Name
Title | ||
|---|---|---|
A Model for Student Action Prediction in 3D Virtual Environments for Procedural Training. |
Abstract | ||
|---|---|---|
This paper presents a predictive student actionmodel, which uses student logs generated by a 3D virtual environment for procedural training to elaborate summarized information. This model can predict the most common behaviors by con- sidering the sequences of more frequent actions, which is useful to anticipate common student? errors. These logs are clustered based on the number of errors made by each stu- dent and the total time that each student spent to complete the entire practice. Next, for each cluster an extended au- tomata is created, which allows us to generate predictions more reliable to each student type. In turn, the action pre- diction based on this model helps an intelligent tutoring sys- tem to generate students? feedback proactively. |
Year | Venue | Field |
|---|---|---|
2015 | EDM | Virtual machine,Diction,Computer science,Human–computer interaction,Artificial intelligence,Multimedia,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
3 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diego Riofrío-Luzcando | 1 | 0 | 0.34 |
| Jaime Ramírez | 2 | 114 | 16.36 |