Introduction to operations research, 4th ed.
Introduction to operations research, 4th ed.
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
An Authoring System for Intelligent Procedural-Skill Tutors
IEEE Intelligent Systems
A conceptual map model for developing intelligent tutoring systems
Computers & Education
A Computational Study of Search Strategies for Mixed Integer Programming
INFORMS Journal on Computing
Capacity Optimization Planning System (Caps)
Interfaces
Development of a Knowledge Based Computer Assisted Instruction System
SEEP '96 Proceedings of the 1996 International Conference on Software Engineering: Education and Practice (SE:EP '96)
Experiencing CORAL: design and implementation of distantcooperative learning
IEEE Transactions on Education
Semiautomatic testing of student software under Unix(R)
IEEE Transactions on Education
A tutoring strategy supporting system for distance learning oncomputer networks
IEEE Transactions on Education
IEEE Transactions on Education
A test-sheet-generating algorithm for multiple assessment requirements
IEEE Transactions on Education
Building intelligent tutorial systems for teaching simulation inengineering education
IEEE Transactions on Education
An enhanced genetic approach to optimizing auto-reply accuracy of an e-learning system
Computers & Education
Evaluating students' answerscripts based on interval-valued fuzzy grade sheets
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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A well-constructed test sheet not only helps the instructor evaluate the learning status of the students, but also facilitates the diagnosis of the problems embedded in the students' learning process. This paper addresses the problem of selecting proper test items to compose a test sheet that conforms to such assessment requirements as average difficulty degree, average discrimination degree, length of test time, number of test items, and specified distribution of concept weights. A mixed integer programming model is proposed to formulate the problem of selecting a set of test items that best fit the multiple assessment requirements. As the problem is a generalization of the knapsack problem, which is known to be NP-hard in the literature, computational challenge hinders the development of efficient solution methods. Seeking approximate solutions in an acceptable time is a viable alternative. In this paper, we propose two heuristic algorithms, based upon iterative adjustment, for finding quality approximate solutions. Extensive experiments are also conducted to assess the performances of different solution methods. Statistics from a series of computational experiments indicate that our proposed algorithms can produce near-optimum combinations of the test items subject to the specified requirements in a reasonable time.