Developing a Model for Performance Evaluaion of Teachers in Electronic Education System Using Adaptive Neuro Fuzzy Inference System (ANFIS)
Subject Areas :
Education
Amir Daneshvar
1
,
Mahdi Homayounfar
2
,
Mahdi Fadaei Eshkiki
3
,
esfandiar doshmanziari
4
1 - Assistant Professor of information technology Management, Faculty of Management, Electronic Branch, Islamic Azad University, Tehran, Iran
2 - Assistant professor of Industrial Management, Rasht branch, Islamic Azad University, Rasht, Iran
3 - Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran
4 - faculty member of islamshahr Azad University
Received: 2019-10-03
Accepted : 2021-11-14
Published : 2021-10-23
Keywords:
learning management system,
Keywords: Teacher Performance Evaluation,
Adaptive Neuro Fuzzy Inference System (ANFIS),
Virtual Education,
Abstract :
Introduction: According to the significant evolution of learning systems in recent years and the prevailing conditions of human life due to the epidemic of COVID 19 virus, the importance of e-learning in the learning management system is undeniable. This has made the role of teachers in education systems more prominent than ever. Accordingly, the aim of this study is to provide an intelligent adaptive neuro fuzzy inference system (ANFIS) to evaluate the performance of teachers in e-learning system, especially in academic institutions.
research methodology: In terms of method, this research is descriptive and from the objective point of view it's applied. In this research, a quantitative approach has been used to design a model for evaluating the performance of teachers in the e-learning system. The statistical population of the study included experts in the field of information technology management of the Islamic Azad University of Yazd Province. Based on the pre-determined specifications, it includes 29 people. Due to the limited number of under study elements, a questionnaire was sent to all elements of the statistical population where 17 experts answered the questions. In this study, an adaptive neuro fuzzy inference system (ANFIS) method has been used to analyze the performance of teachers in educational institutions.
Findings: This system is based on 4 main factors (teaching learning process, teaching method, research orientation and individual capabilities) and 16 sub-factors in the teacher evaluation process. The designed ANFIS system classifies the performance of teachers into four predefined categories: teachers need for training, teachers with good skills, teachers who are very good and teachers who are excellent.
Conclusion: The designed system is a useful tool for evaluating teachers and providing appropriate feedback on their strengths and weaknesses to improve their performance.
References:
Abreo, A., Roch, A., Vidal del carvalho, J., Perez Cota, M. (2017). The electronic booklet on teaching-learning process: Teacher vision and parents of students in primary and secondary education. Telematics and Infarmatic, 34, 861-878.
Aghaali, M., Safaeipour, R. (2016). An Assessment of Some Effective Factors on Faculty Members Evaluation Score by Medical Students in Qom. J Med Educ Dev, 8 (20), 1-8. [in persian]
Balahadia, F.F., Fernando, M.C.G., Juanatas, I.C., (2016). Teacher's performance evaluation tool using opinion mining with sentiment analysis. Conference of Region 10 Symposium, IEEE. Bali, Indonesia.
Brandon, J., Derrington, M..L. (2019). Supporting Teacher Growth and Assuring Teaching Quality Differentiated Teacher Evaluation and Professional Learning, Palgrave Studies on Leadership and Learning in Teacher Education, https://doi.org/10.1007/978-3-030-16454-6_1.
Calabrese, R. L., Sherwood, K., Fast, J., Womack, C. (2004). Teachers' and Principals' Perceptions of the Summative Evaluation Conference: An Examination of Model I theories‐in‐use. International Journal of Educational Management, 18 (2), 109-117.
Campbell, A.B. (2014). Understanding the Teacher Performance Evaluation Process from The Perspective of Jamaican Public School Teachers. PhD thesis, Department of Leadership, Higher and Adult Education, University of Toronto.
Danielson, C. (1996). Enhancing Professional Practice: A Framework for Teaching, 2nd Edition. Alexandria publication.
Dolati, A. A., Jamshidi, L., Aminbeidokhti, A. A. (2015). Improving the teaching process- learning smart schools from the perspective of evaluation, Teaching and Learning Studies, 7(2), 1-20. [in persian]
Dolati, A. A., Jamshidi, L., Aminbeidokhti, A. A. (2016). Essential Characteristics of Teachers in Improving Teaching- Learning Process at Smart School. Instruction and Evaluation, 9, 77-96. [In Persian]
Feng, L., Su, Y., Hsu, C.H., Yang, C.C. (2013). How the Teacher E-evaluation System Enhances the Professional Development of k-12 Teachers: The Case of Taiwan. Procedia- Social and Behavioral Sciences, 106, 1357-1367.
Findawati, Y., Taurusta, C.W.I. (2018). Teacher Performance Assessment Application using Naive Bayes Classifier Method, International Symposium on Materials and Electrical Engineering (ISMEE) .
Flégl, M., Ollivier, M.B.F., Švec, V., Barajas, J. B., Vizuet, C. (2017). Analysis of Professors' Evaluation at La Salle University México from 2010 to 2016: What the Results Indicate? Journal on Efficiency and Responsibility in Education and Science, 10 (3), 76-85.
