Skills Diagnosis Using IRT-Based Latent Class Models

By Louis A. Roussos, Jonathan Templin, Robert Henson. 2007

96 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Science Applications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/298b4441a37dbcd943fa4749cb9e4301fcfa7d12

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. Ryan Shaun Joazeiro de Baker
2. Michel C. Desmarais
3. Jinhee Kim
4. R. Luckin
5. Mutlu Cukurova
6. Alina von Davier
7. Peter F. Halpin
8. Vincent A. W. M. M. Aleven

In Management Science and Operations Research

1. Ryan Shaun Joazeiro de Baker
2. A. Kim
3. Michel C. Desmarais

Citations in the corpus

• Exploring ways to provide diagnostic feedback with an ESL placement test: Cognitive diagnostic assessment of L2 reading ability (2015, background): “Specifically, the Fusion model is a skill-level item-response model (Roussos et al., 2007), which “expresses the probability of an examinee [j] answering an item i correctly as a function of both the examinee characteristics (skills mastery level profile vector) and item characteristics (item…”
• A review of recent advances in learner and skill modeling in intelligent learning environments (2012, background): “Chaouachi and Frasson (2010) use affect detection based on EEG sensors to study student attention in educational software.”