ORIGINAL_ARTICLE
A Meta-Synthesis Approach to Designing a Conceptual Framework for Mobile Learning in Higher Education
Background: Higher education is considered as a source of inspiration and a major factor in the development and advancement of every society. The realization of an effective education in any educational institution requires the formation of an efficient teaching-learning process. The purpose of this study was to design a framework for mobile learning in higher education. Methods: It is an analytical-oriented qualitative study in designing a framework-based meta-synthesis. Data were collected through documentary method using search engines as well as valid websites presenting national and international articles. In the search for mobile learning keywords in higher education, 418 Persian and English papers were found and after examining their titles, it appeared that the majority of them covered topics relevant to mobile learning, such as e-learning. Hence, a total of 119 articles were selected to consider their abstracts. Upon studying the abstracts and contents of the above-mentioned articles, 71 papers were chosen. Due to the principles of conducting meta-synthesis research and omitting incomplete papers, 52 articles were selected for content analysis. Results: According to the results, five main dimensions including: strategy, data, process, infrastructure and human forces are recognized for adopting mobile learning in higher education. Infrastructures develop the highest frequency in the considered studies and out of 52 papers only 42 of them have mentioned codes and factors relevant to the infrastructure. Conclusion: Experts in this study provided their assessments and opinions about research findings in order to score, acknowledge and finalize the dimensions of m-learning in higher education.
https://ijvlms.sums.ac.ir/article_45930_6fb30fb9d4d5b8e05831dc71541aa0ef.pdf
2019-12-01
1
13
10.30476/ijvlms.2019.84413.1008
Designing
Mobile Learning
Mata-Synthesis Approach
Higher Education
Hossein
Dokouhaki
h.dokouhaki@gmail.com
1
Department of Educational Sciences, College of Economics and Management, Islamic Azad University, Shiraz Branch, Shiraz, Iran
AUTHOR
Nahid
Zarifsanaiey
nzarifsanaee@gmail.com
2
Virtual School, Comprehensive Center of Excellence for Electronic Learning in Medical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
LEAD_AUTHOR
Zolghadri S, Mallahi K. A Study on Barriers of E-learning from Viewpoint of University Staff and Students; Iranian Case Study, Islamic Azad University's Branches, Region I (Fars). Res J ApplSciEngTechnol 2013; 6(10):1768-1773. https://doi.org/10.19026/rjaset.6.3901.
1
Ali S, Uppal MA, Gulliver SR. A conceptual framework highlighting e-learning implementation barriers. InfTechnol People 2018;31(1):156-180. https://doi.org/10.1108/ITP-10-2016-0246
2
Briz-Ponce, Laura Anabela Pereira, Lina Carvalho, Juan Antonio Juanes-Mndez, and Francisco Jos Garca-Pealvo. 2017. Learning with mobile technologies Students behavior. Comput. Hum. Behav. 2017;72, 612-620. DOI: https://doi.org/10.1016/j.chb.2016.05.027.
3
Briz-Ponce, L., Juanes-Mendez, J. A., & García-Pe~nalvo, F. J. A systematicreview of using mobile devices in medical education. In J. Sierra-Rodriguez,J. Dodero-Beardo, & D. Burgos (Eds.),Proceedings of 2014 international sympo-sium on computers in education (SIIE)(pp. 205e210). Logro~no, La Rioja, Spain: Institute of Electrical and Electronics Engineers Inc.2014. http://dx.doi.org/10.1109/SIIE.2014.7017731.
4
Briz-Ponce, L., Juanes-Mendez, J. A., & García-Pe~nalvo, F. J. Analysis ofcertificated mobile application for medical education purposes. In Proceedings of the second International Conference on technological Ecosystems for enhancingmulticulturality-TEEM14(pp. 13e17). New York: ACM.2014. http://dx.doi.org/10.1145/2669711.2669871.
5
Briz-Ponce, L., Juanes-Mendez, J. A., & García-Pe~nalvo, F. J. First approach of mobile applications study for medical education purposes. In Proceedings of the second international conference on technological ecosystems for enhancing mul-ticulturality (pp. 647e651).2014. http://dx.doi.org/10.1145/2669711.2669968.
6
Klimova B. Poulová P. Mobile Learning in Higher Education. Advanced Science, 2016; 22(5):1111-1114 . DOI: 10.1166/asl.2016.6673 .
7
Karami R. The efficacy of mobile learning in higher education in agriculture (Case study: Central Zanjan- University of Payam Moor): Journal of Iranian agricultural economics and development research. 2016; 2(2): 441-451.
8
Díez-Echavarría Luisa, Alejandro Valencia, Lorena Cadavid. Mobile learning on higher educational institutions: how to encourage it?. Simulation approach Dyna rev. fac. nac. 2018;85(204). http://dx.doi.org/10.15446/dyna.v85n204.63221
9
Vera I. Toktarova1, Anastasiia D. Blagova, Anna V. Filatova1 & Nikolai V. Kuzmin Design and Implementation of Mobile Learning Tools and Resources in the Modern Educational Environment of University Review of European Studies, 2015;7(8): 318-324. doi:10.5539/res.v7n8p318.
10
Chavoshi A, Hamidi H. Social, individual, technological and pedagogical factors influencing mobile learning acceptance in higher education: A case from Iran. Telematics Inf 2019;38:133-165.
11
https://doi.org/10.1016/j.tele.2018.09.007
12
Sarrab M, Al-Shihi H, Al-Khanjari Z, Bourdoucen H. Development of mobile learning application based on consideration of human factors in Oman. TechnolSoc 2018;55:183-198.
13
https://doi.org/10.1016/j.techsoc.2018.07.004
14
Dashtestani R. Moving bravely towards mobile learning: Iranian students' use of mobile devices for learning English as a foreign language. Comput Assisted Lang Learn 2016;29(4):815-832.
15
https://doi.org/10.1080/09588221.2015.1069360
16
Al-Emran M, Elsherif HM, Shaalan K. Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior,2016; 56: 93-102. DOI 10.1016/j.chb.2015.11.033.
17
Ferreira, J. B., Klein, A. ., Freitas, A., & Schlemmer, E. Mobile learning: Definition, uses and challenges. In L. A. Wankel & P. Blessinger (Eds.), Cutting-edge Technologies in Higher Education (pp. 47–82). Emerald Group Publishing Limited.2013. doi: 10.1108/S2044-9968(2013)000006D005.
18
Hamidi H, Chavoshi A. Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics Inf 2018;35(4):1053-1070. https://doi.org/10.1016/j.tele.2017.09.016.
19
Sahin G, Basak T. Mobile learning in nursing m-learning. Journal of Human Sciences,2017; 14(4): 4480_4491 DOI 10.14687/jhs.v14i4.4891.
20
Patil RN, Almale BD, Patil M, Gujrathi A, Dhakne-Palwe S, Patil AR, Gosavi S. 2016. Attitudes and perceptions of medical undergraduates towards mobile learning (M-learning). Journal of Clinical and Diagnostic Research, 2016; 10(10): 6_10. DOI 10.7860/JCDR/2016/20214.8682.
