Schedule

Full papers have 25 minutes each (including questions); Short papers have 15 minutes each (including questions)
[click for a map of the conference location]

DAY 1: Wednesday, 6 July 2011

8:00-8:50 Registration
8:50–9:10 OPENING CEREMONY
9:10–10:10 INVITED TALK
Barry Smyth: Social Information Discovery
[abstract] [about the speaker]
10:10–10:25 COFFEE BREAK
10:25–11:55 Session I: Predictive Modeling
3 Full + 1 Short [list of papers]
11:55–13:00 Posters session I
15 posters [list of posters]
13:00–14:00 LUNCH
(possibility of walking lunch at posters)
14:00–15:45 Session II: Temporal Issues in Student Modeling
3 Full + 2 Short [list of papers]
15:45–16:15 COFFEE BREAK
16:15-17:25 Session III: Student Performance Mining
1 Full + 3 Short [list of papers]

DAY 2: Thursday, 7 July 2011

8:30-9:00 Registration
9:00-10:45 Session IV: Factorization Models
3 Full + 2 Short [list of papers]
10:45–11:05 COFFEE BREAK
11:05–12:10 Session V: User Interaction Issues
2 Full + 1 Short [list of papers]
12:10–13:15 Posters session II
15 posters [list of posters]
13:15–14:15 LUNCH
(possibility of walking lunch at posters)
14:15–16:15 Session VI: Intelligent Tutoring
3 Full + 3 Short [list of papers]
16:15-16:30 COFFEE BREAK
16:30-17:30 INVITED TALK
Erik-Jan van der Linden: On Exploration and Mining of Data in Educational Practice
[abstract] [details]
17:30-18:15 PANEL DISCUSSIONS
Panelists: Joseph E. Beck, Ryan Baker, Kalina Yacef, Osmar Zaiane, Kenneth Koedinger
19:00-22:00 CONFERENCE DINNER [click for a map of the event location]

DAY 3: Friday, 8 July 2011

9:00-9:30 Registration
9:30-10:30 INVITED TALK
John Stamper: EDM and the 4th Paradigm of Scientific Discovery – Reflections on KDD Cup 2010
[abstract] [details]
10:30-10:50 COFFEE BREAK
10:50-12:00 Session VII: Mining Task-specific Student Strategies
1 Full + 3 Short [list of papers]
12:00-12:30 EDM COMMUNITY MEETING
12:30-13:30 LUNCH
13:30-14:25 Session VIII: Knowledge Tracing
1 Full + 2 Short [list of papers]
14:24-14:45 COFFEE BREAK
14:45-16:00 Session IX: NOMINEES
3 Full [list of papers]
16:00-16:30 CLOSING CEREMONY (Best Paper Awards and Announcements)
16:30-17:30 FAREWELL RECEPTION

List of Papers and Posters by Session

Session I: Predictive Modeling [↑]
Wednesday, July 6, 10:25–11:55
Chair: Ryan Bakker

  • Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions
    Min Chi, Kenneth Koedinger, Geoff Gordon, Pamela Jordan and Kurt Vanlehn [pdf]
  • Learning classifiers from a relational database of tutor logs
    Jack Mostow, José González-Brenes and Bao Hong Tan [pdf]
  • Ensembling Predictions of Student Post-Test Scores for an Intelligent Tutoring System
    Zachary Pardos, Sujith Gowda, Ryan S.J.D. Baker and Neil Heffernan [pdf]
  • Prediction of Perceived Disorientation in Online Learning Environment with Random Forest Regression (Short)
    Gökhan Akçapınar, Erdal Coşgun and Arif Altun [pdf]

Session II: Temporal Issues in Student Modeling [↑]
Wednesday, July 6, 14:00-15:45
Chair: Alina Von Davier

  • Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge Tracing
    Yumeng Qiu, Yingmei Qi, Hanyuan Lu, Zachary Pardos and Neil Heffernan [pdf]
  • The Simple Location Heuristic is Better at Predicting Students’ Changes in Error Rate Over Time Compared to the Simple Temporal Heuristic
    Adaeze Nwaigwe and Kenneth Koedinger [pdf]
  • Automatically Detecting a Student’s Preparation for Future Learning: Help Use is Key
    Ryan S.J.D. Baker, Sujith Gowda and Albert Corbett [pdf]
  • A Method for Finding Prerequisites Within a Curriculum (Short)
    Annalies Vuong, Tristan Nixon and Brendon Towle [pdf]
  • Estimating Prerequisite Structure From Noisy Data (Short)
    Emma Brunskill [pdf]

Session III: Student Performance Mining [↑]
Wednesday, July 6, 16:15-17:25
Chair: Kenneth R. Koedinger

  • Items, skills, and transfer models: which really matters for student modeling?
    Yue Gong and Joseph Beck [pdf]
  • Predicting School Failure Using Data Mining (Short)
    Carlos Marquez-Vera, Cristobal Romero and Sebastián Ventura [pdf]
  • Desperately Seeking Subscripts: Towards Automated Model Parameterization (Short)
    Jack Mostow, Yanbo Xu and Mdahaduzzaman Munna [pdf]
  • What can closed sets of students and their marks say? (Short)
    Dmitry Ignatov, Serafima Mamedova, Nikita Romashkin and Ivan Shamshurin [pdf]

