Development of students 'satisfaction model from the virtual studio of architectural design and implications for educational administrators (Case study: Marvdasht boys' , Bahonar Shiraz and Alzahra Shiraz vocational technical colleges)

Document Type : Research Paper

Authors

• fatemeh niknahad ¹
• Mohammad Parva ²
• Hossein Aflaki Fard ³
• Hadi Keshmiri ⁴

¹ PhD student, Department of Architecture, Shiraz Branch, Islamic Azad University, Shiraz, Iran

² Assistant Professor, Department of Architecture, Shiraz Branch, Islamic Azad University, Shiraz, Iran

³ Assistant Professor, Department of Educational Sciences, Farhangian University, Tehran, Iran.

⁴ Associate Professor, Department of Architecture, Shiraz Branch, Islamic Azad University, Shiraz, Iran.

10.30495/jedu.2022.29270.5855

Abstract

Background and Aim: Due to the spread of the coronavirus in the world, education was shifted to a virtual environment, and the continuation of the architectural education process, as well as training courses, due to the closure of universities, became possible only in the virtual context. This causes problems in the way of teaching and the result is a decrease in learning efficiency. For this purpose, in order to understand the current situation and improve the process of teaching architectural design in the corona pandemic, in the present study, the factors affecting students' satisfaction with the virtual architectural design studio have been developed and evaluated.
Methodology: The present research is mixed Method Approach using the research and has been done in 3 stages. First, the 7-step meta-synthesis method of Barrow Su and Sandlowski has been used and the initial conceptual model of the research has been formed. Kappa-Cohen coefficient was used to evaluate the reliability of qualitative meta-combination research. Then, in the second stage, by distributing a questionnaire among the instructors of the studio, a supplementary model of the research was obtained, and in the third stage, in order to quantitatively validate the proposed model, various tests and confirmatory factor analysis were used. Also, to check the accuracy of the hypotheses and test the proposed model, we have used structural equation modeling and path analysis method by Smartpls3 software.
Results: After confirming the favorableness of the path coefficients and the significance of the coefficients (t-value), we have studied the research model based on various indicators, the results of which showed the suitability of the proposed model. After performing the above steps, the scientific adequacy of the research model was confirmed. Thus, the research model with 4 dimensions: technical facilities and equipment, teaching quality, learning quality and educational content quality with 12 components and 31 indicators was finally approved. Also, the results of t-test show that students' satisfaction with the virtual education of the architectural design studio is at a moderate level and the averages indicate that the quality of the teacher in a relatively good condition and the dimensions of the quality of the learner, equipment and technical facilities and quality Educational content is mediocre.
 

Keywords

• virtual teaching
• Atelier
• Virtual Design
• Mixed Method Approach
• Meta-Synthesis
• Structural Equations Modeling

