ERIC Number: ED615618
Record Type: Non-Journal
Publication Date: 2021
Pages: 10
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
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Available Date: N/A
The Effect of an Intelligent Tutor on Performance on Specific Posttest Problems
Sales, Adam; Prihar, Ethan; Heffernan, Neil; Pane, John F.
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (14th, Online, Jun 29-Jul 2, 2021)
This paper drills deeper into the documented effects of the Cognitive Tutor Algebra I and ASSISTments intelligent tutoring systems by estimating their effects on specific problems. We start by describing a multilevel Rasch-type model that facilitates testing for differences in the effects between problems and precise problem-specific effect estimation without the need for multiple comparisons corrections. We find that the effects of both intelligent tutors vary between problems-- the effects are positive for some, negative for others, and undeterminable for the rest. Next we explore hypotheses explaining why effects might be larger for some problems than for others. In the case of ASSISTments, there is no evidence that problems that are more closely related to students' work in the tutor displayed larger treatment effects. [For the full proceedings, see ED615472.]
Descriptors: Intelligent Tutoring Systems, Academic Achievement, Educational Technology, Algebra, Item Response Theory, Hierarchical Linear Modeling, Program Effectiveness, Pretests Posttests, Achievement Tests, Elementary Secondary Education, Standardized Tests
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: https://educationaldatamining.org/conferences/
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Elementary Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: TerraNova Multiple Assessments
Grant or Contract Numbers: N/A
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