21
Sarani H, Ayati M, Naderi F. The effects of teaching english language course via phone and email on learning and achievement's motivation . IRPHE. 2014; 20 (3) :141-159
22
URL: http://journal.irphe.ac.ir/article-1-2447-en.html
23
Abdolvahabi M, Mehralizadeh Y, Parsa A. Feasibility study of implementation of smart schools in female high schools in Ahvaz: Quarterly journal of educational innovation2011; 11(42): 82-113.
24
Majidi A. E-education, quarterly journal of book,2009; 78:9-26.
25
Talebi H, Basiri B. The effect of activity and practice-based teaching method on academic performance of female students of bachelor's degree in educational sciences. Isfahan-University of Payam Noor (Subject of Statistics). Modern approaches to education,2006; 11(2): 1-26
26
ORIGINAL_ARTICLE
Investigation on the Role of Learning Theory in Learning Analytics
Background: Studies have shown that there is a gap between theory and practice in the use of learning analytics in educational settings. Some researchers attribute this gap to not taking learning theories into consideration in the use of learning analytics in educational contexts. This study was conducted to address the role of learning theory in applying learning analytics in educational contexts. Methods: This is a qualitative study and the study design is content analysis. Thematic analysis was used as the research method. Data for this study was collected through an interview with 14 experts in the fields of learning analytics and learning theory who were selected purposefully. Theoretical saturation method was used to determine the sample size. Content analysis techniques were used to analyze data and content validity index (CVI) and Cohen’s kappa coefficient were performed to measure the validity and reliability of the findings. Results: Data analysis was performed to identify three main roles for learning theory in learning analytics including underpinning role, guiding role, and sense-making role. Conclusion: The results suggest that first, learning theory should underlie learning analytics (where to begin). Second, application of learning analytics in educational settings should be guided by learning theory (what and how to do), and third, learning analytics’ reports should be interpreted based on the learning theory implications for education (answer to question why).
https://ijvlms.sums.ac.ir/article_45903_d4f408a351ea47c4993a8370119f34ce.pdf
2019-12-01
14
27
10.30476/ijvlms.2019.84294.1001
Learning Theory
Learning Analytics
Thematic Analysis
Seyyed Kazem
Banihashem
kazem.banihashem@gmail.com
1
Department of Educational Technology, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University, Tehran, Iran
LEAD_AUTHOR
Khadijeh
Aliabadi
aliabadikh@atu.ac.ir
2
Department of Educational Technology, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University, Tehran, Iran
AUTHOR
Saeid
Pourroostaei Ardakani
spourroostaei@gmail.com
3
Department of Educational Technology, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University, Tehran, Iran
AUTHOR
Mohammad Reza
Nili AhmadAbadi
nili1339@gmail.com
4
Department of Educational Technology, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University, Tehran, Iran
AUTHOR
Ali
Delavar
delavarali@yahoo.com
5
Department of Assessment and Measurement, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University.
AUTHOR
Prensky M. Digital natives, digital immigrants part 1. On the horizon. 2001 Sep 1;9(5):1-6. https://doi.org/10.1108/10748120110424816
1
Zeide E. The structural consequences of big data-driven education. Big data. 2017 Jun 1;5(2):164-72. https://doi.org/10.1089/big.2016.0061
2
Cooper MM. Data-driven education research. Science. 2007 Aug 31;317(5842):1171-1183. https://doi.org/10.1126/science.317.5842.1171
3
Mokhtari K, Rosemary CA, Edwards PA. Making instructional decisions based on data: What, how, and why. The Reading Teacher. 2007 Dec 1;61(4):354-9. http://dx.doi.org/10.1598/RT.61.4.10
4
Siemens G, Long P. Penetrating the fog: Analytics in learning and education. EDUCAUSE review. 2011;46(5):30.
5
Lu OH, Huang JC, Huang AY, Yang SJ. Applying learning analytics for improving students engagement and learning outcomes in an MOOCs enabled collaborative programming course. Interactive Learning Environments. 2017 Feb 17;25(2):220-34. https://doi.org/10.1080/10494820.2016.1278391
6
Ifenthaler D. Are higher education institutions prepared for learning analytics?. TechTrends. 2017 Jul 1;61(4):366-71. http://dx.doi.org/10.1007/s11528-016-0154-0
7
Banihashem SK, Aliabadi K, Ardakani SP, Delaver A, Ahmadabadi MN. Learning analytics: A critical literature review. Interdisciplinary Journal of Virtual Learning in Medical Sciences. 2018; 9(2). https://dx.doi.org/10.5812/ijvlms.63024
8
Mah DK. Learning analytics and digital badges: Potential impact on student retention in higher education. Technology, Knowledge and Learning. 2016 Oct 1;21(3):285-305. https://doi.org/10.1007/s10758-016-9286-8
9
de Freitas S, Gibson D, Du Plessis C, Halloran P, Williams E, Ambrose M, Dunwell I, Arnab S. Foundations of dynamic learning analytics: Using university student data to increase retention. British Journal of Educational Technology. 2015 Nov;46(6):1175-88. https://doi.org/10.1111/bjet.12212
10
Conde MA, Hernandez-Garcia A. Learning analytics for educational decision making. Comput Hum Behav. 2015;47:1–3. https://doi.org/10.1016/j.chb.2014.12.034
11
Lawson C, Beer C, Rossi D, Moore T, Fleming J. Identification of ‘at risk’students using learning analytics: the ethical dilemmas of intervention strategies in a higher education institution. Educational Technology Research and Development. 2016 Oct 1;64(5):957-68. https://doi.org/10.1007/s11423-016-9459-0
12
Siemens G. Learning analytics: The emergence of a discipline. American Behavioral Scientist. 2013 Oct;57(10):1380-400. https://doi.org/10.1177%2F0002764213498851
13
Stewart C. Learning Analytics: Shifting from theory to practice. Journal on Empowering Teaching Excellence. 2017;1(1):10. https://doi.org/10.15142/T3G63W
14
Knight S, Shum SB, Littleton K. Epistemology, assessment, pedagogy: where learning meets analytics in the middle space. Journal of Learning Analytics. 2014 Aug 7;1(2):23-47. https://doi.org/10.18608/jla.2014.12.3
15
Wong J, Baars M, de Koning BB, van der Zee T, Davis D, Khalil M, Houben GJ, Paas F. Educational Theories and Learning Analytics: From Data to Knowledge. InUtilizing Learning Analytics to Support Study Success 2019 (pp. 3-25). Springer, Cham. https://doi.org/10.1007/978-3-319-64792-0_1
16
Ertmer PA. Addressing first-and second-order barriers to change: Strategies for technology integration. Educational technology research and development. 1999 Dec 1;47(4):47-61. https://doi.org/10.1007/BF02299597
17
Wise AF. Designing pedagogical interventions to support student use of learning analytics. InProceedings of the fourth international conference on learning analytics and knowledge 2014 Mar 24 (pp. 203-211). ACM. http://dx.doi.org/10.1145/2567574.2567588
18
Gašević D, Dawson S, Rogers T, Gasevic D. Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success. The Internet and Higher Education. 2016 Jan 1; 28:68-84. https://doi.org/10.1016/j.iheduc.2015.10.002
19
Gašević D, Dawson S, Siemens G. Let’s not forget: Learning analytics are about learning. TechTrends. 2015 Jan 1;59(1):64-71. https://doi.org/10.1007/s11528-014-0822-x
20
Siemens G. Learning and knowing in networks: Changing roles for educators and designers. ITFORUM for Discussion. 2008 Jan 27; 27:1-26
21
Banihashem SK, Aliabadi K. Connectivism: implications for distance education. Interdisciplinary Journal of Virtual Learning in Medical Sciences. 2017;8(3). https://dx.doi.org/10.5812/ijvlms.10030
22
Goldie JG. Connectivism: A knowledge learning theory for the digital age?. Medical teacher. 2016 Oct 2;38(10):1064-9. https://doi.org/10.3109/0142159X.2016.1173661
23
Tennyson RD, Rasch M. Linking cognitive learning theory to instructional prescriptions. Instructional Science. 1988 Dec 1;17(4):369-85. https://doi.org/10.1007/BF00056222
24
Siemens, G. Connectivism. A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2005;2(1).
