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Leo Van Audenhove; Lotte Vermeire; Wendy Van den Broeck; Andy Demeulenaere – Information and Learning Sciences, 2024
Purpose: The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as…
Descriptors: Data Analysis, Data Collection, Information Literacy, Foreign Countries
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Atkinson, Joshua D.; Dorr, Matthew; Pedasanaganti, Vamsi; Sharma, Shudipta – Journal of Ethnographic & Qualitative Research, 2023
The framework of cyber-archaeology was developed by Jones (1997, 2003) and later modified by Zimbra et al. (2010) to examine online networks and virtual communities. Since the modification, the method has fallen out of favor and is no longer utilized by qualitative researchers. To rebuild the method for qualitative research, we engaged in four…
Descriptors: Qualitative Research, Interdisciplinary Approach, Archaeology, Computer Science
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Yun Du – International Journal of Web-Based Learning and Teaching Technologies, 2024
This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…
Descriptors: Educational Innovation, Preschool Education, Data Analysis, Data Collection
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Mohammed, Abdul Hanan Khan; Jebamikyous, Hrag-Harout; Nawara, Dina; Kashef, Rasha – Journal of Computing in Higher Education, 2021
Data Analytics has become an essential part of the Internet of Things (IoT), mainly text analytics-related applications, since they can be utilized to benefit educational institutions, consumers, and enterprises. Text Analytics is excessively used in Smart Education after the emerging technologies such as personal computers, tablets, and even…
Descriptors: Internet, Equipment, Data Analysis, Electronic Learning
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Xie, Charles; Li, Chenglu; Ding, Xiaotong; Jiang, Rundong; Sung, Shannon – Journal of Chemical Education, 2021
Digital sensors allow people to collect a large quantity of data in chemistry experiments. Using infrared thermography as an example, we show that this kind of data, in conjunction with videos that stream the chemical phenomena under observation from a vantage point, can be used to construct digital twins of experiments to support science…
Descriptors: Chemistry, Video Technology, Technology Integration, Laboratory Experiments
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Firat, Mehmet; Altinpulluk, Hakan; Kilinç, Hakan – Asian Association of Open Universities Journal, 2021
Purpose: This study aims to investigate the preferences of 96 educational researchers on the use of digital technologies in scientific research. Design/methodology/approach: The study was designed as a quantitative-dominant sequential explanatory mixed-method research. Findings: Despite the spreading use of advanced technologies of big data and…
Descriptors: Educational Researchers, Preferences, Scientific Research, Technology Uses in Education
Z. W. Taylor; Joshua Childs – Sage Research Methods Cases, 2022
This case study explains how to gather web metrics to measure the size, investment, and popularity of K-12 school system and higher education websites. This case study will first explain and define web metrics in detail, such as keywords, traffic, search engine optimization, and other terminology crucial for educational researchers to understand…
Descriptors: Search Engines, Evaluation, Web Sites, Educational Researchers
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Charles Melvin Ess; Ylva Hård af Segerstad – New Perspectives on Learning and Instruction, 2019
We briefly review the emergence of internet research ethics (IRE) since 2000 across three stages, showing how the last, IRE 3.0, focuses on ethical challenges and issues evoked by Big Data. We explore specific examples of IRE 3.0 as occasioned by requirements for informed consent -- including Big Data analyses of a closed Facebook group -- as…
Descriptors: Ethics, Barriers, Internet, Research Methodology
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Kwet, Michael; Prinsloo, Paul – Teaching in Higher Education, 2020
This article examines developments in the 'smart classroom' as a new frontier for the university. It provides a conceptual map of the scope and limitations of smart classrooms, contextualized to smart university initiatives. First, it introduces the notion of 'smart' technology in cities, campuses, and classrooms. Next, it examines how the smart…
Descriptors: Educational Technology, Classroom Environment, Educational Equipment, College Environment
National Forum on Education Statistics, 2022
Digital inequity has been a long-standing issue in the education community. A lack of home internet and technology devices can not only hinder students' ability to access educational resources at home, but can also have a detrimental effect on student achievement. Education agencies have taken steps over the past decades to address digital…
Descriptors: Access to Computers, Technology Uses in Education, Educational Technology, Internet
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Winne, Philip H.; Nesbit, John C.; Popowich, Fred – Technology, Knowledge and Learning, 2017
A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules…
Descriptors: Data Collection, Research Methodology, Learning Processes, Computer Software
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Chambers, Silvana; Nimon, Kim; Anthony-McMann, Paula – International Journal of Adult Vocational Education and Technology, 2016
This paper presents best practices for conducting survey research using Amazon Mechanical Turk (MTurk). Readers will learn the benefits, limitations, and trade-offs of using MTurk as compared to other recruitment services, including SurveyMonkey and Qualtrics. A synthesis of survey design guidelines along with a sample survey are presented to help…
Descriptors: Surveys, Research, Best Practices, Research Problems
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Quartiroli, Alessandro; Knight, Sharon M.; Etzel, Edward F.; Monaghan, Molly – International Journal of Social Research Methodology, 2017
The usefulness of the online Skype system for qualitative data collection has been well documented, but its application in qualitative data analysis has been largely ignored. This article provides insight into the use of Skype in the context of interdisciplinary team research, with a focus on the analytical phase of a qualitative investigation.…
Descriptors: Computer Mediated Communication, Video Technology, Teamwork, Qualitative Research
Konstantinos Pouliakas – Cedefop - European Centre for the Development of Vocational Training, 2021
The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…
Descriptors: Job Skills, Information Technology, Artificial Intelligence, Employment Qualifications
Barnett, William; Corn, Mike; Hillegas, Curt; Wada, Kent – EDUCAUSE, 2015
This paper is part of series of the EDUCAUSE Center for Analysis and Research Campus Cyberinfrastructure (ECAR-CCI) Working Group. The topic of big data continues to receive a great deal of publicity because of its promise for opening new avenues of scholarly discovery and commercial opportunity. The ability to sift rapidly through massive amounts…
Descriptors: Higher Education, Data Collection, Data Analysis, Information Management
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