Simulated standardized patients (SPs) are trained individuals who pose incognito as people seeking treatment in a health care setting. With the method's increasing use and popularity, we propose some standards to adapt the method to contextual considerations of feasibility, and we discuss current issues with the SP method and the experience of…

To date, research on mixed-reality simulation (MRS) has focused on various skills including applied behavior analysis, but studies have not evaluated the role of preservice teachers' perceived knowledge, confidence, usefulness, or actual practice related to data collection. To address this gap, we conducted two separate MRS studies, one for…

Businesses and other organizations across the globe are becoming more and more data-driven, using a combination of descriptive, diagnostic, predictive and prescriptive analytics to gain a strategic advantage through understanding the past, what we hope to happen in the future, and the ability to accurately predict future outcomes. These forms of…

This small-scale, qualitative study uses educational design research to explore how focusing on argumentation may contribute to students' learning to engage in inquiry independently. Understanding inquiry as the construction of a scientifically cogent argument in support of a claim may encourage students to develop personal reasons for adhering to…

As part of the cycle for reporting on the implementation of the Scottish Attainment Challenge (SAC), attainment advisors produce reports triannually. This process ensures there is a continuous narrative where next steps are identified and progress made towards them. This summary report is an overview of the analysis of the progress of all 32 local…

Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…

Purpose: The purpose of this paper is to examine how higher education students think about educational technologies they have previously used -- and the implications of this understanding for their awareness of datafication and privacy issues in a postsecondary context. Design/methodology/approach: The authors conducted two surveys about students'…

Digital learning environments are becoming increasingly ubiquitous as a wide range of EdTech products and services enter classrooms and households across the globe. One salient attribute of these environments is their capacity to generate large amounts of data as students interact with the technology. These data logs can help construct a detailed…

College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…

Across the international higher education sector, existing studies highlight that student evaluations of courses and teaching are biased and prejudiced towards academics and can cause mental distress. Yet student evaluation data is often used as part of faculty hiring, firing, promotion, award and grant decisions. That a data source known to be…

Student privacy is a critical area of higher education that deserves greater focus, particularly as student data digitalization increases. Many colleges and universities use data literacy as a way to prepare students, sometimes from different disciplines, to work with others' data postgraduation. Data literacy can be an avenue for helping all…

Thanks to COVID-19, schools were closed and tests were canceled. The result is that we may not see test-taking data typically seen before. For some analyses, sample sizes may not meet the minimum requirement. For others, the sample of test-takers may be different from previous years. In some situation, there may be no data at all. What do we do in…

With the creation of interactive tasks that allow students to explore spatial ways of knowing in conjunction with their other ways of knowing the world, we create a space where students can make sense of information as they organize these new ideas into their already existing schema. Through the use of a Common Online Data Analysis Platform…

The designs of many student-facing learning analytics (SFLA) dashboards are insufficiently informed by educational research and lack rigorous evaluation in authentic learning contexts, including during remote laboratory practical work. In this article, we present and evaluate an SFLA dashboard designed using the principles of formative assessment…

With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…