dAFM: Fusing Psychometric and Connectionist Modeling for Q-Matrix Refinement.
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[1] K. Koedinger,et al. Automating Cognitive Model Improvement by A * Search and Logistic Regression , 2005 .
[2] Michel C. Desmarais. Conditions for Effectively Deriving a Q-Matrix from Data with Non-negative Matrix Factorization. Best Paper Award , 2011, EDM.
[3] Kenneth R. Koedinger,et al. Performance Factors Analysis - A New Alternative to Knowledge Tracing , 2009, AIED.
[4] Albert T. Corbett,et al. Cognitive Computer Tutors: Solving the Two-Sigma Problem , 2001, User Modeling.
[5] Zachary A. Pardos,et al. The 2010 KDD Cup Competition Dataset: Engaging the machine learning community in predictive learning analytics , 2016, J. Learn. Anal..
[6] Peter Brusilovsky,et al. General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge , 2014, EDM.
[7] Michel C. Desmarais,et al. A Matrix Factorization Method for Mapping Items to Skills and for Enhancing Expert-Based Q-Matrices , 2013, AIED.
[8] Neil T. Heffernan,et al. The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching , 2014, International Journal of Artificial Intelligence in Education.
[9] Mitchell J. Nathan,et al. Expert Blind Spot : When Content Knowledge Eclipses Pedagogical Content Knowledge , 2001 .
[10] Antonija Mitrovic,et al. Evaluating and improving adaptive educational systems with learning curves , 2011, User Modeling and User-Adapted Interaction.
[11] Jack Mostow,et al. Dynamic Cognitive Tracing: Towards Unified Discovery of Student and Cognitive Models , 2012, EDM.
[12] K. Tatsuoka. RULE SPACE: AN APPROACH FOR DEALING WITH MISCONCEPTIONS BASED ON ITEM RESPONSE THEORY , 1983 .
[13] Chia-Yi Chiu. Statistical Refinement of the Q-Matrix in Cognitive Diagnosis , 2013 .
[14] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[15] Zachary A Pardos,et al. Big data in education and the models that love them , 2017, Current Opinion in Behavioral Sciences.
[16] Kelly G. Shaver,et al. The attribution of blame : causality, responsibility, and blameworthiness , 1985 .
[17] Kenneth R. Koedinger,et al. Is Over Practice Necessary? - Improving Learning Efficiency with the Cognitive Tutor through Educational Data Mining , 2007, AIED.
[18] Kenneth R. Koedinger,et al. Individualized Bayesian Knowledge Tracing Models , 2013, AIED.
[19] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[20] Ran Liu,et al. Modeling common misconceptions in learning process data , 2016, LAK.
[21] Leonidas J. Guibas,et al. Deep Knowledge Tracing , 2015, NIPS.
[22] Richard Scheines,et al. Discovering Prerequisite Relationships Among Knowledge Components , 2014, EDM.
[23] Kenneth R. Koedinger,et al. Automated Student Model Improvement , 2012, EDM.
[24] Sara Fripp. A learning curve. , 2014, Midwives.
[25] Neil T. Heffernan,et al. Automatic and Semi-Automatic Skill Coding With a View Towards Supporting On-Line Assessment , 2005, AIED.
[26] Jenna Burrell,et al. How the machine ‘thinks’: Understanding opacity in machine learning algorithms , 2016 .
[27] David F. Feldon,et al. Cognitive task analysis , 2009 .
[28] Kenneth R. Koedinger,et al. Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models , 2009, EDM.
[29] J. Fodor,et al. Connectionism and cognitive architecture: A critical analysis , 1988, Cognition.
[30] Zachary A. Pardos,et al. Imputing KCs with Representations of Problem Content and Context , 2017, UMAP.
[31] Albert T. Corbett,et al. Cognitive Tutor: Applied research in mathematics education , 2007, Psychonomic bulletin & review.
[32] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[33] G. Rasch. On General Laws and the Meaning of Measurement in Psychology , 1961 .
[34] Yi Sun,et al. Alternating Recursive Method for Q-matrix Learning , 2014, EDM.
[35] Ronald J. Williams,et al. A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.
[36] Kenneth R. Koedinger,et al. Learning Factors Analysis - A General Method for Cognitive Model Evaluation and Improvement , 2006, Intelligent Tutoring Systems.
[37] Jingchen Liu,et al. Data-Driven Learning of Q-Matrix , 2012, Applied psychological measurement.
[38] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[39] Sidney D'Mello,et al. Data mining and education. , 2015, Wiley interdisciplinary reviews. Cognitive science.
[40] Omer Levy,et al. Linguistic Regularities in Sparse and Explicit Word Representations , 2014, CoNLL.
[41] Nils J. Nilsson,et al. A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..
[42] Yann LeCun,et al. The Loss Surfaces of Multilayer Networks , 2014, AISTATS.
[43] Radek Pelánek,et al. Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques , 2017, User Modeling and User-Adapted Interaction.
[44] Shaghayegh Sahebi,et al. Tensor Factorization for Student Modeling and Performance Prediction in Unstructured Domain , 2016, EDM.
[45] Jin Tian,et al. Joint Discovery of Skill Prerequisite Graphs and Student Models , 2016, EDM.
[46] Radek Pelánek,et al. Metrics for Evaluation of Student Models , 2015, EDM.
[47] John R. Anderson,et al. Knowledge tracing: Modeling the acquisition of procedural knowledge , 2005, User Modeling and User-Adapted Interaction.
[48] Robert V. Lindsey,et al. Incorporating Latent Factors Into Knowledge Tracing To Predict Individual Differences In Learning , 2013 .