@inproceedings{7c16d1431d6940a68877ded130431c95,
title = "Using multi-level models to assess data from an intelligent tutoring system",
abstract = "Intelligent tutoring systems yield data with many properties that render it potentially ideal to examine using multi-level models (MLM). Repeated observations with dependencies may be optimally examined using MLM because it can account for deviations from normality. This paper examines the applicability of MLM to data from the intelligent tutoring system Writing-Pal using intraclass correlations. Further analyses were completed to assess the impact of individual differences on daily essay scores along with the differential impact of daily vs. mean attitudinal ratings.",
keywords = "Intelligent tutoring systems, Multi-Level models, Writing",
author = "Weston, {Jennifer L.} and McNamara, {Danielle S.}",
year = "2013",
month = jan,
day = "1",
language = "English (US)",
series = "Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013",
publisher = "International Educational Data Mining Society",
editor = "D'Mello, {Sidney K.} and Calvo, {Rafael A.} and Andrew Olney",
booktitle = "Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013",
note = "6th International Conference on Educational Data Mining, EDM 2013 ; Conference date: 06-07-2013 Through 09-07-2013",
}