It is meaningful to create a comprehensive score to extract information from mass continuous data when they measure the same latent concept. Therefore, this study adopts the logic of psychometrics to conduct scales on continuous data under the Rasch models. This study also explores the effect of different data discretization methods on scale…

Purpose: The main objective of the paper is to develop an investment model using data envelopment analysis (DEA) that provides a decision-making framework to allocate resources efficiently, such that the relative efficiency is improved within an available investment budget. Design/methodology/approach: Firstly, DEA models are used to evaluate the…

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…

Data-based decision-making has been a frequently used policy and practice intervention used in schools to help inform the decision-making processes of educational practitioners, with the aim of improving student outcomes. Interim benchmark assessments are designed by commercial test developers to support educators in this framework. In fact, the…

It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…

Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…

Historically, there has been concern about students losing reading ability over extended breaks from school, commonly in the summer, but studies of this phenomenon have produced inconsistent results. We applied exploratory visual analysis of multiple datasets to examine whether students in Grades K-5 appear to lose or improve in various reading…

The Minnesota K-12 Academic Standards in Mathematics represent the work of the Mathematics Standards Review Committee who, during the 2021-22 school year, reviewed the 2007 Minnesota K-12 Academic Standards in Mathematics, other states' recently revised standards, current academic research, K-12 instructional best practices and public feedback.…

This study aims to conduct differential item functioning analyses in the context of cognitive diagnosis assessments using various formulations of the Wald test. In implementing the Wald test, two scenarios are considered: one where the underlying reduced model can be assumed; and another where a saturated CDM is used. Illustration of the different…

State education departments find themselves pressured to reduce costs while improving student performance. To do so, state education departments must measure the performance of each school district in an objective, data-informed manner. We present a benchmarking methodology and illustrate its application in New York State school districts. We…

Measurement systems give colleges a structure for collecting, sharing, and acting on data. The guidebook and tools presented here help faculty, staff, college leadership, and policymakers understand and use measurement systems--and specifically use data to improve completion rates, close institutional performance gaps, and facilitate economic…

In the domain of programming, a growing number of algorithms automatically generate data-driven, next-step hints that suggest how students should edit their code to resolve errors and make progress. While these hints have the potential to improve learning if done well, few evaluations have directly assessed or compared the quality of different…

Retaining students through degree completion is a challenge for community colleges, with nontraditional, adult students being retained at a lower rate than their traditional counterparts. Though student engagement is recognized as an effective strategy for retaining students, there is a gap in research on how effective these strategies are for…

The paper critiques key international teaching excellence and higher education outcomes frameworks for their lack of attention to epistemic equality. It subsequently argues that adequate 'datafication' of these frameworks, to demonstrate the extent to which universities offer teaching experiences which promote intellectual equivalence of all…

It is important for policymakers and managers of higher education institutions knowing how well their universities are operating. This article aimed to show that data envelopment analysis (DEA) can be an excellent benchmarking instrument in higher education. First, by using several inputs and outputs at the institutional level, DEA can identify…