In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…

The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…

This study presents a monocular approach for capturing students' prototyping activities and interactions in digital-fabrication-based makerspaces. The proposed method uses images from a single camera and applies object reidentification, tracking, and depth estimation algorithms to track and uniquely label participants in the space, extracting both…

Aim/Purpose: To encourage students' engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems -- a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their…

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…

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…

Machine learning models were constructed to predict student performance in an introductory mechanics class at a large land-grant university in the United States using data from 2061 students. Students were classified as either being at risk of failing the course (earning a D or F) or not at risk (earning an A, B, or C). The models focused on…

Student success, both during and after college, is central to the mission of higher education. Within the higher-education and, more specifically, the student-success context, the core raison d'être of machine learning (ML) is to help institutions achieve their social mission in an efficient and effective manner. While there should be synergy…

The quality of writing in a second language (L2) is one of the indicators of the level of proficiency for many college students to be eligible for departmental studies. Although certain software programs, such as Intelligent Essay Assessor or IntelliMetric, have been introduced to evaluate second-language writing quality, an overall assessment of…

Accurate placement into an initial college mathematics course is a key step toward the successful completion of college mathematics and, eventually, a college degree. Conversely, misplacement in mathematics may lead to a reduced likelihood of course completion and degree attainment. This study investigated the ability of two placement models to…