25
Akdeniz C. Instructional Process and Concepts in Theory and Practice. Singapore: Springer; 2016.
26
Bell F. Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning. 2011 Mar 25;12(3):98-118. http://usir.salford.ac.uk/13064/
27
Mergel, B. Instructional design and learning theory. University of Saskatchewan. 1998. https://etad.usask.ca/802papers/mergel/mergel.pdf
28
Ertmer PA, Newby TJ. Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance improvement quarterly. 2013;26(2):43-71. https://doi.org/10.1002/piq.21143
29
Altun S, Büyükduman FI. Teacher and student beliefs on constructivist instructional design: A case study. Kuram ve Uygulamada Egitim Bilimleri. 2007;7(1):30.
30
Richardson V. Constructivist teaching and teacher education: Theory and practice. In Constructivist teacher education 2005 Aug 15 (pp. 13-24). Routledge. http://dx.doi.org/10.4324/9780203973684
31
Braun, V., Clarke, V., Hayfield, N., & Terry, G. Thematic analysis. Handbook of research methods in health social sciences, 2018;1-18. http://dx.doi.org/10.1191/1478088706qp063oa
32
Terry G, Hayfield N, Clarke V, Braun V. Thematic analysis. The Sage handbook of qualitative research in psychology. 2017 Mar 31:17-37.
33
Braun V, Clarke V. Using thematic analysis in psychology. Qualitative research in psychology. 2006 Jan 1;3(2):77-101. https://doi.org/10.1191/1478088706qp063oa
34
Strauss A, Corbin J. Basics of qualitative research. Sage publications; 1998.
35
Glaser B, Strauss AL. The discovery of grounded theory: Strategies for qualitative research. 1967;139.
36
Böhm A. Theoretical Coding: Text Analysis in Grounded Theory. In Flick U. Kardoff E. & Stenlkne I. (Eds). A Companion to Qualitative Research. 2004:270-275.
37
Maher C, Hadfield M, Hutchings M, de Eyto A. Ensuring rigor in qualitative data analysis: A design research approach to coding combining NVivo with traditional material methods. International Journal of Qualitative Methods. 2018 Jul 9;17(1):1609406918786362. https://doi.org/10.1177%2F1609406918786362
38
Scott C, Medaugh M. Axial Coding. The International Encyclopedia of Communication Research Methods. 2017 Apr 24:1-2. https://doi.org/10.1002/9781118901731.iecrm0012
39
Robrecht LC. Grounded theory: Evolving methods. Qualitative health research. 1995 May;5(2):169-77. https://doi.org/10.1177%2F104973239500500203
40
Koh E, Shibani A, Tan JP, Hong H. A pedagogical framework for learning analytics in collaborative inquiry tasks: An example from a teamwork competency awareness program. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge 2016 Apr 25 (pp. 74-83). ACM. https://doi.org/10.1145/2883851.2883914
41
Mezirow, J. Transformative learning theory. In Contemporary Theories of Learning. Routledge. 2018;114-128. https://doi.org/10.4324/9781315147277-8
42
Akers RL, Jennings WG. Social learning theory. The Handbook of Criminological Theory. 2015 Aug 25;4:230-40. https://doi.org/10.1002/9781118512449
43
ORIGINAL_ARTICLE
Designing and Validating a Model for Databases in Open and Distance Universities
Background: Humans have always needed to store and retrieve information. In the last decades, one of the most important phenomena in the information industry was the emergence and popularity of machine reader databases, especially online databases. The main purpose of this study was to design and validate a model for databases in open and distance universities. Methods: This research is a descriptive study conducted by survey method. The statistical population of the present study consists of all specialists in the field of studying databases and open and distance educational universities. In a small part, sampling was done by a census method and in a purposeful manner. The responses were analyzed using descriptive and inferential statistics and by SPSS and Lisrel software. For the purpose of examining the parametric deflections, the Kolmogorov–Smirnov test was used to check the normality of the data. The Levene’s test was used to examine the default of variances and obtain the inferential part of factor analysis. The current research was carried out in 2 qualitative and quantitative phases. In the qualitative phase, some of the distance education scholars and database experts were selected as a purposive sample to analyze the basic parameters obtained in the first phase. In the quantitative phase, sampling was done through census and purposive manner from professors’ at the University of Isfahan (N=211). 22 questionnaires were excluded due to reasons such as non-functional responses, and statisctical analysis was carried out for 189 participants. To measure content validity index (CVI), Waltz and Bausell index was utilized and the instrument under investigation was presented to 8 experts who were engaged in the content validity stage. Results: The results of the research showed that databases in open and distance universities in Iran have high quality and quantity regarding the search and search features and the technical aspects. Conclusion: Based on this research a major issue of concern is to find a framework and model which can be used by executives and managers from distant backgrounds to evaluate the quality of their existing databases.
