The main objective of this dissertation was to investigate factors that affect decision-makers' trust in and reliance on algorithmic predictions as decision aids in the context of college admission prediction tasks. College admission officers often made predictions about the applicants' future success based on multiple pieces of available…

Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…

The Content Proximity Project was designed to improve the content validity of the MAP® Growth™ assessments while retaining the ability for the test to adapt off-grade and meet students wherever they are in their learning. Two main features of the project were the development of an enhanced item selection algorithm, and a spring pilot study…

Despite the increasing ethnic diversity of England's school-age population, academic literature on ethnic school segregation remains small, dated and hindered by methodological challenges. This study seeks to address these issues by measuring ethnic school segregation between 2006-2019 using two methodological innovations. Firstly, it is the first…

Predicting student performance is crucial in higher education, as it facilitates course selection and the development of appropriate future study plans. The process of supporting the instructors and supervisors in monitoring students in order to upkeep them and combine training programs to get the best outcomes. It decreases the official warning…

The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…

Computer science (CS) has become a critical part of K-12 education worldwide. Computational thinking (CT) skills are a key set of competencies in CS education that can solve problems and use computational design to create useful solutions. However, preservice and in-service teachers are not fully prepared to integrate CS and CT into their…

This study explored the effectiveness of scaffolding in students' reflection writing process. We compared two sections of an introductory computer programming course (N=188). In Section 1, students did not receive any scaffolding while generating reflections, whereas in Section 2, students were scaffolded during the reflection writing process.…

Background/purpose: The Computational Thinking ability has become a fundamental skill in the 21st century and has been integrated into educational curricula in various countries. For this curricular integration to be effective, it is essential that teachers are prepared to incorporate the development of this competency into their practices. In…

Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…

The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…

Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available; however, being…

In the context of our rapidly digitizing society, computational thinking stands out as an essential attribute for cultivating aptitude and expertise. Through the prism of computational thinking, learners are more adeptly positioned to dissect and navigate real-world challenges, poising them effectively to meet the exigencies of future societal…

BRIDGES is a software framework for creating engaging assignments for required courses such as data structures and algorithms. It provides students with a simplified API that populates their own data structure implementations with live and real-world data, and provides the ability for students to easily visualize the data structures they create as…

Natural language processing (NLP) has captivated the attention of educational researchers over the past three decades. In this study, a total of 2,480 studies were retrieved through a comprehensive literature search. We used neural topic modeling and pre-trained language modeling to explore the research topics pertaining to the application of NLP…