Session IV: Factorization Models [↑]
Thursday, July 7, 9:00-10:45
Chair: Osmar Zaiane

  • Factorization Models for Forecasting Student Performance
    Nguyen Thai-Nghe, Tomáš Horváth and Lars Schmidt-Thieme [pdf]
  • A Machine Learning Approach for Automatic Student Model Discovery
    Nan Li, William Cohen, Kenneth R. Koedinger and Noboru Matsuda [pdf]
  • Improving Models of Slipping, Guessing, and Moment-By-Moment Learning with Estimates of Skill Difficulty
    Sujith M. Gowda, Jonathan P. Rowe, Ryan S.J.D. Baker, Min Chi and Kenneth R. Koedinger [pdf]
  • Using Logistic Regression to Trace Multiple Sub-skills in a Dynamic Bayes Net (Short)
    Yanbo Xu and Jack Mostow [pdf]
  • What’s an Expert? Using learning analytics to identify emergent markers of expertise through automated speech, sentiment and sketch analysis (Short)
    Marcelo Worsley and Paulo Blikstein [pdf]

Session V: User Interaction Issues [↑]
Thursday, July 7, 11:05-12:10
Chair: Arnon Hershkovitz

  • A Framework for Capturing Distinguishing User Interaction Behaviors in Novel Interfaces
    Samad Kardan and Cristina Conati [pdf]
  • Analyzing Participation of Students in Online Courses Using Social Network Analysis Techniques
    Reihaneh Rabbany Khorasgani, Mansoureh Takaffoli and Osmar Zaïane [pdf]
  • Modeling students’ activity in online discussion forums: a strategy based on time series and agglomerative hierarchical clustering (Short)
    Germán Cobo, David García-Solórzano, Eugènia Santamaría, Jose Antonio Morán, Javier Melenchón and Carlos Monzo [pdf]

Session VI: Intelligent Tutoring [↑]
Thursday, July 7, 14:15-16:15
Chair: Michel Desmarais

  • Spectral Clustering in Educational Data Mining
    Shubhendu Trivedi, Zachary Pardos, Gábor Sárközy and Neil Heffernan [pdf]
  • How to Classify Tutorial Dialogue? Comparing Feature Vectors vs. Sequences
    José González-Brenes, Jack Mostow and Weisi Duan [pdf]
  • Fair Blame Assignment in Student Modeling
    Kenneth Koedinger, Philip I. Pavlik Jr., John Stamper, Tristan Nixon and Steven Ritter [pdf]
  • Exploring user data from a game-like math tutor: a case study in causal modeling (Short)
    Dovan Rai and Joseph Beck [pdf]
  • Establishing the value of dynamic assessment in an online tutoring system (Short)
    Mingyu Feng, Neil Heffernan, Zachary Pardos and Cristina Heffernan [pdf]
  • Automatic Generation of Proof Problems in Deductive Logic (Short)
    Behrooz Mostafavi, Tiffany Barnes and Marvin Croy [pdf]

Session VII: Mining Task-specific Student Strategies [↑]
Friday, July 8, 10:50-12:05
Chair: Jack Mostow

  • Student Translations of Natural Language into Logic: The Grade Grinder Translation Corpus Release 1.0
    Dave Barker-Plummer, Richard Cox and Robert Dale [pdf]
  • Evaluating a Bayesian Student Model of Decimal Misconceptions (Short)
    George Goguadze, Sergey Sosnovsky, Seiji Isotani and Bruce Mclaren [pdf]
  • Analyzing Student Spatial Deployment in a Computer Laboratory (Short)
    Vladimir Ivančević, Milan Čeliković and Ivan Luković [pdf]
  • How university entrants are choosing their department? Mining of university admission process with FCA taxonomies (Short)
    Nikita Romashkin, Dmitry Ignatov and Elena Kolotova [pdf]

Session VIII: Knowledge Tracing [↑]
Friday, July 8, 13:50-14:40
Chair: Cristobal Romero

  • Less is More: Improving the Speed and Prediction Power of Knowledge Tracing by Using Less Data
    Bahador Nooraei B., Zachary Pardos, Neil Heffernan and Ryan Baker [pdf]
  • Monitoring Learners’ Proficiency: Weight Adaptation in the Elo Rating System (Short)
    Kelly Wauters, Piet Desmet and Wim Van Den Noortgate [pdf]
  • A Dynamical System Model of Microgenetic Changes in Performance, Efficacy, Strategy Use and Value during Vocabulary Learning (Short)
    Philip I. Pavlik Jr. and Sue-Mei Wu [pdf]

Session IX: Nominees to Best Paper Awards [↑]
Friday, July 8, 15:00-16:15
Chair:Cristina Conati

  • Conditions for effectively deriving a Q-Matrix from data with Non-negative Matrix Factorization
    Michel Desmarais [pdf]
  • Analysing frequent sequential patterns of collaborative learning activity around an interactive tabletop
    Roberto Martinez Maldonado, Kalina Yacef, Judy Kay, Ahmed Kharrufa and Ammar Al-Qaraghuli [pdf]
  • Acquiring Item Difficulty Estimates: a Collaborative Effort of Data and Judgment
    Kelly Wauters, Piet Desmet and Wim Van Den Noortgate [pdf]

Poster Session I [↑]
Wednesday, July 6, 11:55-13:00

  • Goal Orientation and Changes of Carelessness over Consecutive Trials in Science Inquiry
    Arnon Hershkovitz, Ryan S.J.D. Baker, Janice Gobert and Michael Wixon
    [pdf]
  • Towards improvements on domain-independent measurements for collaborative assessment
    Antonio R. Anaya and Jesús G. Boticario
    [pdf]
  • A Java desktop tool for mining Moodle data
    Rafael Pedraza Perez, Cristobal Romero and Sebastián Ventura
    [pdf]
  • Using data mining in a recommender system to search for learning objects in repositories
    Alfredo Zapata Gonzalez, Victor Hugo Menéndez Domínguez, Manuel Prieto and Cristobal Romero
    [pdf]
  • E-learning Web Miner: A data mining application to help instructors involved in virtual courses
    Diego García-Saiz and Marta Zorrilla
    [pdf]
  • Computerized Coding System for Life Narratives to Assess Students’ Personality Adaption
    Qiwei He, Bernard Veldkamp and Gerben Westerhof
    [pdf]
  • Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System
    Emma Brunskill and Stuart Russell
    [pdf]
  • Variable Construction and Causal Modeling of Online Education Messaging Data: Initial Results
    Stephen Fancsali
    [pdf]
  • The Hospital Classrooms Environments Challenge
    Carina González and Pedro A. Toledo
    [pdf]
  • Logistic Regression in a Dynamic Bayes Net Models Multiple Subskills Better!
    Yanbo Xu and Jack Mostow
    [pdf]
  • Studying the problem-solving strategies in the early stages of learning programming
    Edgar Cambranes-Martinez and Judith Good
    [pdf]
  • Brick: Mining Pedagogically Interesting Sequential Patterns
    Anjo Anjewierden, Hannie Gijlers, Nadira Saab and Robert De Hoog
    [pdf]
  • Intelligent evaluation of social knowledge building using conceptual maps with MLN
    Lorenzo Moreno and Carina Gonzalez, R. Estevez and B. Popescu
    [pdf]
  • Identifying Influence Factors on Students Success by Subgroup Discovery
    Florian Lemmerich, Marianus Ifland and Frank Puppe
    [pdf]
  • Analyzing University Data for Determining Student Profiles and Predicting Performance
    Dorina Kabakchieva, Kamelia Stefanova and Valentin Kisimov
    [pdf]

Poster Session II [↑]
Thursday, July 7, 12:10-13:15

  • The EDM Vis Tool
    Matthew Johnson, Michael Eagle, Leena Joseph and Tiffany Barnes [pdf]
  • Towards Modeling Forgetting and Relearning in ITS: Preliminary Analysis of ARRS Data
    Yutao Wang and Neil Heffernan [pdf]
  • Quality Control and Data Mining Techniques Applied to Monitoring Scaled Scores
    Alina Von Davier [pdf]
  • eLAT: An Exploratory Learning Analytics Tool for Reflection and Iterative Improvement of Technology Enhanced Learning
    Anna Lea Dyckhoff, Dennis Zielke, Mohamed Amine Chatti and Ulrik Schroeder [pdf]
  • Predicting graduate-level performance from undergraduate achievements
    Judith Zimmermann, Kay H. Brodersen, Jean-Philippe Pellet, Elias August and Joachim M. Buhmann [pdf]
  • Mining Assessment and Teaching Evaluation Data of Regular and Advanced Stream Students
    Irena Koprinska [pdf]
  • Investigating Usage of Resources in LMS with Specific Association Rules
    Agathe Merceron [pdf]
  • Towards parameter-free data mining: Mining educational data with yacaree
    Marta E. Zorilla, Diego Garcia-Saiz and Jose L. Balcazar [pdf]
  • Factors Impacting Novice Code Comprehension in a Tutor for Introductory Computer Science
    Leigh Ann Sudol-DeLyser and Jonathan Steinhart [pdf]
  • Investigating the Transitions between Learning and Non-learning Activities as Students Learn Online
    Paul Salvador Inventado, Roberto Legaspi, Merlin Suarez and Masayuki Numao [pdf]
  • Learning parameters for a knowledge diagnostic tools in orthopedic surgery
    Sebastien Lalle and Vanda Luengo [pdf]
  • Problem Response Theory and its Application for Tutoring
    Petr Jarušek and Radek Pelánek [pdf]
  • Towards Better Understanding of Transfer in Cognitive Models of Practice
    Michael Yudelson, Philip I. Pavlik and Kennth R. Koedinger [pdf]
  • Mining Teaching Behaviors from Pedagogical Surveys
    Joana Barracosa and Claudia Antunes [pdf]
  • Combining study of complex network and text mining analysis to understand growth mechanism of communities on SNS
    Osamu Yamakawa [pdf]