ORIGINAL_ARTICLE
Effectiveness of E-Curriculum in Social Networks during the COVID-19 Pandemic: Parents’, Teachers’ and Students’ Perspectives
Background: This study aimed to determine the effectiveness of e-curriculum in social networks from the perspectives of parents, teachers, and students during the COVID-19 pandemic. Methods: This was a descriptive study using a survey method in 2020-2021 academic year. The statistical population consisted of three groups of teachers, parents, and primary school students in Dehloran County, Iran. The sampling method included a census of teachers (97 teachers) and random cluster sampling of parents and students (150 parents and 340 students). The data collection tool was a questionnaire for all three groups. Kolmogorov-Smirnov test and one-sample t-test were used to analyze the data. Results: In assessing the effectiveness of e-curriculum in social networks based on the education triangle (teachers, parents, and students) different levels of effectiveness were reported (P<0.05), in the sense that the elements of content, teaching strategies, and evaluation methods were in a desirable condition only for teachers and parents, but not for students. Only the element of objectives received favorable scores from all three groups (teachers=3.73, parents=3.42, and students=3.06). Conclusion: Educational policymakers and planners should take note of different perspectives in the education triangle when evaluating the effectiveness of e-curriculums for primary schools during the COVID-19 pandemic.
https://ijvlms.sums.ac.ir/article_47098_904771f04d1faaf5f296d5ffd672af3c.pdf
2020-12-01
207
214
10.30476/ijvlms.2020.47098
E-curriculum
E-Learning
Curriculum
Social Networks
COVID-19
Ahmad
Malekipour
malekipour95@gmail.com
1
Department of Educational Management, Farhangian University, Rasoul Akram Campus, Ahvaz, Iran
LEAD_AUTHOR
Teo TS, Kim SL, Jiang L. E-learning implementation in south Korea: Integrating Effectiveness and Legitimacy Perspectives. Information Systems Frontiers. 2020 Apr;22(2):511-28. doi:10.1007/s10796-018-9874-3
1
Al-Fraihat D, Joy M, Sinclair J. Evaluating E-learning systems success: An empirical study. Computers in Human Behavior. 2020 Jan 1; 102:67-86. doi:10.1016/j.chb.2019.08.004.
2
Wong AO, Sixl-Daniell K. The importance of e-learning as a teaching and learning approach in emerging markets. International Journal of Advanced Corporate Learning (iJAC). 2017 Mar 30;10(1):45-54. doi:10.3991/ijac.v10i1.6471
3
Yogita N, Ansari MA. A Comparative Study of e-Learning Readiness of Two State Agricultural Universities (SAUs) in Northern India. Journal homepage. 2020 Apr;9(7): 1-11. doi:10.20546/ijcmas.2020.907.xx
4
Kullenberg G. The virtual university approach. Ocean & coastal management. 2002 Jan 1;45(9-10):709-18. doi:10.1016/S0964-5691(02)00095-9
5
Koka A, Suppan L, Cottet P, Carrera E, Stuby L, Suppan M. Teaching the National Institutes of Health Stroke Scale to Paramedics (E-Learning vs Video): Randomized Controlled Trial. Journal of Medical Internet Research. 2020;22(6):e18358. DOI: 10.2196/18358
6
Al-Fraihat D, Joy M, Sinclair J. Evaluating E-learning systems success: An empirical study. Computers in Human Behavior. 2020 Jan 1;102:67-86. doi:10.1016/j.chb.2019.08.004
7
Ortega-Auquilla D, Fajardo-Pacheco I, Cabrera-Vintimilla J, Siguenza-Garzón P. A comprehensive overview on the fundamentals of curriculum development: understanding key interrelated theoretical aspects. Revista Boletín Redipe. 2019 Nov 1;8(11):148-68. doi:10.36260/rbr.v8i11.866
8
Wraga WG. Understanding the Tyler rationale: Basic Principles of Curriculum and Instruction in historical context. Espacio, Tiempo y Educación. 2017 Jul 1;4(2):227-52. doi:10.14516/ete.156
9
Ansyari MF. Developing a rubric for assessing pre-service English teacher struggles with instructional planning. Cogent Education. 2018 Jan 1;5(1):1507175. doi:10.1080/2331186X.2018.1507175
10
Klein MF. A perspective on the gap between curriculum theory and practice. Theory into Practice. 1992 Jun 1;31(3):191-7. doi.org/10.1080/00405849209543542.
11
Musiał K, Kazienko P. Social networks on the internet. World Wide Web. 2013 Jan 1;16(1):31-72. DOI: 10.1007/s11280-011-0155-z
12
Halevy A, Ferrer CC, Ma H, Ozertem U, Pantel P, Saeidi M, Silvestri F, Stoyanov V. Preserving Integrity in Online Social Networks. arXiv preprint arXiv:2009.10311. 2020 Sep 22. DOI: 10.1386/ajms.6.2.207_1
13
Villi M, Noguera-Vivo JM. Sharing media content in social media: The challenges and opportunities of user-distributed content (UDC). Journal of Applied Journalism & Media Studies. 2017 Jun 1;6(2):207-23. DOI: 10.1386/ajms.6.2.207_1
14
Komasi M, aliabadi K, zareii zavaraki E. Comparing The Method of Teaching Through Social Network And Face Training And Its Impact On The Level Of Learning And Retention Of Adult Students In The Social Sciences. Educ Strategy Med Sci. 2019; 11 (5) :25-32. doi: 10.29252/edcbmj.11.05.03
15
Dartaj F, Rajabian M, Asadi R. Study of the relationship between the use of virtual social networks and the quality of learning experiences in students. Journal of Research in Educational Systems, 2016; 10(33): 212-229.
16
Mirkamali S, arjmandnia A, Nasirian A. Surveying the Feasibility for Holding E-learning Courses for Students with Physical Disability in Retarded Student Schools in Kerman. TLR. 2015; 2 (5) :79-96
17
Assareh, Ph.D. A R, Modaresi Saryazdi A, Bahadoran, Ph.D. H R. Evaluation of the Implementation of Smart Schools Program in Yazd Based on CIPP Model. QJFR. 2015; 11 (4) :37-55.
