In the present study, we examined how the perceived attainability and relatability of moral exemplars predicted moral elevation and pleasantness among both adult and college student participants. Data collected from two experiments were analyzed with Bayesian multilevel modeling to explore which factors significantly predicted outcome variables at…

Preventing panel members from attriting is a fundamental challenge for panel surveys. Research has shown that response behavior in earlier waves (response or nonresponse) is a good predictor of panelists' response behavior in upcoming waves. However, response behavior can be described in greater detail by considering the time until the response is…

The full implementation of MOOCs in online education offers new opportunities for integrating multidisciplinary and comprehensive STEM education. It facilitates the alignment between online learning content and learning behaviors. However, it also presents new challenges, such as a high rate of STEM dropouts. Many learners struggle to establish…

With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…

This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series…

Phishing has become a preferred method among cyber criminals looking to gain access to confidential information. Although most businesses and governmental organizations provide employees with some sort of cyber security training, there is a lack of research examining whether such training methods work to actually reduce susceptibility to…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

Alcohol consumption and related negative consequences continues to be a systemic societal problem. College students are a population that has been identified as particularly high risk for a number of negative consequences as they are more likely to engage in binge drinking and heavy episodic drinking even when compared to same age non-college…

This single explorative case study investigated the causes of churn in the telecommunication industry in Kenya, narrowed down to include only the capital city of Nairobi. The question of this dissertation was split into three sub-questions. The first sub-question investigated the behavioral patterns of customers causing churn. The second…

Purpose: The purpose of this study is to examine the relationship of sustainability knowledge to pro-environmental behaviour. A common misperception is that unsustainable behaviours are largely driven by a lack of knowledge of the underlying societal costs and the contributing factors leading to environmental degradation. Such a perception assumes…

During the semester break, 36 second-grade students accessed a set of resources and completed a series of online math activities focused on the application of the model method for arithmetic in two contexts 1) addition/subtraction and 2) multiplication/division. The learning environment first modeled and then supported the use of a scripted series…

Affect control theory and the stereotype content model share explanatory goals and employ compatible measurement strategies but have developed in largely separate literatures. The present article examines the models' commensurability and discusses new insights that can be gained by comparing theories. We first demonstrate that the unique…