Ryan Shaun Joazeiro de Baker, Agathe Merceron, Philip I. Pavlik Jr.
Proceedings of the Third International Conference on Educational Data Mining
EDM, 2010.

@proceedings{EDM-2010,
	editor        = "Ryan Shaun Joazeiro de Baker and Agathe Merceron and Philip I. Pavlik Jr.",
	isbn          = "978-0-615-37529-8",
	publisher     = "{www.educationaldatamining.org}",
	title         = "{Proceedings of the Third International Conference on Educational Data Mining}",
	year          = 2010,
}

Contents (64 items)

EDM-2010-ArroyoMW #approach #empirical

Effort-based Tutoring: An Empirical Approach to Intelligent Tutoring (IA, HM, BPW), pp. 1–10.

EDM-2010-BakerG #analysis #difference #student

An Analysis of the Differences in the Frequency of Students’ Disengagement in Urban, Rural, and Suburban High Schools (RSJdB, SMG), pp. 11–20.

EDM-2010-DesmaraisP #on the #performance #student

On the Faithfulness of Simulated Student Performance Data (MCD, IP), pp. 21–30.

EDM-2010-DMelloG #experience #learning #mining

Mining Bodily Patterns of Affective Experience during Learning (SKD, ACG), pp. 31–40.

EDM-2010-FengH #assessment #learning #question #student #testing

Can We Get Better Assessment From A Tutoring System Compared to Traditional Paper Testing? Can We Have Our Cake (Better Assessment) and Eat It too (Student Learning During the Test)? (MF, NTH), pp. 41–50.

EDM-2010-FinchamABF #modelling #using

Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System (JMF, JRA, SB, JLF), pp. 51–60.

EDM-2010-GongBH #multi #parametricity #using

Using multiple Dirichlet distributions to improve parameter plausibility (YG, JEB, NTH), pp. 61–70.

EDM-2010-HowardJN #mining #process #using

Examining Learner Control in a Structured Inquiry Cycle Using Process Mining (LH, JJ, CN), pp. 71–80.

EDM-2010-JeongBJH #analysis #behaviour #effectiveness #learning #markov #modelling #using

Analysis of Productive Learning Behaviors in a Structured Inquiry Cycle Using Hidden Markov Models (HJ, GB, JJ, LH), pp. 81–90.

EDM-2010-DominguezYC #data mining #generative #mining #python

Data Mining for Generating Hints in a Python Tutor (AKD, KY, JRC), pp. 91–100.

EDM-2010-LehmanCO #learning #topic

Off Topic Conversation in Expert Tutoring: Waste of Time or Learning Opportunity (BL, WLC, AO), pp. 101–110.

EDM-2010-KimC #analysis #case study #experience #learning #sentiment #student

Sentiment Analysis in Student Experiences of Learning (SMK, RAC), pp. 111–120.

EDM-2010-MaullSS #behaviour #education #online

Online Curriculum Planning Behavior of Teachers (KEM, MGS, TS), pp. 121–130.

EDM-2010-KrugerMW #analysis #education #mining

A Data Model to Ease Analysis and Mining of Educational Data (AK, AM, BW), pp. 131–140.

EDM-2010-MontalvoBPNG #identification #machine learning #student #using

Identifying Students’ Inquiry Planning Using Machine Learning (OM, RSJdB, MASP, AN, JDG), pp. 141–150.

EDM-2010-NugentDA #algorithm #automation #clustering #set #specification

Skill Set Profile Clustering: The Empty K-Means Algorithm with Automatic Specification of Starting Cluster Centers (RN, ND, EA), pp. 151–160.

EDM-2010-PardosH #algorithm #convergence #modelling #navigation #parametricity #visualisation

Navigating the parameter space of Bayesian Knowledge Tracing models: Visualizations of the convergence of the Expectation Maximization algorithm (ZAP, NTH), pp. 161–170.

EDM-2010-RomeroRLV #mining

Mining Rare Association Rules from e-Learning Data (CR, JRR, JML, SV), pp. 171–180.