18
Cooze M, Barbour M. Learning Styles: A Focus Upon E-learning Practices and Pedagogy and Their Implications for Designing E-learning for Secondary School Students in Newfoundland and Labrador. Malaysian Online Journal of Instructional Technology. 2005;2(1):1823-1144
19
Coopasami M, Knight S, ́ Pete M. e-Learning readiness amongst nursing students at the Durban University of Technology. health sa gesondheid. 2017;22(1):300-6. doi:10.1016/j.hsag.2017.04.003
20
Hendricson WD, Panagakos F, Eisenberg E, McDonald J, Guest G, Jones P, Johnson L, Cintron L. Electronic curriculum implementation at North American dental schools. Journal of dental education. 2004 Oct;68(10):1041-57. doi:10.1002/j.0022-0337.2004.68.10.tb03851.x
21
Greenhow C. Online social networks and learning. On the horizon. 2011 Feb 1. DOI: 10.1108/10748121111107663
22
Lone SA, Ahmad A. COVID-19 pandemic–An African perspective. Emerging Microbes & Infections. 2020 May 28:1-28. doi:10.1080/22221751.2020.1775132
23
Subedi S, Nayaju S, Subedi S, Shah SK, Shah JM. Impact of E-learning during COVID-19 pandemic among nursing students and teachers of Nepal. Intl J of Sci Healthcare Res. 2020;5(3):68-76. doi:inrein.com/10.4444/ijshr.1003/495
24
Regmi K, Jones L. A systematic review of the factors–enablers and barriers–affecting e-learning in health sciences education. BMC medical education. 2020 Dec;20:1-8. doi:10.1186/s12909-020-02007-6
25
ORIGINAL_ARTICLE
The Effects of Audio-Only and Audio-Video Materials on Listening Comprehension and Critical Thinking among Dental Students: A Focus Group Analysis
Background: Listening is a fundamental skill in learning a second language and improving speaking proficiency. Despite the growing tendency among EFL teachers to test listening comprehension using computer-based audiovisual materials, the reported effects have been contradictory. This study aimed to compare students’ comprehension levels in audio-only and audio-video listening tests and their correlation with critical thinking abilities. Methods: This was a quasi-experimental study. Participants included 53 second and third year students at the Dental School of Babol University of Medical Sciences in 2018-2019 academic year. They were selected using convenience sampling, and answered 20 multiple-choice test items after listening to three different passages. The test was repeated in audio-video format after a two-week interval. In addition, the participants were administered a California Critical Thinking Skills test following the listening test. Results: The t-test results indicated that the students’ level of comprehension was significantly higher in the audio-video listening test compared to the audio-only test (t=-9.030, df=52, P<0.05). A notable relationship was also observed between students’ performance in listening tests and their level of critical thinking. Given the results of the two tests, this relationship was found to be stronger in the audio-video test (r=0.353) than in the audio-only listening test (r=0.313). Conclusion: Audio-video materials in listening tests appear to be more conducive to student comprehension, especially among those with higher critical thinking abilities. The findings in this study necessitate further assessment of the factors contributing to the learning process.
https://ijvlms.sums.ac.ir/article_47066_3341044498be2c4f4d4f03032cb8e566.pdf
2020-12-01
215
223
10.30476/ijvlms.2020.86920.1045
Audio
Audio-video
Listening comprehension
Critical thinking
dentistry
Zahra
Ahmadpour Kasgari
z.ahmadpour@umz.ac.ir
1
Department of English Language Teaching and Literature, Faculty of Humanities, University of Mazandaran, Babolsar, Iran
LEAD_AUTHOR
Yalda
Abdollahi
gharibee0018@gmail.com
2
Department of English Language Teaching and Literature, Faculty of Humanities, University of Mazandaran, Babolsar, Iran
AUTHOR
Shirin
Abadikhah
abadikhah@umz.ac.ir
3
Department of English Language Teaching and Literature, Faculty of Humanities, University of Mazandaran, Babolsar, Iran
AUTHOR
Hamouda A. An investigation of listening comprehension problems encountered by Saudi students in the EL listening classroom. International Journal of Academic Research in Progressive Education and Development. 2013 Apr;2(2):113-55.
1
Hsiao HS, Chang CS, Lin CY, Chen B, Wu CH, Lin CY. The development and evaluation of listening and speaking diagnosis and remedial teaching system. British Journal of Educational Technology. 2016 Mar;47(2):372-89. doi:10.1111/bjet.12237.
2
Sulaiman N, Muhammad AM, Ganapathy NN, Khairuddin Z, Othman S. A Comparison of Students' Performances Using Audio Only and Video Media Methods. English Language Teaching. 2017;10(7):210-5. doi:10.5539/elt.v10n7p210.
3
Taylor L, Geranpayeh A. Assessing listening for academic purposes: Defining and operationalising the test construct. Journal of English for Academic Purposes. 2011 Jun 1;10(2):89-101. doi:10.1016/j.jeap.2011.03.002.
4
Vandergrift L. Second language listening: Listening ability or language proficiency?. The modern language journal. 2006 Mar;90(1):6-18. doi:10.1111/j.1540-4781.2006.00381.x.
5
Woottipong K. Effect of using video materials in the teaching of listening skills for university students. International Journal of Linguistics. 2014 Jul 1;6(4):200. doi:10.5296/ijl.v6i4.5870.
6
Başal A, Gülözer K, Demir İ. Use of video and audio texts in EFL listening test. Journal of Education and Training Studies. 2015 Aug 27;3(6):83-9. doi:10.11114/jets.v3i6.1001.
7
Nation P, Newton J. Teaching ESL/EFL listening and speaking. London, England: Routledge; 2009. doi:10.4324/9780203891704
8
Vandergrift L. Recent developments in second and foreign language listening comprehension research. Language teaching. 2007 Jul 1;40(3):191. doi:10.1017/s0261444807004338.
9
Vandergrift L. 1. Listening to learn or learning to listen?. Annual review of applied linguistics. 2004 Mar 1;24:3. doi:10.1017/s0267190504000017.
10
Canning-Wilson C, Wallace J. Practical aspects of using video in the foreign language classroom. The Internet TESL Journal. 2000 Nov;6(11):36-1.
11
Wagner E. The effect of the use of video texts on ESL listening test-taker performance. Language testing. 2010 Oct;27(4):493-513. doi:10.1177/0265532209355668.
12
Feak, C. B., & Salehzadeh, J. Challenges and issues in developing an EAP video listening placement assessment: A view from one program. English for Specific Purposes. 2001;20, 477-493. doi:10.1016/S0889-4906(01)00021-7
13
Chun DM, Plass JL. Effects of multimedia annotations on vocabulary acquisition. The modern language journal. 1996 Jun;80(2):183-98. doi:10.1111/j.1540-4781.1996.tb01159.x.
14
Sadoski M, Paivio A. A dual coding theoretical model of reading. Theoretical models and processes of reading. 2004;5:1329-62. doi:10.1598/0872075028.47
15
Diao Y, Chandler P, Sweller J. The effect of written text on comprehension of spoken english as a foreign language. Am J Psychol. 2007;120(2):237. doi:10.2307/20445397.
16
Sweller J. Implications of cognitive load theory for multimedia learning. The Cambridge handbook of multimedia learning. 2005 Aug 15;3(2):19-30. doi:10.1017/CBO9780511816819.003
17
Mayer RE. Multimedia learning: Are we asking the right questions?. Educational psychologist. 1997 Jan 1;32(1):1-9. doi:10.1207/s15326985ep3201_1.
18
Ginther A. Context and content visuals and performance on listening comprehension stimuli. Lang Test. 2016;19(2):133-67. doi:10.1191/0265532202lt225oa.
19
Baltova I. The impact of video on the comprehension skills of core french students. Can Modern Lang Rev. 1994;50(3):507-31. doi:10.3138/cmlr.50.3.507.
20
Sueyoshi A, Hardison DM. The role of gestures and facial cues in second language listening comprehension. Language Learning. 2005 Dec;55(4):661-99. doi:10.1111/j.0023-8333.2005.00320.x.
