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Francis, Mary – ProQuest LLC, 2023
Learning analytics are starting to become standardized in higher education as institutions use the techniques of Big Data analytics to make decisions to help them reach their goals. The widespread use of student information brings forth ethical concerns primarily in relation to privacy. While the overarching ethical issues related to learning…
Descriptors: Learning Analytics, College Students, Privacy, Ethics
Bader Muteb Alsulami; Abdullah Baihan; Ahed Abugabah – Cogent Education, 2024
The COVID-19 pandemic precipitated an abrupt transition to online learning, impacting students with disabilities uniquely. This study examines the experiences of 62 such students in the new educational paradigm, employing a mixed-methods approach. Quantitative data were collected through surveys and questionnaires to assess privacy and security…
Descriptors: Students with Disabilities, Inclusion, Artificial Intelligence, Computer Security
Nadia Ahmad; Hirok Chakraborty; Ratnesh Sinha – Cogent Education, 2024
Background: Artificial Intelligence (AI) has immense potential varying from diagnosing, decision-making in-patient care, and education. To successfully integrate AI into medicine and medical education, it is important to know the outlook and willingness of medical students. This study was done to learn about the medical students opinions about it…
Descriptors: Medical Students, Student Attitudes, Artificial Intelligence, Medical Education
Jones, Kyle M. L.; Goben, Abigail; Perry, Michael R.; Regalado, Mariana; Salo, Dorothea; Asher, Andrew D.; Smale, Maura A.; Briney, Kristin A. – portal: Libraries and the Academy, 2023
Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…
Descriptors: College Students, Student Attitudes, Data Collection, Learning Analytics
Bart Rienties; John Domingue; Subby Duttaroy; Christothea Herodotou; Felipe Tessarolo; Denise Whitelock – Distance Education, 2025
With the release of Generative AI systems such as ChatGPT, an increasing interest in using Artificial Intelligence (AI) has been observed across domains, including higher education. While emerging statistics show the popularity of using AI amongst undergraduate students, little is yet known about students' perceptions regarding AI including…
Descriptors: Distance Education, Student Attitudes, Artificial Intelligence, Technology Uses in Education
Alexander John Karran; Patrick Charland; Joé Trempe-Martineau; Ana Ortiz de Guinea Lopez de Arana; Anne-Marie Lesage; Sylvain Sénécal; Pierre-Majorique Léger – npj Science of Learning, 2025
Recognising a need to investigate the concerns and barriers to the acceptance of artificial intelligence (AI) in education, this study explores the acceptability of different AI applications in education from a multi-stakeholder perspective, including students, teachers, and parents. Acknowledging the transformative potential of AI, it addresses…
Descriptors: Stakeholders, Artificial Intelligence, Technology Uses in Education, Student Attitudes
Greenhalgh, Spencer P.; DiGiacomo, Daniela K.; Barriage, Sarah – Information and Learning Sciences, 2023
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'…
Descriptors: Ethics, Privacy, Learning Management Systems, Learning Analytics
Elma Hajric – ProQuest LLC, 2024
Smart cities surveil through ubiquitous and intrusive data collection via networked sensors. Smart city efforts are also frequently imagined as primarily top-down and male visions of the future in service of economic benefit. The smart campus presents a new dimension of smart city urbanism as an identified gap in literature. In the following…
Descriptors: Research Universities, Campuses, Information Technology, Design
Tal Soffer; Anat Cohen – Australasian Journal of Educational Technology, 2024
The rapid recent use of learning analytics (LA) in higher education, specifically during the COVID-19 pandemic, allows the monitoring of users' behavior while learning. Using LA may promote students' learning outcomes but also intrude into their privacy. This study aimed to explore students' behaviour and perceptions towards privacy and data…
Descriptors: Privacy, Educational Practices, College Students, Student Attitudes
Harris, Lois; Wyatt-Smith, Claire; Adie, Lenore – Teachers and Teaching: Theory and Practice, 2020
Data walls are a data use practice increasingly being adopted in western, Anglophone countries to display student academic achievement data. The purpose of data walls is to improve teaching and learning by helping teachers and/or students to identify patterns of growth and achievement, set goals, and plan instructional interventions or…
Descriptors: Academic Achievement, Data Use, Teaching Methods, Goal Orientation
Renata Mekovec; Marija Kustelega – International Association for Development of the Information Society, 2024
The demand for privacy specialists is expected to increase, but there is a shortage of them to meet market demands. Certain ICT skills and competencies are required for professionals who develop, manage, and protect data that drive the digital world. The current study explores undergraduate students' attitude about different teaching strategies…
Descriptors: Undergraduate Students, Privacy, Specialists, Demand Occupations
West, Deborah; Luzeckyj, Ann; Searle, Bill; Toohey, Danny; Vanderlelie, Jessica; Bell, Kevin R. – Australasian Journal of Educational Technology, 2020
This article reports on a study exploring student perspectives on the collection and use of student data for learning analytics. With data collected via a mixed methods approach from 2,051 students across six Australian universities, it provides critical insights from students as a key stakeholder group. Findings indicate that while students are…
Descriptors: Stakeholders, Undergraduate Students, Graduate Students, Student Attitudes
Robertson, Judy; Tisdall, E. Kay M. – Journal of Media Literacy Education, 2020
Given the importance of data skills to the economy and the skills shortage within data science, educational policy makers have identified the importance of including technical and analytical data skills in the school curriculum. An equally important aim is to educate children and young people to become "data citizens" who are aware of…
Descriptors: Children, Adolescents, Elementary School Students, Secondary School Students
Mubashrah Saddiqa; Kristian Helmer Kjær Larsen; Robert Nedergaard Nielsen; Jens Myrup Pedersen – Journal of Cybersecurity Education, Research and Practice, 2024
Cybersecurity has traditionally been perceived as a highly technical field, centered around hacking, programming, and network defense. However, this article contends that the scope of cybersecurity must transcend its technical confines to embrace a more inclusive approach. By incorporating various concepts such as privacy, data sharing, and…
Descriptors: Labor Force Development, Diversity, Educational Background, Information Security
Ilci, Ahmet – ProQuest LLC, 2020
Privacy and surveillance are pervasive words not only in higher education but also in many areas in our life. We use and hear them often while shopping online, reading the news, or checking the policies and terms of websites. In this study, I highlight the challenges of data collection and surveillance in education, specifically, in online…
Descriptors: Privacy, Information Security, Case Studies, Undergraduate Students