EDM-2010-PedroBMNG #behaviour #detection #using

Using Text Replay Tagging to Produce Detectors of Systematic Experimentation Behavior Patterns (MSP, RSJdB, OM, AN, JDG), pp. 181–190.

EDM-2010-ShanabrookCWA #behaviour #identification #student #using

Identifying High-Level Student Behavior Using Sequence-based Motif Discovery (DHS, DGC, BPW, IA), pp. 191–200.

EDM-2010-ShihKS #student

Unsupervised Discovery of Student Strategies (BS, KRK, RS), pp. 201–210.

EDM-2010-XiongLS #locality #mining #performance #problem

Assessing Reviewer’s Performance Based on Mining Problem Localization in Peer-Review Data (WX, DJL, CDS), pp. 211–220.

EDM-2010-YudelsonBMM #adaptation #education #integration #optimisation #semantics #using

Using Numeric Optimization To Refine Semantic User Model Integration Of Adaptive Educational Systems (MY, PB, AM, MM), pp. 221–230.

EDM-2010-ChampaignC #approach

An Annotations Approach to Peer Tutoring (JC, RC), pp. 231–240.

EDM-2010-FalakmasirH #data mining #education #mining #using

Using Educational Data Mining Methods to Study the Impact of Virtual Classroom in E-Learning (MHF, JH), pp. 241–248.

EDM-2010-Rajibussalim #interactive #learning #mining #student

Mining Students’ Interaction Data from a System that Support Learning by Reflection (R), pp. 249–256.

EDM-2010-SouthavilayYC #collaboration #mining #process #student

Process Mining to Support Students’ Collaborative Writing (VS, KY, RAC), pp. 257–266.

EDM-2010-AleahmadAK #automation #rating

Automatic Rating of User-Generated Math Solutions (TA, VA, RK), pp. 267–268.

EDM-2010-BachmannGB #analysis #student

Tracking Students’ Inquiry Paths through Student Transition Analysis (MB, JDG, JB), pp. 269–270.

EDM-2010-BeckerWV #interactive #named #tutorial

DISCUSS: Enabling Detailed Characterization of Tutorial Interactions Through Dialogue Annotation (LB, WHW, SvV), pp. 271–272.

EDM-2010-BernauerP #data mining #mining #student

Data Mining of both Right and Wrong Answers from a Mathematics and a Science M/C Test given Collectively to 11, 228 Students from India in years 4, 6 and 8 (JB, JP), pp. 273–274.

EDM-2010-SrinivasBG #mining

Mining information from tutor data to improve pedagogical content knowledge (SS, MB, AG), pp. 275–276.

EDM-2010-Bian #clustering #learning #process #student

Clustering Student Learning Activity Data (HB), pp. 277–278.

EDM-2010-BousbiaLBR #behaviour #learning #using #web

Analyzing Learning Styles using Behavioral Indicators in Web based Learning Environments (NB, JML, AB, IR), pp. 279–280.

EDM-2010-CadeO #modelling #topic #using

Using Topic Models to Bridge Coding Schemes of Differing Granularity (WLC, AO), pp. 281–282.

EDM-2010-ChampaignC10a #approach #learning

A Distillation Approach to Refining Learning Objects (JC, RC), pp. 283–284.

EDM-2010-BoyerPHWVL #markov #modelling #tutorial

A Preliminary Investigation of Hierarchical Hidden Markov Models for Tutorial Planning (KEB, RP, EH, MDW, MAV, JCL), pp. 285–286.

EDM-2010-ForsythBGH #correlation #learning

Higher Contributions Correlate with Higher Learning Gains (CF, HB, ACG, DFH), pp. 287–288.

EDM-2010-GoldsteinBH #learning

Pinpointing Learning Moments; A finer grain P(J) model (ABG, RSJdB, NTH), pp. 289–290.

EDM-2010-Gonzalez-BrenesM #predict

Predicting Task Completion from Rich but Scarce Data (JPGB, JM), pp. 291–292.

EDM-2010-Hardof-JaffeHAN

Hierarchical Structures of Content Items in LMS (SHJ, AH, RA, RN), pp. 293–294.

EDM-2010-HershkovitzN #persistent #process #question #student

Is Students’ Activity in LMS Persistent? (AH, RN), pp. 295–296.

EDM-2010-JohnsonB #student #visualisation

EDM Visualization Tool: Watching Students Learn (MJ, TB), pp. 297–298.

EDM-2010-KhodeirWDH #abduction #difference #network #probability #student #using

Inferring the Differential Student Model in a Probabilistic Domain Using Abduction inference in Bayesian networks (NK, NMW, NMD, NH), pp. 299–300.

EDM-2010-MacfadyenS #design #interactive #monitoring #online #using

Using LiMS (the Learner Interaction Monitoring System) to Track Online Learner Engagement and Evaluate Course Design (LM, PS), pp. 301–302.

EDM-2010-MaullSS10a #behaviour #education #online

Observing Online Curriculum Planning Behavior of Teachers (KEM, MGS, TS), pp. 303–304.

EDM-2010-KrugerMW10a #data analysis #data mining #mining

When Data Exploration and Data Mining meet while Analysing Usage Data of a Course (AK, AM, BW), pp. 305–306.

EDM-2010-MostowT #named #query

AutoJoin: Generalizing an Example into an EDM query (JM, BH(T), pp. 307–308.

EDM-2010-MozinaGSGKB #concept #student

Conceptualizing Procedural Knowledge Targeted at Students with Different Skill Levels (MM, MG, AS, VG, JK, IB), pp. 309–310.

EDM-2010-Pavlik #comprehension #learning #reduction

Data Reduction Methods Applied to Understanding Complex Learning Hypotheses (PIPJ), pp. 311–312.

EDM-2010-RaiB #analysis #approach #case study #education #modelling

Analysis of a causal modeling approach: a case study with an educational intervention (DR, JEB), pp. 313–314.

EDM-2010-XuR #analysis #learning #network #online #social

Peer Production of Online Learning Resources: A Social Network Analysis (BX, MR), pp. 315–316.

EDM-2010-RomeroVVP #mining #student #testing

Class Association Rules Mining from Students’ Test Data (CR, SV, EV, MP), pp. 317–318.

EDM-2010-RuppSC #analysis #game studies #learning #modelling #network #novel

Modeling Learning Trajectories with Epistemic Network Analysis: A Simulation-based Investigation of a Novel Analytic Method for Epistemic Games (AAR, SJS, YC), pp. 319–320.

EDM-2010-SongmuangU #algorithm #multi

Multiple Test Forms Construction based on Bees Algorithm (PS, MU), pp. 321–322.

EDM-2010-SoundranayagamY #learning #order #predict #question

Can Order of Access to Learning Resources Predict Success? (HS, KY), pp. 323–324.

EDM-2010-KoedingerS #approach #data-driven #modelling

A Data Driven Approach to the Discovery of Better Cognitive Models (KRK, JCS), pp. 325–326.

EDM-2010-StamperBC #knowledge base #problem #using

Using a Bayesian Knowledge Base for Hint Selection on Domain Specific Problems (JCS, TB, MJC), pp. 327–328.

EDM-2010-UbiL #overview #student

A Review of Student Churn in the Light of Theories on Business Relationships (JU, IL), pp. 329–330.

EDM-2010-VasilyevaPTKVB #framework #information management #personalisation #towards

Towards EDM Framework for Personalization of Information Services in RPM Systems (EV, MP, AT, EK, SV, PDB), pp. 331–332.

EDM-2010-VialardiCBVEPO #case study #data mining #mining #student

A Case Study: Data Mining Applied to Student Enrollment (CVS, JC, AB, DV, JE, JPP, AO), pp. 333–334.

EDM-2010-WangHB #performance #representation #student

Representing Student Performance with Partial Credit (YW, NTH, JEB), pp. 335–336.

EDM-2010-ReckerXHG

Where in the World? Demographic Patterns in Access Data (MR, BX, SH, CG), pp. 337–338.

EDM-2010-RankaAC #named #recommendation

Pundit: Intelligent Recommender of Courses (AR, FA, HSC), pp. 339–340.