How to cite this paper
Do, A., Pham, M., Dinh, T., Ngo, T., Luu, Q., Pham, N., Ha, D & Vuong, H. (2020). Evaluation of lecturers’ performance using a novel hierarchical multi-criteria model based on an interval complex Neutrosophic set.Decision Science Letters , 9(2), 119-144.
Refrences
Akram, M., Shahzadi, S., & Smarandache, F. (2018). Multi-Attribute Decision-Making Method Based on Neutrosophic Soft Rough Information. Axioms, 7(1), 19. doi:10.3390/axioms7010019
Aldrup, K., Klusmann, U., Lüdtke, O., Göllner, R., & Trautwein, U. (2018). Student misbehavior and teacher well-being: Testing the mediating role of the teacher-student relationship. Learning and Instruction, 58, 126-136.
Ali, M., Dat, L. Q., Son, L. H., & Smarandache, F. (2018). Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making. International Journal of Fuzzy Systems, 20(3), 986-999.
Ali, M., & Smarandache, F. (2017). Complex neutrosophic set. Neural Computing and Applications, 28(7), 1817-1834.
Alias, M., Masek, A., & Salleh, H. H. M. (2015). Self, Peer and Teacher Assessments in Problem Based Learning: Are They in Agreements? Procedia - Social and Behavioral Sciences, 204, 309-317.
Almeida, J. de C. (2017). Teacher Performance Evaluation: The Importance of Performance Standards. International Journal for Cross-Disciplinary Subjects in Education, 8(1), 2973-2981.
Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96.
Bambaeeroo, F., & Shokrpour, N. (2017). The impact of the teachers’ non-verbal communication on success in teaching. Journal of Advances in Medical Education and Professionalism, 5(2), 51-59.
Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. D. U., & Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907.
Biggs, J. B., & Collis, K. F. (2014). Evaluating the Quality of Learning: The SOLO Taxonomy (Structure of the Observed Learning Outcome). Academic Press, 245 pages.
Bohlmann, N. L., & Weinstein, R. S. (2013). Classroom context, teacher expectations, and cognitive level: Predicting children’s math ability judgments. Journal of Applied Developmental Psychology, 34(6), 288-298.
Bottani, E., & Rizzi, A. (2006). A fuzzy TOPSIS methodology to support outsourcing of logistics services. Supply Chain Management: An International Journal, 11(4), 294–308. doi: 10.1108/13598540610671743
Bradford, A. (2015). Adopting English-Taught Degree Programs. International Higher Education, 69, 8-10.
Brookfield, S. D. (2017). Becoming a Critically Reflective Teacher. John Wiley and Sons.
Buttram, J. L., & Wilson, B. L. (1987). Promising trends in teacher evaluation. Educational Leadership, 44(7), 4-6.
Cegarra-Navarro, J.-G., Soto-Acosta, P., and Martinez-Caro, E. (2016). Linking counter-knowledge to goal orientation through an unlearning context - A study from a Spanish University. Learning and Individual Differences, 45, 260-267.
Cegarra-Sánchez, J., & Cegarra-Navarro, J.-G. (2017). Making meaning out of noise: A knowledge management core competence for higher education students. VINE Journal of Information and Knowledge Management Systems, 47(4), 506-521.
Chappuis, S., Commodore, C., and Stiggins, R. (2016). Balanced Assessment Systems: Leadership, Quality, and the Role of Classroom Assessment. Corwin Press.
Cheng, M. M. H., Chan, K.-W., Tang, S. Y. F., and Cheng, A. Y. N. (2009). Pre-service teacher education students’ epistemological beliefs and their conceptions of teaching. Teaching and Teacher Education, 25(2), 319-327.
Chi, P., & Liu, P. (2013). An extended TOPSIS method for the multiple attribute decision making problems based on interval neutrosophic set. Neutrosophic Sets and Systems, 1, 1-8.
Colby, S. A., Bradshaw, L. K., & Joyner, R. L. (2002). Teacher evaluation: A review of the literature. Annual Meeting of the American Educational Research Association, New Orleans, LA, 1-18.
Cuevas, R., Ntoumanis, N., Fernandez-Bustos, J. G., and Bartholomew, K. (2018). Does teacher evaluation based on student performance predict motivation, well-being, and ill-being? Journal of School Psychology, 68, 154-162.
Danielson, C. (2000). Teacher evaluation to enhance professional practice. Retrieved from http://ebookcentral.proquest.com/lib/ucm/detail.action?docID=280406
Darling-Hammond, L. (2017). Teacher education around the world: What can we learn from international practice? European Journal of Teacher Education, 40(3), 291-309.
