|
Title:
|
A IN-DEEP BEHAVIORAL MODEL FOR E-LEARNING ASSESSMENT |
|
Author(s):
|
Stefania Mignani , Claudio Sartori |
|
ISBN:
|
978-972-8924-83-6 |
|
Editors:
|
Miguel Baptista Nunes and Maggie McPherson (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
|
Year:
|
2009 |
|
Edition:
|
V II, 2 |
|
Keywords:
|
e-learning, assessment, user, behavior, item response theory |
|
Type:
|
Short Paper |
|
First Page:
|
160 |
|
Last Page:
|
164 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
E-learning platforms often include assessment tools to measure the outcomes of the learning process. Such tools can be
used both for self-evaluation, while the learning activity is in progress, and for external final evaluation, e.g. to
automatically measure the learning outcomes, ensuring standard evaluation criteria. Assessment is also available during
the learning process, for self-evaluation purpose: in this case the student gets some kind of measurement about his
knowledge/skills, based on the answers, and hints on the effectiveness of the learning process. Our claim is that
computer-based assessment systems can provide a large amount of information, beyond the simple answers, e.g. the time
spent on each question and the changes of mind, that hide a deeper insight on students. This preliminary paper introduces
a new behavioral student model, based on this concept, discusses some of the techniques useful to analyse these kinds of
data and sketches an architecture able to support this analysis. |
|
|
|
|
|
|
