The increasing use of geographic information system (GIS) technology in various fields suggests the need for professionals, including those in Extension, to be mindful of communicating data accurately and effectively. This article examines approaches to creating classes or groupings within data as well as the weaknesses of each approach. Data…

This study aims to determine the overt and covert patterns that teachers' and prospective teachers' views on the use of information and communication technology (ICT) instruments contain by using the method of data mining. The study group was composed of 192 prospective teachers attending a state university in Ankara, Turkey and 101 teachers…

The goal of this study is to identify major research trends and focus in the field of educational research. To this end, 22,000 titles consisting of PhD dissertations, journal papers and conference proceedings were retrieved from the ERIC (Education Resources Information Center - https://eric.ed.gov/?) database in the period from 2009 to 2018. A…

Certain planned-missing designs (e.g., simple-matrix sampling) cause zero covariances between variables not jointly observed, making it impossible to do analyses beyond mean estimations without specialized analyses. We tested a multigroup confirmatory factor analysis (CFA) approach by Cudeck (2000), which obtains a model-estimated…

In "Applied Research for Sustainable Change," Sharon M. Ravitch and Nicole Mittenfelner Carl draw on twenty years of teaching and research to offer an incisive guide to practitioner-led qualitative research. They make the case for "local knowledge generation"--inquiry-based, school-level research that can contextualize…

Institutions of higher education are required by U.S. accrediting bodies to articulate their conceptual framework and develop a viable program improvement plan through a continuous reflective process of progressive problem solving that enables data-driven decision-making practices. To meet or exceed national accreditation standards for leadership,…

This paper describes an innovative approach for teaching the challenges in the management of data warehouse development. The approach contains lecture material providing conceptual background about the management of data warehouse development, a simulation game supporting experiential learning, and a post-play debriefing to support synthesis of…

In the age of big data and analytics, it is important that students learn about artificial intelligence (AI) and machine learning (ML). Machine learning is a discipline that focuses on building a computer system that can improve itself using experience. ML models can be used to detect patterns from data and recommend strategic marketing actions.…

Organizational patterns can serve as a teaching strategy for instructors and as a learning tool for students to develop their expository writing skills, which are commonly required for assignments (for example, laboratory reports and research papers) in Food Science courses and in their future careers. The article discusses the importance of…

Increased value is placed on students having real-world learning experiences. Application classes such as Digital Marketing provide the opportunity for students to achieve this experience. Employers place value with employees having both hard skills and soft skills. To support learning both hard and soft skills, the Enterprise Marketing Variation…

In response pressures on teacher education programs to demonstrate accountability, the concept of teacher professional vision (TPV) was introduced. TPV is used to measure the ability among teachers to detect and interpret relevant events as part of their own professional learning. While the construct has been a reliable indicator of the relevance…

Massive open online courses (MOOCs) provide hundreds of students with teaching materials, assessment tools, and collaborative instruments. The assessment activity, in particular, is demanding in terms of both time and effort; thus, the use of artificial intelligence can be useful to address and reduce the time and effort required. This paper…

For outsiders to higher education institutions (HEIs) in South Korea, predicting the outcomes of the International Education Quality Assurance System (IEQAS)--a Korean institutional accreditation system for HEIs--is challenging. The annual IEQAS accreditation has been conducted behind closed doors; the assessment process is confidential, and there…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

The age of big data drives the need for emerging technologies to enable scalable analytics on massive, rapidly generated, and varied data. It requires "data scientists" with deep knowledge of managing the six Vs of big data: volume, velocity, variety, volatility, veracity, and value. As a result of this trend, new analytical tools are…