Davey, B. (1991). Evaluating teacher competence through the use of performance assessment tasks: An overview. Journal of Personnel Evaluation in Education, 5(2), 121-132.
Derrington, M. L., and Campbell, J. W. (2015). Implementing new teacher evaluation systems: Principals’ concerns and supervisor support. Journal of Educational Change, 16(3), 305-326.
Fabjanowicz, M., Bystrzanowska, M., Namieśnik, J., Tobiszewski, M., and Płotka-Wasylka, J. (2018). An analytical hierarchy process for selection of the optimal procedure for resveratrol determination in wine samples. Microchemical Journal, 142, 126-134.
Fauth, B., Decristan, J., Rieser, S., Klieme, E., and Büttner, G. (2014). Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29, 1-9.
Fischer, C., Fishman, B., Dede, C., Eisenkraft, A., Frumin, K., Foster, B., … McCoy, A. (2018). Investigating relationships between school context, teacher professional development, teaching practices, and student achievement in response to a nationwide science reform. Teaching and Teacher Education, 72, 107-121.
Frunză, V. (2014). Implications of Teaching Styles on Learning Efficiency. Procedia - Social and Behavioral Sciences, 127, 342-346.
Gormally, C., Evans, M., and Brickman, P. (2014). Feedback about teaching in higher Ed: Neglected opportunities to promote change. CBE Life Sciences Education, 13(2), 187-199.
Hein, N., Kroenke, A., & Júnior, M. M. R. (2015a). Professor assessment using multi-criteria decision analysis. Procedia Computer Science, 55, 539-548.
Hwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications A State-of-the-Art Survey. Berlin Heidelberg: Springer-Verlag.
Iantorno, S. E., Andras, L. M., and Skaggs, D. L. (2016). Variability of reviewers’ comments in the peer review process for orthopaedic research. Spine Deformity, 4(4), 268-271.
Ishizaka, A., & Labib, A. (2009). Analytic hierarchy process and expert choice: Benefits and limitations. OR Insight, 22(4), 201-220.
Jaramillo, I. F., Pico, R. B., & Marquez, C. V. (2017). A model for faculty evaluation in higher education ecuadorian through multi-criteria decision Analysis. Indian Journal of Science and Technology, 10(18), 1-8.
Jiayi, W., & Ling, C. (2012). Reviewing teacher evaluation of rewards and punishments: The overview of Chinese teacher evaluation research. Education Research International, 1-16. doi: 10.1155/2012/184640
Johnson, E. D., Al-Mahmood, R., & Maierb, A. G. (2012). Student and staff perceptions of teamwork in groupwriting for science honours. International Journal of Innovation in Science and Mathematics Education, 20(4), 25-41.
Karthikeyan, R., Venkatesan, K. G. S., & Chandrasekar, A. (2016). A comparison of strengths and weaknesses for analytical hierarchy process. Journal of Chemical and Pharmaceutical Sciences 9(3), S-12-S-15.
Kilic, A. (2010). Learner-centered micro teaching in teacher education. International Journal of Instruction, 3(1) 77-100.
King, F. (2014). Evaluating the impact of teacher professional development: An evidence-based framework. Professional Development in Education, 40(1), 89-111.
Kunter, M., & Baumert, J. (2006). Who is the expert? Construct and criteria validity of student and teacher ratings of instruction. Learning Environments Research, 9(3), 231-251.
Kupers, E., van Dijk, M., & van Geert, P. (2015). Within-teacher differences in one-to-one teacher–student interactions in instrumental music lessons. Learning and Individual Differences, 37, 283-289.
Kurtz, S., Draper, J., Silverman, J., Draper, J., & Silverman, J. (2017). Teaching and Learning Communication Skills in Medicine. CRC Press, 2nd edition, 388 Pages.
Lans, R. M. van der, Grift, W. J. C. M. van de, & Veen, K. van. (2018). Developing an instrument for teacher feedback: Using the rasch model to explore teachers’ development of effective teaching strategies and behaviors. The Journal of Experimental Education, 86(2), 247-264.
Lazarides, R., Viljaranta, J., Aunola, K., & Nurmi, J.-E. (2018). Teacher ability evaluation and changes in elementary student profiles of motivation and performance in mathematics. Learning and Individual Differences, 67, 245-258.
Li, G., Gang KOU, G., and Peng, Y. (2015). Dynamic fuzzy multiple criteria decision making for performance evaluation. Technological and Economic Development of Economy, 21(5), 705-719.
Liu, S., & Teddlie, C. (2007). A follow-up study on teacher evaluation in China: Historical analysis and latest trends. Journal of Personnel Evaluation in Education, 18(4), 253-272.
Liu, S., & Zhao, D. (2013). Teacher evaluation in China: Latest trends and future directions. Educational Assessment, Evaluation and Accountability, 25(3), 231-250.
