Travelled to:1 × Austria
1 × France
1 × South Korea
1 × USA
Collaborated with:A.Bauer B.Shih R.Scheines H.Cen J.C.Stamper M.Feng J.E.Beck N.T.Heffernan N.Yannier S.E.Hudson P.I.P.Jr. D.Lomas K.Patel J.Forlizzi K.Cunningham A.Skogsholm B.Leber P.I.Pavlik L.Wu R.S.Baker A.T.Corbett A.Z.Wagner B.E.John K.C.Prevas D.D.Salvucci
Talks about:model (5) learn (4) student (3) predict (3) analysi (3) select (3) tutor (3) game (3) use (3) discoveri (2)
Person: Kenneth R. Koedinger
DBLP: Koedinger:Kenneth_R=
Contributed to:
20152013
20102009200820072004
2008Wrote 14 papers:
- CHI-2015-YannierKH #effectiveness #game studies #learning #physics #question #tablet
- Learning from Mixed-Reality Games: Is Shaking a Tablet as Effective as Physical Observation? (NY, KRK, SEH), pp. 1045–1054.
- CHI-2013-LomasPFK #challenge #design #education #game studies #optimisation #scalability #using
- Optimizing challenge in an educational game using large-scale design experiments (DL, KP, JF, KRK), pp. 89–98.
- 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-ShihKS #student
- Unsupervised Discovery of Student Strategies (BS, KRK, RS), pp. 201–210.
- EDM-2009-PavlikCK #analysis #automation #domain model #learning #modelling #using
- Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models (PIPJ, HC, KRK), pp. 121–130.
- EDM-2008-FengBHK #predict #question
- Can an Intelligent Tutoring System Predict Math Proficiency as Well as a Standarized Test? (MF, JEB, NTH, KRK), pp. 107–116.
- EDM-2008-FengHBK #predict #question #student
- Can we predict which groups of questions students will learn from? (MF, NTH, JEB, KRK), pp. 218–225.
- EDM-2008-KoedingerCSL #analysis #fine-grained #repository #tool support
- An Open Repository and analysis tools for fine-grained, longitudinal learner data (KRK, KC, AS, BL), pp. 157–166.
- EDM-2008-PavlikCWK #performance #using
- Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor (PIP, HC, LW, KRK), pp. 77–86.
- EDM-2008-ShihKS
- A Response Time Model For Bottom-Out Hints as Worked Examples (BS, KRK, RS), pp. 117–126.
- CHI-2007-BauerK
- Selection-based note-taking applications (AB, KRK), pp. 981–990.
- CHI-2004-BakerCKW #behaviour #game studies #student
- Off-task behavior in the cognitive tutor classroom: when students “game the system” (RSB, ATC, KRK, AZW), pp. 383–390.
- CHI-2004-JohnPSK #modelling #performance #predict
- Predictive human performance modeling made easy (BEJ, KCP, DDS, KRK), pp. 455–462.
- JCDL-2008-BauerK #design #interface
- Note-taking, selecting, and choice: designing interfaces that encourage smaller selections (AB, KRK), pp. 397–406.