A New Method for Assessment of Engineering Drawing Answer Scripts Using Fuzzy Logic

Document Type : Research Paper

Authors

1 Engineering Graphics Center, Sharif University of Technology, Tehran, Iran

2 Head of engineering graphics center, Sharif University of Technology, Tehran, Iran

Abstract

Popular method for assessment of final exam answer scripts in university and among the engineering drawing answer scripts based on absolute true or false judgment and assigning a single number or letter to answer of each problem cannot be so fair.
To obtain a fair assessment method, we considered “imagination”, “accuracy”, “drawing” and “innovation” that are objectives of engineering drawing course to be separately assessed for each problem. Flexibility and linguistic properties of fuzzy logic made us use it as the basis of our method. In addition, fuzzy variables and membership functions are easily linguistic explainable, and adjustable to different conditions. “Answering time” was added as a factor with only a positive effect on the final grade. Between these five factors, imagination has special importance because it supports one of seven human intelligences which is spatial ability
Finally, however we applied the proposed method to engineering drawing course, it can be applied to other courses with considering their properties.

Keywords

[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. 
Volume 51, Issue 1
June 2020
Pages 170-183
  • Receive Date: 09 September 2018
  • Revise Date: 22 April 2019
  • Accept Date: 22 April 2019