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Lee, Sang Eun; Choi, Naya; Kiaer, Jieun – Contemporary Educational Technology, 2023
The study explored the social perceptions of young children's use of smart devices in South Korea using big data methodologies. Big data methodologies allowed to uncover underlying thoughts and feelings about young children's use of smart devices that had not been discovered in existing studies. The study extracted raw data from three different…
Descriptors: Foreign Countries, Social Attitudes, Educational Technology, Technology Uses in Education
Yürüm, Ozan Rasit; Taskaya-Temizel, Tugba; Yildirim, Soner – Education and Information Technologies, 2023
Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…
Descriptors: Video Technology, Educational Technology, Learning Management Systems, Data Collection
Haynes-Brown, Tashane K. – Journal of Mixed Methods Research, 2023
The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the…
Descriptors: Theories, Models, Mixed Methods Research, Teacher Attitudes
Janis, Ilyana – Field Methods, 2022
Dependability (also known as consistency) is one of four criteria in rigor and trustworthiness in qualitative research. In this article, the process of establishing consistency is discussed through the lenses of constructivism and interpretivism, as the observed social reality is viewed as epistemologically counter-intuitive. Two strategies were…
Descriptors: Reliability, Qualitative Research, Case Studies, Data Collection
Feng, Tianying; Chung, Gregory K. W. K. – Grantee Submission, 2022
A critical issue in using fine-grained gameplay data to measure learning processes is the development of indicators and the algorithms used to derive such indicators. Successful development--that is, developing traceable, interpretable, and sensitive-to-learning indicators--requires understanding the underlying theory, how the theory is…
Descriptors: Games, Data Collection, Learning Processes, Measurement
Ivimey-Cook, Edward R.; Noble, Daniel W. A.; Nakagawa, Shinichi; Lajeunesse, Marc J.; Pick, Joel L. – Research Synthesis Methods, 2023
Extracting data from studies is the norm in meta-analyses, enabling researchers to generate effect sizes when raw data are otherwise not available. While there has been a general push for increased reproducibility in meta-analysis, the transparency and reproducibility of the data extraction phase is still lagging behind. Unfortunately, there is…
Descriptors: Replication (Evaluation), Data Collection, Meta Analysis, Computer Software
Education Commission of the States, 2020
Following a high-quality early care and pre-K experience, the kindergarten-through-third-grade years set the foundation upon which future learning builds; and strengthening this continuum creates opportunities for later success. Key components of a quality experience in K-3 include school readiness and transitions, kindergarten requirements,…
Descriptors: State Policy, Educational Policy, Primary Education, Data Use
Snyder, Johnny – Information Systems Education Journal, 2019
Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…
Descriptors: Data Analysis, Error Patterns, Data Collection, Spreadsheets
Hawkins, Christie; Bailey, Lucy E. – New Directions for Institutional Research, 2020
The increasing volume of information and the intense pace of its circulation are changing the ways universities access, use, analyze, and provide data. Many have championed the use of large-scale databases to track student admissions and retention, faculty productivity, student wellness, and other phenomena that shape our understandings of higher…
Descriptors: Institutional Research, Data Analysis, Data Use, Colleges
Travis, Tiffini A.; Ramirez, Christian – portal: Libraries and the Academy, 2020
Libraries remain one of the last places on campus where the purging of usage data is encouraged and "tracking" is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of privacy and debate the feasibility of student-generated library data for planning and assessment. Using a study…
Descriptors: Academic Libraries, Data Collection, Learning Analytics, Ethics
Stelmach, Rachel D.; Fitch, Elizabeth; Chen, Molly; Meekins, Meagan; Flueckiger, Rebecca M.; Colaço, Rajeev – American Journal of Evaluation, 2022
Monitoring, evaluation, and research activities generate important data, but they often fail to change policies or programs. In addition, local program staff and partners often feel disconnected from these activities, which undermines their ownership of data and results. To bridge the gaps between monitoring, evaluation, and research and to give…
Descriptors: Evidence Based Practice, Evaluation, Research, Global Approach
Silva, Meghan R.; Collier-Meek, Melissa A.; Codding, Robin S.; Kleinert, Whitney L.; Feinberg, Adam – Contemporary School Psychology, 2021
Response-to-intervention (RtI) is a multi-tiered framework designed to prevent academic difficulties by facilitating robust, research-based instruction and providing targeted or individualized short-term interventions for students at-risk per periodic screening and progress monitoring data. The cornerstone of RtI is data-based decision-making to…
Descriptors: Data Collection, Data Analysis, Response to Intervention, Decision Making
Liu, Min; Pan, Zilong; Li, Chenglu; Han, Songhee; Shi, Yi; Pan, Xin – International Journal on E-Learning, 2021
There has been an increasing interest in learning analytics (LA) research especially in higher education (HE) in recent years. In this study, we conducted a systematic focused review of research, from 2016 to present, on using analytics in HE (specifically system- or user-generated data) to understand in what way such analytics has been…
Descriptors: Learning Analytics, Educational Research, Higher Education, Data Collection
Odegard, Nina – Contemporary Issues in Early Childhood, 2021
This article draws on a new materialist paradigm to explore bricolaging data from an early childhood research project through an immanent ethical lens. This lens enables the researcher to stretch towards non-hierarchical relationships in between subjects and objects, thinking and doing. A bricoleur explores and builds different…
Descriptors: Data Collection, Early Childhood Education, Ethics, Educational Research
Nkomo, Larian M.; Nat, Muesser – TechTrends: Linking Research and Practice to Improve Learning, 2021
With various digital technologies increasingly integrated into higher education, understanding how students engage with such technologies has become vital. There are different ways to measure student engagement; however, self-reported measures such as questionnaires are predominantly used to understand student engagement. In contrast, this study…
Descriptors: Learner Engagement, Blended Learning, Educational Environment, Data Collection

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