Submitted

Currently Submitted paper are stored here


Paper that are submitted to EDM2015 are here.



Full PAPER: 32 36% accerpate rate
TITLE: Using Partial Credit and Response History to Model User Knowledge
AUTHORS: Eric Van Inwegen, Seth Adjei, Yan Wang and Neil Heffernan
Full PAPER: 152
TITLE: The Impact of Incorporating Student Confidence Items into an Intelligent Tutor: A Randomized Controlled Trial
AUTHORS: Charles Lang, Neil Heffernan, Korinn Ostrow and Yutao Wang

Full PAPER: 94

TITLE: Exploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test Achievement

AUTHORS: Maria Ofelia San Pedro, Erica Snow, Ryan Baker, Danielle McNamara and Neil Heffernan



ShortPAPER: 52
TITLE: Optimizing Partial Credit Algorithms to Predict Student Performance
AUTHORS: Korinn Ostrow, Christopher Donnelly and Neil Heffernan

Short Paper: 38
Title: Building Models to Predict Hint-or-Attempt Actions of Students
Authors: Francisco Enrique Vicente, Seth Adjei, Tyler Colombo, Neil Heffernan


Poster PAPER: 108   
TITLE: An examination of metrics that describe user models
AUTHORS: Eric Van Inwegen, Yan Wang, Seth Adjei and Neil Heffernan


Poster PAPER: 231
TITLE: Defining Mastery: Knowledge Tracing Versus N-Consecutive Correct Responses
AUTHORS: Kim Kelly, Yan Wang, Tamisha Thompson and Neil Heffernan

Poster PAPER: 228
TITLE: Predicting Student Aptitude Using Performance History
AUTHORS: Anthony F. Botelho, Seth A. Adjei, Hao Wan and Neil T. Heffernan


156Yan Wang, Korinn OstrowNeil Heffernan and Joseph BeckEnhancing the Efficiency and Reliability of Group Differentiation through Partial Credit
209Siyuan Zhao and Neil HeffernanExploiting Correctness Sequence and Problem Difficulty Over Time to Predict Student’s Performance


#authorstitletrackinformationsubmission
32Eric Van Inwegen, Seth Adjei, Yan Wang and Neil HeffernanUsing Partial Credit and Response History to Model User KnowledgeEDM 2015informationEDM_2015_submission_32.pdf
38Francisco Enrique Vicente Castro, Seth Adjei, Tyler Colombo and Neil HeffernanBuilding Models to Predict Hint-or-Attempt Actions of StudentsEDM 2015informationEDM_2015_submission_38.pdf
52Korinn Ostrow, Christopher Donnelly and Neil HeffernanOptimizing Partial Credit Algorithms to Predict Student PerformanceEDM 2015informationEDM_2015_submission_52.pdf
94Maria Ofelia San Pedro, Erica Snow, Ryan Baker, Danielle McNamara and Neil HeffernanExploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test AchievementEDM 2015informationEDM_2015_submission_94.pdf
108Eric Van Inwegen, Yan Wang, Seth Adjei and Neil HeffernanAn examination of metrics that describe user modelsEDM 2015informationEDM_2015_submission_108.pdf
152Charles Lang, Neil Heffernan, Korinn Ostrow and Yutao WangThe Impact of Incorporating Student Confidence Items into an Intelligent Tutor: A Randomized Controlled TrialEDM 2015informationEDM_2015_submission_152.pdf
156Yan Wang, Korinn OstrowNeil Heffernan and Joseph BeckEnhancing the Efficiency and Reliability of Group Differentiation through Partial CreditEDM 2015informationEDM_2015_submission_156.pdf





209Siyuan Zhao and Neil HeffernanExploiting Correctness Sequence and Problem Difficulty Over Time to Predict Student’s PerformanceEDM 2015informationEDM_2015_submission_209.pdf
228Anthony F. Botelho, Seth A. Adjei, Hao Wan and Neil T. HeffernanPredicting Student Aptitude Using Performance HistoryEDM 2015informationEDM_2015_submission_228.pdf
231Kim Kelly, Yan Wang, Tamisha Thompson and Neil HeffernanDefining Mastery: Knowledge Tracing Versus N-Consecutive Correct ResponsesEDM 2015informationEDM_2015_submission_231.pdf
247Kim Kelly and Neil HeffernanDeveloping Self-Regulated Learners Through an Intelligent Tutoring SystemDCinformationEDM_2015_submission_247.pdf
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AIED submissions
Paper submitted to AIED2015 are here with CU for Current.

CU1  Jiang, Y., Baker, R. Paquette, L. San Pedro, M. & Heffernan, N. T. (submitted)  Learning, Moment-by-Moment and Over the Long TermThe 17th Proceedings of the  Conference on Artificial Intelligence in Education, Madrid, Spain. 
CU4 Williams, J.J., Ostrow, K., Xionag, X., Glassman, E., Kim, J., Maldonado, S., Reich, J & Heffernan, N.T. (submitted) Technology for In Vivo Educational Experiments. The 17th Proceedings of the  Conference on Artificial Intelligence in Education, Madrid, Spain. 
CU8 Zhao, S., Lu, Y. & Heffernan, N.T. (submitted) Cluster students to improve predictive accuracy on student performance. The 17th Proceedings of the  Conference on Artificial Intelligence in Education, Madrid, Spain. 


Heffernan, Ostrow, K.. Kelly, K., Selent, D., VanInwegen, E., Xiong, X. & Williams, J. (submitted) The Future of Adaptive Learning: Does the Crowd Hold the Key? Submitted to the International Journal of Artificial Intelligence in Education. Retrievied from https://goo.gl/TJXyfB


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