21
Coniam D. The use of audio or video comprehension as an assessment instrument in the certification of English language teachers: A case study. System. 2001;29(1):1-14. doi:10.1016/s0346-251x(00)00057-9. 23.
22
Suvorov, R. S. Context visuals in L2 listening tests: The effectiveness of photographs and video vs. audio-only format. 2008.
23
Brett, P. A comparative study of the effects of the use of multimedia on listening comprehension. System. 1997; 25(1), 39-53. doi:10.1016/S0346-251X(96)00059-0
24
Hernandez, S. S. The effects of video and captioned text and the influence of verbal and spatial abilities on second language listening comprehension in a multimedia learning environment. New York University. 2004.
25
Cubilo J, Winke P. Redefining the L2 listening construct within an integrated writing task: Considering the impacts of visual-cue interpretation and note-taking. Lang Assess Q. 2013;10(4):371-97. doi:10.1080/15434303.2013.824972
26
Hashemi MR, Zabihi R. Does critical thinking enhance EFL learners' receptive skills? J Lang Teach Res. 2012;3(1). doi:10.4304/jltr.3.1.172-179.
27
Scriven M, Paul R. Defining critical thinking: A draft statement for the national council for excellence in critical thinking. Manila, Philippines; 1987; Available from: http://www.criticalthinking.org/University/univlibrary/library.nclk.
28
Belecina RR, Ocampo JJM. Effecting change on students' critical thinking in problem solving. EDUCARE. 2018;10(2). doi:10.15408/es.v10i1.7218
29
Angelo TA. Beginning the dialogue: Thoughts on promoting critical thinking: Classroom assessment for critical thinking. Teaching of Psychology; 1995. p. 6-7. doi:10.1207/s15328023top2201_1
30
Lai ER. Critical thinking: A literature review. 2011; Available from: https://images.pearsonassessments.com/images/tmrs/CriticalThinkingReviewFINAL.pdf.
31
Ten Dam G, Volman M. Critical thinking as a citizenship competence: Teaching strategies. Learn Instruc. 2004;14(4):359-79. doi:10.1016/j.learninstruc.2004.01.005.
32
Hashemi MR, Ghanizadeh A. Critical discourse analysis and critical thinking: An experimental study in an EFL context. System. 2012 Mar 1;40(1):37-47. doi:10.1016/j.system.2012.01.009
33
Bonk CJ. Online training in an online world. Bloomington, IN: CourseShare.com; 2002 Jan.
34
Walker G. Critical thinking in asynchronous discussions. International Journal of Instructional Technology and Distance Learning. 2005;2(6):15-22.
35
Ahmadpour Z, Khaaste R. Writing Behaviors and Critical Thinking Styles: The Case of Blended Learning. doi:10.5782/2223-2621.2017.20.1.5
36
Kolour DM, Yaghoubi A. The impact of teaching critical thinking tasks on coherence in argumentative essay writing among EFL learners. Mediterranean journal of social sciences. 2015 Nov 2;6(6):460. doi:10.5901/mjss.2015.v6n6p460
37
Malmir A, Shoorcheh S. An investigation of the impact of teaching critical thinking on the Iranian EFL learners' speaking skill. Journal of Language Teaching and Research. 2012 Jul 1;3(4):608-17. doi:10.4304/jltr.3.4.608-617
38
ORIGINAL_ARTICLE
An investigation into the Factors Affecting Perceived Enjoyment of Learning in Augmented Reality: A Path Analysis
Background: Teaching and learning are undergoing a dramatic transformation thanks to the technological advances in areas like Augmented Reality (AR). The main purpose of this study was to investigate the factors affecting perceived enjoyment of learning in AR. Methods: This was an applied research in terms of purpose and a descriptive and correlative study in terms of methodology. The statistical population included all undergraduate students at Payam-e Noor University in western areas of Iran during 20192020 academic year (n=24000). A sample of 600 students were selected through randomized multistage cluster sampling based on Cochran’s formula. The participants used an AR application, and then completed an integrated questionnaire, which was a combination of 5 questionnaires (flow, perceived enjoyment, need for cognition, cognitive absorption and self-efficacy). A total of 556 questionnaires were returned. The data were analyzed through path analysis using Amos 22, Lisrel 8.50 and Spss 22. Results: Among the direct effects, self-efficacy had the highest effect on perceived enjoyment (0.28) and need for cognition had the lowest effect on self-efficacy (0.16). On the other hand, cognitive absorption had the highest indirect effect on perceived enjoyment (0.13) and the lowest indirect effects were those of the need for cognition on flow (0.04) and self-efficacy on flow (0.04). The highest total effect was related to the effect of self-efficacy on perceived enjoyment (0.28) and the lowest one was related to the effect of selfefficacy on flow (0.04). Conclusion: The results obtained for the fit indices of the proposed model showed that it had a good fit with the data collected from the respondents (X2=22.14, P=0.179, CFI=0.99, GFI=0.99, AGFI=0.98 & RMSEA=0.023). Accordingly, this model can provide educators and education leaders with critical information for improving learning outcomes.
https://ijvlms.sums.ac.ir/article_47089_e6f921befc5be7409de19b240fb488ff.pdf
2020-12-01
224
235
10.30476/ijvlms.2020.47089
Augmented reality
Cognitive absorption
Need for cognition
Self-efficacy
Flow
Perceived enjoyment
Maryam
Darvishi
m.darvishi61@yahoo.com
1
Department of Educational Sciences, Payame Noor University, Tehran, Iran
LEAD_AUTHOR
Mohammad Hassan
Seif
hassanseif@gmail.com
2
Department of Educational Sciences, Payame Noor University, Tehran, Iran
AUTHOR
Mohammad Reza
Sarmadi
ms84sarmadi@yahoo.com
3
Department of Educational Sciences, Payame Noor University, Tehran, Iran
AUTHOR
Mehran
Farajollahi
farajollahim@yahoo.com
4
Department of Educational Sciences, Payame Noor University, Tehran, Iran
AUTHOR
Serio AD, Ibanez MB, & Kloos CD. Effect of an augmented reality system on students’ motivation for a visual art course. Computers and education. 2013; 68: 586-596.
