Mixed methods surveys using multilingual assistants in areas without clear pre-defined sampling units are often difficult to manage and unpredictable, thereby threatening data quality. More so when such surveys are executed in unfamiliar territories where cultural and language barriers prevent direct communication between the principal researcher…

This paper discusses the key findings from a qualitative case study examining the implementation of an activity-based cost management model (ABC model) at a large community college. In a climate of fiscal uncertainty, the college adopted this model with the goal of improving budgetary decision-making. The paper examines faculty and administrators'…

The aim of this paper is to identify and describe the key traits of research with life histories. Previous studies on disability and my own work conducting research with the life histories and university experiences of students with disabilities help to explain how these key characteristics manifest themselves in practice. There are six traits…

Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data…

The authors developed a teaching project for students to debate data and workplace privacy dilemmas, formulate plans of action for the use of certain data about workers and job applicants, and apply the law to reach and defend their solutions. The purpose of this versatile exercise is to sensitize both undergraduate and graduate business students…

In March 2020, the National Center for Special Education Research (NCSER) virtually convened a group of experts to discuss gaps in research on eighth grade mathematics for students with disabilities (SWD) that could be addressed with the NAEP process data and data science techniques for this research. Invited experts also provided recommendations…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…

Purpose: The emergence of social media has provided an alternative mechanism for students to provide and access online reviews about universities. These forms of feedback are often not systematically monitored and interpreted by universities. The purpose of this paper is to analyse quantitative ratings and qualitative comments provided by students…

Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…

The aim of this research is to analyze dissertations on organizational trust conducted from 2000 to 2018 in Turkey comprehensively and from a holistic point of view and reveal similarities and differences between these studies. In the study, descriptive content analysis method was used. The data source of this study was dissertations on…

The Education Insights Center produced a series of reports culminating in recommendations for the structure and governance of a preschool through higher education and into the workforce (known as a P20W data system). This brief follows up on that series, with a focus on data quality; the brief was informed by the author's experience using…

Predicting student success in a data science degree program is a challenging task due to the interdisciplinary nature of the field, the diverse backgrounds of the students, and an incomplete understanding of the precise skills that are most critical to success. In this study, the applicant's future academic performance in a Master of Data Science…

The explosion of Open Educational Resources (OERs) in the recent years creates the demand for scalable, automatic approaches to process and evaluate OERs, with the end goal of identifying and recommending the most suitable educational materials for learners. We focus on building models to find the characteristics and features involved in…

Single subject design (SSD) research is a quantitative approach used to investigate basic and applied research questions. It has been used for decades to examine issues of social importance such as those related to general and special education strategies, therapeutic approaches in mental health, community health practices, safety, and business…