Malakolunthu, S., & Vasudevan, V. (2012). Teacher evaluation practices in Malaysian primary schools: Issues and challenges. Asia Pacific Education Review, 13(3), 449-456.
Malen, B., Rice, J. K., Matlach, L. K. B., Bowsher, A., Hoyer, K. M., and Hyde, L. H. (2015). Developing organizational capacity for implementing complex education reform initiatives: Insights from a multiyear study of a teacher incentive fund program. Educational Administration Quarterly, 51(1), 133-176.
Malik, M. M., Abdallah, S., and Hussain, M. (2016). Assessing supplier environmental performance: Applying Analytical Hierarchical Process in the United Arab Emirates healthcare chain. Renewable and Sustainable Energy Reviews, 55, 1313-1321.
Maltarich, M. A., Nyberg, A. J., Reilly, G., Abdulsalam, D. “Dee,” & Martin, M. (2017). Pay-for-performance, sometimes: An Interdisciplinary Approach to Integrating Economic Rationality with Psychological Emotion to Predict Individual Performance. Academy of Management Journal, 60(6), 2155-2174.
Marzano, R. J., & Toth, M. D. (2013). Teacher Evaluation that Makes a Difference: A New Model for Teacher Growth and Student Achievement. Association for Supervision and Curriculum Development, 192 pages.
Muijs, D., & Reynolds, D. (2017). Effective Teaching: Evidence and Practice. SAGE.
Nahid, B. S., Nasr isfahani, A., Rouhollahi, A., & Khalili, R. (2016). Effective teaching methods in higher education: Requirements and barriers. Journal of Advances in Medical Education and Professionalism, 4(4), 170-178.
Nilson, L. B. (2016). Teaching at Its Best: A Research-Based Resource for College Instructors. John Wiley and Sons, 400 pages.
Odden, A. (2014). Lessons Learned About Standards-Based Teacher Evaluation Systems. Peabody Journal of Education, 79(4), 126-137.
OECD. (2009). Teacher Evaluation: Current Practices in OECD Countries and a Literature Review. OECD Education Working papers, 49 pages.
OECD (Ed.). (2013). Synergies for better learning: An international perspective on evaluation and assessment. OECD reviews of evaluation and assessment in education, 670 pages.
Ovando, M. N. (2001). Teachers’ perceptions of a learner-centered teacher evaluation system. Journal of Personnel Evaluation in Education, (15), 213-231.
Parrish, D. R. (2016). Principles and a model for advancing future-oriented and student-focused teaching and learning. Procedia - Social and Behavioral Sciences, 228, 311-315.
Ramot, D., Milo, R., Friedman, M., and Kandel, A. (2002). Complex fuzzy sets. IEEE Transactions on Fuzzy Systems, 10(2), 171-186.
Reddy, L. A., Dudek, C. M., Peters, S., Alperin, A., Kettler, R. J., and Kurz, A. (2018). Teachers’ and school administrators’ attitudes and beliefs of teacher evaluation: A preliminary investigation of high poverty school districts. Educational Assessment, Evaluation and Accountability, 30(1), 47-70.
Saaty, T. L. (1980). The analytic hierarchy process. Newyork, NY: McGraw-Hill Inc, 17-34.
Saaty, Thomas L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98.
Said, B., Ye, J., & Smarandache, F. (2015). An extended TOPSIS method for multiple attribute decision making based on interval neutrosophic uncertain linguistic variables. Neutrosophic Sets and Systems, 8, 22-31.
Schön, D. A. (2017). The Reflective Practitioner: How Professionals Think in Action. Basic Books, 384 pages.
Sharp, J. A., Peters, J., Howard, K., Peters, J., and Howard, K. (2017). The Management of a Student Research Project. Taylor and Fancis, 278 pages.
Shingphachanh, S. (2018). Teachers’ understanding and concerns about the practices of lesson study in suburb schools in Laos. International Journal for Lesson and Learning Studies, 7(2), 150-162.
Singh, I., & Jha, A. (2014). Difference in Self-reported and Students-rated Teacher Effectiveness among Medical and Engineering Faculty Members: Need for Direct Informal Feedback. American Journal of Educational Research, 2(5), 272-277.
Skedsmo, G., & Huber, S. G. (2018). Teacher evaluation: The need for valid measures and increased teacher involvement. Educational Assessment, Evaluation and Accountability, 30(1), 1-5.
Smarandache, F. (1998). A unifying field in logics. Neutrosophy: Neutrosophic probability, set and logic. American Research Press, Rehoboth, 105 pages.
