Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…

This study explored the core competencies, technological skills, functional proficiencies, and professional experiences of data scientists at higher education institutions. The specific population of interest was higher education administrators and staff professionals identified as data scientists. This study was informed by the following guiding…

Purpose: This paper explores the challenges of conducting qualitative research from ELT (English Language Teaching) Ph.D. candidates' perspectives. Design/methodology/approach: The participants of the study consisted of 30 Iranian Ph.D. students majoring in ELT. The semi-structured interview was employed to investigate the heart of experiences,…

In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics' data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the…

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

The calls for accountability in higher education have made outcome-based assessment a key accreditation component. Accreditation remains a well-regarded seal of approval on college quality, and requires the programme to set clear, appropriate, and measurable goals and courses to attain them. Furthermore, programmes must demonstrate that…

The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability to understand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello,…

This paper identifies some of the main challenges of data governance modelling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data…

The purpose of this study is that to evaluate nine educational management plans between the years 1963-2013 and one plan in the process of implementation educational management. Document analysis technique from the qualitative research methods was used in this research. Data was analyzed as three stages: description, analysis and interpretation.…

Phillip Henry is a semi-retired former U.K. Registrar and Secretary with almost 40 years' experience in higher education. He has been active in staff development in the United Kingdom (Association of University Administrators, Academic Registrars Council, and Association of Heads of University Administration), in the United States (AACRAO and a…

This Intersegmental Data Partnerships Resource Guide, and the accompanying PACE policy brief (see ED591080), are products of a year-long qualitative research project exploring promising practices in data sharing and data use among intersegmental partnerships throughout California. This Resource Guide provides institutions engaged in intersegmental…

There is much agreement among chemical education researchers that expertise in chemistry depends in part on the ability to coordinate understanding of phenomena on three levels: macroscopic (observable), sub-microscopic (atoms, molecules, and ions) and symbolic (chemical equations, graphs, etc.). We hypothesize this "level-coordination…

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

Background: Historically, significant advances in scientific understanding have followed advances in measurement and observation. As the resolving power of an instrument increased, so have gains in the understanding of the phenomena being observed. Modern interactive systems are potentially the new "microscopes" when they are…

There are an increasing number of students with learning difficulties attending university, and currently much debate about the suitability and ability of students with dyslexia at both medical school and once they graduate into clinical practice. In this study we describe the performance of students with dyslexia compared to fellow students in…