https://ijvlms.sums.ac.ir/article_45908_ae675cf71cca8b44922f39b2fcbe9820.pdf
2019-12-01
28
39
10.30476/ijvlms.2019.84299.1000
Distance Learning
Open Education
Databases
Evaluation
Mostafa
Kalani
mkalani_2005@yahoo.com
1
PhD Student in Distance Education Planning, Faculty of Education, Graduate School, Payam-e-Noor University, Tehran, Iran
AUTHOR
Mehran
Farajollahi
farajollahim@yahoo.com
2
Department of Educational Sciences, Faculty of Education, Payam-e-Noor University, Tehran, Iran
LEAD_AUTHOR
Mohammad Reza
Sarmadi
ms84sarmadi@yahoo.com
3
Department of Educational Sciences, Faculty of Education, Payam-e-Noor University, Tehran, Iran
AUTHOR
Tayebeh
Safaeei
t_safaee@yahoo.com
4
Department of Educational Sciences, Faculty of Education, Payam-e-Noor University, Tehran, Iran
AUTHOR
Bates AWT. Teaching in a digital age: Guidelines for designing teaching and learning for a digital age: Tony Bates associates. University of British Columbia: BCcampus; 2015. https://doi.org/10.14288/1.0107914
1
Douglass BG, Moustakas C. Heuristic inquiry. J Hum Psychol.2016;25(3):39-55. doi: 10.1177/0022167885253004. https://doi.org/10.1177/0022167885253004
2
Bergamaschi S, Guerra F, Interlandi M, Trillo-Lado R, Velegrakis Y. Combining user and database perspective for solving keyword queries over relational databases. Information Systems. 2016 Jan 1;55:1-9. https://doi.org/10.1016/j.is.2015.07.005 https://doi.org/10.1016/j.is.2015.07.005
3
Magdalena N I. (PSBS) The use of distributed databases in e-learning systems, 2011 December, Volume 15, 2673-2677. DOI: 10.1016/j.sbspro.2011.04.168 https://doi.org/10.1016/j.sbspro.2011.04.168
4
Mbabu GL, Bertram A, Varnum K. (TJAL). Patterns of Undergraduates' Use of Scholarly Databases in a Large Research University. 2013 March; 39 (2): 189-193 https://doi.org/10.1016/j.acalib.2012.10.004 https://doi.org/10.1016/j.acalib.2012.10.004
5
Sohrabi Safa N, Von Solms R, Furnell S. Computers & Security. Information security policy compliance model in organizations. 2016 February; 56(1): 70-82. https://doi.org/10.1016/j.cose.2015.10.006 https://doi.org/10.1016/j.cose.2015.10.006
6
Ebben M, Murphy JS. Unpacking MOOC scholarly discourse: A review of nascent MOOC scholarship. Learn Media Technol. 2014;39(3):328-45. doi: 10.1080/17439884.2013.878352. https://doi.org/10.1080/17439884.2013.878352
7
Liyanagunawardena TR, Adams AA, Williams SA. MOOCs: A systematic study of the published literature 2008-2012. Int Rev Res Open Dis Learn. 2013;14(3):202. doi: 10.19173/irrodl.v14i3.1455. https://doi.org/10.19173/irrodl.v14i3.1455
8
Gore H. Massive open online courses (MOOCs) and their impact on academic library services: Exploring the issues and challenges. New Rev Academic Librarian. 2014;20(1):4-28. doi:10.1080/13614533.2013.851609. https://doi.org/10.1080/13614533.2013.851609
9
Ommati E, Alipour A. (JMMIS). Important elements in the design of user interface, usability and technical issues of databases during the years 2014 -2016. 2016; 2 (2) :59-72 URL: http://jmis.hums.ac.ir/article-1-86-fa.html
10
Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, Lago BA, Dave BM, Pereira S, Sharma AN, Doshi S. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic acids research. 2016 Oct 25: https://doi.org/10.1093/nar/gkw1004
11
Mojtabazadeh M, Abbaspour A, Maleki H, Farasatkhah M, Rahimian H. (Educ Strategy Med Sci). Designing and validation of a scale to assess the quality of universities in Iran. 2016; 9 (1) :42-62 URL: http://edcbmj.ir/article-1-955-fa.html
12
Wright F. What do librarians need to know about MOOCs? D-Lib Magazine. 2013;19(3/4). https://doi.org/10.1045/march2013-wright
13
Bolchini C, Quintarelli E, Tanca L. CARVE: Context-aware automatic view definition over relational databases. Information Systems. 2013 Mar 1;38(1):45-67. https://doi.org/10.1016/j.is.2012.05.004
14
Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, Kiefer F, Cassarino TG, Bertoni M, Bordoli L, Schwede T. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic acids research. 2014 Apr 29;42(W1):W252-8. https://doi.org/10.1093/nar/gku340
15
Fariborzi, E., & Bakar, K. bt A. Factors influencing the effectiveness of courses in Iranian university e-learning centers. The International Journal of Technology, Knowledge and Society. 2010. 6(1), 72-80. https://doi.org/10.18848/1832-3669/CGP/v06i01/56057
16
Van Horn JD. Databases, Brain Mapping, Volume 1, 2015. https://doi.org/10.1016/B978-0-12-397025-1.00351-1
17
Cristiana Bolchini, Elisa Quintarelli, Letizia Tanca (2013). CARVE: Context-aware automatic view definition over relational databases. Information Systems, Volume 38, Issue 1. https://doi.org/10.1016/j.is.2012.05.004
18
Simpson O. Supporting students in online, open and distance learning. Routledge; 2018 Oct 24. https://doi.org/10.4324/9780203417003
19
Raffaghelli JE, Cucchiara S, Persico D. Methodological approaches in MOOC research: Retracing the myth of Proteus. Brit J Educ Technol. 2015;46(3):488-509. doi: 10.1111/bjet.12279. https://doi.org/10.1111/bjet.12279
20
ORIGINAL_ARTICLE
Teachers' Professional Development through Online Learning Environment: A Phenomenological Study
Background: Online learning environment (OLE) has provided teachers with excellent opportunities for professional development. The present study attempted to investigate how Iranian teachers used this for their professional development. Methods: In this study qualitative research approach was used. The participants consist of 25 teachers who actively promote the educational applications of the virtual environment. They were selected from among the teachers of Hamedan Province and were invited to a semi-structured interview. Snowball sampling technique was used, and the number of participants was decided to be 25 according to the principle of theoretical saturation. Results: The findings suggested that teachers mostly use information retrieval, production and presentation of contents, and interactive tools for their professional development. By using information retrieval tools, they can access their required information in various fields, become informed about conferences and educational workshops, rethink their experience as well as improve their self-confidence in responding to students’ questions. By using content production and presentation tools, they can produce high-quality multimedia contents, design various learning activities, encourage students to participate in activities, and adopt active teaching methods. Conclusion: teachers can use online learning environment (OLE) for their self-directed professional development through searching, interactive and content production tools.
https://ijvlms.sums.ac.ir/article_45916_6851304ff3b464d6107e8e69cff4666c.pdf
2019-12-01
40
53
10.30476/ijvlms.2019.84317.1004
Teacher's Professional Development
Virtual Environment
Phenomenology
Curriculum Implementation
Farhad
Seraji
fseraji@gmail.com
1
Education, humanities, Bu Ali Sina University
LEAD_AUTHOR
Sara
Khodaveisi
sarakhodaveisi@gmail.com
2
Education, humanities, Bu Ali Sina university
AUTHOR
Brooks C, Gibson S. Professional Learning in a Digital Age. Canadian Journal of Learning and Technology. 2012;38(2):n2.
1
Avalos B. Teacher professional development in teaching and teacher education over ten years. Teaching and teacher education. 2011 Jan 1;27(1):10-20.http://doi.org/10.1016/j.tate.2010.08.007.
2
Guskey TR, Sparks D. Evaluating professional development. Corwin press; 2000.
