Definite Integral Automatic Analysis Mechanism Research and Development Using the "Find the Area by Integration" Unit as an Example.

This approach was particularly applied to solve problems with the definite integral in university-level calculus courses Assessment of Content Analysis Expert Knowledge Structure Participators Error Type Analysis Research Tools The results show that the overall recognition rate of the BN (Model 2) is better than that of Model 1, which has only the multiple choice items. This research focuses on definite integral diagnostic tests and automated analysis mechanisms. Future studies may focus on remedial teaching.

[1]  T. P. Carpenter,et al.  Learning and teaching with understanding. , 1992 .

[2]  Bahram Sadeghpour Gildeh,et al.  Learning parameters of fuzzy Bayesian Network based on imprecise observations , 2014, Int. J. Knowl. Based Intell. Eng. Syst..

[3]  Anastasios A. Economides,et al.  Adaptive assessment of student's knowledge in programming courses , 2010, J. Comput. Assist. Learn..

[4]  I. Marchiş.  Future Primary and Preschool Pedagogy Specialization Students' Mathematical Problem Solving Competency. , 2013 .

[5]  Leong Kwan Eu,et al.  Teaching and Learning Calculus in Secondary Schools with the TI-Nspire. , 2014 .

[6]  P. M. Neumann.  The Future for Honours Degree Courses in Mathematics , 1992 .

[7]  Kikumi K. Tatsuoka,et al.  A Probabilistic Model for Diagnosing Misconceptions By The Pattern Classification Approach , 1985 .

[8]  Fernando Barrera-Mora,et al.  Cognitive processes developed by students when solving mathematical problems within technological environments , 2013, The Mathematics Enthusiast.

[9]  R. A. Tarmizi.  Visualizing Student's Difficulties in Learning Calculus , 2010 .

[10]  Bor-Chen Kuo,et al.  Evaluating Knowledge Structure-based Adaptive Testing Algorithms and System Development , 2012, J. Educ. Technol. Soc..

[11]  David Heckerman,et al.  Challenge: What is the Impact of Bayesian Networks on Learning? , 1997, IJCAI.

[12]  B. Junker,et al.  Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric Item Response Theory , 2001 .

[13]  Phillip Kent,et al.  Mathematics thinking and learning at post-secondary level , 2007 .

[14]  J. B. Olsen,et al.  THE FOUR GENERATIONS OF COMPUTERIZED EDUCATIONAL MEASUREMENT , 1988 .

[15]  Lynn S. Fuchs,et al.  The Predictive Validity of Dynamic Assessment , 2008 .

[16]  Sujata U. Tapare.  Conceptual Understanding of Undergraduate Students of Calculus in Cooperative Learning Using Calculus Education Software ( CES ) , 2013 .

[17]  Yu-Lung Wu,et al.  A Practical Computer Adaptive Testing Model for Small-Scale Scenarios , 2008, J. Educ. Technol. Soc..

[18]  R. Zerr.  Promoting Students' Ability to Think Conceptually in Calculus , 2009 .

[19]  Judea Pearl,et al.  Bayesian Networks , 1998, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

[20]  J. D. L. Torre,et al.  DINA Model and Parameter Estimation: A Didactic , 2009 .

[21]  Jean-Claude Falmagne,et al.  Knowledge spaces , 1998 .

[22]  David Tall.  Students' Difficulties in Calculus Plenary presentation in Working Group 3, ICME, Québec, August 1992 , 1993 .

[23]  N. Herscovics.  Cognitive Obstacles Encountered in the Learning of Algebra , 2018, Research Issues in the Learning and Teaching of Algebra.

[24]  Chris Rasmussen,et al.  Modeling Perspectives in Math Education Research , 2010 .

[25]  E. Rosch.  Cognitive Representations of Semantic Categories. , 1975 .

[26]  Daniel G. Mallet,et al.  An example of cognitive obstacles in advanced integration: the case of scalar line integrals , 2012 .

[27]  R. L. E. Schwarzenberger.  The Importance of Mistakes: The 1984 Presidential Address , 1984 .

[28]  Wim van den Noortgate,et al.  Adaptive item-based learning environments based on the item response theory: possibilities and challenges , 2010, J. Comput. Assist. Learn..

[29]  E. Moise.  An indecomposable plane continuum which is homeomorphic to each of its nondegenerate subcontinua , 1948 .

[30]  Shailey Minocha,et al.  The strengths, weaknesses, opportunities and threats of using social software in higher and further education teaching and learning , 2010, J. Comput. Assist. Learn..

[31]  David Tall,et al.  THINKING THROUGH THREE WORLDS OF MATHEMATICS , 2004 .