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Jungsun Go – ProQuest LLC, 2023
The purpose of this study was to investigate the effectiveness of four different models (bifactor, CTC(M-1), CTCU and unidimensional) as to optimal model selection when the wording effect associated with negatively worded items was present. A Monte Carlo simulation study was conducted to compare model-data fit and accuracy in parameter estimates…
Descriptors: Language Usage, Negative Attitudes, Models, Goodness of Fit
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Ramlah Mailok; Haslina Hassan; Che Soh Said; Mashitoh Hashim – International Journal on Social and Education Sciences, 2023
Over recent years, the sharing of personal data among students is uncontrolled, especially on the social media networks, resulting in widespread data intrusions that compromise their privacy and confidentiality. Against this backdrop, this study was conducted to identify the level of knowledge of personal data protection among students. This…
Descriptors: Information Security, Knowledge Level, Foreign Countries, Privacy
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Semih Asiret; Seçil Ömür Sünbül – International Journal of Psychology and Educational Studies, 2023
In this study, it was aimed to examine the effect of missing data in different patterns and sizes on test equating methods under the NEAT design for different factors. For this purpose, as part of this study, factors such as sample size, average difficulty level difference between the test forms, difference between the ability distribution,…
Descriptors: Research Problems, Data, Test Items, Equated Scores
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Thomas Nordström; André Kalmendal; Lucija Batinovic – Review of Education, 2023
In order to produce the most reliable syntheses of the effectiveness of educational interventions, systematic reviews need to adhere to rigorous methodological standards. This meta-review investigated risk of bias occurring while conducting a systematic review and the presence of open science practices like data sharing and reproducibility of the…
Descriptors: Bias, Scientific Research, Data Use, Sharing Behavior
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QunBi Lei – International Journal of Web-Based Learning and Teaching Technologies, 2023
Data mining (DM) is an in-depth approach to data analysis by mining useful information from large amounts of data, and this technique is now being used in an increasing number of fields. In this paper, the authors present the design of a real-time data analysis system for sports training based on DM technology and use the corresponding mining…
Descriptors: Data Analysis, Athletics, Training, Information Retrieval
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Araitz Uskola; Nahia Seijas – Research in Science & Technological Education, 2023
Background: Science education should encompass enculturation in science which implies performing scientific practices such as use of data and modelling, in authentic contexts like the field. Purpose: This work aims to determine how preservice elementary teachers (PETs) use data obtained in the field, and how these data contribute to the process of…
Descriptors: Geology, Preservice Teachers, Elementary School Teachers, Science Education
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Giorgio Di Pietro – European Education, 2023
We use Eurobarometer data to examine barriers to international student mobility. Multivariate analysis is employed to study how individual characteristics are related to the obstacles preventing higher education students from participating in activities in another EU country. The results suggest that several demographic factors including area of…
Descriptors: Student Characteristics, Barriers, Student Mobility, Foreign Countries
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Janessa Bower; Selcuk Acar; Ugur Kursuncu – Journal of Advanced Academics, 2023
The demand for a creative workforce has never been higher, yet schools struggle to teach and assess creativity among students efficiently. Compositions are an effective way to incorporate creativity across the curriculum; however, essays are time consuming to evaluate for quality or creativity. This study explored (a) if high creativity scores are…
Descriptors: Creativity, Academic Language, Writing (Composition), Advanced Placement
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Adam Sales; Sooyong Lee; Tiffany Whittaker; Hyeon-Ah Kang – Society for Research on Educational Effectiveness, 2023
Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…
Descriptors: Program Implementation, Data Collection, Randomized Controlled Trials, Program Effectiveness
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Adam Sales; Ethan Prihar; Johann Gagnon-Bartsch; Neil Heffernan – Society for Research on Educational Effectiveness, 2023
Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…
Descriptors: Learning Analytics, Randomized Controlled Trials, Data Use, Accuracy
Susan Bush-Mecenas; Jonathan Schweig; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2023
The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to its devasting effects on students' academic development, the disruptions to schooling had important consequences for researchers conducting effectiveness studies on educational programs during this era. Given the likelihood of future large-scale disruptions, it is…
Descriptors: Research Problems, Educational Research, COVID-19, Pandemics
Baeza Dager, Yahemn – ProQuest LLC, 2023
This study aimed to address the state of data driven decision practices within the Division of Student Affairs at South County College. Framed by an exploratory qualitative case study, this project conducted semi-structured interviews of directors of student affairs and a document analysis of annual reports of the seven departments that constitute…
Descriptors: Student Personnel Services, Decision Making, Data Use, Administrators
Barker, Rick Don – ProQuest LLC, 2023
While some engineering students develop proper critical thinking skills, most engineering students do not. Engineers must critically think to tackle various problems on the job, but many schools do not properly instill critical thinking in engineering students. With engineers working on multiple tasks in little time, a knowledge of critical…
Descriptors: Engineering Education, Data Interpretation, Critical Thinking, Cognitive Processes
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Spry, Amber – Journal of Political Science Education, 2023
Universities are increasingly interested in providing courses that equip students with data science skills and engage experiential learning, particularly in the social sciences. However, these courses can be costly to implement and time-consuming for instructors to develop. This article describes an integrative learning model for teaching…
Descriptors: Social Science Research, Computation, Information Literacy, Data
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Tim Erickson – Australian Mathematics Education Journal, 2023
At the school level statistics begins with exploratory data analysis, or EDA. Statistical learning goes on to include statistical inference, which will be discussed in the second part of this article. In this article, the author will talk about EDA and CODAP. EDA can be thought of as looking for patterns in data using graphs and simple statistics…
Descriptors: Statistics Education, Data Analysis, Mathematical Concepts, Foreign Countries
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