1
Bujak KR, Radu I, Catrambone R, MacIntyre B, Golubski G, & Zheng R. A psychological perspective on augmented reality in the mathematics Classroom. Computer and education.2013; 68: 536-544. doi:10.1016/j.compedu.2013.02.017
2
Rauschnabel PA, Brem A, & Ivens, B S. Who will buy smart glasses? Empirical results of two pre-market-entry studies on the role of personality in individual awareness and intended adoption of Google Glass wearables. Computers in Human Behavior. 2015; 49 :635-647.doi:10.1016/j.chb.2015.03.003
3
Patrick RPL, Zheng J, Guo Z & Li J. Speed reading on virtual reality and augmented reality. Computers & Education.2018;125:240-245. doi:10.1016/j.compedu.2018.06.016
4
Hwang WY, & Hu SS. Analysis of peer learning behaviors using multiple representations in virtual reality and their impacts on geometry problem solving. Computers & Education. 2013;62: 308–319. doi:10.1016/j.compedu.2012.10.005
5
Fransson BA, Chen C Y ,Noyes J A & Ragle CA. Instrument Motion Metrics for Laparoscopic Skills Assessment in Virtual Reality and Augmented Reality. Veterinar Surgery, American College of Veterinary Surgeons. 2016; 1- 9. doi:10.1111/vsu.12483
6
Chang HY, Wu HK & Hsu YS. Integrating a mobile augmented reality activity to contextualize student learning of a socioscientific issue. British Journal of Educational Technology. 2013;3: 95-99.doi:10.1111/j.1467-8535.2012.01379.x
7
Kesima M, OzarslanbY. Augmented reality in education: current technologies and the potential for education. Procedia - Social and Behavioral Sciences.2012; 47: 297 – 302.
8
Davis FD, Bagozzi RP & Warshaw PR. Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology.1992; 22 (14): 1111-1132.
9
Mubuke F, Ogenmungu C, Mayoka KG, Masaba AK & Andrew W. The predictability of perceived enjoyment and its effect on the intention to use mobile learning systems. Asian Journal of Computer Science and Information Technology.2017;7(1):1-7. http://dx.doi.org/10.15520/ajcsit.v6i8.51
10
Huang, Y. Empirical Analysis on Factors Effecting Mobile Learning Acceptance in Higher Engineering Education[dissertation].[ Tennessee ]:University of Tennessee;2014.
11
Nguyen D. Understanding Perceived Enjoyment and Continuance Intention in Mobile Games[dissertation].[Aalto]: Aalto University;2015.
12
Wong WT, & Huang NTN. The effects of eLearning system service quality and users' acceptance on organizational learning. International Journal of Business and Information. 2015; 6(2): 205-225.
13
Jambulingam M.Behavioral intention to adopt mobile technology among tertiary students. World Applied Sciences Journal. 2013 ;22(9): 1262-1271.
14
Yi, M. Y., & Hwang, Y. Predicting the use of web-based information systems: Self efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal Human-Computer Studies. 2003;59: 431-449. doi:10.1016/S1071-5819(03)00114-9
15
Ahmadi Deh Ghotbadini, M. & Moshkani, M. The Effect of Computer Self-Efficacy and Perceived Enjoyment on Davis, Technology Acceptance Model Constructs. Journal of Psychology. 2011; 15: 58-75.
16
Gou YM, Ro YK. Capturing Flow in the Business Classroom. Decision Sciences Journal of Innovative Education.2008; 6(2):437-462. DOI:10.1111/j.1540-4609.2008. 00185.x
17
WeibelD, and Wissmath B. Immersion in Computer Games: The Role of Spatial Presence and Flow. International Journal of Computer Games Technology.2011; 2011, Article ID 282345, 14 pages doi:10.1155/2011/282345
18
Min Huang Y & Hsuan Lin P. Evaluating students’ learning achievement and flow experience with tablet PCs based on AR and tangible technology in u-learning. Library Hi Tech.2017;35(4):602-614.doi:10.1108/LHT-01-2017-0023
19
Hatlevik OE, Throndsen I, Loi M & Gudmundsdottir GB. Students’ ICT self-efficacy and computer and information literacy: Determinants and relationships. Computers & Education.2018;118:107-119.doi:10.1016/j.compedu.2017.11.011
20
Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review.1977; 84(2):191-215. doi:10.1037/0033-295X.84.2.191
21
Hwang Y, Lee Y & Shin DH. The role of goal awareness and information technology self-efficacy on job satisfaction of healthcare system users. Behavior & Information Technology.2016; 35(7):548-558. doi:10.1080/0144929X.2016.1171396
22
Sun JCY & Rueda R. Situational interest, computer self-efficacy and self-regulation: their effect on student engagement in distance education.British Journal of Educational Technology.2012; 43(2):191-204. doi:10.1111/j.1467-8535.2010.01157.x
23
Elias, S. M., & Loomis, R. J. Utilizing need for cognition and perceived self-efficacy to predict academic performance. Journal of Applied Social Psychology. 2002. 32(8): 1687-1702. doi:10.1111/j.1559-1816.2002.tb02770.x
24
Weniger, S., Loebbecke, C. Cognitive absorption: literature review and suitability in the context of hedonic IS usage. Department of business, media and technology management, University of Cologne, Germany. 2007.
25
Boyle EA, Connolly TM., Hainey T & Boyle JM. Engagement in digital entertainment games: A systematic review. Computers in Human Behavior.2012; 5(28), no.3:771-780 ISSN 0747-5632. DOI: http://dx.doi.org/10.1016/j.chb.2011.11.020.
26
Csikszentmihalyi M & Csikszentmihalyi I. Optimal experience. Psychological studies of flow in Consciousness. Cambridge: Cambridge University Press; 1988.
27
Agarwal R, & Karahanna E. Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly.2000;24(4):665-694.doi:10.2307/3250951
28
Huprich, j. Enhancing learner flow and cognitive absorption. 2019; Available from: https://experience.exceedlms.com/student/activity/453887
29
Cacioppo JT & Petty RE.The need for cognition. Journal of Personality and Social Psychology.1982; 42:116-131. http://dx.doi.org/10.1037/0022-3514.42.1.116
30
Petty R E, Brinol P, Loersch C & McCaslin,M J. The need for cognition. In M. R. Leary & R. H. Hoyle(Eds.), Handbook of individual differences in social behavior. New York: Guilford Press;2009.
31
Negahdari S, Seif MH, Farajollahi M & Rastegar A. Providing a Causal Model of Perceived Learning on the Basis of Digital Games. Quarterly Journal of Research in School and Virtual Learning. 2018;21(1): 105-119.
32
Li, Dahui and Browne, Glenn. The Role of Need for Cognition in Online Flow Experience: An Empirical Investigation. 2004; AMCIS, Proceedings.386.
33
Cacioppo JT, Petty RE & Kao C F. The efficient assessment of need for cognition. Journal of Personality Assessment.1984; 48: 306-307. http://dx.doi.org/10.1207/s15327752jpa4803_13
34
Sadowski CJ. An examination of the short need for cognition scale. Journal of Psychology.1993; 127:451-454. http://dx.doi.org/10.1080/00223980.1993.9915581
35
Rastegar, A. Presenting a Causal Model of Relationships between Need for Cognition and Cognitive Engagement With Emphasis on the Mediating Role of Achievement Goals and Academic Emotion. Social Cognition. 2017;6(1): 8-26.
