This article aims to clarify the fundamental aspects of aggregating fuzzy scores of conditions with multiple attributes in fuzzy set qualitative comparative analysis (fsQCA). Fuzzy multiple attribute conditions (FMACs) are conditions that are built using different types of concepts. FMACs are flexible conditions that express the ontological nature…

When examinees' test-taking motivation is questionable, practitioners must determine whether careless responding is of practical concern and if so, decide on the best approach to filter such responses. As there has been insufficient research on these topics, the objectives of this study were to: a) evaluate the degree of underestimation in the…

This article presents a new score generation algorithm to compute the accuracy of student concept maps in comparison to teacher maps. The algorithm follows a "compare and remove" method to remove the extra vertices and wrong edges of student concept map with respect to teacher map. A group of 230 students were taken to generate student…

The maximal reliability of a congeneric measure is achieved by weighting item scores to form the optimal linear combination as the total score; it is never lower than the composite reliability of the measure when measurement errors are uncorrelated. The statistical method that renders maximal reliability would also lead to maximal criterion…

Computational thinking (CT) is one of the systematic tools in problem solving and widely accepted as an important skill in the 21st century. This study aimed to identify the effectiveness of the Chemistry Computational Thinking (CT-CHEM) Module on achievement in chemistry. This study also employed a quasi-experimental design with the participation…

Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…

This paper revisits the use of effect sizes in the analysis of experimental and similar results, and reminds readers of the relative advantages of the mean absolute deviation as a measure of variation, as opposed to the more complex standard deviation. The mean absolute deviation is easier to use and understand, and more tolerant of extreme…

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

In this study, we examined the potential impact of item misfit on the reported scores of an admission test from the subpopulation invariance perspective. The target population of the test consisted of 3 major subgroups with different geographic regions. We used the logistic regression function to estimate item parameters of the operational items…

Student growth percentiles (SGPs) express students' current observed scores as percentile ranks in the distribution of scores among students with the same prior-year scores. A common concern about SGPs at the student level, and mean or median SGPs (MGPs) at the aggregate level, is potential bias due to test measurement error (ME). Shang,…

School districts across the United States increasingly use value-added models (VAMs) to evaluate teachers. In practice, VAMs typically rely on lagged test scores from the previous academic year, which necessarily conflate summer with school-year learning and potentially bias estimates of teacher effectiveness. We investigate the practical…

Student growth percentiles (SGPs, Betebenner, 2009) are used to locate a student's current score in a conditional distribution based on the student's past scores. Currently, following Betebenner (2009), quantile regression (QR) is most often used operationally to estimate the SGPs. Alternatively, multidimensional item response theory (MIRT) may…

Math skills are critical for children's future success in school, as school-entry math knowledge is the strongest predictor of later academic achievement. Although there is a recent increase of literature on math with young children, there is a scarcity of research related to young children with disabilities. This quasi-experimental study with 50…

Deep Thought is a logic tutor where students practice constructing deductive logic proofs. Within Deep Thought is a data-driven mastery learning system (DDML), which calculates student proficiency based on rule scores weighted by expert-decided weights in order to assign problem sets of appropriate difficulty. In this study, we designed and tested…

The current study employed a randomized controlled trial to evaluate the use of peer tutoring and fluency-based instruction to increase mathematics fluency with addition and subtraction computation skills. Forty-one elementary school students between the ages of eight and 12 years participated in the 8-week study using cross-age peer tutoring, Say…