College student satisfaction and engagement are important indicators of the quality of student learning experiences and outcomes in higher education. Researchers have found student satisfaction to be positively related to student persistence and academic success (Kuh, 2009; Strahan & Credé, 2015). Understanding the level of student…

The developments and changes that have accompanied the COVID-19 pandemic have affected the educational world and all sectors. Educational institutions around the world have implemented emergency and online educational practises to ensure continuity of education as opposed to the planned distance education activities that were implemented for…

Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…

We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…

Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…

Teachers in today's society are having increasing difficulties with Individualized Education Program (IEP) implementation because teachers struggle with assessing data, designing instruction to fit individual needs, providing accommodations, and working as a team with a general education teacher in a co-teaching environment (Cawthon, 2009; Kosko…

This dissertation documents and analyzes phonetic and phonological features of Gua, an under-documented, understudied and nearly-endangered Guang language, spoken in the Eastern Region of Ghana. The language has two dialects, Anum and Boso. The data for this dissertation is from the Boso dialect spoken in the Boso community. The dissertation…

Many core graduate-level seminars claim to expose students to their discipline's "canon." The contents of this canon, however, can and do differ across departments and instructors. This project employs a survey of core American politics PhD seminar syllabi at highly ranked universities to construct a systematic account of the American…

Ontologies are emerging as best representation techniques for knowledge based context domains. The continuing need for interoperation, collaboration and effective information retrieval has lead to the creation of semantic web with the help of tools and reasoners which manages personalized information. The future of semantic web lies in an ontology…

In this article we present a review of literature on the concept of Artefact, Tool and Technical Object in the light of sociocultural approach. Particular attention is given to present and discuss the French research tradition on the Technical Object and Technological education. The aim is to give a broad perspective to explore the mediation…

This commentary will take an historical perspective on the Kaufman Test of Educational Achievement (KTEA) error analysis, discussing where it started, where it is today, and where it may be headed in the future. In addition, the commentary will compare and contrast the KTEA error analysis procedures that are rooted in psychometric methodology and…

Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional…

This study analyzed articles published in four school psychology journals ("Journal of School Psychology," "Psychology in the Schools," "School Psychology Quarterly," and "School Psychology Review") between the years 2009 and 2015. Articles were classified based on whether they were narrative or empirical,…

Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…

Collapsing categories is a commonly used data reduction technique; however, to date there do not exist principled methods to determine whether collapsing categories is appropriate in practice. With ordinal responses under the partial credit model, when collapsing categories, the true model for the collapsed data is no longer a partial credit…