In this dissertation, I establish a research program that uses computational modeling as a testbed for theories of phonological learning. This dissertation focuses on a fundamental question: how do children acquire sound patterns from noisy, real-world data, especially in the presence of lexical exceptions that defy regular patterns? For instance,…

Given the current rapid development of informatization, people will increasingly use online teaching methods to learn for their quality improvement. Starting from the fundamental theories, such as the concept, classification, basic process, task, and method of data mining under the background of Internet Plus, this article analyzes the problems…

The author of this article provides an example of how one might incorporate behavioral economics into teaching macroeconomics or labor economics at an undergraduate level. The focus is on two macroeconomic concepts--wage determination and the Phillips curve--and shows that the implications and conclusions of both models differ from their textbook…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…

Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…

Colleges face growing pressures to maintain or enhance the quality of what they offer while being challenged to meet the needs of an increasingly diverse range of students. Staff in higher education face the challenge of supporting students to feel they belong and are valued. The co-creation of teaching and learning is one model in which we may be…

Using data from multiple informants has long been considered best practice in education. However, multiple informants often disagree on similar constructs, complicating decision-making. Polynomial regression and response-surface analysis (PRA) is often used to test the congruence effect between multiple informants on an outcome. However, PRA…

This study investigates the relationship between first-year higher education students' (N = 405) approaches to learning and academic performance on engineering mathematics courses. In addition, we study what combinations of approaches to learning students apply, how these combinations change over time, and whether they are linked to the…

This study delves into the transformative impact of a professional development model (PDM) across three affiliated private schools in Beirut, Lebanon, spanning three years, with a primary focus on nurturing teacher leadership. At the heart of this PDM, teachers assumed the role of trainers, guiding their colleagues during dedicated professional…

Purpose: Mathematical literacy and mathematical problem-solving are crucial abilities that link mathematics content to real life applications, facilitating both mathematics understanding and mathematical processes. The present study aimed to investigate the effectiveness of the STEMEN (STEM and educational neuroscience) teaching model in enhancing…

Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for…

Background: The landscape of education is increasingly recognizing the impactful role of Career and Technical Education (CTE) programs in preparing students for the workforce. In Delaware, the implementation of CTE programs has been substantial, offering students opportunities to earn college credits, attain industry certifications, and gain…

Graph Signal Processing (GSP) plays a crucial role in addressing the growing need for information processing across networks, especially in tasks like supervised classification. However, the success of GSP in such tasks hinges on accurately identifying the underlying relational structures, which are often not readily available and must be inferred…

Narratives have a unique capacity to hold attention, challenge assumptions, and create transformative experiences. In this paper, I will draw upon narrative homiletics to show how educators who teach theology or scriptural texts can create learning experiences that follow narrative structure. First, I will discuss the advantages of teaching in a…

Constructivist learning theories have emphasized learners' interactions with the environment, which includes their peers. Therefore, student cooperation/collaboration has been considered crucial in science education. However, although there have been many science cooperative/collaborative learning (CCL) studies reported in Korea, there has been a…