36
Kazuki, Y., Asakawa, K., Taro, Y., Satoshi, S., Daisuke, S., Yui, M. The Flow State Scale for Occupational Tasks: Development, Reliability, and Validity. Hong Kong Journal of Occupational Therapy. 2013;23: 54-61. http://dx.doi.org/10.1016/j.hkjot.2013.09.002
37
Reychav, I., Dezhi, W. Are your users actively involved? A cognitive absorption perspective in mobile training. Computers in Human Behavior. 2015; 44 :335–346. doi:10.1016/j.chb.2014.09.021
38
Mahat, Mohd Ayub AF & Wong SL. An assessment of students’ mobile self-efficacy, readiness and personal innovativeness towards mobile learning in higher education in Malaysia. Social and behavioral sciences.2012; 64:284-290. doi:10.1016/j.sbspro.2012.11.033
39
Elias SM. & Loomis RJ. Utilizing Need for Cognition and Perceived Self-Efficacy to Predict Academic Performance. Journal of Applied Social Psychology.2002; 32(8): 1687-1 702. doi:10.1111/j.1559-1816.2002.tb02770.x
40
ORIGINAL_ARTICLE
Efficiency Evaluation of E-Learning Courses at Payam Noor University Based on Learning Usability Criteria
Background: The aim of this study is to evaluate e-learning systems at Payam Noor University (PNU) based on learning usability criteria. Methods: This was an applied research in terms of purpose and a descriptive survey in terms of data analysis. The statistical population included 2600 undergraduate and graduate students at the Shahriar branch of PNU using e-learning methods in 2019-2020 academic year. The sample size was estimated using Morgan table. A total of 335 participants were selected through stratified sampling. The validity of questionnaire was verified by consulting 25 experts in distance education using Delphi method, and the reliability of the total questionnaire, as measured by Cronbach’s alpha, was found to be (α=0.73). Statistical analysis was conducted using SPSS 25. Results: In the e-learning courses offered by PNU, the components of “visibility”, “flexibility”, “course management”, “accessibility”, “consistency and functionality”, “memorability”, “completeness” and “aesthetics” are in a favorable situation (P<0.001). However, the components of “error prevention”, “interactivity, feedback and help”, “assessment strategy” and “reducing redundancy” are not in a favorable situation (P>0.05). Conclusion: Educational institutions should not merely focus on content in their design of e-learning courses. They should also incorporate interactive and group exercises so that students can understand educational materials, and actively and creatively engage in the learning process based on their personal experiences.
https://ijvlms.sums.ac.ir/article_47090_fa790c38cd43ae65f994e0c20a6626a0.pdf
2020-12-01
236
245
10.30476/ijvlms.2020.47090
Efficiency
E-Learning
Usability
Payam Noor University
Mahdi
Mahmodi
mahmodi86@gmail.com
1
Department of Educational Sciences and Psychology, Payam Noor University, Tehran, Iran
LEAD_AUTHOR
Marjan
Masomifard
mmf587@gmail.com
2
Department of Educational Sciences and Psychology, Payam Noor University, Tehran, Iran
AUTHOR
Nazila
KhatibZanjani
drkhatibzanjani@yahoo.com
3
Department of Educational Sciences and Psychology, Payam Noor University, Tehran, Iran
AUTHOR
Manije
Ahmadi
manijehahmadi@gmail.com
4
Department of Educational Sciences and Psychology, Payam Noor University, Tehran, Iran
AUTHOR
Martinez-Caro E. Factors Affecting Effectiveness in E-Learning: An Analysis in Production Management Courses. Computer Applications in Engineering Education.2011; 19(3):572 – 581. doi:10.1002/cae.20337
1
Hubalovsky S, Hubalovska M, Musilek M. Assessment of the influence of adaptive E-learning on learning effectiveness of primary school pupils. Computers in Human Behavior. 2019 Mar 1;92:691-705. doi:10.1016/j.chb.2018.05.033
2
Choi H. A problem-based learning trial on the Internet involving undergraduate nursing students. Journal of Nursing Education. 2003 Aug 1;42(8):359-63. doi:10.3928/0148-4834-20030801-07
3
Holmes B, Gardner J. E-learning: Concepts and practice. Sage; 2006.
4
Liao HL, Lu HP. Richness versus parsimony antecedents of technology adoption model for E-learning websites. InInternational Conference on Web-Based Learning 2008 Aug 20 (pp. 8-17). Springer, Berlin, Heidelberg. doi:10.1007/978-3-540-85033-5_2.
5
Vanitha V, Krishnan P, Elakkiya R. Collaborative optimization algorithm for learning path construction in E-learning. Computers & Electrical Engineering. 2019 Jul 1;77:325-38. doi:10.1016/J.COMPELECENG.2019.06.016
6
Mahmodi, M. Measuring Electronic Learning Readiness of Semnan University Students. Higher Education Letter, 2015; 8(31): 113-134.
7
Nikolić V, Petković D, Denić N, Milovančević M, Gavrilović S. Appraisal and review of e-learning and ICT systems in teaching process. Physica A: Statistical Mechanics and its Applications. 2019 Jan 1;513:456-64. doi:10.1016/j.physa.2018.09.003
8
Firipis A, Chandrasekaran S, Joordens M. Influence of Critical Thinking on Creativity When Using Mobile Devices for Learning. Asian Education Studies, 2018; 3(2), p40. doi:10.20849/aes.v3i2.366
9
Erhel S, Jamet E. Digital game-based learning: Impact of instructions and feedback on motivation and learning effectiveness. Computers & education. 2013 Sep 1;67:156-67. doi:10.1016/j.compedu.2013.02.019
10
Cinquin PA, Guitton P, Sauzéon H. Online e-learning and cognitive disabilities: A systematic review. Computers & Education. 2019 Mar 1;130:152-67. doi:10.1016/j.compedu.2018.12.004.
11
Spylka M, Sofianopoulou CH. E-Learning, a dynamic tool for the cognitive development of primary school pupils in Greece. InINTED2016 Proceedings 2016 (pp. 998-1007). IATED. doi:10.21125/inted.2016.1228
12
Yazdani F, Ebrahimzadeh E, Zandi B, Aleepoor B, Zare H. Effectiveness of the Electronic Learning System at the virtual college of Oloome Hadees. The Journal of New Thoughts on Education, 2010; 6(3): 137-183. doi:10.22051/jontoe.2010.215
13
Lughofer E. On-line active learning: a new paradigm to improve practical useability of data stream modeling methods. Information Sciences. 2017 Nov 1;415:356-76. doi:10.1016/j.ins.2017.06.038
14
Karahoca D, Karahoca A, Karaoglu A, Gulluoglu B, Arifoglu E. Evaluation of web based learning on student achievement in primary school computer courses. Procedia-Social and Behavioral Sciences. 2010 Jan 1;2(2):5813-9. doi:10.1016/j.sbspro.2010.03.948
15
Fernandez A, Insfran E, Abrahão S. Usability evaluation methods for the web: A systematic mapping study. Information and software Technology. 2011 Aug 1;53(8):789-817. doi:10.1016/j.infsof.2011.02.007
16
Omoda-Onyait G, Lubega JT. E-learning readiness assessment model: A case study of higher institutions of learning in Uganda. InInternational Conference on Hybrid Learning 2011 Aug 10 (pp. 200-211). Springer, Berlin, Heidelberg. doi:10.1007/978-3-642-22763-9_19
17
Paechter M, Maier B, Macher D. Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers & education. 2010 Jan 1;54(1):222-229. doi:10.1016/j.compedu.2009.08.005
18
Esmaeeli H, Rahmani Sh, Kazemi A, Aliahmadi M. Evaluation of E-Learning of the virtual learning program from the student's point of view. Public Management Research. 2016;9(34): 203-222. doi:10.22111/jmr.2017.3109
19
Khatib Zanjani N. The Evaluation of E-Learning in Payame Noor University and Compare with Other Selected Universities in the World and Iran. Quarterly Journal of Research in School and Virtual Learning. 2017; 5:81-94.
