Equating words-correct-per-minute (WCPM) scores across passages of MAP Reading Fluency
NWEA equated words-correct-per-minute (WCPM) scores from oral reading passages included in the NWEA MAP Reading Fluency assessment. Equipercentile equating with loglinear presmoothing was applied to convert raw WCPM scores from a non-reference passage to those from a reference passage. The goals of this study were to (1) develop a method to choose a reference passage and passage pairs for equating WCPM scores from a large number of passages and (2) determine if equated WCPM scores provide a more accurate indication of students’ oral reading fluency ability compared to the raw WCPM scores from passages that vary in difficulty.See More
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 country’s level of educational attainment. In this paper, the author discusses six important insights yielded by 20 years of research on this and implications for assessment programs.
By: Steven Wise
This technical report documents the processes and procedures employed by NWEA to build and support the MAP Reading Fluency assessment.
Products: MAP Reading Fluency
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.
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.
To avoid the subjectivity of having a single person evaluate a construct of interest, multiple raters are often used. While a range of models to address measurement issues that arise when using multiple raters have been presented, few are available to estimate growth in the presence of multiple raters. This study provides a model that removes all but the shared perceptions of raters at a given timepoint then adds on a latent growth curve model across timepoints. Results indicate that the model shows promise for use by researchers who want to estimate growth based on longitudinal multi-rater data.
To avoid the subjectivity of having a single person evaluate a construct of interest (e.g., a student’s self-efficacy in school), multiple raters are often used. This study provides a model for estimating growth in the presence of multiple raters.
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