The question of integrating learning content into a serious game is a recurring one, although no clear theoretical framework has yet been provided. It is often argued that integration should occur at the core mechanic level, but this simple statement conceals the complexity of serious game design. The authors therefore propose a theoretical…

Effective communication skills are essential for success in both academic and professional contexts. This concept paper presents a novel framework designed to operationally define and support the development of assessments of communication skills with a specific emphasis on K-12 settings. Through discussions on important considerations for the…

Regression discontinuity (RD) designs are increasingly used for causal evaluations. However, the literature contains little guidance for conducting a moderation analysis within an RDD context. The current article focuses on moderation with a single binary variable. A simulation study compares: (1) different bandwidth selectors and (2) local…

Many large-scale assessments model proficiency with a latent regression on contextual variables. Item-response data are used to estimate the parameters of the latent variable model and are used in conjunction with the contextual data to generate plausible values of individuals' proficiency attributes. These models typically incorporate numerous…

This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…

Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…

In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…

This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…

The rapid development of higher education in China has significantly advanced physical education within universities, contributing to students' comprehensive development and national health improvement. However, the expansion of university enrollment has introduced challenges such as a decrease in per capita sports resources and declines in…

Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…

This paper begins by establishing the A+ Inquiry model as a theoretical lens for assessing needs related to program assessment workload by demonstrating its alignment with elements of five published frameworks associated with higher education assessment. Then, it uses the model as a frame of reference to explore faculty needs related to program…

Multimodal learning analysis emphasizes using diverse data from various sources and forms for precise examination of learning patterns. Despite recent rapid advancements in this field, conventional learning analysis remains predominantly cross-sectional and group-focused, which is insufficient for understanding continuous and personalized learning…

False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error…

Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper…