بهبود ارزشیابی اساتید با استفاده از منطق فازی
محورهای موضوعی : پژوهش در برنامه ریزی درسی
ایمان ذباح
1
(گروه کامپیوتر، دانشگاه آزاد اسلامی تربت‌حیدریه، تربت‌حیدریه، ایران)
سعید میرزاده
2
(گروه کامپیوتر، دانشگاه آزاد اسلامی تربت‌حیدریه، تربت‌حیدریه، ایران)
سمانه جعفری
3
(گروه کامپیوتر، دانشگاه آزاد اسلامی تربت‌حیدریه، تربت‌حیدریه، ایران)
کلید واژه: استنتاج فازی, ارزشیابی اساتید, منطق فازی,
چکیده مقاله :
ارزشیابی‌های متکی بر روش‌های کلاسیک آماری عموماً مطلق‌گرا هستند و از این‌رو دستیابی به نتیجه قابل اعتماد را با مشکل مواجه می‌سازند. یکی از دلایل این است که منابع مورد استفاده ذاتاً اطلاعات نادقیق دارند و از این‌رو شرایط را برای یک ارزشیابی سالم سخت می‌کنند. ارزشیابی مبتنی بر منطق فازی به دلیل توانایی استنتاج از داده‌های نایقین می‌تواند جایگزین مناسبی بر روش‌های کلاسیک باشد که در این پژوهش مورد بررسی قرار گرفته است. در این پژوهش جامعة آماری تحقیق را 105 نفر از دانشجویان و 15 نفر از اساتید رشته‌های مختلف دانشگاه آزاد اسلامی تربت‌حیدریه تشکیل می‌دادند. توزیع پرسش‌نامه استاندارد سازمان مرکزی دانشگاه آزاد اسلامی بین این تعداد از دانشجویان جهت ارزیابی اساتید انجام گرفت. سپس درجه اهمیت هر سؤال نظرسنجی توسط این تعداد از اساتید تعیین شد. همچنین اثر وزنی تجربه هر استاد در پاسخ به درجه اهمیت هر سؤال و نیز پارامتر تعداد ارزیابان در سیستم ارزشیابی اساتید مد نظر قرار گرفت. روش تحقیق از نوع توصیفی تحلیلی بوده است. سیستم استنتاج فازی از نوع ممدانی انتخاب شد که با دریافت دو ورودی فازی و با توجه به پایگاه قوانین فازی، خروجی مطلوب را فراهم می‌کند. برای تجزیه‌وتحلیل از 50 گروه درس متفاوت استفاده شد. نتایج نشان می‌دهد که در ارزشیابی‌های مختلف به روش‌های کلاسیک آماری و امید ریاضی و استنتاج فازی، روش ارزشیابی فازی می‌تواند با دقت بالاتری به رتبه‌بندی اساتید بپردازد.
Classic statistical evaluation models are generally absolute and therefore make it difficult to achieve reliable results. One reason for this is that the sources used, inherently, contain inaccurate information and make the conditions difficult for a valid evaluation. In this study, using fuzzy inference, educational evaluation of professors was conducted. Due to the uncertain nature of the fuzzy theory, it is possible to analyze and evaluate information more precisely. The standard questionnaire of Islamic Azad University was distributed among 105 students to evaluate teachers. Then, the priority of each survey question was determined by interviewing some professors. The weighting effect of each professor's experience in response to each question priority and, also, the number of assessors' parameter in their evaluation system were considered. Mamdani type fuzzy inference system was chosen which receives two input fuzzy and provides the desired output based on fuzzy rule base. Finally, using three methods for evaluation including classic evaluation, evaluation with the expected value and fuzzy evaluation, have shown that the rating of teachers using fuzzy logic could be closer to reality.
Aghmolaie, Temour, and Sedighi Abedini. 2007. “Comparison of Educational Performance Evaluation of Faculty Members of School of Health of Hormozgan University of Medical Sciences by Students with Self-Assessment of Professors.” 2(7): 191–99.
Arabi Mianroudi AA, Askari Baravati Z, and Khanjani N. 2012. “Determining Advantages and Disadvantages of Different Teachers` Evaluation from Teachers Affiliated with Kerman University of Medical Sciences Points of View.” Development Steps in Medical Education 9(2): 65–76.
Atashak, Mohammad, and Isa Samari. 2011. “The Effect of Teachers’ Knowledge and Application of Teaching Technology in Improving the Quality of Students Learning Process.” Educational Technology 2(4): 101–11.
Bastani, Peyvand, Mitra Amini, Ali Tahernejad, and Naire Rouhollahi. 2014. “The Tehran University of Medical Sciences Faculty Members’ Viewpoints about the Teachers’ Evaluation System: A Qualitative Study.” thums-jms YR - 2014 (1): 7–16 K1 Evaluation K1 Faculty Member K1 Teacher K1. http://jms.thums.ac.ir/article-1-102-fa.html.
Beheshti Rad, R, H Ghalavandi, and A R Ghale’ei. 2014. “Faculty Members Performance Evaluation by Nursing Students Urmia University of Medical Sciences.” Education Strategies in Medical Sciences 6(4): 223–28.
Causeman, R, and J Hermen. 1995. “Strategic Planning in Educational System (Reevaluating, Reconstructing the Structures, Regenerating), Translated by Farideh Mashayekh and Abbas Bazargan.” Tehran: Madreseh.
Fattahi, Z. 2005. “Review of the Opinions of Scientific Board’s Members of Tehran Medical Sciences University about the Evaluation of the Professor in Academic Year of 2002-2003.” Hormozgan Medical journal 9: 59–66.
Gien, Lan T. 1991. “Evaluation of Faculty Teaching Effectiveness-toward Accountability in Education.” Journal of Nursing Education 30(2): 92–94.
Golec, Adem, and Esra Kahya. 2007. “A Fuzzy Model for Competency-Based Employee Evaluation and Selection.” Computers & Industrial Engineering 52(1): 143–61.
Guruprasad, Mamatha, R Sridhar, and S Balasubramanian. 2016. “Fuzzy Logic as a Tool for Evaluation of Performance Appraisal of Faculty in Higher Education Institutions.” In SHS Web of Conferences, EDP Sciences.
Jyothi, G, C Parvathi, P Srinivas, and Mr Sk Althaf. 2014. “Fuzzy Expert Model for Evaluation of Faculty Performance in Technical Educational Institutions.” International Journal of Engineering Research and Applications 4(5): 41–50.
Khademi Zare, Hassan, and Mohammad Bagher Fakhrzad. 2013. “Integration of Collaborative Management and Fuzzy Systems for Evaluating of Students’ Educational Performance.” Quarterly Journal of Research and Planning in Higher Education 19(3): 23–40.
MAAROFI, YAHYA. 2011. “THE DETERMINING OF TEACHING COMPONENT WEIGHT FOR EVALUATION OF FACULTY MEMBER PERFORMANCE WITH ANALYTICAL HIERARCHY PROCESS MODELS.”
Mirfakhradin, S.H., Owlia, M.S., & Jamali, R. 2009. “Reverse Engineering Quality Management in Center Learning Higher.” Quarterly Journal of Research and Planning in Higher Education 15: 131–57.
Mirza Mohamadi, M.H. 2010. “Design Algorithm Evaluation, Improvement Education Group Art and Architected on Research Program.” Quarterly Journal of Research and Planning in Higher Education 17: 153–77.
Motamedi, Ahman, and Sadegh Rafie. 2001. “A Flexible Way to Evaluate Students’ Performance Using Fuzzy Logic.” In 11th Iranian Fuzzy Systems Conference, http://www.civilica.com/Paper-ICFUZZYS11-ICFUZZYS11_099.html.
Mousavi, Shokufeh et al. 2014. “Evaluation of Faculty Members in the Psychiatry Group of Babol University of Medical Sciences: Viewpoints of Internship Medical Students.” Biannual Journal of Medical Education Education Development Center (edc) Babol University of Medical Sciences 2(2): 37–42.
Rasti, Mehdi. 2016. “Presenting a Model for Determining the Relationship between the Responded Educational Planning and Perceived Evaluation of Class on the Basis of Mediation of Academic Involvement.” JSR 2(23): 64–78.
rigi, atefeh, mostafa ghaderi, and Jamal salimi. 2016. “Comparing Teachers’ Function Evaluation by Video Data with Other Methods of Teaching Function Evaluation.” JSR 2(23): 27–39.
Saberi, Reza. 2017. “Evaluation the Art Education System in Primary School with Approach of Major Areas and Content Structure: A Study of Teachers, Principals and Experts’ Views.” Research in Curriculum Planning Vol 13(. No 24): 75–86.
Sarchami, R. 2005. “Review of the Professors and Managers’ Opinions of Group of Iran Medical Sciences University about the Effect of Evaluation of the Students by the Professors on the Performance of the Professors during Years 2001-2008 [Thesis in Persian]. Iran University .” Management Faculty and Medical Information.
Seif, A A. 1991. “Evaluation of the Students by the Professors: How Much Can It Be Trusted.” Tehran: Psychological researches: 1–2.
Upadhyay, Mamatha S. 2012. “Fuzzy Logic Based on Performance of Students in College.” Journal of Computer Applications (JCA) 5(1): 6–9.
Zabbah, I., S. Foolad, B. Chaharaqran, and R. Mazlooman. 2013. “Designing and Making the Intelligence Assistant Robot and Controlling It by the Fuzzy Procedure.” International Conference on Electronics, Computer and Computation, ICECCO 2013,.
Zameni, Farshide, and Sahar Kardan. 2010. “The Effect of Applying Information and Communication Technology on Math Learning.” Journal of Information and Communication Technology in Educational Sciences 1(1): 23–38.
_||_