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Collaborated with:
J.E.Beck M.Feng Z.A.Pardos Y.Gong J.Beck K.R.Koedinger A.B.Goldstein R.S.J.d.Baker Y.Wang D.Rai C.Ruiz
Talks about:
learn (6) student (4) can (4) test (3) question (2) knowledg (2) predict (2) paramet (2) system (2) random (2)

Person: Neil T. Heffernan

DBLP DBLP: Heffernan:Neil_T=

Contributed to:

EDM 20102010
EDM 20092009
EDM 20082008

Wrote 11 papers:

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-GoldsteinBH #learning
Pinpointing Learning Moments; A finer grain P(J) model (ABG, RSJdB, NTH), pp. 289–290.
EDM-2010-GongBH #multi #parametricity #using
Using multiple Dirichlet distributions to improve parameter plausibility (YG, JEB, NTH), pp. 61–70.
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-WangHB #performance #representation #student
Representing Student Performance with Partial Credit (YW, NTH, JEB), pp. 335–336.
EDM-2009-FengBH #composition #education #learning #using
Using Learning Decomposition and Bootstrapping with Randomization to Compare the Impact of Different Educational Interventions on Learning (MF, JB, NTH), pp. 51–60.
EDM-2009-GongRBH #learning #question #self #student
Does Self-Discipline impact students’ knowledge and learning? (YG, DR, JB, NTH), pp. 61–70.
EDM-2009-PardosH #order #problem #random #set
Determining the Significance of Item Order In Randomized Problem Sets (ZAP, NTH), pp. 111–120.
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-PardosHRB #analysis #composition #multi
The Composition Effect: Conjuntive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS (ZAP, NTH, CR, JEB), pp. 147–156.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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