20
Aman zadeh A, Al Noman FM. studying the influence of training based on web and computer and mobile learning on students' critical thinking skills and creative thinking in students of Mazandaran province universities. Research in School and Virtual Learning Journal. 2015; 3(9): 57-68.
21
Anarinejad, A., Mohammadi, M. The Practical Indicators for Evaluation of E-Learning in Higher Education in Iran. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 2020; 5(1): 11-25.
22
Zeytoonli AH, Rezaei Soufi M. Study the Effectiveness of E-Learning Courses in Payame Noor University, Communication Management in Sports Media, 2017; 4(13): 48-55.
23
Tseng M, Lin R, Chen H. Evaluating the effectiveness of e‐learning system in uncertainty", Industrial Management & Data Systems, 2011; 111(6), 869-889. doi:10.1108/02635571111144955
24
Vahidi, H. Designing a Domestic E-readiness Assessment Model for the Deployment of Mobile Learning. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 2020; 4(1): 1-10.
25
Farazkish, M., Montazer, G. E-Learning Readiness among Faculty Members of Iranian Universities: A Survey of 23 Universities. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 2019; 10(4): 54-64. doi:10.30476/ijvlms.2019.84302.1003
26
Rafiei M, Ghaffari H, Khorami M. Evaluating the Effectiveness of E-Learning Method in Human Resource Education (Case Study of Markazi Province PNU). Research in School and Virtual Learning. 2017; 4(16), 71-84.
27
ORIGINAL_ARTICLE
The Challenges of Implementing E-learning Courses in Iran’s Higher Education: A University Management Perspective
Background: Integrating e-learning into the higher education of developing countries entails identifying the challenges of setting up e-learning courses in these countries. The present article aimed to identify these challenges in Iran. For this purpose, Isfahan University was selected as a leading institution in innovative developments. The University launched its e-learning courses in 2012, and the associated challenges were evaluated from the viewpoints of university officials at the time. Methods: This research was a qualitative study. Based on the literature review, a guideline devised by Ojo and Awiah was used for semi-structured interviews. This instrument categorizes the technological challenges in developing countries into strategic, operational, and thematic limitations. Further, researchers divided the thematic problems into two subgroups: administrative and cultural–legal problems. Then, they interviewed 10 university officials who were course supervisors during 2012-2013 and were practically involved in addressing the problems of organizing these courses in that period. After gathering data, an analysis was conducted by coding the interviews. Then the challenges and their solutions were determined. Results: The major challenges in setting up e-learning courses were lack of strategic insight and planning for using e-learning courses in line with the University’s mission (strategic challenge) and lack of active participation by instructors and learners in e-learning due to limited face-to-face interactions between them in online classes (operational challenge). Conclusions: Research findings pointed to the need for a change in outlook on the part of authorities and policymakers for the purpose of identifying and removing the existing challenges of implementing e-learning in higher education institutions.
https://ijvlms.sums.ac.ir/article_47065_fb3406c26f673c2ad929aaa7639fc4a1.pdf
2020-12-01
246
255
10.30476/ijvlms.2020.47065
E-Learning
Challenges
Developing countries
Solutions
Isfahan University
Seyyed Majid
Abdellahi
magidabdellahi@gmail.com
1
Department of Educational Sciences, Payame Noor University, Tehran, Iran
LEAD_AUTHOR
Amir
Bagherzadegan
bagherzadeganamir@yahoo.com
2
Department of Law, Payame Noor University, Tehran, Iran
AUTHOR
Zohreh
Aghakasiri
zohrehaghakasiri@gmail.com
3
Department of Educational Sciences, Yazd Branch, Islamic Azad University, Yazd, Iran
AUTHOR
Garrison DR. E-learning in the 21st century: A framework for research and practice (2nd ed.). New York: Taylor & Francis; 2011. doi:10.4324/9780203838761
1
Sangrà A, Vlachopoulos, D., & Cabrera, N. Building an inclusive definition of e-learning: An approach to the conceptual framework. The International Review of Research in Open and Distributed Learning. 2012;13(2):145-59. doi:10.19173/irrodl.v13i2.1161
2
Al-Ghaith W, Sanzogni, L. and Sandhu, K. Factors influencing the adoption and usage of online services in Saudi Arabia. The Electronic Journal on Information Systems in Developing Countries. 2010;40(1):1-32 doi:10.1002/j.1681-4835.2010.tb00283.x
3
Grace Ssekakubo HS, Gary Marsden, editor. issues of adoption: Have e-learning management systems fulfilled their potential in developing countries? Annual Conference of the South African Institute of Computer Scientists and Information Technologists; 2011 October 3-5; Cape Town, South Africa. doi:10.1145/2072221.2072248
4
Mubarak M Alkharang GG. E-learning in Higher Educational Institutions in Kuwait: Experiences and Challenges. International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 4, 2013 doi:10.14569/IJACSA.2013.040401
5
Touray A, Salminen, A., & Mursu, A. ICT Barriers and Critical Success Factors in Developing Countries. The Electronic Journal of Information Systems in Developing Countries. 2013;7(1):1-17. doi:10.1002/j.1681-4835.2013.tb00401.x
6
Tarus JK, Gichoya, D., & Muumbo, A. Challenges of implementing e-learning in Kenya: A case of Kenyan public universities. . The International Review of Research in Open and Distributed Learning. 2015;16(1). doi:10.19173/irrodl.v16i1.1816
7
Aldowah HG, Samar & Umar, Irfan. Instructors' Challenges in Implementing E-Learning in a Public University in Yemen. The Turkish Online Journal of Design, Art and Communication 2018;8: 1138-46. doi:10.7456/1080SSE/155
8
Matti Tedre NB, Seth I. Nyagava. Contextualized IT Education in Tanzania: Beyond Standard IT Curricula Journal of Information Technology Education: Research. 2009 8:101-24. doi:10.28945/162
9
Nawaz AaK, G. M. Demographic implications for the user-perceptions of e-learning in higher education institutions of N-W.F.P, Pakistan. The Electronic Journal on Information Systems inDeveloping Countries. 2010;41(5): 1-17. doi:10.1002/j.1681-4835.2010.tb00294.x
10
Fooladvand, M., & Yarmohammadian, M. H. A comparative study between virtual and traditional approaches in higher education in Iran. Procedia - Social and Behavioral Sciences, 2011 28, 646–650. doi:10.1016/j.sbspro.2011.11.122
11
Feizi KR, Mohammad. e-learning in Iran: problems and solutions by emphasis on higher education. Quarterly journal of Research and Planning in Higher Education 2004;10(3):99 - 120.
