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Education Scotland, 2023
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…
Descriptors: Achievement Gap, Poverty, Outcomes of Education, Educational Improvement
Nayak, Padmalaya; Vaheed, Sk.; Gupta, Surbhi; Mohan, Neeraj – Education and Information Technologies, 2023
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.…
Descriptors: Predictor Variables, Academic Achievement, Data Collection, Information Retrieval
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
Karen Dan Wang – ProQuest LLC, 2023
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…
Descriptors: Educational Technology, Electronic Learning, Data Collection, Problem Solving
Educational Data Mining: An Application of a Predictive Model of Online Student Enrollment Decisions
Cody Gene Singer – ProQuest LLC, 2023
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…
Descriptors: Data Collection, Predictor Variables, Electronic Learning, Enrollment
Heffernan, Troy; Harpur, Paul – Assessment & Evaluation in Higher Education, 2023
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…
Descriptors: Student Evaluation of Teacher Performance, Bias, School Policy, Universities
Blackmon, Stephanie J. – Change: The Magazine of Higher Learning, 2023
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…
Descriptors: Privacy, Data Collection, Data Use, Higher Education
Mojgan Rashtchi; SeyyedeFateme Ghazi Mir Saeed – Sage Research Methods Cases, 2023
The reason for conducting the present case study was the problems the researchers encountered during data collection for another research project (Primary Study) entitled "The effects of virtual versus traditional flipped classes on EFL learners' grammar knowledge, self-regulation, and autonomy." Two online questionnaires were…
Descriptors: Data Collection, Questionnaires, Barriers, Research Methodology
Cui, Zhongmin – Educational Measurement: Issues and Practice, 2020
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…
Descriptors: Testing, Sample Size, Data Collection, COVID-19
Poling, Lisa; Weiland, Travis – Teaching Statistics: An International Journal for Teachers, 2020
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…
Descriptors: Data Analysis, Data Collection, Spatial Ability, Statistics
David P. Reid; Timothy D. Drysdale – IEEE Transactions on Learning Technologies, 2024
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…
Descriptors: Learning Analytics, Laboratory Experiments, Electronic Learning, Feedback (Response)
Leif Sundberg; Jonny Holmström – Journal of Information Systems Education, 2024
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…
Descriptors: Artificial Intelligence, Conventional Instruction, Data Collection, Models
Yoolim Kim; Vita V. Kogan; Cong Zhang – Applied Linguistics, 2024
Gamification of behavioral experiments has been applied successfully to research in a number of disciplines, including linguistics. We believe that these methods have been underutilized in applied linguistics, in particular second-language acquisition research. The incorporation of games and gaming elements (gamification) in behavioral experiments…
Descriptors: Gamification, Game Based Learning, Data Collection, Citizen Participation
Anais Roque; Amber Wutich; Alexandra Brewis; Melissa Beresford; Laura Landes; Olga Morales-Pate; Ramon Lucero; Wendy Jepson; Yushiou Tsai; Michael Hanemann – Field Methods, 2024
Community-based participant-observation purposefully combines participant-observation and community-based participatory research. While participant-observation is the core method of ethnography and foundational to cultural anthropology, community-based participatory research initially emerged from health and related applied sciences to align…
Descriptors: Participant Observation, Participatory Research, Ethnography, Communities of Practice
Emma Heywood; Beatrice Ivey; Sacha Meuter – International Journal of Social Research Methodology, 2024
This article provides an original and timely contribution to current cutting-edge methodological debates by discussing the ongoing need to ensure communities in zones which are inaccessible through war, conflict or disease still have a voice and are not side-lined. As seen during COVID-19, traditional methods of gaining opinions from these…
Descriptors: Foreign Countries, Access to Information, Computer Mediated Communication, Communication (Thought Transfer)