Sonnert, G., Hazari, Z., & Sadler, P. M. (2018). Evaluating the quality of middle school mathematics teachers, using videos rated by college students. Studies in Educational Evaluation, 58, 60-69.
Steinberg, M. P., and Garrett, R. (2016). Classroom Composition and Measured Teacher Performance: What Do Teacher Observation Scores Really Measure? Educational Evaluation and Policy Analysis, 38(2), 293-317.
Taut, S., Santelices, M. V., Araya, C., & Manzi, J. (2011). Perceived effects and uses of the national teacher evaluation system in Chilean elementary schools. Studies in Educational Evaluation, 37(4), 218-229.
Thomas, S., Chie, Q. T., Abraham, M., Jalarajan Raj, S., & Beh, L.-S. (2014). A Qualitative Review of Literature on Peer Review of Teaching in Higher Education: An Application of the SWOT Framework. Review of Educational Research, 84(1), 112-159.
Tondeur, J., van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555-575.
Torkabadi, A. M., Pourjavad, E., & Mayorga, R. V. (2018). An integrated fuzzy MCDM approach to improve sustainable consumption and production trends in supply chain. Sustainable Production and Consumption, 16, 99-109.
Turksen, I. B. (1986). Interval valued fuzzy sets based on normal forms. Fuzzy Sets and Systems, 20(2), 191-210.
Tuytens, M., & Devos, G. (2017). The role of feedback from the school leader during teacher evaluation for teacher and school improvement. Teachers and Teaching, 23(1), 6-24.
Wager, E., & Kleinert, S. (2012). Cooperation between research institutions and journals on research integrity cases: Guidance from the committee on publication ethics. Saudi Journal of Anaesthesia, 6(2), 155-160.
Wang, H., Smarandache, F., Zhang, Y., & Sunderraman, R. (2010). Single valued Neutrosophic sets. Technical Sciences and Applied Mathematics, 10-14.
Wang, J.-W., Cheng, C.-H., & Huang, K.-C. (2009). Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing, 9(1), 377-386.
Wang, T.-Y., & Hsieh, F.-J. (2017). Taiwanese high school students’ perspectives on effective mathematics teaching behaviors. Studies in Educational Evaluation, 55, 35-45.
Wang, X.,& Chan, H. K. (2013). A hierarchical fuzzy TOPSIS approach to assess improvement areas when implementing green supply chain initiatives. International Journal of Production Research, 51(10), 3117-3130.
Wardil, L., & Hauert, C. (2015). Cooperation and coauthorship in scientific publishing. Physical Review E, 91(1), 1-6.
Wiliam, D., Thompson, M., & Thompson, M. (2017). Integrating assessment with learning: what will it take to make it work? In: Dwyer, C A, (ed.) The Future of Assessment: Shaping Teaching and Learning. (pp. 53-82). Lawrence Erlbaum Associates: Mahwah, New Jersey.
Wisker, G. (2012). The Good Supervisor: Supervising Postgraduate and Undergraduate Research for Doctoral Theses and Dissertations. Palgrave Macmillan, 400 pages.
Wolf, L. A. (2016). The peer review process. Journal of Emergency Nursing, 42(5), 454-456.
Wu, H.-Y., Chen, J.-K., Chen, I.-S., and Zhuo, H.-H. (2012). Ranking universities based on performance evaluation by a hybrid MCDM model. Measurement, 45(5), 856-880.
Wu, M.-J., Huang, C.-Y., Kao, Y.-S., Lue, Y.-F., Chen, L.-C. (2018). Developing a professional performance evaluation system for pre-Service automobile repair vocational high school teachers in Taiwan. Sustainability, 10(10), 3537.
Yang, W., & Pang, Y. (2018). New multiple attribute decision making method based on DEMATEL and TOPSIS for multi-valued interval Neutrosophic sets. Symmetry, 10(4), 115.
Ye, J. (2014). Some aggregation operators of interval neutrosophic linguistic numbers for multiple attribute decision making. Journal of Intelligent and Fuzzy Systems, 27(5), 2231-2241.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
Zare, M., Pahl, C., Rahnama, H., Nilashi, M., Mardani, A., Ibrahim, O., & Ahmadi, H. (2016). Multi-criteria decision-making approach in E-learning: A systematic review and classification. Applied Soft Computing, 45, 108-128.
Zerem, E. (2017). The ranking of scientists based on scientific publications assessment. Journal of Biomedical Informatics, 75, 107-109.
Zhang, H., Wang, J., & Chen, X. (2014). Interval Neutrosophic sets and their application in multicriteria decision making problems. The Scientific World Journal, 2014, 1-15.
Zhou, H., Liu, Q., Tian, J., & Li, Q. (2018). Rights and interests guarantee of private school teachers. In H. Zhou, Q. Liu, J. Tian, & Q. Li (Eds.), Private Education in China: Achievement and Challenge, 169-211.
