Measurement & scaling
Six insights regarding test-taking disengagement
There has been increasing concern about the presence of disengaged test taking in international assessment programs and its implications for the validity of inferences made regarding a countryās level of educational attainment. In this paper, the author discusses six important insights yielded by 20 years of research on this andĀ implications for assessment programs.
By: Steven Wise
MAP Reading Fluency theory of action
The MAP Reading Fluency theory of action shows the hypothesized mechanisms of change and intermediate goals leading to the overarching goal of helping all students read fluently with comprehension.
By: Mary Ann Simpson
Products: MAP Reading Fluency
Topics: Equity, Measurement & scaling
The impact of disengaged test taking on a stateās accountability test results
This study investigated test-taking engagement on a large-scale state summative assessment. Overall, results of this study indicate that disengagement has a material impact on individual state summative test scores, though its impact on score aggregations may be relatively minor.
By: Steven Wise, Jonghwan (Jay) Lee, Sukkeun Im
Topics: Equity, Measurement & scaling, School & test engagement
A method for identifying partial test-taking engagement
This paper describes a method for identifying partial engagement and provides validation evidence to support its use and interpretation. When test events indicate the presence of partial engagement, effort-moderated scores should be interpreted cautiously.
By: Steven Wise, Megan Kuhfeld
Topics: Measurement & scaling, Innovations in reporting & assessment, School & test engagement
A multi-rater latent growth curve model
To avoid the subjectivity of having a single person evaluate a construct of interest (e.g., a studentās self-efficacy in school), multiple raters are often used. This study provides a model for estimating growth in the presence of multiple raters.
By: James Soland, Megan Kuhfeld
Topics: Measurement & scaling, Growth modeling, Social-emotional learning
A semi-supervised learning-based diagnostic classification method using artificial neural networks
This research study is the first time of applying the thinking of semi-supervised learning into CDM. Also, we used the validating test to choose the appropriate parameters for the ANNs instead of using typical statistical criteria, such as AIC, BIC.
By: Kang Xue, Laine Bradshaw
Topics: Measurement & scaling
This report presents the results of a mode comparability study conducted through simulations to evaluate how scores from MAP Growth administered on the constraint-based engine (CBE) compare to those administered on the current MAP Growth engine known as COLO.
By: Ann Hu, Patrick Meyer, May Chien
Products: MAP Growth
Topics: Measurement & scaling, Test design