20.1001.1.20086369.1401.13.3.8.5

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References

1. Abbasi Kasani H, Shams Mourkani Gh. (2019). A research synthesis of critical success factors of e-learning: A model development. Technology of Education Journal. 13(1): 25-39.
2. Abbasi N, Adams N, Gide E, O’Brien D,& Lawrence P. (2018). Online delivery of architecture and building design studios: a case study of Central Queensland University. In International Conference of the Architectural Science Association. 469-475.
3. Abbasi-Parsa A. (2012). Feasibility study of implementing virtual education in the Faculty of Psychology and Educational Sciences of Allameh Tabatabai University and providing appropriate solutions. Master Thesis, Allameh University. Faculty of Psychology and Educational Sciences. [persian].
4. Alanazi A., Frey B. B., Niileksela C., Lee S. W., Nong, A., & Alharbi, F. (2021). The Role of Task Value and Technology Satisfaction in Student Performance in Graduate-Level Online Courses. TechTrends. 64: 922-930.
5. Al-Fraihat D, Joy M, & Sinclair J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior. 102; 67-86.
6. Alnusairat S, Al Maani D, & Al-Jokhadar A. (2020). Architecture students' satisfaction with and perceptions of online design studios during COVID-19 lockdown: the case of Jordan universities. Archnet-IJAR: International Journal of Architectural Research.
7. Alqurashi E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education. 40(1): 133-148
8. Armaghan M, & Sarvatjoo H. (2015). the nature and role of virtual architecture education in the information technology age. International Conference on Architecture, Urban Planning. Civil Engineering. Art and Environment; Future Horizons. Looking to the Past.Tehran. [persian].
9. Asadpour A. (2021). Student challenges in online architectural design courses in Iran during the COVID-19 pandemic. E-Learning and Digital Media.
10. Azar A, & Gholamzadeh R, & Ghanavati M . (2012). SEM in Managment with Smart Tehran. Negah Danesh Publications. [persian].
11. Azizi A, & Zarabian F. (2020). Investigating the effect of corona on students' electronic satisfaction in universities with virtual systems. Sixth International Conference on Psychology. Counseling and Educational Sciences. [persian].
12. Azizi far M.J, Mohammadian A, Safari A. (2015). Provide an e-learning model based on strategic and architectural perspectives. The Second International Conference on Industrial Management and Engineering.
13. Bakhtiari R. (2013). Measuring the success of e-learning in government and non-profit centers in Iran. Master Thesis, Allameh Tabatabai University. Faculty of Management and Accounting.
14. Barat Dastjerdi N, & Davarpanah S. (1398). Structural Equation Modeling of Relationships between Learning Management System (LMS) Capabilities by Strengthening Motivational Beliefs and Self-Regulated Learning Strategies of Virtual Students of Isfahan University. Bi-Quarterly Journal of Cognitive Strategies in Learning. 7 (12): 108-87. [persian]
15. Bonk C.J., KimK.J. & Zeng T.T. (2006). Future directions of blended learning in higher education and workplace learning settings, in Handbook of blended learning: Global perspectives. local designs. 550-567.
16. Chen W. S., & Yao A. Y. T. (2016). An empirical evaluation of critical factors influencing learner satisfaction in blended learning: A pilot study. Universal Journal of Educational Research. 4(7): 1667-1671.‏
17. Chin W. (1998). The partial least squares approach to structural equation modelling. In G. A.
18. Cidral W. A., Oliveira T, Di Felice M, & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education. 122: 273-290.
19. Cross J. (2006). Forewards, in The handbook of blended learning: Global perspectives, local designs, C.J. Bonk and C.R. Graham. Editors.
20. Ebrahimpour M, Sobhani Nejad, M. (2015). Assessing the current and desirable status of the virtual university curriculum from the students' point of view. Two scientific-research quarterly journals of Shahed University. 22 (7).
21. Ebrahimzadeh S, Mousavi MS, & Adam Nohusi Sh. (2013). Investigating the position of virtual education in learning architecture. The first ever new ideas and technologies in architecture. 78-84.[persian].
22. El-Masri M, & Tarhini A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Educational Technology Research and Development. 65(3): 743-763.
23. Eom S. B., & Ashill N. (2016). The determinants of students’ perceived learning outcomes and satisfaction in university online education: An update. Decision Sciences Journal of Innovative Education. 14(2): 185-215.
24. Faizi K,Taqwaifard M.T , Sufi gang C, & Vahidi H. (1398). Identifying and modeling the factors affecting the electronic readiness of manufacturing industries to establish electronic production. Journal of Tomorrow Management. 18. [persian].
25. Fan C. K., & Cheng C. L. A (2006). study to identify the training needs of life insurance sales representatives in Taiwan using the Delphi approach, Int. J. Train. Dev. 10: 212–226.
26. Ghanbari S, Razzaqi Shirsavar, H, Ziaee, M. S, & Mosleh, M. (2018). Presenting an evaluation model of e-learning in the electronic unit of Islamic Azad University. Journal of Educational Management Research. 11 (41): 100-75. .[persian]
27. Grover R, & Wright A. (2020). National Design Studio Survey: Findings.
28. Ishrat Zamani, B, Abstinence, R, & Kaviani, H. (2015). Identify the challenges of evaluating students' academic performance in e-courses. Journal of Educational Technology. 9 (3): 206-99.
29. Jafari H, Kashmiri, F, Darreh Shiri, S, Abraghai s.k, Baghean N. (2020). Explain the views and experiences of e-teachers and learners in relation to the challenges of e-learning in Shahid Sadoughi University of Medical Sciences, Yazd. Journal of Yazd Medical Education Studies and Development Center. 15 (2):128-116.
30. Jochems W,. van Merriënboer J.J.G, & Koper (2004). Integrated e-learning: Implications for pedagogy, technology and organization. Routledge.
31. Karslı U. T. (2015). Factors influencing function and form decisions of interior architectural design studio students. Procedia-social and behavioral sciences. 174: 1090-1098.