Zyad, H. (2016). Integrating Computers in the Classroom: Barriers and Teachers’ Attitudes. International Journal of Instruction, 9(1), 65-78.
Aldrup, K., Klusmann, U., Lüdtke, O., Göllner, R., & Trautwein, U. (2018). Student misbehavior and teacher well-being: Testing the mediating role of the teacher-student relationship. Learning and Instruction, 58, 126-136.
Ali, M., Dat, L. Q., Son, L. H., & Smarandache, F. (2018). Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making. International Journal of Fuzzy Systems, 20(3), 986-999.
Ali, M., & Smarandache, F. (2017). Complex neutrosophic set. Neural Computing and Applications, 28(7), 1817-1834.
Alias, M., Masek, A., & Salleh, H. H. M. (2015). Self, Peer and Teacher Assessments in Problem Based Learning: Are They in Agreements? Procedia - Social and Behavioral Sciences, 204, 309-317.
Almeida, J. de C. (2017). Teacher Performance Evaluation: The Importance of Performance Standards. International Journal for Cross-Disciplinary Subjects in Education, 8(1), 2973-2981.
Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96.
Bambaeeroo, F., & Shokrpour, N. (2017). The impact of the teachers’ non-verbal communication on success in teaching. Journal of Advances in Medical Education and Professionalism, 5(2), 51-59.
Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. D. U., & Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907.
Biggs, J. B., & Collis, K. F. (2014). Evaluating the Quality of Learning: The SOLO Taxonomy (Structure of the Observed Learning Outcome). Academic Press, 245 pages.
Bohlmann, N. L., & Weinstein, R. S. (2013). Classroom context, teacher expectations, and cognitive level: Predicting children’s math ability judgments. Journal of Applied Developmental Psychology, 34(6), 288-298.
Bottani, E., & Rizzi, A. (2006). A fuzzy TOPSIS methodology to support outsourcing of logistics services. Supply Chain Management: An International Journal, 11(4), 294–308. doi: 10.1108/13598540610671743
Bradford, A. (2015). Adopting English-Taught Degree Programs. International Higher Education, 69, 8-10.
Brookfield, S. D. (2017). Becoming a Critically Reflective Teacher. John Wiley and Sons.
Buttram, J. L., & Wilson, B. L. (1987). Promising trends in teacher evaluation. Educational Leadership, 44(7), 4-6.
Cegarra-Navarro, J.-G., Soto-Acosta, P., and Martinez-Caro, E. (2016). Linking counter-knowledge to goal orientation through an unlearning context - A study from a Spanish University. Learning and Individual Differences, 45, 260-267.
Cegarra-Sánchez, J., & Cegarra-Navarro, J.-G. (2017). Making meaning out of noise: A knowledge management core competence for higher education students. VINE Journal of Information and Knowledge Management Systems, 47(4), 506-521.
Chappuis, S., Commodore, C., and Stiggins, R. (2016). Balanced Assessment Systems: Leadership, Quality, and the Role of Classroom Assessment. Corwin Press.
Cheng, M. M. H., Chan, K.-W., Tang, S. Y. F., and Cheng, A. Y. N. (2009). Pre-service teacher education students’ epistemological beliefs and their conceptions of teaching. Teaching and Teacher Education, 25(2), 319-327.
Chi, P., & Liu, P. (2013). An extended TOPSIS method for the multiple attribute decision making problems based on interval neutrosophic set. Neutrosophic Sets and Systems, 1, 1-8.
Colby, S. A., Bradshaw, L. K., & Joyner, R. L. (2002). Teacher evaluation: A review of the literature. Annual Meeting of the American Educational Research Association, New Orleans, LA, 1-18.
Cuevas, R., Ntoumanis, N., Fernandez-Bustos, J. G., and Bartholomew, K. (2018). Does teacher evaluation based on student performance predict motivation, well-being, and ill-being? Journal of School Psychology, 68, 154-162.
Danielson, C. (2000). Teacher evaluation to enhance professional practice. Retrieved from http://ebookcentral.proquest.com/lib/ucm/detail.action?docID=280406
Darling-Hammond, L. (2017). Teacher education around the world: What can we learn from international practice? European Journal of Teacher Education, 40(3), 291-309.
Davey, B. (1991). Evaluating teacher competence through the use of performance assessment tasks: An overview. Journal of Personnel Evaluation in Education, 5(2), 121-132.
Derrington, M. L., and Campbell, J. W. (2015). Implementing new teacher evaluation systems: Principals’ concerns and supervisor support. Journal of Educational Change, 16(3), 305-326.