3
Cook DA, Steinert Y. Online learning for faculty development: A review of the literature. Medical teacher. 2013 Nov 1;35(11):930-7. .http://doi:10.3109/0142159X.2013.827328
4
Kwakman K. Factors affecting teachers’ participation in professional learning activities. Teaching and teacher education. 2003 Feb 1;19(2):149-70.https://doi10.1016/s0742-051x(02)00101-4.
5
Tan AL, Chang CH, Teng P. Tensions and dilemmas in teacher professional development. Procedia-Social and Behavioral Sciences. 2015 Feb 12;174:1583-91. https:// doi10.1016/j.sbspro.2015.01.808.
6
Koehler M, Mishra P. What is technological pedagogical content knowledge (TPACK)?. Contemporary issues in technology and teacher education. 2009 Mar;9(1):60-70. doi10.1177/002205741319300303
7
Mishra P, Koehler MJ. Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers college record. 2006 Jun;108(6):1017-54.http://doi 10.1111/j.1467-9620.2006.00684.x.
8
Holmes K, Preston G, Shaw K, Buchanan R. " Follow" Me: Networked Professional Learning for Teachers. Australian Journal of Teacher Education. 2013 Dec;38(12):n12.https://doi.org/10.14221/ajte.2013v38n12.4.
9
Blonder R, Rap S. I like Facebook: Exploring Israeli high school chemistry teachers’ TPACK and self-efficacy beliefs. Education and Information Technologies. 2017 Mar 1;22(2):697-724. http:// doi 10.1007/s10639-015-9384-6.
10
Laurillard D.(2002). Rethinking University Teaching: A Conversational Framework for the Effective Use of Learning Technologies. London and New York: Rutledge Flamer.
11
Nind M, Boorman G, Clarke G. Making schools fitting places for all: a creative approach. 2010.
12
Veletsianos G, editor. Emerging technologies in distance education. Athabasca University Press; 2010.
13
Tomei LA, editor. Encyclopedia of information technology curriculum integration. IGI Global; 2008 Feb 28.
14
Prestridge SJ. Reflective blogging as part of ICT professional development to support pedagogical change. Australian Journal of Teacher Education. 2014;39(2):6.https://doi.org/10.14221/ajte.2014v39n2.4.
15
Sun A, Chen X. Online education and its effective practice: A research review. Journal of Information Technology Education. 2016 Jan 1;15. Retrieved from http://www.informingscience.org/Publications/3502
16
Zandi P, Thang SM, Krish P. Teacher professional development through blogging: Some preliminary findings. Procedia-Social and Behavioral Sciences. 2014 Mar 19;118:530-6.https://doi.org/10.1016/j.sbspro.2014.02.072
17
Ertmer PA, Ottenbreit-LeftwichAT. Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of research on Technology in Education. 2010 Mar 1;42(3):255-84.
18
Hussein HB. The Effectiveness of Using Social Communications Networks in Mathematics Teachers Professional Development. Procedia-Social and Behavioral Sciences. 2013 Dec 10;106:2756-61.http:'// doi 10.1016/j.sbspro.2013.12.316.
19
Carpenter JP, Krutka DG. How and why educators use Twitter: A survey of the field. Journal of research on technology in education. 2014 Oct 2;46(4):414-34.
20
Alabdulkareem SA. Exploring the use and the impacts of social media on teaching and learning science in Saudi. Procedia-Social and Behavioral Sciences. 2015 May 13;182:213-24. http://doi: 10.1016/j.sbspro.2015.04.758.
21
Hökkä P, Eteläpelto A. Seeking new perspectives on the development of teacher education: A study of the Finnish context. Journal of teacher education. 2014 Jan;65(1):39-52.https://doi.org/10.1177/0022487113504220
22
VanEekelen IM, Boshuizen HP, Vermunt JD. Self-regulation in higher education teacher learning. Higher education. 2005 Oct 1;50(3):447-71.https;// doi 10.1007/s10734-004-6362-0
23
Shwartz Y, Katchevitch D. Using wiki to create a learning community for chemistry teacher leaders. Chemistry Education Research and Practice. 2013;14(3):312-23.https://doi10.1039/c31p20180e.
24
Rolando LG, Salvador DF, Luz MR. The use of internet tools for teaching and learning by in-service biology teachers: A survey in Brazil. Teaching and Teacher Education. 2013 Aug 1;34: 46-55. https://doi10.1016/j.tate.2013.3.007
25
Cilesiz S. A phenomenological approach to experiences with technology: Current state, promise, and future directions for research. Educational Technology Research and Development. 2011 Aug 1;59(4):487-510.
26
Yüksel P , Yıldırım S . Theoretical Frameworks, Methods, and Procedures for Conducting Phenomenological Studies in Educational Settings. Turkish Online Journal of Qualitative Inquiry. 2015; 6(1): 20-1.
27
Braun V, Clarke V. Using thematic analysis in psychology. Qualitative research in psychology. 2006 Jan 1;3(2):77-101..https:// doi10.1191/1478088706qp0630a.
28
Daugherty JL. Engineering professional development design for secondary school teachers: A multiple case study. Journal of Technology Education. 2010;21(1):10. https//doi 10.21061/jte.v21i1.a.1.
29
Jobe W, Östlund C, Svensson L. MOOCs for professional teacher development. In Society for Information Technology & Teacher Education International Conference 2014 Mar 17 (pp. 1580-1586). Association for the Advancement of Computing in Education (AACE).
30
Laurillard D. The educational problem that MOOCs could solve: Professional development for teachers of disadvantaged students. Research in Learning Technology. 2016 Apr 13;24. https://doi.org/10.3402/rlt.v24.29369.
31
Cviko A, McKenney S, Voogt J. Teacher roles in designing technology-rich learning activities for early literacy: A cross-case analysis. Computers & education. 2014 Mar 1;72: 68-79.https://doi.org/10.14742/ajet.2502.
32
Serin G. The effect of gender and professional development in information and communication technology (ICT) on science teachers’ use of classroom practices. Anadolu Journal of Educational Sciences International. 2015;5(1):20-37. . https:// dx.doi.org/10.18039/ajesi.43444.
33
Wiseman AW, Al-bakr F, Davidson PM, Bruce E. Using technology to break gender barriers: gender differences in teachers’ information and communication technology use in Saudi Arabian classrooms. Compare: A Journal of Comparative and International Education. 2018 Mar 4;48(2):224-43.
