Zachary A. Pardos (zpardos@wpi) Major: Computer Science Degree status: Ph.D. Candidate National Science Foundation GK-12 Fellow Research: Bayesian models of student learning, Quasi-randomized controlled trial analysis, Spectral clustering methods for prediction, educational data mining Anticipated graduation: May, 2012

Acknowledgement: This material is based in part upon work supported by the National Science Foundation under the GK-12 PIMPSE Grant.  Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

*[06/21/2010: KDD Cup results: 2nd place student & 4th place overall]
- (journal article on the solution - WPI news announcement about the research and placement)
[03/31/2010: GRAD Poster Competition - 2nd place Science award for work on improving model convergence with EM - WPI - Poster (based on EDM2010 paper)]
[04/03/2011: GRAD Poster Competition - 1st place Science award for work on student assesment and prediction - WPI - Poster (based on JMLR article)]

Book

2010:

Pardos, Z. A., Heffernan, N. T., Anderson, B., Heffernan, C. (2010) Using Fine-Grained Skill Models to Fit Student Performance with Bayesian Networks. In C. Romero, S. Ventura, S. R. Viola, M. Pechenizkiy and R. S. J. Baker (Eds.) Handbook of Educational Data Mining. CRC Press, pp. 417-426.  - CRC

Journal Publications

2012:	Pardos, Z.A., Gowda, S. M., Baker, R. S.J.D., Heffernan, N. T., The Sum is Greater than the Parts: Ensembling Models of Student Knowledge in Educational Software. To appear in ACM's Knowledge Discovery and Datamining Explorations, 13(2)
2011: 2011:	Pardos, Z.A., Heffernan, N. T.: Using HMMs and bagged decision trees to leverage rich features of user and skill from an intelligent tutoring system dataset. To appear in the Journal of Machine Learning Research W & CP, In Press - PDF (pre-press) Pardos, Z.A., Dailey, M. & Heffernan, N. (In Press) Learning what works in ITS from non-traditional randomized controlled trial data. The International Journal of Artificial Intelligence in Education.
2007:	Razzaq, L., Heffernan, N.T., Feng, M., Pardos, Z.A. (2007) Developing Fine-Grained Transfer Models in the ASSISTment System. Journal of Technology, Instruction, Cognition, and Learning, Vol. 5. Number 3. Old City Publishing, Philadelphia, PA. 2007. pp. 289-304.
TBD: TBD: TBD:	Trivedi S, Pardos Z. A., Heffernan N. T., "The Utility of Clustering in Prediction Tasks”, IEEE Transactions on Systems, Man and Cybernetics, Part B. (Under Review) Trivedi S, Pardos Z. A., Sárközy G. N., Heffernan N. T., “Out of Sample Extensions to Spectral Clustering”, Statistics and Computing, Springer. (In Preparation) Pardos, Z. A., Heffernan, N. T. Determining the Significance of Item Order . Journal of Educational Data Mining. (Under Review)

Conference Publications (full chapter proceedings with a 15-35% acceptance rate)

2011: 2011: 2011: 2011: 2011: 2011: 2011:	KT-IDEM: Introducing Item Difficulty to the Knowledge Tracing Model - UMAP - PDF Ensembling Predictions of Student Knowledge within Intelligent Tutoring Systems - UMAP - PDF Clustering Students to Generate an Ensemble to Improve Standard Test Score Prediction - AIED - PDF Less is More: Improving the Speed and Prediction Power of Knowledge Tracing by Using Less Data - EDM - PDF Spectral Clustering in Educational Data Mining - EDM - PDF Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge Tracing - EDM - PDF Ensembling Predictions of Student Post-Test Scores for an Intelligent Tutoring System - EDM - PDF
2010: 2010: 2010:	Navigating the parameter space of Bayesian Knowledge Tracing models - EDM - PDF, Presentation - WPI - Poster Modeling individualization in a bayesian networks implementation of knowledge tracing - UMAP - PDF Learning what works in ITS from non-traditional randomized controlled trial data - ITS - PDF
2009: 2009:	Detecting the learning value of items in a randomized problem set - AIED - PDF Determining the significance of item order in randomized problem sets - EDM - PDF
2008:	The composition effect: conjunctive or compensatory? An analysis of multi-skill math questions in ITS - EDM - PDF

Workshop Papers (poster paper and workshop proceedings)

2011: 2011: 2011: 2011:	The Sum is Greater than the Parts: Ensembling Student Knowledge Models in ASSISTments - KDD - PDF Response Tabling - A simple and practical complement to Knowledge Tracing - KDD - PDF An Analysis of Response Time Data for Improving Student Performance Prediction - KDD - PDF Establishing the value of dynamic assessment in an online tutoring system - EDM - PDF
2008:	Effective skill assessment using expectation maximization in a multi network temporal Bayesian network - ITS - PDF
2007: 2007:	Analyzing fine-grained skill models using Bayesian and mixed effect methods - AIED - PDF, Poster The effect of model granularity on student performance prediction using bayesian networks - UM - PDF, 5-page, Poster
2006:	Using fine-grained skill models to fit student performance with Bayesian networks - ITS - PDF

Tools (for CS525 class)

2010: 2010:

Dataset of student responses to 42 problem sets in The ASSISTment System - download - analyzed in this paper: PDF Temporal Bayes Net Experimenter for MATLAB - download - requires: BNT

Zach A. Pardos | 100 Institute Road #3213, Worcester, MA 01609-2280 | +1-321-219-9224