32. Kim J., Kim J. J., & Han S. H. (2021). Understanding Student Acceptance of Online Learning Systems in Higher Education: Application of Social Psychology Theories with Consideration of User Innovativeness. Sustainability. 13(2): 896.
33. Maleki A, Alizadeh P. (2007). Develop a model for a virtual online architectural design workshop. The second e-learning conference, Zahedan. [persian].
34. Mojtahedzadeh R, Mohammadi, R, Emami A. H. (2011). Educational design, implementation and evaluation of an e-learning system, an experience in Tehran University of Medical Sciences. Iranian Journal of Medical Education. 11 (4): 359-348.
35. Mtebe J. S., & Raphael C. (2018). Key factors in learners’ satisfaction with the E-Learningsystem at the University of Dar es Salaam, Tanzania. Australasian Journal of Educational Technology. 34(4):107–122.
36. Namehe (2017). Predicting the level of user satisfaction with the quality of e-learning courses using adaptive neural fuzzy inference system design. Master Thesis. Allameh Tabatabai University, Faculty of Management and Accounting.
37. Narenji Thani, F, Pourkarimi, J, Hejazi, .S. (2021). Identifying the components of e -learning system at University of Tehran. Technology of Education Journal. 15(2): 321-337.
38. Phutela N, & Dwivedi (2020). "A qualitative study of students' perspective on e-learning adoption in India", Journal of Applied Research in Higher Education. 12 (4): 545-559.
39. Portavakoli Chatroudi (1396). Designing an e-content development model based on the factors affecting e-learning satisfaction. Master Thesis. Faculty of Literature and Humanities. Shahid Bahonar University of Kerman..[persian]
40. Portavakoli, A, Ali Nejad, M, & the Daneshmand, B. (2020). Designing an e-content development model based on the factors affecting e-learning satisfaction. Scientific Journal of Education Technology. 15 (1). .[persian]
41. Pourkarimi J, & Alimardani Z. (2020). Factors affecting interactions in e-learning environments (meta-combined studies). Quarterly Journal of Information and Communication Technology in Educational Sciences. 11 (1): 44-25.[persian].
42. Pozón-López I, Higueras-Castillo E, Muñoz-Leiva F, & Liébana-Cabanillas F. J. (2020). Perceived user satisfaction and intention to use massive open online courses (MOOCs). Journal of Computing in Higher Education. 1-36.
43. Rashidi H, Movahedin, M. (1399). Providing a model for accepting the e-learning system in Qazvin University of Medical Sciences. Technology Development Quarterly. 16 (64). [persian].
44. Rasouli R, Pahlavani najad D. (2013). Designing a model to measure the factors affecting learner satisfaction in the e-learning system of universities with distance education system. PhD Thesis, Faculty of Psychology and Educational Sciences, Payame Noor University.
45. Rayat-Pishe S, Ahmadi Kohnali R, Abbasi M. (1397). Applying a combined, qualitative approach and multi-criteria decision making in order to present a sustainable supply chain model in the petrochemical industry. Journal of Industrial Management Studies. 16 (51): 180-145. [persian].
46. Riandi H., Respati H., & Hidayatullah S. (2021). Conceptual Model of User Satisfaction as Mediator of E-Learning Services and System Quality on Students’ Individual Performance. International Journal of Research in Engineering, Science and Management. 4(1): 60-65.
47. Saghafi M.R. (2016). A comprehensive combined model for teaching architecture: a combination of face-to-face and virtual learning environments. Journal of Education Technology. 9 (4): 263-253. [persian].
48. Salama A & Wilkinson N. (2007). Introduction: Legacies for the future of design studio pedagogy, in Design studio pedagogy: horizons for the future, A. Salama and N. Wilkinson. Editors. The Urban International Press: Gateshead. p. 3-8.
49. Salehi S, Ghasemi M, Shalbaf O, & Namdari W. (2016). Analysis of cognitive themes of teachers' lived experience regarding the quality of e-learning courses. Applied Psychological Research. University of Tehran. 1 (7): 136-115.
50. Sandelowski M, Barroso J. (2003). Reading qualitative studies. International journal of qualitative methods. 9 (9):72-912.
51. Sarboland Kh. (2019). Presenting an e-learning model on teachers' satisfaction with learning in the units of Islamic Azad University of Ardabil province. [persian]
52. Serdyukov P, & Hill R. (2013). “Flying with clipped wings: Are students independent in online college classes”. Journal of Research in Innovative Teaching. 6(1): 52-65.
53. Shao Y.J., Daley & Vaughan L. (2007). Exploring Web 2.0 for virtual design studio teaching, in Australasian Society for Computers in Learning in Tertiary Education. Singapore. 918-922.
54. Shareat-Rad F, Adineh Dostabadi M,Dehbandi R, & Senmari, F. (2021). Factors affecting online education of architectural design workshop Case study of the Faculty of Architecture and Urban Planning of Shahid Beheshti University. Scientific Journal of Architecture and Urban Planning, 31 (2): 82-61. [persian].
55. Shaver J. M. (2015). Testing for mediating variables in management research: concerns, implications, and alternative strategies, Journal of Management. (39): 331-313.
56. Strauss A.L., & Corbin JM, (1998). Basics of qualitative research: techniques and procedures for developing grounded theory. 8 nd edn. Thousand Oaks. California.
57. Ustaomeroglu A. A. (2015). Concept-interpretation-product in architectural design studios-Karadeniz technical universty 2nd semester sample. Procedia-social and behavioral sciences. 197:1897-1906.
58. Vica c. (2015). A case study for evaluating nursing and health sciences student satisfaction with e-Learning. Unpublished Master’s thesis. University of Ontario Institute of Technology.
59. Viera A. J., & Garrett J. M. (2005). Understanding interobserver agreement: the kappa statistic. FAM Med. 37(5): 360-363.
60. Wang C. H., Shannon M., & Ross M. E. (2013). “Students’ characteristics, selfregulated learning, technology self-efficacy, and course outcomes in online learning”. Distance Education. 34(3): 302-323.
61. Yunusa A. A., & Umar I. N. (2021). A scoping review of Critical Predictive Factors (CPFs) of satisfaction and perceived learning outcomes in E-learning environments. Education and Information Technologies. 26(1): 1223-1270.
62. Zimmer L. (2006). Qualitative meta-synthesis: a question of dialoguing with texts, Journal of Advanced Nursing. 13 (3 ): 399-392.