34
ORIGINAL_ARTICLE
E-Learning Readiness among Faculty Members of Iranian Universities: A Survey of 23 Universities
Background: The aim of this study was to assess the level of e-learning readiness among the faculty members in Iranian universities. Methods: This is a survey research and the statistical population included all faculty members of 23 selected Iranian universities in March-September 2018. The population of the study included about 750 professors selected through simple random sampling. The instrument of study was a questionnaire titled “Evaluation of Instructors’ Readiness for E-learning in Iranian Universities”. Its content and face validity were verified by professionals, and its reliability was measured through Cronbach’s Coefficient alpha which was (0.72-0.86). To analyze the data, descriptive and mean, SD statistics (independent T-test) were used. Results: The average e-readiness score of professors from the 23 selected universities amounted to approximately 4.3 out of 10, which is indicative of a relatively “weak” e-readiness status. Also, the score of over 60% of the criteria was “less than average”. Conclusion: Given the decreasing numbers of e-learning students in Iran, the results of this study show that one of the important reasons for the failure in the development of universities’ e-learning systems can be the lack of e-learning readiness among instructors.
https://ijvlms.sums.ac.ir/article_45937_d163bcdc446c4c8caee3d70df635af0a.pdf
2019-12-01
54
64
10.30476/ijvlms.2019.84302.1003
E-Learning
E-learning Readiness Assessment
Faculty Members
Higher Education
Iranian Universities
Mahdieh
Farazkish
mfarazkish@gmail.com
1
Faculty of Management, Tarbiat Modares University
LEAD_AUTHOR
Gholam Ali
Montazer
montazer@modares.ac.ir
2
Department of IT, Engineering School of Tarbiat Modares University
AUTHOR
Institute for Research and Planning in Higher Education. Iran's higher education statistics in the academic year 2017-2018. Tehran. 2018.
1
Ketelhut DJ, Nelson BC, Clarke J, Dede C. A multi‐user virtual environment for building and assessing higher order inquiry skills in science. British Journal of Educational Technology. 2010; 41(1):56-68. https://doi.org/10.1111/j.1467-8535.2009.01036.x
2
Petter S, DeLone W, McLean ER. Information systems success: The quest for the independent variables. Journal of management information systems. 2013; 29(4):7-62. https://doi.org/10.2753/MIS0742-1222290401
3
Liaw SS, Huang HM, Chen GD. Surveying instructor and learner attitudes toward e-learning. Computers & Education. 2007; 49(4):1066-80. https://doi.org/10.1016/j.compedu.2006.01.001
4
Hashim H, Tasir Z. E-learning readiness: A literature review. In2014 International Conference on Teaching and Learning in Computing and Engineering 2014; 267-271. IEEE. https://doi.org/10.1109/LaTiCE.2014.58
5
Darab B, Montazer GA. An eclectic model for assessing e-learning readiness in the Iranian universities. Computers & Education. 2011; 56(3):900-10. https://doi.org/10.1016/j.compedu.2010.11.002
6
Hung WH, Chang LM, Lin CP, Hsiao CH. E-readiness of website acceptance and implementation in SMEs. Computers in Human Behavior. 2014; 40:44-55. https://doi.org/10.1016/j.chb.2014.07.046
7
Gay GH. An assessment of online instructor e-learning readiness before, during, and after course delivery. Journal of Computing in Higher Education. 2016; 28(2):199-220. https://doi.org/10.1007/s12528-016-9115-z
8
Pillay H, Irving K, Tones M. Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. High Education Research & Development. 2007; 26(2):217 https://doi.org/10.1080/07294360701310821
9
Usagawa T. Change in E-learning Readiness and Challenge for Myanmar Higher Education. Creative Education. 2018; 9(09):1277. https://doi.org/10.4236/ce.2018.99095
10
Lee YH, Hsiao C, Purnomo SH. An empirical examination of individual and system characteristics on enhancing e-learning acceptance. Australasian Journal of Educational Technology. 2014; 30(5). https://doi.org/10.14742/ajet.381
11
El Gamal S, Abd El Aziz R. Improving higher education in Egypt through e-learning programs: HE students and senior academics perspective. International Journal of Innovation in Education. 2012; 1(4):335-61. https://doi.org/10.1504/IJIIE.2012.052738
12
Ojo RA, Ayanda DO. Handling internet connectivity challenges in a typical university academic library in Nigeria: A case study of Kenneth Dike Library. Journal of Interlibrary Loan, Document Delivery & Electronic Reserve. 2012; 22(5):223-34. https://doi.org/10.1080/1072303x.2012.740440
13
The MM, Usagawa T. Evaluation on e-learning readiness of Yangon and Mandalay technological universities, Myanmar. In TENCON 2017-2017 IEEE Region 10 Conference 2017; 2072-2076. IEEE. https://doi.org/10.1109/TENCON.2017.8228202
14
Pillay K, Erasmus L. e-Readiness in South African Higher Education: A Delphi study: With a focus on determining key factors and stakeholders. In2017 IEEE AFRICON 2017; 758-763. IEEE. https://doi.org/10.1109/AFRCON.2017.8095578
15
Lou EC, Goulding JS. The pervasiveness of e-readiness in the global built environment arena. Journal of Systems and Information Technology. 2010; 12(3):180-95. https://doi.org/10.1108/13287261011070812
16
Maugis V, Choucri N, Madnick SE, Siegel MD, Gillett SE, Haghseta F, Zhu H, Best ML. Global e‐readiness—for what? Readiness for e‐banking. Information technology for development. 2005; 11(4):313-42. https://doi.org/10.1002/itdj.20022
17
Watkins R, Leigh D, Triner D. Assessing readiness for e‐learning. Performance Improvement Quarterly. 2004; 17(4):66-79. https://doi.org/10.1111/j.1937-8327.2004.tb00321.x
18
Al-Samarraie H, Selim H, Teo T, Zaqout F. Isolation and distinctiveness in the design of e-learning systems influence user preferences. Interactive Learning Environments. 2017; 25(4):452-66. https://doi.org/10.1080/10494820.2016.1138313
19
Sadik A. Digital storytelling: A meaningful technology-integrated approach for engaged student learning. Educational technology research and development. 2008; 56(4):487-506. https://doi.org/10.1007/s11423-008-9091-8
20
Rahim NM, Yusoff SH, Latif SA. Assessing students’ readiness towards e-learning. InAIP Conference Proceedings 2014; 1605(1): 750-755. AIP. https://doi.org/10.1063/1.4887684
21
MCCONNELL D. Technologies for CSCL. Implementing Computer Supported Cooperative Learning. 2000:27-67.
22
Rosenberg MJ, Foshay R. E‐learning: Strategies for delivering knowledge in the digital age. Performance Improvement. 2002; 41(5):50-1. https://doi.org/10.1002/pfi.4140410512
23
Engholm P, McLean J. What determines an organisation's readiness for e-learning.online? Available: http://www2. sbbs.se/hp/erson/academia/Thesis% 20FINAL. htm. 2001.
24
Broadbent, B. Championing e-learning. www.e-learninghub.com/articles/championing.html# Pros% 20and% 20cons% 20of% 20e-teaming. 2000.
25
Anderson, T. Is elearning Right for your organization? Learning Circuits Update. Available at: http//www.learningcircuits.org/2002/jan2002/ Anderson.html. 2002.
26
Haney BD. Assessing organizational readiness for E‐learning: 70 questions to ask. Performance improvement. 2002; 41(4):10-5. https://doi.org/10.1002/pfi.4140410404
27
Worknowledge. E-learning Assessment Readiness. Available at: http//www.worknowledge.com. 2004.
