[1] H. H. Gorgani, Improvements in Teaching Projection Theory Using Failure Mode and Effects Analysis (FMEA), Journal of Engineering and Applied Sciences, Vol. 100, No. 1, pp. 37-42, 2016.
[2] M. Murthy, K. M. Babu, P. M. Jebaraj, L. R. Maddinapudi, V. Sunkari, D. V. Reddy, Augmented Reality as a tool for teaching a course on Elements of Engineering Drawing, Journal of Engineering Education Transformations, pp. 295-297, 2015.
[3] H. H. Gorgani, I. M. S. Neyestanaki, A. J. Pak, Solid Reconstruction from Two Orthographic Views Using Extrusion and Comparative Projections, Journal of Engineering and Applied Sciences, Vol. 12, No. 7, pp. 1938-1945, 2017.
[4] H. H. Gorgani, A. J. Pak, A Genetic Algorithm based Optimization Method in 3D Solid Reconstruction from 2D Multi-View Engineering Drawings, Computational Applied Mechanics, Vol. 49, No. 1, pp. 10, 2018, 2018.
[5] S. Olkun, Making connections: Improving spatial abilities with engineering drawing activities, International Journal of Mathematics Teaching and Learning, Vol. 3, No. 1, pp. 1-10, 2003.
[6] Z. Zuo, K. Feng, B. Chen, The modern education mode for engineering drawing, JGG, Vol. 7, No. 1, pp. 121-128, 2003.
[7] X. Yang, T. Zhang, Q. Jiang, Research and Practice of Project-Based Teaching and Examination Methods on Engineering Drawing for Excellent Class, in Proceeding of, Citeseer, pp.
[8] M. G. Violante, E. Vezzetti, Design of web‐based interactive 3D concept maps: A preliminary study for an engineering drawing course, Computer Applications in Engineering Education, Vol. 23, No. 3, pp. 403-411, 2015.
[9] M. Ismail, H. Othman, M. Amiruddin, A. Ariffin, The use of animation video in teaching to enhance the imagination and visualization of student in engineering drawing, in Proceeding of, IOP Publishing, pp. 012023.
[10] L. Zadeh, Inform, Control, Vol. 8, pp. 338-353, 1965.
[11] D. Chang, C. Sun, Fuzzy assessment of learning performance of junior high school students, in Proceeding of, 1-10.
[12] T. Chiang, C. Lin, Application of fuzzy theory to teaching assessment, in Proceeding of, 92-97.
[13] R. Biswas, An application of fuzzy sets in students' evaluation, Fuzzy sets and systems, Vol. 74, No. 2, pp. 187-194, 1995.
[14] J. R. Echauz, G. J. Vachtsevanos, Fuzzy grading system, IEEE Transactions on Education, Vol. 38, No. 2, pp. 158-165, 1995.
[15] C.-K. Law, Using fuzzy numbers in educational grading system, Fuzzy sets and systems, Vol. 83, No. 3, pp. 311-323, 1996.
[16] C. Cheng, K. Yang, Using fuzzy sets in education grading system, Journal of Chinese Fuzzy Systems Association, Vol. 4, No. 2, pp. 81-89, 1998.
[17] E. Wilson, C. L. Karr, L. Freeman, Flexible, adaptive, automatic fuzzy-based grade assigning system, in Proceeding of, IEEE, pp. 334-338.
[18] S.-M. Chen, C.-H. Lee, New methods for students' evaluation using fuzzy sets, Fuzzy sets and systems, Vol. 104, No. 2, pp. 209-218, 1999.
[19] J. Ma, D. Zhou, Fuzzy set approach to the assessment of student-centered learning, IEEE Transactions on Education, Vol. 43, No. 2, pp. 237-241, 2000.
[20] S. Weon, J. Kim, Learning achievement evaluation strategy using fuzzy membership function, in Proceeding of, IEEE, pp. T3A-19.
[21] S.-M. Bai, S.-M. Chen, Automatically constructing concept maps based on fuzzy rules for adapting learning systems, Expert systems with Applications, Vol. 35, No. 1-2, pp. 41-49, 2008.
[22] S.-M. Bai, S.-M. Chen, Automatically constructing grade membership functions of fuzzy rules for students’ evaluation, Expert Systems with Applications, Vol. 35, No. 3, pp. 1408-1414, 2008.
[23] S.-M. Bai, S.-M. Chen, Evaluating students’ learning achievement using fuzzy membership functions and fuzzy rules, Expert Systems with Applications, Vol. 34, No. 1, pp. 399-410, 2008.
[24] H.-Y. Wang, S.-M. Chen, Evaluating students' answerscripts using fuzzy numbers associated with degrees of confidence, IEEE Transactions on Fuzzy Systems, Vol. 16, No. 2, pp. 403-415, 2008.
[25] T.-K. Li, C.-M. Chen, A new method for students' learning achievement evaluation by automatically generating the weights of attributes with fuzzy reasoning capability, in Proceeding of, IEEE, pp. 2834-2839.
[26] E. H. Mamdani, Application of fuzzy algorithms for control of simple dynamic plant, in Proceeding of, IET, pp. 1585-1588.
[27] I. Saleh, S.-i. Kim, A fuzzy system for evaluating students’ learning achievement, Expert systems with Applications, Vol. 36, No. 3, pp. 6236-6243, 2009.
[28] G. Gokmen, T. Ç. Akinci, M. Tektaş, N. Onat, G. Kocyigit, N. Tektaş, Evaluation of student performance in laboratory applications using fuzzy logic, Procedia-Social and Behavioral Sciences, Vol. 2, No. 2, pp. 902-909, 2010.
[29] S. Prokhorov, I. Kulikovskikh, Fuzzy learning performance assessment based on decision making under internal uncertainty, in Proceeding of, IEEE, pp. 65-70.
[30] A. K. NUTHANAPATI, D. Rao, M. S. Reddy, Indexing Student Performance with Fuzzy Logics Evaluation in Engineering Education, 2018.
[31] T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE transactions on systems, man, and cybernetics, No. 1, pp. 116-132, 1985.
[32] S.-M. Chen, T.-K. Li, Evaluating students’ learning achievement based on fuzzy rules with fuzzy reasoning capability, Expert Systems with Applications, Vol. 38, No. 4, pp. 4368-4381, 2011.
[33] H. H. Gorgani, Innovative conceptual design on a tracked robot using TRIZ method for passing narrow obstacles, Indian Journal of Science and Technology, Vol. 9, No. 7, 2016.