References
[1]. Ahmad, M. & Leddo, J. (2023). The Effectiveness of Cognitive Structure Analysis in Assessing Students’ Knowledge of the Scientific Method. International Journal of Social Science and Economic Research, 8(8), 2397-2410.
[2]. Anderson, J.R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-405.
[3]. Chaoui, N (2011) "Finding Relationships Between Multiple-Choice Math Tests and Their Stem-Equivalent Constructed Responses". CGU Theses & Dissertations. Paper 21.
[4]. de Ayala, R. J. (2009). The theory and practice of item response theory. New York: The Guilford Press.
[5]. de Kleer, J. and Brown, J.S. (1981). Mental models of physical mechanisms and their acquisition. In J.R. Anderson (Ed.), Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.
[6]. Elbrink, L., & Waits, B. (Spring, 1970). A Statistical Analysis of MultipleChoice Examinations in Mathematics. The Two-Year College Mathematics Journal, 1(1), 25-29.
[7]. Frary, R. (Spring, 1985). Multiple-Choice Versus Free-Response: A Simulation Study. Journal of Educational Measurement, 22, 21-31.
[8]. Herman, J. L., Klein, D. C., Heath, T. M., & Wakai, S. T. (1994). A first look: Are claims for alternative assessment holding up? (CSE Tech. Rep. No. 391). Los Angeles: University of California, Center for Research on Evaluation, Standards, and Student Testing.
[9]. Leddo, J., Cohen, M.S., O'Connor, M.F., Bresnick, T.A., and Marvin, F.F. (1990). Integrated knowledge elicitation and representation framework (Technical Report 90?3). Reston, VA: Decision Science Consortium, Inc.
[10]. Leddo, J., Li, S. & Zhang, Y. (2022). Cognitive Structure Analysis: A technique for assessing what students know, not just how they perform. International Journal of Social Science and Economic Research, 7(11), 3716-3726.
[11]. Leddo, J. and Sak, S. (1994). Knowledge Assessment: Diagnosing what students really know. Presented at Society for Technology and Teacher Education. .
[12]. Leddo, J., Zhang, Z. and Pokorny, R. (1998).Automated Performance Assessment Tools. Proceedings of the Interservice/Industry Training Systems and Education Conference. Arlington, VA: National Training Systems Association.
[13]. Liang, I. and Leddo, J. (2020). An intelligent tutoring system-style assessment software that diagnoses the underlying causes of students’ mathematical mistakes. International Journal of Advanced Educational Research, 5(5), 26-30.
[14]. National Council of Teachers of Mathematics (2000). Principles and Standards for School Mathematics. Reston, VA: NCTM.
[15]. Newell, A. and Simon, H.A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice Hall.
[16]. O'Neil Jr., H., & Brown, R. (1997). Differential Effects Of Question Formats In Math Assessment On Metacognition And Affect. Applied Measurement in Education, 331-351.
[17]. Quillian, M.R. (1966). Semantic memory. Cambridge, MA: Bolt, Beranek and Newman.
[18]. Schank, R.C. and Abelson, R.P. (1977). Scripts, Plans, Goals, and Understanding. Hillsdale, NJ: Erlbaum.
[19]. Schank, R.C. (1982). Dynamic Memory: A theory of learning in computers and people. New York: Cambridge University Press.
[20]. Zhou, L.N. & Leddo, J. (2023). Cognitive Structure Analysis: Assessing Students’ Knowledge of Precalculus. International Journal of Social Science and Economic Research, 8(9), 2826-2836.