28
Rohayani AH. A literature review: readiness factors to measuring e-learning readiness in higher education. Procedia Computer Science. 2015; 59:230-4. https://doi.org/10.1016/j.procs.2015.07.564
29
Cloete E. Electronic education system model. Computers & Education. 2001; 36(2):171-82. https://doi.org/10.1016/S0360-1315(00)00058-0
30
Hamburg I. eLearning 2.0 and social, practice-oriented communities to improve knowledge in companies. In 2010 Fifth International Conference on Internet and Web Applications and Services 2010; 411-416. IEEE. https://doi.org/10.1109/ICIW.2010.68
31
Adiyarta K, Napitupulu D, Rahim R, Abdullah D, Setiawan MI. Analysis of e-learning implementation readiness based on integrated ELR model. In Journal of Physics: Conference Series 2018; 1007(1): 12-41. IOP Publishing. https://doi.org/10.1088/1742-6596/1007/1/012041
32
Machado C. Developing an e‐readiness model for higher education institutions: Results of a focus group study. British journal of educational technology. 2007; 38(1):72-82. https://doi.org/10.1111/j.1467-8535.2006.00595.x
33
Kolo I, Zuva T. Comparison between the e-Learning Readiness of Educators and Learners in South African Schools. In 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC) 2018; 1-6. IEEE. https://doi.org/10.1109/ICONIC.2018.8601266
34
Akaslan D, Law EL. Measuring teachers' readiness for e-learning in higher education institutions associated with the subject of electricity in Turkey. In2011 IEEE Global Engineering Education Conference (EDUCON) 2011; 481-490. IEEE. https://doi.org/10.1109/EDUCON.2011.5773180
35
Saekow A, Samson D. E-learning Readiness of Thailand's Universities Comparing to the USA's Cases. International Journal of e-Education, e-Business, e-Management and e-Learning. 2011; 1(2):126. https://doi.org/10.7763/IJEEEE.2011.V1.20
36
Mertler CA, Reinhart RV. Advanced and multivariate statistical methods: Practical application and interpretation. Routledge; 2016. https://doi.org/10.4324/9781315266978
37
Quamar MK. Global trends in agricultural extension: challenges facing Asia and the Pacific region. http://www.fao.org/sd/2002/KN0903a_en. htm. 2002. https://doi.org/10.1109/ijcnn.2003.1223719
38
Farazkish M, Montazer Gh. Measuring readiness of digital content in selected universities of Iran. 12th E-Learning Conference, Tehran. 2016.
39
Farazkish M, Montazer Gh. A comparative analysis of pro and students' readiness of universities in Iran, Turkey and Azerbaijan for the realization of e-learning system. 13th Conference on Quality Assessment in Academic Systems, Shiraz. 2019.
40
Kamalian A, Fazel A. Check prerequisites and feasibility of the implementation of thee-learning system. Journal of Education Technology.2009; 4(1):13–27.
41
Babakhani, M., Allah Karami, A., Amirteimori, M., Aslani, E., EIC, P., Ahmadpour Kasgari, Z., Abedini Baltork, M., Mansoori, S. Evaluation of the Readiness for E-Learning from the Viewpoints of the Students and Professors of Allameh Tabataba’i University. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 2016; 7(1). https://doi.org/10.5812/ijvlms.12072
42
ORIGINAL_ARTICLE
The Mediating Role of Blended Learning Infrastructures in the Relationship Between Good Governance, Social Capital and General Attitude Toward Business Environment
Background: Personality traits and the perception of chief background factors, are largely influenced by educational systems. Therefore, the present study believes that a collective understanding of a particular context leads to the creation of a culture that forms the basis of entrepreneurial activities. Objectives: Examining the mediating role of blended learning infrastructures in the relationships between social capital, good governance and the general perception of business environment among the owners of small and medium sized enterprises in Fars province, Iran. Methods: This is an applied research, and in terms of data collection it is a descriptive-correlation analysis of variance based on path analysis. For data gathering, stratified sampling was applied to select 366 samples among 3887 active small and medium-sized enterprises in Fars province. Results: Good governance has a direct effect (P=0.736, sig.<0.001) as well as an indirect effect (P=0.059, sig.<0.001) on the perceived business environment through the blended learning infrastructures. Also, the direct effect of social capital on the perceived business environment (P=0.041, sig.=0.315) was not confirmed, but its indirect effect through blended learning infrastructures was confirmed (P=0.305, sig.=0.03). Conclusions: Before reinforcing the blended learning infrastructures, one needs to initially strengthen the macro political and economic factors, followed by social, cultural and educational factors, in order to improve the perceived business environment and create a positive attitude towards this atmosphere. This is due to the fact that governmental infrastructures are not yet as developed as much as the educational infrastructures for developing entrepreneurship.
https://ijvlms.sums.ac.ir/article_45962_651151093ccac16d9e17195c0857551f.pdf
2019-12-29
65
74
10.30476/ijvlms.2019.84320.1005
Social capital
Good governance
Perceived business environment
blended learning infrastructures
Khalil
Safari
kh.safari@gmail.com
1
Management, Economics, and Accounting, Business Management, Payam Noor University, Tehran, Iran.
AUTHOR
Ali Mohammad
Ahmadi Gharacheh
amag2004@gmail.com
2
Department of Educational Sciences and Psychology, Payame Noor University, pobox 19395 -3697 Tehran, Iran
LEAD_AUTHOR
Habibollah
Danai
h.danai@live.com
3
Management, Economics, and Accounting Department, Business management Faculty, Payam Noor University, Tehran, Iran.
AUTHOR
Galloway L, Brown W. Entrepreneurship education at university: a driver in the creation of high growth firms? Educ and Train . 2002 Dec;44(8/9):398–405.
1
Safari Kh. Designing a model for improving the percieved business environment in the small and medium industries (Case study: SMEs of Fars Province). Postgraduate Center of Payame Noor University; 2017.
2
Entrialgo M, Fernandez E, Vazquez CJ. The effect of the organizational context on SME’s entrepreneurship: Some Spanish evidence. Small Bus Econ. 2001;16(3):223–36.
3
Cuervo A. Individual and Environmental Determinants of Entrepreneurship. Int Entrep Manag J . 2005 Sep;1(3):293–311.
4
Rizzello S. Economic Change, Subjective Perception and Institutional Evolution. Metroeconomica . 2000 May;51(2):127–50.
5
A. Zeithaml V. Consumer Perceptions of Price, Quality, and Value. J Mark . 1988;52(3):2
6
Welter F. Contextualizing Entrepreneurship-Conceptual Challenges and Ways Forward. Entrep Theory Pract. 2011 Jan;35(1):165–84.
7
North DC. Understanding the process of economic change. Academic foundation; 2006.
8
Mack E, Mayer H. The evolutionary dynamics of entrepreneurial ecosystems. Urban Stud . 2016 Aug 1;53(10):2118–33.
9
Huysman M, Wulf V. Social capital and information technology. Mit Press; 2004.
10
Grootaert C, Narayan D, Jones VN, Woolcock M. Measuring Social Capital. Washington; 2004. Report No.: 18.
11
Adler PS, Kwon S-W. Social capital: Prospects for a new concept. Acad Manag Rev. 2002;27(1):17–40.
12
Landry R, Amara N, Lamari M. Does social capital determine innovation? To what extent? Technol Forecast Soc Change. 2002;69(7):681–701.