Fabjanowicz, M., Bystrzanowska, M., Namieśnik, J., Tobiszewski, M., and Płotka-Wasylka, J. (2018). An analytical hierarchy process for selection of the optimal procedure for resveratrol determination in wine samples. Microchemical Journal, 142, 126-134.
Fauth, B., Decristan, J., Rieser, S., Klieme, E., and Büttner, G. (2014). Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29, 1-9.
Fischer, C., Fishman, B., Dede, C., Eisenkraft, A., Frumin, K., Foster, B., … McCoy, A. (2018). Investigating relationships between school context, teacher professional development, teaching practices, and student achievement in response to a nationwide science reform. Teaching and Teacher Education, 72, 107-121.
Frunză, V. (2014). Implications of Teaching Styles on Learning Efficiency. Procedia - Social and Behavioral Sciences, 127, 342-346.
Gormally, C., Evans, M., and Brickman, P. (2014). Feedback about teaching in higher Ed: Neglected opportunities to promote change. CBE Life Sciences Education, 13(2), 187-199.
Hein, N., Kroenke, A., & Júnior, M. M. R. (2015a). Professor assessment using multi-criteria decision analysis. Procedia Computer Science, 55, 539-548.
Hwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications A State-of-the-Art Survey. Berlin Heidelberg: Springer-Verlag.
Iantorno, S. E., Andras, L. M., and Skaggs, D. L. (2016). Variability of reviewers’ comments in the peer review process for orthopaedic research. Spine Deformity, 4(4), 268-271.
Ishizaka, A., & Labib, A. (2009). Analytic hierarchy process and expert choice: Benefits and limitations. OR Insight, 22(4), 201-220.
Jaramillo, I. F., Pico, R. B., & Marquez, C. V. (2017). A model for faculty evaluation in higher education ecuadorian through multi-criteria decision Analysis. Indian Journal of Science and Technology, 10(18), 1-8.
Jiayi, W., & Ling, C. (2012). Reviewing teacher evaluation of rewards and punishments: The overview of Chinese teacher evaluation research. Education Research International, 1-16. doi: 10.1155/2012/184640
Johnson, E. D., Al-Mahmood, R., & Maierb, A. G. (2012). Student and staff perceptions of teamwork in groupwriting for science honours. International Journal of Innovation in Science and Mathematics Education, 20(4), 25-41.
Karthikeyan, R., Venkatesan, K. G. S., & Chandrasekar, A. (2016). A comparison of strengths and weaknesses for analytical hierarchy process. Journal of Chemical and Pharmaceutical Sciences 9(3), S-12-S-15.
Kilic, A. (2010). Learner-centered micro teaching in teacher education. International Journal of Instruction, 3(1) 77-100.
King, F. (2014). Evaluating the impact of teacher professional development: An evidence-based framework. Professional Development in Education, 40(1), 89-111.
Kunter, M., & Baumert, J. (2006). Who is the expert? Construct and criteria validity of student and teacher ratings of instruction. Learning Environments Research, 9(3), 231-251.
Kupers, E., van Dijk, M., & van Geert, P. (2015). Within-teacher differences in one-to-one teacher–student interactions in instrumental music lessons. Learning and Individual Differences, 37, 283-289.
Kurtz, S., Draper, J., Silverman, J., Draper, J., & Silverman, J. (2017). Teaching and Learning Communication Skills in Medicine. CRC Press, 2nd edition, 388 Pages.
Lans, R. M. van der, Grift, W. J. C. M. van de, & Veen, K. van. (2018). Developing an instrument for teacher feedback: Using the rasch model to explore teachers’ development of effective teaching strategies and behaviors. The Journal of Experimental Education, 86(2), 247-264.
Lazarides, R., Viljaranta, J., Aunola, K., & Nurmi, J.-E. (2018). Teacher ability evaluation and changes in elementary student profiles of motivation and performance in mathematics. Learning and Individual Differences, 67, 245-258.
Li, G., Gang KOU, G., and Peng, Y. (2015). Dynamic fuzzy multiple criteria decision making for performance evaluation. Technological and Economic Development of Economy, 21(5), 705-719.
Liu, S., & Teddlie, C. (2007). A follow-up study on teacher evaluation in China: Historical analysis and latest trends. Journal of Personnel Evaluation in Education, 18(4), 253-272.
Liu, S., & Zhao, D. (2013). Teacher evaluation in China: Latest trends and future directions. Educational Assessment, Evaluation and Accountability, 25(3), 231-250.
Malakolunthu, S., & Vasudevan, V. (2012). Teacher evaluation practices in Malaysian primary schools: Issues and challenges. Asia Pacific Education Review, 13(3), 449-456.
