This study addressed a critical gap in the literature by investigating the relationship between organizational culture and mission drift within Christian higher education. While mission drift has been widely discussed in popular press, limited academic research has explored the factors influencing it, particularly organizational culture. Utilizing…

Bullying, particularly among teenagers and young adults, is one of the most important issues facing school communities. At its very heart, this issue speaks to a troubling form of deviant behavior. When students engage in bullying behaviors, the effects are felt far beyond that of the direct victim. As such, it is important to investigate the…

In a very short time, higher education transitioned to online and blended learning, in response to the global COVID-19 pandemic. Although research literature is replete with rationale for instructors to develop digital competence during the Great Online Transition, research on the correlates of digital competence and effort expectancy in relation…

Transfer motivation is an important factor influencing transfer of training. However, earlier research often did not investigate transfer motivation as a multidimensional construct. The unified model of task-specific motivation (UMTM) takes into account that (transfer) motivation is multidimensional by including both affective and cognitive…

The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…

Previous work on indices of error-monitoring strongly supports that errors are distracting and can deplete attentional resources. In this study, we use an ecologically valid multitasking paradigm to test post-error behavior. It was predicted that after failing an initial task, a subject re-presented with that task in conflict with another…

MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to…

Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…

Background: For peer assessment, reliability (i.e., consistency in ratings across peers) and validity (i.e., consistency of peer ratings with instructors or experts) are frequently examined in the research literature to address a central concern of instructors and students. Although the average levels are generally promising, both reliability and…

Past research on knowledge has differentiated between dimensions of knowledge, for example amount or coherence. This dissertation introduces a novel dimension of knowledge, the Motivational Utility of Knowledge (MUK), that is based on hierarchies of human needs (e.g., physical safety, status/esteem, actualization, reproduction). The effects of MUK…

The multifaceted disruption of social and political processes during the most intense phases of the COVID crisis encouraged many groups and individuals to propose change and reform to education. This current report is a distinctive voice in the debate about 'assessment futures'. Not least, it outlines the nature of human construction of the…

Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an…

This dissertation examines the effectiveness of machine learning algorithms and feature engineering techniques for analyzing process data and predicting test performance. The study compares three classification approaches and identifies item-specific process features that are highly predictive of student performance. The findings suggest that…

Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…

We propose new ways of robustifying goodness-of-fit tests for structural equation modeling under non-normality. These test statistics have limit distributions characterized by eigenvalues whose estimates are highly unstable and biased in known directions. To take this into account, we design model-based trend predictions to approximate the…