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Henshaw, Alexis Leanna; Meinke, Scott R. – Journal of Political Science Education, 2018
While data analysis and the related skills of data management and data visualization are important skills for undergraduates in the field of political science, the process of learning these skills can also be used to develop critical thinking, encourage active and collaborative learning, and to apply knowledge gained in the classroom. Drawing on…
Descriptors: Undergraduate Students, Data Analysis, Visualization, Active Learning
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Schumacher, Clara; Ifenthaler, Dirk – Journal of Computing in Higher Education, 2018
Depending on their motivational dispositions, students choose different learning strategies and vary in their persistence in reaching learning outcomes. As learning is more and more facilitated through technology, analytics approaches allow learning processes and environments to be analyzed and optimized. However, research on motivation and…
Descriptors: Student Motivation, Learning Strategies, Goal Orientation, Self Concept
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English, Lyn D.; Watson, Jane – ZDM: The International Journal on Mathematics Education, 2018
This article explores 6th-grade students' modelling with data in generating models for selecting an Australian swimming team for the (then) forthcoming 2016 Olympics, using data on swimmers' times at various previous events. We propose a modelling framework comprising four components: working in shared problem spaces between mathematics and…
Descriptors: Foreign Countries, Mathematical Models, Data Analysis, Elementary School Students
Golden, Cindy – Brookes Publishing Company, 2018
Collecting data on behavior, academic skills, and Individualized Education Plan (IEP) goals is an essential step in showing student progress--but it can also be a complicated, time-consuming process. Take the worry and stress out of data collection with this ultra-practical resource, packed with the tools you need to organize, manage, and monitor…
Descriptors: Data Collection, Information Management, Student Records, Student Behavior
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Sen, Ayon; Patel, Purav; Rau, Martina A.; Mason, Blake; Nowak, Robert; Rogers, Timothy T.; Zhu, Xiaojin – International Educational Data Mining Society, 2018
In STEM domains, students are expected to acquire domain knowledge from visual representations that they may not yet be able to interpret. Such learning requires perceptual fluency: the ability to intuitively and rapidly see which concepts visuals show and to translate among multiple visuals. Instructional problems that engage students in…
Descriptors: Visual Aids, Visual Perception, Data Analysis, Artificial Intelligence
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Reilly, Joseph M.; Ravenell, Milan; Schneider, Bertrand – International Educational Data Mining Society, 2018
In this paper, we describe the analysis of multimodal data collected on small collaborative learning groups. In a previous study, we asked pairs (N=84) with no programming experience to program a robot to solve a series of mazes. The quality of the dyad's collaboration was evaluated, and two interventions were implemented to support collaborative…
Descriptors: Cooperative Learning, Programming, Nonverbal Communication, Motion
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Durand, Guillaume; Goutte, Cyril; Léger, Serge – International Educational Data Mining Society, 2018
Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…
Descriptors: Error of Measurement, Models, Goodness of Fit, Predictive Validity
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Enders, Craig K.; Keller, Brian T.; Levy, Roy – Grantee Submission, 2018
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…
Descriptors: Hierarchical Linear Modeling, Behavioral Science Research, Computer Software, Bayesian Statistics
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Eacott, Scott – Journal of Educational Administration, 2023
Purpose: Education is a key institution of modern society, long recognized for its central role in the reproduction of inequities and with the potential to challenge them. Schools behave as their systems are designed. Achieving equity and excellence is not possible through attempts to fix "the school" or educators. Principles of systemic…
Descriptors: Equal Education, Educational Quality, Instructional Design, Outcomes of Education
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Mason, Claire M.; Chen, Haohui; Evans, David; Walker, Gavin – International Journal of Information and Learning Technology, 2023
Purpose: This paper aims to demonstrate how skills taxonomies can be used in combination with machine learning to integrate diverse online datasets and reveal skills gaps. The purpose of this study is then to show how the skills gaps revealed by the integrated datasets can be used to achieve better labour market alignment, keep educational…
Descriptors: Taxonomy, Artificial Intelligence, Data Collection, Data Analysis
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Ipek, Ziyaeddin Halid; Gözüm, Ali Ibrahim Can; Papadakis, Stamatios; Kallogiannakis, Michail – Educational Process: International Journal, 2023
Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Educational Benefits
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Rammstedt, Beatrice; Martin, Silke; Zabal, Anouk; Carstensen, Claus; Schupp, Jürgen – Large-scale Assessments in Education, 2017
In Germany, the respondents who had participated in the 2012 survey of the Programme for the International Assessment of Adult Competencies (PIAAC) were re-approached for the panel study PIAAC-L. PIAAC-L aims at investigating the longitudinal effects of skill outcomes over the life course and the development of the key skills assessed in PIAAC.…
Descriptors: Foreign Countries, International Assessment, Adults, Competence
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Piccarreta, Raffaella – Sociological Methods & Research, 2017
In its standard formulation, sequence analysis aims at finding typical patterns in a set of life courses represented as sequences. Recently, some proposals have been introduced to jointly analyze sequences defined on different domains (e.g., work career, partnership, and parental histories). We introduce measures to evaluate whether a set of…
Descriptors: Data Analysis, Multivariate Analysis, Social Science Research, Factor Analysis
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Soland, James – Research & Practice in Assessment, 2017
Research shows college readiness can be predicted using a variety of measures, including test scores, grades, course-taking patterns, noncognitive instruments, and surveys of how well students understand the college admissions process. However, few studies provide guidance on how educators can prioritize predictors of college readiness across…
Descriptors: College Readiness, Predictor Variables, Data Analysis, Measures (Individuals)
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Alabdulmenem, Fahad Mohammed – International Education Studies, 2017
Saudi Arabia is one of the countries that allot substantial amount of government resources for education. Thus, it is important to measure how these resources are used to generate favorable academic outcomes for its nationals. In this study, data envelopment analysis (DEA) is used to measure the relative efficiency of 25 public universities in…
Descriptors: Foreign Countries, Efficiency, Public Colleges, Universities
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