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…

Learning analytics have proved promising capabilities and opportunities to many aspects of academic research and higher education studies. Data-driven insights can significantly contribute to provide solutions for curbing costs and improving education quality. This paper adopts a two-phase machine learning approach, which utilizes both…

Integrating engineering design into K-12 curricula is increasingly important as engineering has been incorporated into many STEM education standards. However, the ill-structured and open-ended nature of engineering design makes it difficult for an instructor to keep track of the design processes of all students simultaneously and provide…

Community colleges are a major entry point for many students to post-secondary education, particularly for minority, first-generation, low-income, and older students. A range of factors including transfer-readiness, curricular alignment, financial barriers, and transfer guidance, influence successful transfer between two-year colleges (2YCs) and…

Data modeling is an essential part of IT studies. Learning how to design and structure a database is important when storing data in a relational database and is common practice in the IT industry. Most students need much practice and tutoring to master the skill of data modeling and database design. When a student is in a learning process,…

This study explores how Deleuzian concepts of assemblage, affect, and rhizome can inform, and transform, our understanding of how technology shapes second language academic writing. More specifically, it focuses on the practice of L2 academic writing as novice writers compose a source-based research paper in an English for Academic Purposes…