Malen, B., Rice, J. K., Matlach, L. K. B., Bowsher, A., Hoyer, K. M., and Hyde, L. H. (2015). Developing organizational capacity for implementing complex education reform initiatives: Insights from a multiyear study of a teacher incentive fund program. Educational Administration Quarterly, 51(1), 133-176.
Malik, M. M., Abdallah, S., and Hussain, M. (2016). Assessing supplier environmental performance: Applying Analytical Hierarchical Process in the United Arab Emirates healthcare chain. Renewable and Sustainable Energy Reviews, 55, 1313-1321.
Maltarich, M. A., Nyberg, A. J., Reilly, G., Abdulsalam, D. “Dee,” & Martin, M. (2017). Pay-for-performance, sometimes: An Interdisciplinary Approach to Integrating Economic Rationality with Psychological Emotion to Predict Individual Performance. Academy of Management Journal, 60(6), 2155-2174.
Marzano, R. J., & Toth, M. D. (2013). Teacher Evaluation that Makes a Difference: A New Model for Teacher Growth and Student Achievement. Association for Supervision and Curriculum Development, 192 pages.
Muijs, D., & Reynolds, D. (2017). Effective Teaching: Evidence and Practice. SAGE.
Nahid, B. S., Nasr isfahani, A., Rouhollahi, A., & Khalili, R. (2016). Effective teaching methods in higher education: Requirements and barriers. Journal of Advances in Medical Education and Professionalism, 4(4), 170-178.
Nilson, L. B. (2016). Teaching at Its Best: A Research-Based Resource for College Instructors. John Wiley and Sons, 400 pages.
Odden, A. (2014). Lessons Learned About Standards-Based Teacher Evaluation Systems. Peabody Journal of Education, 79(4), 126-137.
OECD. (2009). Teacher Evaluation: Current Practices in OECD Countries and a Literature Review. OECD Education Working papers, 49 pages.
OECD (Ed.). (2013). Synergies for better learning: An international perspective on evaluation and assessment. OECD reviews of evaluation and assessment in education, 670 pages.
Ovando, M. N. (2001). Teachers’ perceptions of a learner-centered teacher evaluation system. Journal of Personnel Evaluation in Education, (15), 213-231.
Parrish, D. R. (2016). Principles and a model for advancing future-oriented and student-focused teaching and learning. Procedia - Social and Behavioral Sciences, 228, 311-315.
Ramot, D., Milo, R., Friedman, M., and Kandel, A. (2002). Complex fuzzy sets. IEEE Transactions on Fuzzy Systems, 10(2), 171-186.
Reddy, L. A., Dudek, C. M., Peters, S., Alperin, A., Kettler, R. J., and Kurz, A. (2018). Teachers’ and school administrators’ attitudes and beliefs of teacher evaluation: A preliminary investigation of high poverty school districts. Educational Assessment, Evaluation and Accountability, 30(1), 47-70.
Saaty, T. L. (1980). The analytic hierarchy process. Newyork, NY: McGraw-Hill Inc, 17-34.
Saaty, Thomas L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98.
Said, B., Ye, J., & Smarandache, F. (2015). An extended TOPSIS method for multiple attribute decision making based on interval neutrosophic uncertain linguistic variables. Neutrosophic Sets and Systems, 8, 22-31.
Schön, D. A. (2017). The Reflective Practitioner: How Professionals Think in Action. Basic Books, 384 pages.
Sharp, J. A., Peters, J., Howard, K., Peters, J., and Howard, K. (2017). The Management of a Student Research Project. Taylor and Fancis, 278 pages.
Shingphachanh, S. (2018). Teachers’ understanding and concerns about the practices of lesson study in suburb schools in Laos. International Journal for Lesson and Learning Studies, 7(2), 150-162.
Singh, I., & Jha, A. (2014). Difference in Self-reported and Students-rated Teacher Effectiveness among Medical and Engineering Faculty Members: Need for Direct Informal Feedback. American Journal of Educational Research, 2(5), 272-277.
Skedsmo, G., & Huber, S. G. (2018). Teacher evaluation: The need for valid measures and increased teacher involvement. Educational Assessment, Evaluation and Accountability, 30(1), 1-5.
Smarandache, F. (1998). A unifying field in logics. Neutrosophy: Neutrosophic probability, set and logic. American Research Press, Rehoboth, 105 pages.
Sonnert, G., Hazari, Z., & Sadler, P. M. (2018). Evaluating the quality of middle school mathematics teachers, using videos rated by college students. Studies in Educational Evaluation, 58, 60-69.
Steinberg, M. P., and Garrett, R. (2016). Classroom Composition and Measured Teacher Performance: What Do Teacher Observation Scores Really Measure? Educational Evaluation and Policy Analysis, 38(2), 293-317.
Taut, S., Santelices, M. V., Araya, C., & Manzi, J. (2011). Perceived effects and uses of the national teacher evaluation system in Chilean elementary schools. Studies in Educational Evaluation, 37(4), 218-229.
Thomas, S., Chie, Q. T., Abraham, M., Jalarajan Raj, S., & Beh, L.-S. (2014). A Qualitative Review of Literature on Peer Review of Teaching in Higher Education: An Application of the SWOT Framework. Review of Educational Research, 84(1), 112-159.
Tondeur, J., van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555-575.
Torkabadi, A. M., Pourjavad, E., & Mayorga, R. V. (2018). An integrated fuzzy MCDM approach to improve sustainable consumption and production trends in supply chain. Sustainable Production and Consumption, 16, 99-109.
Turksen, I. B. (1986). Interval valued fuzzy sets based on normal forms. Fuzzy Sets and Systems, 20(2), 191-210.
Tuytens, M., & Devos, G. (2017). The role of feedback from the school leader during teacher evaluation for teacher and school improvement. Teachers and Teaching, 23(1), 6-24.
Wager, E., & Kleinert, S. (2012). Cooperation between research institutions and journals on research integrity cases: Guidance from the committee on publication ethics. Saudi Journal of Anaesthesia, 6(2), 155-160.
Wang, H., Smarandache, F., Zhang, Y., & Sunderraman, R. (2010). Single valued Neutrosophic sets. Technical Sciences and Applied Mathematics, 10-14.
Wang, J.-W., Cheng, C.-H., & Huang, K.-C. (2009). Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing, 9(1), 377-386.
Wang, T.-Y., & Hsieh, F.-J. (2017). Taiwanese high school students’ perspectives on effective mathematics teaching behaviors. Studies in Educational Evaluation, 55, 35-45.
Wang, X.,& Chan, H. K. (2013). A hierarchical fuzzy TOPSIS approach to assess improvement areas when implementing green supply chain initiatives. International Journal of Production Research, 51(10), 3117-3130.
Wardil, L., & Hauert, C. (2015). Cooperation and coauthorship in scientific publishing. Physical Review E, 91(1), 1-6.
Wiliam, D., Thompson, M., & Thompson, M. (2017). Integrating assessment with learning: what will it take to make it work? In: Dwyer, C A, (ed.) The Future of Assessment: Shaping Teaching and Learning. (pp. 53-82). Lawrence Erlbaum Associates: Mahwah, New Jersey.
Wisker, G. (2012). The Good Supervisor: Supervising Postgraduate and Undergraduate Research for Doctoral Theses and Dissertations. Palgrave Macmillan, 400 pages.
Wolf, L. A. (2016). The peer review process. Journal of Emergency Nursing, 42(5), 454-456.
Wu, H.-Y., Chen, J.-K., Chen, I.-S., and Zhuo, H.-H. (2012). Ranking universities based on performance evaluation by a hybrid MCDM model. Measurement, 45(5), 856-880.
Wu, M.-J., Huang, C.-Y., Kao, Y.-S., Lue, Y.-F., Chen, L.-C. (2018). Developing a professional performance evaluation system for pre-Service automobile repair vocational high school teachers in Taiwan. Sustainability, 10(10), 3537.
Yang, W., & Pang, Y. (2018). New multiple attribute decision making method based on DEMATEL and TOPSIS for multi-valued interval Neutrosophic sets. Symmetry, 10(4), 115.
Ye, J. (2014). Some aggregation operators of interval neutrosophic linguistic numbers for multiple attribute decision making. Journal of Intelligent and Fuzzy Systems, 27(5), 2231-2241.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
Zare, M., Pahl, C., Rahnama, H., Nilashi, M., Mardani, A., Ibrahim, O., & Ahmadi, H. (2016). Multi-criteria decision-making approach in E-learning: A systematic review and classification. Applied Soft Computing, 45, 108-128.
Zerem, E. (2017). The ranking of scientists based on scientific publications assessment. Journal of Biomedical Informatics, 75, 107-109.
Zhang, H., Wang, J., & Chen, X. (2014). Interval Neutrosophic sets and their application in multicriteria decision making problems. The Scientific World Journal, 2014, 1-15.
Zhou, H., Liu, Q., Tian, J., & Li, Q. (2018). Rights and interests guarantee of private school teachers. In H. Zhou, Q. Liu, J. Tian, & Q. Li (Eds.), Private Education in China: Achievement and Challenge, 169-211.
Zyad, H. (2016). Integrating Computers in the Classroom: Barriers and Teachers’ Attitudes. International Journal of Instruction, 9(1), 65-78.