational computing research. Journal of Electronic Commerce Research 1, 28–42.Google Scholar
Davenport, TH, Beck, JC (2000). Getting the attention you need. Harvard Business Review 78, 118–126.Google ScholarPubMed
Davenport, TH, Beck, JC (2001). The Attention Economy: Understanding the New Currency of Business. Harvard Business School Press: Boston, MA.Google Scholar
Day, R, Payne, L (1987). Computer-managed instruction: an alternative teaching Strategy. Journal of Nursing Education 26, 30–36.CrossRefGoogle ScholarPubMed
Dixon, N (1999). The Organizational Learning Cycle. How We Can Learn Collectively. Gower: London, United Kingdom.Google Scholar
Edgerton, D (2007). The shock of the old: Technology and global history since 1900. Oxford University Press: USA.Google Scholar
Evans, C, Edwards, M (1999). Navigational interface design for multimedia courseware. Journal of Educational Multimedia and Hypermedia 8, 151–174.Google Scholar
Evans, C, Gibbons, NJ, Shah, K, Griffin, DK (2004). Virtual learning in the biological sciences: pitfalls of simply ‘putting notes on the web’. Computers & Education 43, 49–61.CrossRefGoogle Scholar
Felder, RM (1988). Learning and teaching styles in engineering education. Engineering Education 78, 674–681.Google Scholar
Ferrari, J (2006). End of the med school lecture. The Australian, (http://www.theaustralian.com.au/news/nation/end-of-the-med-school-lecture/story-e6frg6nf-1111112576617). Accessed 1 December 2013.Google Scholar
Fitzmaurice, B, Armstrong, K, Carrol, V, Dagger, D, Gill, M (2007). Virtual Interviews for Students Interacting Online for Psychiatry (VISIOn): a novel resource for learning clinical interview skills. Psychiatric Bulletin 31, 218–220.Google Scholar
Froman, RD, Hence, C, Neafsey, PJ (1993). A comparative assessment interactive videodisc instruction. Computers in Nursing 11, 236–241.Google ScholarPubMed
Galanter, M, Keller, DS, Dermatisa, H, Biderman, D (1998). Use of the internet for addiction education. The American Journal on Addictions 7, 7–13.Google Scholar
Galanter, MK, Dermatisa, H (1997). Using the internet for clinical training: a course on network therapy for substance abuse. Psychiatric Services 48, 999–1008.Google ScholarPubMed
Galitz, W (2002). The Essential Guide to User Interface Design. John Wiley: USA.Google Scholar
Geri, N (2011). Students’ adoption of online video based distance learning. Proceedings of the Chais Conference on Instructional Technologies Research: Learning in the Technological Era, The Open University of Israel, Raanana, February 11, 2011.Google Scholar
Geri, N, Gegen, D (2007). Is there a value paradox of e-learning in MBA programs? Issues in Informing Science and Information Technology 4, 163–174.Google Scholar
Guri-Rosenblit, S (2005). Eight paradoxes in the implementation process of e-learning in higher education. Higher Education Policy 18, 5–29.CrossRefGoogle Scholar
Hare, EH, Evans, P, McIntosh, CE, Thomson, LDG (2007). Case based online learning for medical undergraduates. Psychiatric Bulletin 31, 73–75.Google Scholar
Hasebrook, J, Herrmann, W, Rudolph, D (2003). Perspectives for European E-Learning for Business: Markets, Technologies and Strategies. Office for Official Publications of the European Communities: Luxembourg.Google Scholar
Hong, KS (2002). Relationships between students’ and instructional variables with satisfaction and learning from a web-based course. Internet and Higher Education 5, 267–281.Google Scholar
Huntley, AC, Conrad, SJ (1994). Internet tools in the medical classroom. Medical Education 28, 508–512.CrossRefGoogle ScholarPubMed
Jiang, M, Ting, E (1998). Course design, instruction, and students’ online behaviors: a study of instructional variables and student perceptions of online learning. Paper presented at the Annual Meeting of the American Educational Research Association, San Diego, California, USA, April 13–17, 1998.Google Scholar
Keane, DR, Norman, GR, Vickers, J (1991). The inadequacy of recent research on computer-assisted instruction. Journal of Chemical Information and Computer Sciences 66, 444–448.Google Scholar
