Structural Model of Factors Affecting Educators' Information Self-Efficacy

Document Type : Original Article


1 Associate Professor, Department of Education, University of Mohaghegh Ardabili, Ardabil, Iran

2 Associate Professor, Department of Education, University of Mohaghegh Ardabili, Ardabil, Iran.

3 M.A., Educational Administration, Department of Education, University of Mohaghegh Ardabili, Ardabil, Iran


Objectives: In terms of essence, content, and process, education is an interaction-oriented subject. Considering changes in the form and quality of communication, educators should optimally use information technologies for establishing efficient educational interactions; this depends on the development of necessary knowledge, attitude, skills, and belief in abilities. Various factors affect competence development and belief formation. This research aimed to identify the factors that affect the belief formation in informational abilities, particularly in the informational self-efficiency of educators.
Methods: The present study was conducted using a correlational design. The statistical population consisted of primary educators in Ardabil city. Using Cochran's formula, 317 educators were randomly selected as a sample and participated in the research. Donohoo scale and Murphy, Coover and Owen questionnaire were used to measure enabling factors and information self-efficacy. Data analysis was done using descriptive statistics, Pearson correlation test and structural equation analysis through SPSS and LISREL.
Results: Structural equation modeling showed that the model of informational self-efficiency enabling factors has a good fit with the data and all six factors (including advanced influence, goal consensus, awareness of each other, cohesiveness, responsiveness of leadership and effective systems of intervention) have a significant positive effect on informational self-efficiency.
According to these results, the responsiveness of leadership with a coefficient of 0.68 had the greatest impact on information self-efficacy, followed by advanced influence with a coefficient ‎ of 0.63, cohesiveness with a coefficient of 0.47, awareness from each other with a coefficient of 0.42, intervention system effective systems of intervention with the coefficient of 0.39 and goal consensus with the coefficient ‎ of 0.29.
Conclusions: With regard to confirming the significant role of the sextuplet factors in information self-efficacy and fitting the examined model using the data, the intervention can be concentrated on the plans and instructions developed based on the mentioned factors for enhancing the educational agents’ belief in their information capabilities. Participation and effectiveness in determining the goals and the opportunity to play a role provide the educational workers with a chance to achieve successful experiences. Consensus on the goals results in more cohesion, integration, and coordination of educators. Awareness of the other educators’ experiences provides the opportunity of modeling, observe, and learn. In addition, the educational leader can provide educators with the conditions, motivation, and focus necessary for training, mastery, learning from others, and acquiring experience in information technologies. Finally, implementing interventions strengthens the belief in educators that they can make changes with their efforts and contribute to educational achievement.


Main Subjects

Association of College & Research Libraries (2016). Framework for Information Literacy. Retrieved in May 2021 from:
Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2): 191.
DiPaola, M. & Hoy, W.K. (2008). Principals improving instruction: Supervision, evaluation, and professional development. IAP.
Doğru, M. (2017). Development of a self-efficacy scale of technology usage in education. Eurasia Journal of Mathematics, Science and Technology Education, 13(6): 1785-1798.     
Donohoo, J. & Katz, S. (2019). What drives collective efficacy?. Educ Leadersh, 76(6): 24-29.
Donohoo, J. (2017). Collective efficacy: How educators' beliefs impact student learning. Corwin Press.
Donohoo, J., O'Leary, T. & Hattie, J. (2020). The design and validation of the enabling conditions for collective teacher efficacy scale (EC-CTES). Journal of Professional Capital and Community, 5(2): 147-166. DOI:
Goddard, R., Goddard, Y., Sook Kim, E. & Miller, R. (2015). A theoretical and empirical analysis of the roles of instructional leadership, teacher collaboration, and collective efficacy beliefs in support of student learning. American Journal of Education, 121(4): 501-530.
Gudek, B. (2019). Computer Self-Efficacy Perceptions of Music Teacher Candidates and Their Attitudes towards Digital Technology. European Journal of Educational Research, 8(3):
683-696. DOI:
Halverson, R. & Smith, A. (2009). How new technologies have (and have not) changed teaching and learning in schools. Journal of computing in Teacher Education, 26(2): 49-54.
Hamidi, F. & Shirzad Aski, M. (2016). Relationship between Personality Characteristics and Metacognitive Strategies with Computer Self-efficacy in Student-Teachers. Information and Communication Technology in Educational Sciences, 6 (24): 23-38. [in persian]
Hattie, J. (2016). Third annual visible learning conference (subtitled Mindframes and Maximizers). Washington, DC, July, 11, 2016. Retrieved in May 2021 from:
Hoy, W.K. & Miskel, C. (Eds.). (2013). Educational Administration: Theory, Research, and Practice. McGraw Hill.
Keshavarz, H., Shabani, A. & Fahimniya, F. (2015). Information Literacy Self-efficacy: Conceptual Framework and Research Background. Academic Librarianship and Information Research, 49(1): 1-22. [in persian] DOI:
Khaleghkhah, A. & Babaei Menghari, M.M. (2016). Relationship between Identity Properties and Computer Anxiety with Computer Self-efficacy of High Schools Students. Educational Psychology, 12(39): 157-173. [in persian] DOI:
Kurbanoglu, S. (2010). Self-efficacy: an alternative approach to the evaluation of information literacy. In: Qualitative and Quantitative Methods In Libraries: Theory and Applications
(pp. 323-328). DOI:
Lee, J.C.K., Zhang, Z. & Yin, H. (2011). A multilevel analysis of the impact of a professional learning community, faculty trust in colleagues and collective efficacy on teacher commitment to students. Teaching and teacher education, 27(5): 820-830.          
López-Vargas, O., Duarte-Suárez, L. & Ibáñez-Ibáñez, J. (2017). Teacher’s computer self-efficacy and its relationship with cognitive style and TPACK. Improving Schools, 20(3): 264-277.      
Safari, M., Soleimani, N. & Jafari, P. (2019). Identifying the Development Factors of Teachers’ Collective Efficacy Culture in Tehran Schools from the Perspective of Experts. Journal of New Approaches in Educational Administration, 10(37): 335-358. [in persian]      
Schumacker, R.E. & Lomax, R.G. (2004). A beginner's guide to structural equation modeling. psychology press.
Shahin, S. (2011). The Relationship between Instructional Leadership Style and School Culture (Izmir Case). Educational Sciences: Theory and Practice, 11(4): 1920-1927.
Shonfeld, M., Aharony, N. & Kritz, N. (2020). The Impact of Participating in a Digital Program on Teachers' Perceptions of Their Information Literacy. In: Society for Information Technology & Teacher Education International Conference (pp. 1262-1266). Association for the Advancement of Computing in Education (AACE).
Shonfeld, M., Aharony, N. & Nadel-Kritz, N. (2021). Teachers’ perceived information literacy self-efficacy. Journal of Librarianship and Information Science, 2: 1-4. 
Taqavi, H., Shakeri, M. & Zand Amogain, F. (2020). Validation of Enabling Conditions for Collective Teacher Efficacy Scale (EC-CTES). Applied Educational Leadership, 1(3): 17-32. [in persian]
Taşkın, Z., Doğan, G. & Şencan, İ. (2013). Analyzing the intellectual structure of world information literacy literature through citations and co-citations. In: European Conference on Information Literacy (pp. 54-60). DOI:
Yeşilyurt, E., Ulaş, A.H. & Akan, D. (2016). Teacher self-efficacy, academic self-efficacy, and computer self-efficacy as predictors of attitude toward applying computer-supported education. Computers in Human Behavior, 64: 591-601. DOI: