John C. Stamper, Zachary A. Pardos, Manolis Mavrikis, Bruce M. McLaren
Proceedings of the Seventh International Conference on Educational Data Mining
EDM, 2014.
Contents (119 items)
- EDM-2014-PapousekPS #adaptation #information management
- Adaptive Practice of Facts in Domains with Varied Prior Knowledge (JP, RP, VS), pp. 6–13.
- EDM-2014-SunYIS #learning #recursion
- Alternating Recursive Method for Q-matrix Learning (YS, SY, SI, YS), pp. 14–20.
- EDM-2014-Pelanek14a #modelling #student
- Application of Time Decay Functions and the Elo System in Student Modeling (RP), pp. 21–27.
- EDM-2014-Fancsali #algebra #behaviour #learning #modelling
- Causal Discovery with Models: Behavior, Affect, and Learning in Cognitive Tutor Algebra (SF), pp. 28–35.
- EDM-2014-ChiSBC #assessment #game studies #predict #question #student
- Choice-based Assessment: Can Choices Made in Digital Games Predict 6th-Grade Students' Math Test Scores? (MC, DLS, KPB, DBC), pp. 36–43.
- EDM-2014-BazalduaBP
- Comparing Expert and Metric-Based Assessments of Association Rule Interestingness (DLB, RSB, MOSP), pp. 44–51.
- EDM-2014-KaserKG #analysis #learning #parametricity #predict
- Different parameters - same prediction: An analysis of learning curves (TK, KRK, MHG), pp. 52–59.
- EDM-2014-SaarelaK #education #using
- Discovering Gender-Specific Knowledge from Finnish Basic Education using PISA Scale Indices (MS, TK), pp. 60–67.
- EDM-2014-SegalKGSS #approach #collaboration #named #personalisation
- EduRank: A Collaborative Filtering Approach to Personalization in E-learning (AS, ZK, KG, GS, BS), pp. 68–75.
- EDM-2014-EagleB #approach #data-driven #difference #problem
- Exploring Differences in Problem Solving with Data-Driven Approach Maps (ME, TB), pp. 76–83.
- EDM-2014-HuangGB #multi
- General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge (YH0, JPGB, PB), pp. 84–91.
- EDM-2014-PeddycordHB #generative #problem #programming #using
- Generating Hints for Programming Problems Using Intermediate Output (BWPI, AH, TB), pp. 92–98.
- EDM-2014-KhajahWLM #difference #learning #modelling #predict
- Integrating latent-factor and knowledge-tracing models to predict individual differences in learning (MK, RW, RVL, MM), pp. 99–106.
- EDM-2014-LiuMK #dataset #testing
- Interpreting model discovery and testing generalization to a new dataset (RL0, EAM, KRK), pp. 107–113.
- EDM-2014-LeeLP #approach #behaviour #data-driven #education #game studies #learning
- Learning Individual Behavior in an Educational Game: A Data-Driven Approach (SJL, YEL, ZP), pp. 114–121.
- EDM-2014-GrafsgaardWBWL #data type #learning #multimodal #predict #tutorial
- Predicting Learning and Affect from Multimodal Data Streams in Task-Oriented Tutorial Dialogue (JFG, JBW, KEB, ENW, JCL), pp. 122–129.
- EDM-2014-WenYR #analysis #question #sentiment #what
- Sentiment Analysis in MOOC Discussion Forums: What does it tell us? (MW, DY, CPR), pp. 130–137.
- EDM-2014-SchneiderP #coordination #student
- The Effect of Mutual Gaze Perception on Students' Verbal Coordination (BS, RP), pp. 138–144.
- EDM-2014-WixonAMBRW #detection #scalability
- The Opportunities and Limitations of Scaling Up Sensor-Free Affect Detection (MW, IA, KM, WB, DR, BPW), pp. 145–152.
- EDM-2014-GuerraSLB #problem #student
- The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises (JG, SS, YRL, PB), pp. 153–160.
- EDM-2014-LiuMBP #learning #multi
- Trading Off Scientific Knowledge and User Learning with Multi-Armed Bandits (YEL, TM, EB, ZP), pp. 161–168.
- EDM-2014-AlmondGGW
- Vertical and Stationary Scales for Progress Maps (RGA, IMG, YG, NW), pp. 169–176.
- EDM-2014-BergnerSD #assessment #clustering #sequence #visualisation
- Visualization and Confirmatory Clustering of Sequence Data from a Simulation-Based Assessment Task (YB, ZS, AAvD), pp. 177–184.
- EDM-2014-SnowVRM #behaviour #categorisation #game studies
- Who's in Control?: Categorizing Nuanced Patterns of Behaviors within a Game-Based Intelligent Tutoring System (ELS, LKV, DGR, DSM), pp. 185–192.
- EDM-2014-AtapattuFF #approach
- Acquisition of Triples of Knowledge from Lecture Notes: A Natural Langauge Processing Approach (TA, KF, NJGF), pp. 193–196.
- EDM-2014-StefanescuRG #information management #student #towards #tutorial
- Towards Assessing Students' Prior Knowledge from Tutorial Dialogues (DS, VR, ACG), pp. 197–201.
- EDM-2014-KokkodisKK #education
- Assigning Educational Videos at Appropriate Locations in Textbooks (MK, AK, KK), pp. 201–204.
- EDM-2014-YudelsonFRBNJ #big data
- Better Data Beats Big Data (MY, SF, SR, SRB, TN, AJ), pp. 205–208.
- EDM-2014-DesmaraisBX #refinement #validation
- The refinement of a Q-matrix: Assessing methods to validate tasks to skills mapping (MCD, BB, PX), pp. 208–311.
- EDM-2014-AgnihotriO #student
- Building a Student At-Risk Model: An End-to-End Perspective From User to Data Scientist (LA, AO), pp. 209–212.
- EDM-2014-TanSK #comparison
- Can Engagement be Compared? Measuring Academic Engagement for Comparison (LT, XS, STK), pp. 213–216.
- EDM-2014-0001RRM #algorithm #automation #comparison #modelling
- Comparison of Algorithms for Automatically Building Example-Tracing Tutor Models (RK0, MER, RBR, JM), pp. 217–220.
- EDM-2014-BengsB #adaptation #testing
- Computer-based Adaptive Speed Tests (DB, UB), pp. 221–224.
- EDM-2014-TothRGW #assessment #education #problem #student
- Discovering Students' Complex Problem Solving Strategies in Educational Assessment (KT, HR, SG, SW), pp. 225–228.
- EDM-2014-ForsythGPMS #learning #predict
- Discovering Theoretically Grounded Predictors of Shallow vs. Deep- level Learning (CF, ACG, PIPJ, KKM, BS), pp. 229–232.
- EDM-2014-SameiOKNDBSGG #assessment #independence
- Domain Independent Assessment of Dialogic Properties of Classroom Discourse (BS, AO, SK, MN, SKD, NB, XS, MG, ACG), pp. 233–236.
- EDM-2014-LynchA #empirical
- Empirically Valid Rules for Ill-Defined Domains (CL, KDA), pp. 237–240.
- EDM-2014-SnowJVDM #learning #named
- Entropy: A Stealth Measure of Agency in Learning Environments (ELS, MEJ, LKV, JD, DSM), pp. 241–244.
- EDM-2014-MorganBR #analysis #fault #learning #validation
- Error Analysis as a Validation of Learning Progressions (BM, WB, VR), pp. 245–248.
- EDM-2014-EaglePMB #logic #student #using
- Exploration of Student's Use of Rule Application References in a Propositional Logic Tutor (ME, VP, BM, TB), pp. 249–252.
- EDM-2014-NyeHFSHM #modelling #realtime #student
- Exploring real-time student models based on natural-language tutoring sessions (BN, MHH, CF, BS, XH, KKM), pp. 253–256.
- EDM-2014-YangPHR #concurrent #online #recommendation #thread
- Forum Thread Recommendation for Massive Open Online Courses (DY, MP, IKH, CPR), pp. 257–260.
- EDM-2014-YudelsonHVB #automation #java #modelling #student
- Investigating Automated Student Modeling in a Java MOOC (MY, RH, AV, PB), pp. 261–264.
- EDM-2014-NiraulaRSG #mining #tutorial
- Mining Gap-fill Questions from Tutorial Dialogues (NBN, VR, DS, ACG), pp. 265–268.
- EDM-2014-ClementORL #education #multi #online #optimisation #sequence
- Online Optimization of Teaching Sequences with Multi-Armed Bandits (BC, PYO, DR, ML0), pp. 269–272.
- EDM-2014-JiangWSWO #behaviour #performance #predict
- Predicting MOOC performance with Week 1 Behavior (SJ, AEW, KS, MW, DKO), pp. 273–275.
- EDM-2014-PedroOBH #education #interactive #predict
- Predicting STEM and Non-STEM College Major Enrollment from Middle School Interaction with Mathematics Educational Software (MOSP, JO, RSB, NTH), pp. 276–279.
- EDM-2014-LanSB #learning #matrix #personalisation
- Quantized Matrix Completion for Personalized Learning (ASL, CS, RGB), pp. 280–283.
- EDM-2014-PaquetteCBO #case study #detection #game studies #process #re-engineering
- Reengineering the Feature Distillation Process: A case study in detection of Gaming the System (LP, AMJBdC, RSB, JO), pp. 284–287.
- EDM-2014-SmithWML #abstraction #mining #named #sketching
- SKETCHMINER: Mining Learner-Generated Science Drawings with Topological Abstraction (AS, ENW, BWM, JCL), pp. 288–291.
- EDM-2014-BoutnaruH #education #quality #security #student
- Teachers and Students Learn Cyber Security: Comparing Software Quality, Security (SB, AH), pp. 292–295.
- EDM-2014-OstrowH #authentication #comparison #feedback #multi #testing #video
- Testing the Multimedia Principle in the Real World: A Comparison of Video vs. Text Feedback in Authentic Middle School Math Assignments (KO, NTH), pp. 296–299.
- EDM-2014-CrossleyKVM #assessment #data mining #mining
- The Importance of Grammar and Mechanics in Writing Assessment and Instruction: Evidence from Data Mining (SAC, KK, LKV, DSM), pp. 300–303.
- EDM-2014-VarnerSM #difference
- The Long and Winding Road: Investigating the Differential Writing Patterns of High and Low Skilled Writers (LKV, ELS, DSM), pp. 304–407.
- EDM-2014-SchultzA14a #parallel
- Tracing Knowledge and Engagement in Parallel in an Intelligent Tutoring System (SES, IA), pp. 312–315.
- EDM-2014-SnowVM #analysis #learning
- Tracking Choices: Computational Analysis of Learning Trajectories (ELS, LKV, DSM), pp. 316–319.
- EDM-2014-SchneiderB #gesture #interactive #interface #recognition #student #using
- Unraveling Students' Interaction Around a Tangible Interface Using Gesture Recognition (BS, PB), pp. 320–323.
- EDM-2014-SilvaPC #classification #predict #video
- A Predictive Model for Video Lectures Classification (PS, RP, EC), pp. 325–326.
- EDM-2014-FuentesRGV #data mining #mining #self #student #using
- Accepting or Rejecting Students_ Self-grading in their Final Marks by using Data Mining (JF, CR, CGM, SV), pp. 327–328.
- EDM-2014-WatanabeOK #analysis #behaviour #student
- Analysis and extraction of behaviors by students in lectures (EW, TO, TK), pp. 329–330.
- EDM-2014-GerykP #analysis #student #using #visual notation
- Analysis of Student Retention and Drop-out using Visual Analytics (JG, LP), pp. 331–332.
- EDM-2014-MintzSFDG #assessment #automation #comprehension #student #summary
- Automatic assessment of student reading comprehension from short summaries (LM, DS, SF, SKD, ACG), pp. 333–334.
- EDM-2014-MorrisonNSDKR #data mining #database #mining
- Building an Intelligent PAL from the Tutor.com Session Database Phase 1: Data Mining (DMM, BN, BS, VVD, CK, VR), pp. 335–336.
- EDM-2014-RoweBAKH #automation #detection #learning
- Building Automated Detectors of Gameplay Strategies to Measure Implicit Science Learning (ER, RSB, JAC, EK, WJH), pp. 337–338.
- EDM-2014-NetoBGCWC #challenge #framework #learning #multi #online #platform #student
- Challenges on adopting BKT to model student knowledge in multi-context online learning platform (WLDMN, EB, FG, LC, NLW, PC), pp. 339–340.
- EDM-2014-KochROL #data flow #re-engineering #semantics #statistics
- Combination of statistical and semantic data sources for the improvement of software engineering courses (Vision Paper) (MK0, MR, FO, DL), pp. 341–342.
- EDM-2014-ColvinCLFP #learning
- Comparing Learning in a MOOC and a Blended, On-Campus Course (KFC, JC, AL, CF, DEP), pp. 343–344.
- EDM-2014-BakerO #detection #effectiveness #scalability
- Cost-Effective, Actionable Engagement Detection at Scale (RSB, JO), pp. 345–346.
- EDM-2014-SyedJG #data mining #mining
- Data mining of undergraduate course evaluations (SJS, YHJ, LG), pp. 347–348.
- EDM-2014-Brawner #low cost
- Data Sharing: Low-Cost Sensors for Affect and Cognition (KWB), pp. 349–350.
- EDM-2014-RaffertyG #algebra #comprehension
- Diagnosing Algebra Understanding via Bayesian Inverse Planning (ANR, TLG), pp. 351–352.
- EDM-2014-McTavishL #fault
- Discovering and describing types of mathematical errors (TSM, JAL), pp. 353–354.
- EDM-2014-ScheinesSG #component
- Discovering Prerequisite Relationships Among Knowledge Components (RS, ES, IMG), pp. 355–356.
- EDM-2014-ZhengP #algorithm #learning #using
- Dynamic Re-Composition of Learning Groups Using PSO-Based Algorithms (ZZ, NP), pp. 357–358.
- EDM-2014-ShuQF #data mining #education #experience #learning #mining #student
- Educational Data Mining and Analyzing of Student Learning Outcomes from the Perspective of Learning Experience (ZS, QFQ, LQF), pp. 359–360.
- EDM-2014-XuCYM #using
- Using EEG in Knowledge Tracing (YX, KmC, YY, JM), pp. 361–362.
- EDM-2014-HsiaoCMBN #video
- Exploring Engaging Dialogues in Video Discussions (IHH, HSC, MM, RSB, GN), pp. 363–364.
- EDM-2014-Salmeron-Majadas #interactive #predict
- Exploring indicators from keyboard and mouse interactions to predict the user affective state (SSM, OCS, JB), pp. 365–366.
- EDM-2014-OedaIY
- Extracting Latent Skills from Time Series of Asynchronous and Incomplete Examinations (SO, YI, KY), pp. 367–368.
- EDM-2014-JoshiFRNB #interactive #predict #standard
- Generalizing and Extending a Predictive Model for Standardized Test Scores Based On Cognitive Tutor Interactions (AJ, SF, SR, TN, SRB), pp. 369–370.
- EDM-2014-PeroH #detection #how #programming #question #source code #student
- How patterns in source codes of students can help in detection of their programming skills? (SP, TH), pp. 371–372.
- EDM-2014-Ezen-CanB14a #classification
- A Preliminary Investigation of Learner Characteristics for Unsupervised Dialogue Act Classification (AEC, KEB), pp. 373–374.
- EDM-2014-XiongAH #performance #predict
- Improving Retention Performance Prediction with Prerequisite Skill Features (XX, SA, NTH), pp. 375–376.
- EDM-2014-MavrikisSPZ #adaptation #learning #visualisation
- Indicator Visualization for Adaptive Exploratory Learning Environments (MM, SGS, AP, ZZ), pp. 377–378.
- EDM-2014-VelasquezGMM #learning #online #performance
- Learning Aid Use Patterns and Their Impact on Exam Performance in Online Developmental Mathematics (NFV, IMG, TM, JM), pp. 379–380.
- EDM-2014-PechenizkiyT #education #learning
- Learning to Teach like a Bandit (MP, PAT), pp. 381–382.
- EDM-2014-LynchFA #diagrams
- Matching Hypothesis Text in Diagrams and Essays (CL, MHF, KDA), pp. 383–384.
- EDM-2014-SchattenJMS #adaptation #matrix
- Matrix Factorization Feasibility for Sequencing and Adaptive Support in Intelligent Tutoring Systems (CS, RJ, MM, LST), pp. 385–386.
- EDM-2014-MartinVAMJ #data mining #design #education #mining #research
- Microgenetic Designs for Educational Data Mining Research: Poster (TM, NFV, AA, JM, PJ), pp. 387–388.
- EDM-2014-YeKB #identification #learning #mining #multi #process
- Mining and Identifying Relationships Among Sequential Patterns in Multi-Feature, Hierarchical Learning Activity Data (CY, JSK, GB), pp. 389–390.
- EDM-2014-ValeMA #clustering #education #evolution #mining
- Mining coherent evolution patterns in education through biclustering (AV, SCM, CA), pp. 391–392.
- EDM-2014-SilvaA #mining #modelling #multi #student
- Mining Multi-dimensional Patterns for Student Modelling (AS0, CA), pp. 393–394.
- EDM-2014-PeckhamM #comprehension #education #framework #mining
- Mining Reading Comprehension Within Educational Objective Frameworks (TP, GM), pp. 395–396.
- EDM-2014-SantosMP #collaboration #learning #mining #student
- Mining students' strategies to enable collaborative learning (SGS, MM, AP), pp. 397–398.
- EDM-2014-CadeDGTP #chat #collaboration #interactive #modelling #online #student
- Modeling Student Socioaffective Responses to Group Interactions in a Collaborative Online Chat Environment (WLC, ND, ACG, YRT, JWP), pp. 399–400.
- EDM-2014-AllenSM #development #natural language #power of
- Now We're Talking: Leveraging the Power of Natural Language Processing to Inform ITS Development (LKA, ELS, DSM), pp. 401–402.
- EDM-2014-CiselBB #assessment #behaviour
- Peer assessment in the first French MOOC : Analyzing assessors' behavior (MC, RB, EB), pp. 403–404.
- EDM-2014-YangWR #online
- Peer Influence on Attrition in Massively Open Online Courses (DY, MW, CPR), pp. 405–406.
- EDM-2014-KimPSJ #comparison #learning #linear #online #predict #student #using
- Predicting students' learning achievement by using online learning patterns in blended learning environments: Comparison of two cases on linear and non-linear model (JK, YP, JS, IHJ), pp. 407–408.
- EDM-2014-BeheshtiD #assessment #performance #predict #set
- Predictive performance of prevailing approaches to skills assessment techniques: Insights from real vs. synthetic data sets (BB, MCD), pp. 409–410.
- EDM-2014-GalyardtG #analysis
- Recent-Performance Factors Analysis (AG, IMG), pp. 411–412.
- EDM-2014-AdjeiSHPBK #learning
- Refining Learning Maps with Data Fitting Techniques: Searching for Better Fitting Learning Maps (SA, DS, NTH, ZAP, AB, NK), pp. 413–414.
- EDM-2014-Cordova-Sanchez #education #predict
- Relevancy prediction of micro-blog questions in an educational setting (MCS, PR, LS, JF), pp. 415–416.
- EDM-2014-CarballoA #case study #composition #education #recommendation
- Singular Value Decomposition in Education: a case study on recommending courses (FC, CA), pp. 417–418.
- EDM-2014-Garcia-SaizPZ #education #metric #power of #predict
- The predictive power of the SNA metrics for education (DGS, CP, MEZ), pp. 419–420.
- EDM-2014-MorettiGM14a #data-driven #design #education #mining #web
- Data-Driven Curriculum Design: Mining the Web to Make Better Teaching Decisions (AM, JPGB, KM), pp. 421–422.
- EDM-2014-HernandoGSAN #modelling #problem #student #towards
- Towards IRT-based student modeling from problem solving steps (MH, EG, SAS, EA, SN), pp. 423–424.
- EDM-2014-Feng #towards
- Towards Uncovering the Mysterious World of Math Homework (MF), pp. 425–426.
- EDM-2014-ToussaintLT #automation #behaviour #detection #similarity #towards #using
- Towards Using Similarity Measure for Automatic Detection of Significant Behaviors from Continuous Data (BMT, VL, JT), pp. 427–428.
- EDM-2014-RayBR #data mining #mining #using
- Using Data Mining to Automate ADDIE (FR, KWB, RR), pp. 429–430.
- EDM-2014-WorsleyB #learning #multimodal #using
- Using Multimodal Learning Analytics to Study Learning Mechanisms (MW, PB), pp. 431–432.
- EDM-2014-NiznanPR #detection #problem #using
- Using Problem Solving Times and Expert Opinion to Detect Skills (JN, RP, JR), pp. 433–434.
- EDM-2014-Schneider #collaboration #detection #learning #multimodal #towards
- Toward Collaboration Sensing: Multimodal Detection of the Chameleon Effect in Collaborative Learning Settings (BS), pp. 435–437.
- EDM-2014-Lang #predict #student #using
- The Use of Student Confidence for Prediction & Resolving Individual Student Knowledge Structure (CL), pp. 438–440.
- EDM-2014-Barmaki #communication #education #performance
- Nonverbal Communication and Teaching Performance (RB), pp. 441–443.
- EDM-2014-EagleB14a #data-driven #feedback
- Data-Driven Feedback Beyond Next-Step Hints (ME, TB), pp. 444–446.
- EDM-2014-Aghababyan #education #game studies #named
- E3: Emotions, Engagement and Educational Games (AA), pp. 447–451.
- EDM-2014-Wang #learning #motivation
- MOOC Leaner Motivation and Learning Pattern Discovery (YW), pp. 452–454.
- EDM-2014-Segal #design #personalisation
- Personalization and Incentive Design in E-Learning Systems (AS), pp. 455–457.