13
Tymon WG, Stumpf SA. Social capital in the success of knowledge workers. Career Dev Int. 2003;8(1):12–20.
14
Das TK, Teng B-S. Alliance constellations: A social exchange perspective. Acad Manag Rev. 2002;27(3):445–56.
15
Speck E. Leading Organizations: Perspectives for a New Era, 2nd edition , by Gill Robinson Hickman. Adm Soc Work . 2012 Nov;36(5):547–9.
16
Sahabi B., Etesami M., Aminpour Kh., The effect of good governance and government size on financial development in selected countries. Economic growth and development research. 2014; 3 (12): 105–18.
17
Smallbone D, Welter F. Entrepreneurship and government policy in former Societ republics: Belarus and Estonia compared. Environ Plan C Gov Policy . 2010;28(2):195–210.
18
Herger N, Hodler R, Lobsiger M. What Determines Financial Development? Culture, Institutions or Trade. Rev World Econ . 2008 Oct;144(3):558–87.
19
Lee J-W, W.Tai S. Motivators and inhibitors of entrepreneurship and small business development in Kazakhstan. World J Enterprenuership, Manag Sustain Dev . 2010;6:61–75.
20
Thai MTT, Turkina E. Macro-level determinants of formal entrepreneurship versus informal entrepreneurship. J Bus Ventur. 2014;29(4):490–510.
21
North D. The New Institutional Economics and Development. In 1995. p. 17–26.
22
Eschenbach F, Hoekman B. Services policy reform and economic growth in transition economies, 1990-2004. 2006.
23
Jafari Eskandari M., AliAhmadi A., Khaleghi Gh., Heidari M., Evaluating Iran's Industrial Business Environment in Support of the Private Sector with Balanced Scorecard Approach. International Journal of Industrial Engineering and Production Management. 2011; 21 (2): 37-52.
24
Rindermann H, Kodila-Tedika O, Christainsen G. Cognitive capital, good governance, and the wealth of nations. Intelligence . 2015 Jul;51:98–108.
25
Khan BH. Managing e-learning: Design, delivery, implementation, and evaluation. IGI Global; 2005.
26
Amin Bidokhti A., Nazari M., Providing a theoretical model for institutionalizing social capital components to improve economic performance. Development Strategy. 2010; (19): 53–75.
27
Meyers LS, Gamst GC, Guarino AJ. Applied multivarite research: design and interpretation [Internet]. second. SAGE Publications, Inc; 2012. 1104 p. Available from: https://www.amazon.com/Applied-Multivariate-Research-Design-Interpretation/dp/141298811X
28
Huang Y. Political institutions and financial development: An empirical study. World Dev. 2010;38(12):1667–77.
29
Smith KG, Collins CJ, Clark KD. existing knowledge, knowledge creation capability, and the rate of new product introduction in high-technology firms. Acad Manag J . 2005 Apr 1;48(2):346–57.
30
Rezaei Mirghaed M., Arabiyon A., Alizadeh M., Investigating the Relationship between Entrepreneurship, Business Environment and Economic Development in GEM Member countries. Human Geography Research. 2014; 45 (84): 37-50.
31
ORIGINAL_ARTICLE
The Application of Interactive and Intelligent Web in E-Learning
Web learning is a learning method in which the Web and its various services are used as a teaching tool for diverse learning activities. This can be a fully online learning process implemented through one of the web services, where the curriculum and learning activities are online or blended and intelligent. With the ever growing popularity of computers and networks, web learning (e-learning) has turned into a more feasible and accepted approach worldwide (1). Being an essential tool for supporting education and learning, the Web has become an important component of higher education programs. A variety of learning activities including communication, information retrieval, collaboration, evaluation, etc. are performed in this network. Researchers believe that web learning will continue to grow and claim a larger share of the higher education market.
https://ijvlms.sums.ac.ir/article_45952_24c646eacf515c1568a185ee34ab5fd4.pdf
2019-12-01
75
77
10.30476/ijvlms.2019.84720.1015
E-Learning
Interactive web
Intelligent Web
Mohammad Bagher
Negahban
bm.negahban@gmail.com
1
Assistant Professor of Information Science Shahid Bahonar University of Kerman . Shiraz University of Medical Sciences
LEAD_AUTHOR
A
Selvaraja
librarianpes@gmail.com
2
Librarian , P. E.S of Science Arts & Commerce , Mandaya College, india
AUTHOR
De Moor A. A practical method for courseware evaluation. In Proceedings of the 2nd international conference on Pragmatic web. 2007, Tilburg, The Netherlands, Oct 22 (pp. 57-63). ACM. Doi:10.1145/1324237.1324244
1
Fan S, Lê Q. Web-Based Learning: Status Quo and Trend. In Technologies for Enhancing Pedagogy, Engagement and Empowerment in Education: Creating Learning-Friendly Environments. 2012 (pp. 217-230). IGI Global. DOI: 10.4018/978-1-61350-074-3.ch019
2
Anderson P. All That Glisters Is Not Gold'—Web 2.0 And The Librarian. Journal of Librarianship and Information Science. 2007; 39: 195-198. Doi: 10.1177/0961000607083210
3
AjazMoharkan Z, Choudhury T, Gupta SC, Raj G. Internet of Things and its applications in E-learning. In2017 3rd International Conference on Computational Intelligence & Communication Technology. (CICT) 2017 Feb 9 (pp. 1-5). IEEE.
4
ORIGINAL_ARTICLE
Setting up the Structure and Process for E-Content Development
I am writing to thank you for publishing the interesting article titled: “The effect of Social Networks and Short Messages through e-Content on Reducing Negative Thoughts in Women”(1). In this article the authors have first developed an e-content and then accomplished the intervention. In this regard I should mention that nowadays, using e-contents in different kinds of education including mobile-based or webbased, synchronous or asynchronous are the necessities in educational settings. It is a pleasure that Iranian universities are taking steps toward the use of technology in their educational research, but these steps should be wisely in line with standards and qualifications. One of the most important components of e-learning discipline is e-content because, on the one hand, without content no education is imagined (2), and on the other hand, inappropriate content can disturb audience learning (3).
https://ijvlms.sums.ac.ir/article_45984_e40f519364cd0b36f615b3ae68680c55.pdf
2019-12-01
78
80
10.30476/ijvlms.2019.84733.1016
e-Content development
e-Content Development Team Structure
e-content Development Process
Manoosh
Mehrabi
mehrabi.manoosh@gmail.com
1
Department of e-Learning in medical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
LEAD_AUTHOR
Razmgah P, Mojtahedzadeh R, Borjaliloo S, Mohammadi A. The Effect of Social Network and Short Messages through E-Content on Reducing Negative Thoughts in Women. Inter Discip J Virtual Learn Med Sci. 2016;7(4):1–7.
1
Ferdig RE. Assessing technologies for teaching and learning: understanding the importance of technological pedagogical content knowledge. Br J Educ Technol. 2006;37(5):749–60.
2
Istrate O. Visual and pedagogical design of eLearning content. E-learning Pap. 2009;17.
3