Galavandi, H., Ghalee, A., Beheshtirad, R. (2014). Investigation of the Students\' Perceptions and Expectations of Educational Service Quality in Urmia University and Its Relationship with the Evaluation of Faculty Members' Performance. The Journal of New Thoughts on Education, 9 (4), 119-145. [in persian]
Goos, M., Salomons, A. (2017). Measuring teaching quality in higher education: assessing selection bias in course evaluations. Research in Higher Education, 58(4), 341–364.
Heneman, H.G. Milanowski, A. Kimball, S.M., Odden, A. (2006). Standards-based teacher evaluation as a foundation for knowledge-and skill based pay (RB-45). Consortium for Policy Research in Education. Philadelphia.
Hooshi-al-Sadat, S., Ebrahimi, A., Molaei, H. (2017). Creation and validation of the questionnaire on the quality assessment of faculty members of the Farhangian University: A 360-degree approach. Educational and Scholastic studies, 6 (1), 89-103. [in persian]
Hosseini, S., Shahhosseini, M., Fani, A.A., Ahmadzehi, A. (2021). Developing and Designing Competency-Based Performance Management Elevation Model on High School Teacher in Iran: a mixed-method approach. Journal of Management and Planning in Educational System, 13 (2), 195-236. [in persian]
Joy, J., Vemballiveli, R., Govinda Pillai, R.V. (2021). Review and classification of content recommenders in E-learning environment. Journal of King Saud University - Computer and Information Sciences (In press).
Khaleghinejad, S.A. (2011). Evaluation of Primary and Secondary School Teachers Performance Based on the Framework for Education Model. First National Conference on Education in Iran 1404. Tehran, Science, Technology and Industry Policymaking Institute. [in persian]
Lin, Y. Lian, J. (2018). Intelligent Recommendation System for Education. Precedia Computer Science, 129, 449-453.
Liu, D., huang, R., wosinski, M. (2017), Characteristics and framework of smart learning in smart learning in smart cities. Lecture notes in educational technology. Springer, singapre.
López-Cámara, A. B., Eslava-Suanes, M. D., González-López, I., González, H. G., León-Huertas, C. D. (2018). Skills of university professor and their evaluation. In Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality, 175-179.
Mohajeran, B., Pashaei, A., Kondy, Y. (2020). Analysis of the Performance Evaluation Process of University Professors. Second National Conference on Humanities and Development, 1-9. [In persian]
M. (2017). Evaluation Study Effect of Allowances and Job Creativity Performance of the Teacher in Secondary Vocational School Province, International Education Studies, 10(8), 96-107.
Pianta, R. C., Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38(2), 109-119.
Pourbaghban, S., Mahmoodi, F., Fathiazar, E, Kohestani, B., (2020). Virtual Reality Based Curriculum in Science Education. CSTP, 8 (16), 41-118. [in persian]
Pourhaydari, R., sameri, M., Hassani, M., Mirtazanejad, N. (2019). Structural Relationships between Organizational Trust, Professional Ethics, Organizational Structure with school Effectiveness with Mediating Role of Teachers’ Performance Evaluation. Journal of Instruction and Evaluation, 12 (47), 93-116. [in persian]
Poorrashidi, Z., Akhlaghy, M., Alinejad, M. (2019). Analysis of Intelligent making of Schools Based on Swot model. Educational and Scholastic studies, 7 (2), 85-111. [in persian]
Saneii, Z. (2018). Students’ Standpoint about Qualitative Assessment of Performance of Faculty Members. Educ Strategy Med Sci, 11 (2), 97-105. [in persian]
Stobie, T. (2016). Developing your school with Cambridge, A guide for school leaders. Director of Education, Cambridge International Examinations.
Strong, M., Gargani, J., Hacifazlioğlu, O. (2011). Do we know a successful teacher when we see one? Experiments in the identification of effective teachers. Journal of Teacher Education, 62 (4), 367-382.
Thawabieh, A. M. (2017). Students Evaluation of Faculty. International Education Studies, 10 (2), 35-43.
Tuytens, M., Devos, G. (2010). The influence of school leadership on teachers’ perception of teacher evaluation policy. Educational Studies, 36 (5), 521-536.
Vahabi, A., Rahmani, S., Rostami, S., Vahabi, B., Hosseini, M., Roshani, D. (2015). Factors affecting teacher evaluation scores: the studentsviewpoints of Kurdistan University of Medical Sciences. Iranian J Med Educ,15, 111-121.
Windsor, A. (2017). Nursing student’s perceptions ofclinical experience. J Nurs Educ. 26 (4), 150-154.
Xinyu, N. (2019). What influences school district effectiveness growth trajectories? A growth mixture modeling (GMM) analysis. Doctoral tesis, Columbia University.
Yaghoubi, M., Salimi, M. (2018). Determining the Factors affecting Faculties’ educational evaluation in a Military University of Medical Sciences in Tehran, Iran. J Mil Med, 20 (1), 73-82. [in persian]
Yoo, J. (2018). Evaluating the new teacher evaluation system in South Korea: Case studies of successful implementation, adaptation, and transformation of mandated policy. Policy Futures in Education, 1-14.
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