12
Ahmadpour A. legal problems on e-learning by emphasis on publication and proliferation right. the 2nd National Online Education Conference; Zahedan, Sistan and Baluchistan University. 2007.
13
Ojo S., Awuah B. Building resource capacity for IT education and education in schools - the case of Botswana. In: Marshall G., Ruohonen M. (eds) Capacity Building for IT in Education in Developing Countries. IFIP — The International Federation for Information Processing. Springer, Boston, MA. 1998 doi:10.1007/978-0-387-35195-7_3
14
Atashak M. Theoretical and Applied Principles of Electronic Learning. Qurterly Journal of Research and Planing in Higher Education. 2007;13(1): 135 – 56.
15
Krefting L. Rigor in qualitative research: The assessment of trustworthiness. American journal of occupational therapy. 1991 Mar 1;45(3):214-22. doi:10.5014/ajot.45.3.214.
16
ORIGINAL_ARTICLE
Factors Affecting a Medical Faculty’s Engagement in Virtual Learning Environments
Background: This study aimed to investigate the intrinsic and extrinsic factors affecting faculty engagement in virtual learning environments at Shiraz University of Medical Sciences (SUMS) in Shiraz, Iran. Methods: In this comparative study, 112 eligible faculty members at SUMS were enrolled in 2018-2019 academic year. The sample was surveyed by a researcher-made questionnaire consisting of 28 items, including 17 questions on intrinsic factors (familiarity with e-learning, faculty attitudes and human resources) and 11 on extrinsic factors (financial resources, inherent barriers, infrastructural factors and institutional support). The reliability of the research instrument, as measured by internal consistency and Cronbach’s alpha, stood at 0.92. It was measured at 0.87 and 0.92 for extrinsic and intrinsic factors respectively. The CVR and CVI values were found to be 0.6 and 0.8 respectively. One-sample t-test was applied to compare the mean scores of the intrinsic and extrinsic factors with the hypothetical mean, and to determine the ranking of the factors. Results: In order of their impact, the intrinsic and extrinsic factors included inadequate financial resources (P=0.566) lack of familiarity with electronic learning (P<0.001), inherent barriers such as institutional disbelief in the complementary role of e-learning (P=0.001), infrastructural factors (P<0.001), faculty attitudes (P<0.001), inadequate human resources (P<0.001), and lack of institutional support (P<0.001). Conclusion: University administrators should provide educators with adequate resources for handling new educational environments, remove administrative and structural obstacles, and create motivation among faculty members to use e-learning systems.
https://ijvlms.sums.ac.ir/article_47099_6061e47578d5c75e9363d814abd79786.pdf
2020-12-01
256
264
10.30476/ijvlms.2020.47099
education
Virtual learning environment
Intrinsic and extrinsic factors
Electronic Learning
Mehdi
Vares
mwtechnology@gmail.com
1
Department of Educational Management, School of Economy and Management, Islamic Azad University, Shiraz, Iran
AUTHOR
Maryam
Moalemi
maryam.moalemi@yahoo.com
2
Department of Educational Management, School of Economy and Management, Islamic Azad University, Shiraz, Iran
LEAD_AUTHOR
Manoosh
Mehrabi
mehrabi.manoosh@gmail.com
3
Department of e-Learning in medical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Sim TY, Lau SL, Zipf P, Kimm K. Design and development of a supported tiered software for teaching and learning using a connected mobile learning application. World Applied Sciences Journal. 2014;30(1):247-55. doi: 10.5829/idosi.wasj.2015.30.icmrp.32
1
Khasawneh R, Simonsen K, Snowden J, Higgins J, Beck G. The effectiveness of e-learning in pediatric medical student education. Medical education online. 2016 Jan 1;21(1):29516. doi: 10.3402/meo.v21.29516.
2
Ertmer, P.A., Richardson, J.C., Belland, B., Camin, D., Connolly, P., Coulthard, G., Lei, K. and Mong, C., 2007. Using peer feedback to enhance the quality of student online postings: An exploratory study. Journal of Computer-Mediated Communication, 12(2), pp.412-433. doi:10.1111/j.1083-6101.2007.00331.x
3
Coopasami M, Knight S, ́ Pete M. e-Learning readiness amongst nursing students at the Durban University of Technology. health sa gesondheid. 2017;22(1):300-6. doi:10.1016/j.hsag.2017.04.003
4
Drent M, Meelissen M. Which factors obstruct or stimulate teacher educators to use ICT innovatively?. Computers & Education. 2008 Aug 1;51(1):187-99. DOI: 10.1016/j.compedu.2007.05.001
5
Valdez G. Technology: A catalyst for teaching and learning in the classroom. Retrieved, Feb. 2005;9:2014.
6
Wang Q. A generic model for guiding the integration of ICT into teaching and learning. Innovations in education and teaching international. 2008 Nov 1;45(4):411-9. doi:10.1080/14703290802377307
7
Nazeri N, Dorri S, Atashi A. The Effective Factors on Success of E-learning in Medical Sciences Fields. Journal of Health and Biomedical Informatics. 2017; 4 (2) :98-107 URL: http://jhbmi.ir/article-1-218-fa.html
8
Roodsaz H., Kamalian AR, Amiri M, Ghaemmagami Tabrizi A. Identifying the Factors Affecting the Pattern of Virtual Vocational Education in Iran, Research in Educational Systems, 2017; 11(36): 121-144. doi:10.22034/jiera.2017.51088
9
Kumar N, Rose RC, D’Silva JL. Teachers’ readiness to use technology in the classroom: An empirical study. European Journal of Scientific Research. 2008;21(4):603-16.
10
Anthoine E, Moret L, Regnault A, Sébille V, Hardouin JB. Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health and quality of life outcomes. 2014 Dec;12(1):1-0. doi:10.1186/s12955-014-0176-2
11
Hope J, Hope T. Competing in the third wave: the ten key management issues of the information age. Harvard Business Press; 1997.
12
Sife A, Lwoga E, Sanga C. New technologies for teaching and learning: Challenges for higher learning institutions in developing countries. International journal of education and development using ICT. 2007 Jun 13;3(2):57-67.
13
Panda S, Mishra S. E‐Learning in a Mega Open University: Faculty attitude, barriers and motivators. Educational Media International. 2007 Dec 1;44(4):323-38. doi:10.1080/09523980701680854
14
Oomen-Early J, Murphy L. Self-actualization and e-learning: A qualitative investigation of university faculty’s perceived barriers to effective online instruction. International Journal on E-Learning. 2009 Apr;8(2):223-40.
15
Tedre M, Ngumbuke F, Kemppainen J. Infrastructure, human capacity, and high hopes: A decade of development of e-Learning in a Tanzanian HEI. RUSC. Universities and Knowledge Society Journal. 2010;7(1):7-20.
16
Alsabawy AY, Cater-Steel A, Soar J. IT infrastructure services as a requirement for e-learning system success. Computers & Education. 2013 Nov 1;69:431-51. doi:10.1016/j.compedu.2013.07.035
17
Muñoz Carril PC, González Sanmamed M, Hernández Sellés N. Pedagogical roles and competencies of university teachers practicing in the e-learning environment. International Review of Research in Open and Distributed Learning. 2013;14(3):462-87. doi:10.19173/irrodl.v14i3.1477
18
ORIGINAL_ARTICLE
Blended Teaching/Learning Approach in Medical Schools: Need of the Day in the 21st Century
COVID-19 pandemic has challenged educators to creatively develop teaching and assessment methods that can work effectively and efficiently while maintaining the social distancing and avoiding large gatherings in classrooms and examination halls. To address this state of affairs, several online teaching facilities have been employed and the number of institutions offering web-based courses has increased exponentially. For example, Cambridge University has announced that, until summer of 2021, all the lectures will be delivered online only. However, whereas the solely theory-based courses can be offered online, the theory-pluslaboratory courses must be delivered partly in person since they generally involve handson experiments. To effectively manage the latter situation, the blended teaching/learning approach has emerged as one of the popular options. In the following passages we have attempted to explain the theoretical basis of Blended Learning (BL), its usefulness in teaching/learning activities and the possible challenges in its implementation.
https://ijvlms.sums.ac.ir/article_47021_c61c3ba91f00c05e3ad365f4876ed2b5.pdf
2020-12-01
265
268
10.30476/ijvlms.2020.88050.1055
COVID-19 pandemic
Blended Learning
Online teaching
Clinical teaching
Interprofessional education
Staff Development
Alam
Malik
alamshermalik@hotmail.com
1
International Medical School, Management and Science University, Malaysia
LEAD_AUTHOR
Rukhsana
Malik
rukhsanahussainmalik@hotmail.com
2
International MedicalSchool, Management and Science University, Malaysia
AUTHOR
Ellaway R, Masters K. AMEE Guide 32: e-Learning in medical education Part 1: Learning, teaching and assessment. Med Teach, 2008, 20:455–473. doi:10.1080/01421590802108331
1
Gray K, Tobin J. Introducing an online community into a clinical education setting: A pilot study of student and staff engagement and outcomes using blended learning. BMC Med Educ, 2010, 10:6. doi:10.1186/1472-6920-10-6
2
N. de Jong, J S M Krumeich, D M L Verstegen. To what extent can PBL principles be applied in blended learning: Lessons learned from health master programs, Medical Teacher, 2017, 39:2, 203-211. doi:10.1080/01421 59X.2016.1248915
3
Cooner T. Creating opportunities for students in large cohorts to reflect in and on practice: Lessons learnt from a formative students’ experiences of a technology – enhanced blended learning design. Br J Educ Technol, 2010, 41(2):271–286. doi:10.1111/j.1467-8535.2009.00933.x
4
Sung Y, Kwon I, Rya E. Blended learning on medication administration for new nurses: Integration of e-learning and face-to-face instruction in the classroom. Nurse Educ Today, 2008, 28(8): 943–952. doi: 10.1016/j.nedt.2008.05.007
5
Tan SM, Ladyshewsky RK, Gardner P. Using blogging to promote clinical reasoning and metacognition in undergraduate physiotherapy fieldwork programs. Australian J Educ Technol, 2010, 26(3):355–368.
6
Gordon D, Issenberg SB, Gordon MS, Lacombe D, Gaghi W. Stroke training of prehospital providers: An example of simulation-enhanced blended learning and evaluation. Med Teach, 2005, 27(2):114–121. doi:10.1080/01421590400029756
7
Chen AK, Dennehy C, Fitzsimmons A, Hyde S, Lee K, Rivera J, Shunk R, Wamsley M. Teaching interprofessional collaborative care skills using a blended learning approach, JIEP, 2017, 8; 86-90 doi:10/1016/j.xjep.2017.07.002
8
Buus L, Georgsen M. A learning design methodology for developing short learning programmes in further and continuing education. Journal of Interactive Media in Education, 2018, 1. doi:10.5334/ jime.469
9
ORIGINAL_ARTICLE
Student Engagement: Developing Self-Generated Game-Assisted Activities for Teaching and Learning Language for Medical Purposes
Today, teaching Language for Medical Purposes (LMP) in higher education is a highly demanding conception of language pedagogy. LMP teaching and learning in real-life-like situations have plausible implications for using language in real-life healthcare settings. LMP skills can be considered a bridge between the instructional-learning context of medical higher education and therapeutic fields, enabling the students to keep their knowledge of tackling the emerging needs up to date (1). Parallel with the application of educational technology in medical higher education, the stakeholders’ interest in synthesizing the games is now revolving around the application of Science, Technology, Engineering, Art, and Mathematics (STEAM) approach; in the light of this, LMP learning is not a vicarious experience (2). Games have long been recognized as a vehicle for both language learning and therapy; however, the makeup of the new generations of games as educational-therapeutic LMP activities still resembles their prototypes. The novelty, driven in part by a host of educational technology and simulation tools, has made it easier than ever to introduce the games into LMP education.
https://ijvlms.sums.ac.ir/article_47063_be27378a2aa3053f5b3d84a199f593c3.pdf
2020-12-01
269
271
10.30476/ijvlms.2020.88488.1061
LMP
Game
Self-Generated Activities
Student Engagement
Saeed
Khazaie
saeed.khazaie@gmail.com
1
Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
AUTHOR
Nasrin
Shokrpour
shokrpourn@gmail.com
2
Shiraz University of Medical Sciences, Faculty of Paramedical Sciences, English Department, Shiraz, Iran
LEAD_AUTHOR
Ibrahim HH. Needs analysis as a prerequisite for designing an ESP course for Medical students. Open Journal of Modern Linguistics. 2020 Apr 10;10(2):83-103. doi:10.4236/ojml.2020.102006
1
Webb DL, LoFaro KP. Sources of engineering teaching self‐efficacy in a STEAM methods course for elementary preservice teachers. School Science and Mathematics. 2020 Apr;120(4):209-19. doi:10.1111/ssm.12403
2
Carnando G. Need analysis for designing ESP course for medical students. Anglo-Saxon: Jurnal Ilmiah Program Studi Pendidikan Bahasa Inggris. 2020 Jul 1;11(1):1-2. doi:10.33373/as.v11i1.2140
3
Prensky M. Digital natives, digital immigrants. On the Horizon. 2001 Nov;9(5): 6-11. doi:10.1108/10748120110424816
4
Courtier J, Webb EM, Phelps AS, Naeger DM. Assessing the learning potential of an interactive digital game versus an interactive-style didactic lecture: The continued importance of didactic teaching in medical student education. Pediatric Radiology. 2016 Dec 1;46(13):1787-96. doi:10.1007/s00247-016-3692-x PMid:27580908
5
Grabowski D. Health identity, participation and knowledge: A qualitative study of a computer game for health education among adolescents in Denmark. Health Education Journal. 2013 Nov;72(6):761-8. doi:10.1177/0017896912469559
6
Clochesy JM, Buchner M, Hickman Jr RL, Pinto MD, Znamenak K. Creating a serious game for health. Journal of Health and Human Services Administration. 2015 Oct; 1:162-73.
7