King, CR (1989). Innovations in human genetics education: alternative methods of instruction in medical genetics. American Journal of Human Genetics 45, 182–184.Google ScholarPubMed
Kolb, D (1985). Learning Style Inventory and Technical Manual. McBer: Boston, MA, USA.Google Scholar
Kulik, J, Bangert, R, Williams, G (1983). Effects of computer-based teaching on secondary school students. Journal of Educational Psychology 75, 19–26.Google Scholar
Kulik, J, Kulik, C, Cohen, P (1980). Effectiveness of computer-based college teaching: a meta-analysis of findings. Review of Educational Research 50, 525–544.CrossRefGoogle Scholar
Link, TM, Marz, R (2006). Computer literacy and attitudes towards e-learning among first year medical students. BMC Medical Education 6, 34.CrossRefGoogle ScholarPubMed
Maag, M (2004). The effectiveness of an interactive multimedia learning tool on nursing students’ math knowledge and self-efficacy. Computers in Nursing 22, 26–33.Google Scholar
Maguire, P, Fairburn, S, Fletcher, C (1986). Consultation skills of young doctors: I – benefits of feedback training in interviewing as students persist. BMJ 293, 26.Google Scholar
Manochehr, N (2006). The influence of learning styles on learners in e-learning environments: an empirical study. CHEER 18, 10–14.Google Scholar
Marshall, JN, Stewart, M, Ostbye, T (2001). Small group CME using e-mail discussions: can it work? Canadian Family Physician Médecin de Famille Canadien 47, 557–563.Google Scholar
Najjar, L (1996). Multimedia information and learning. Journal of Educational Multimedia and Hypermedia 5, 129–150.Google Scholar
Nielsen, J (2000). Designing Web Usability: The Practice of Simplicity. New Riders: Indianapolis, USA.Google Scholar
Postman, N (1993). Technopoly: the surrender of culture to technology. Vintage Books: New York, USA.Google Scholar
Rashid, B (2006). A training evaluation on the capacity building for open and distance learning materials at Bangladesh Open University. Journal of Agriculture & Rural Development 4, 27–34.CrossRefGoogle Scholar
Ruiz, JG, Mintzer, MJ, Rosanne, ML (2006). The impact of e-learning in medical education. Academic Medicine 81, 207–212.Google Scholar
Salant, P, Dillman, DA (1994). How to Conduct your Own Survey. John Wiley & Sons, Inc: New York, USA.Google Scholar
Schanze, S (2004). The use of concept mapping in the med: u project – e-learning in medical education. A tool for structuring complex information and for testing learning performance (in German). In Evaluation of E-Learning Goals, Methodological Aspects, Future (in German) (ed. D. M. Meister, S. Tergan and P. Zentel), pp. 171–187. Waxmann, Münster: Germany.Google Scholar
Schwartz, RA (1995). The virtual university. American Society for Engineering Education Prism 5, 22–26.Google Scholar
Seabra, D, Srougi, M, Baptista, R, Nesrallah, LJ, Ortiz, V, Sigulem, D (2004). Computer aided learning versus standard lecture for undergraduate education in Urology. Journal of Urology 171, 1220–1222.CrossRefGoogle ScholarPubMed
Shih, C, Gamon, J (2002). Relationships among learning strategies, patterns, styles, and achievement in web-based courses. Journal of Applied Econometrics 43, 1–11.Google Scholar
Simmers, CA, Anandarajan, M (2001). User satisfaction in the internet-anchored workplace: and exploratory study. Journal of Information Technology Theory and Application 3, 39–62.Google Scholar
Turchin, A, Lechmann, C (2000). Active learning centre: design and evaluation of an educational World Wide Web site. Medical Informatics and the Internet 25, 195–206.Google ScholarPubMed
Vassilas, C, Ho, L (2000). Video for teaching purposes. Advances in Psychiatric Treatment 6, 304–311.Google Scholar
Volery, T, Lord, D (2000). Critical success factors in online education. Indian Journal of Endocrinology and Metabolism 14, 216–223.Google Scholar
Yellowlees, PM, Cook, JN (2006). Education about hallucinations using an Internet virtual reality system: a qualitative survey. Academic Psychiatry 30, 534–539.Google Scholar