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Showing 1 to 15 of 33 results Save | Export
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Done, Elizabeth J.; Knowler, Helen – Educational Review, 2022
In this paper, the concepts of fabrication, subjectivation and performativity are mobilised in an analysis of varied exclusionary practices in England's schools with particular reference to "off-rolling", defined by the national school inspectorate as the illegal removal of a student from a school roll in order to enhance academic…
Descriptors: Admission (School), Principals, Inclusion, Foreign Countries
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Marcus Kubsch; Sebastian Strauß; Adrian Grimm; Sebastian Gombert; Hendrik Drachsler; Knut Neumann; Nikol Rummel – Educational Psychology Review, 2025
Recent research underscores the importance of inquiry learning for effective science education. Inquiry learning involves self-regulated learning (SRL), for example when students conduct investigations. Teachers face challenges in orchestrating and tracking student learning in such instruction; making it hard to adequately support students. Using…
Descriptors: Inquiry, Science Instruction, Electronic Books, Workbooks
Nancy Montes; Fernanda Luna – UNESCO International Institute for Educational Planning, 2024
This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…
Descriptors: Data Collection, Data Use, At Risk Students, Foreign Countries
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Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
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Wu, Fati; Lai, Song – Distance Education, 2019
Open, flexible and distance learning has become part of mainstream education in China. Using a blended learning program in a Chinese high school as the case, this study adopted data-mining approaches to establish predictive models using personality traits. Results showed that, for students with high OE and low extraversion, and students who are…
Descriptors: Personality Traits, Learning Analytics, Foreign Countries, At Risk Students
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Berens, Johannes; Schneider, Kerstin; Gortz, Simon; Oster, Simon; Burghoff, Julian – Journal of Educational Data Mining, 2019
To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and private university to predict student dropout as a basis for a targeted…
Descriptors: Risk Management, At Risk Students, Dropout Prevention, College Students
McBrien, Jody; Rutigliano, Alexandre; Sticca, Adam – OECD Publishing, 2022
Students who identify as lesbian, gay, bisexual, transgender, queer, intersex or somewhere else on the gender/sexuality spectrum (LGBTQI+) are among the diverse student groups in need of extra support and protection in order to succeed in education and reach their full potential. Because they belong to a minority that is often excluded by…
Descriptors: LGBTQ People, Inclusion, Student Diversity, At Risk Students
Çöker, Berna – Online Submission, 2020
In this study, I aim to provide an analysis of gender equality in the Turkish education system by looking at policies and their outcomes on girl's schooling. My goal is to demonstrate the ways educational policies have been complicit in reproducing inequality and difference between the sexes by examining what issues regarding education and gender…
Descriptors: Foreign Countries, Females, Womens Education, Gender Bias
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Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
Valenza, Marco; Dreesen, Thomas; Kan, Sophia – UNICEF Office of Research - Innocenti, 2022
One tool that many families own, across the globe, is a basic mobile phone. The use of low-cost basic mobile phones for educational purposes in humanitarian settings is critical where access to connectivity and higher cost devices is limited. The portability of mobile phones, combined with their communication features, offers multiple uses to…
Descriptors: COVID-19, Pandemics, Telecommunications, Handheld Devices
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Choi, Samuel P. M.; Lam, S. S.; Li, Kam Cheong; Wong, Billy T. M. – Educational Technology & Society, 2018
While learning analytics (LA) practices have been shown to be practical and effective, most of them require a huge amount of data and effort. This paper reports a case study which demonstrates the feasibility of practising LA at a low cost for instructors to identify at-risk students in an undergraduate business quantitative methods course.…
Descriptors: Data Collection, Data Analysis, Educational Research, Audience Response Systems
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West, Deborah; Huijser, Henk; Heath, David; Lizzio, Alf; Toohey, Danny; Miles, Carol; Searle, Bill; Bronnimann, Jurg – Australasian Journal of Educational Technology, 2016
This paper presents findings from a study of Australian and New Zealand academics (n = 276) that teach tertiary education students. The study aimed to explore participants' early experiences of learning analytics in a higher education milieu in which data analytics is gaining increasing prominence. Broadly speaking participants were asked about:…
Descriptors: Higher Education, Teaching Experience, Educational Research, Data Collection
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Kelly, Nick; Montenegro, Maximiliano; Gonzalez, Carlos; Clasing, Paula; Sandoval, Augusto; Jara, Magdalena; Saurina, Elvira; Alarcón, Rosa – International Journal of Information and Learning Technology, 2017
Purpose: The purpose of this paper is to demonstrate the utility of combining event-centred and variable-centred approaches when analysing big data for higher education institutions. It uses a large, university-wide data set to demonstrate the methodology for this analysis by using the case study method. It presents empirical findings about…
Descriptors: Educational Research, Data Collection, Data Analysis, Units of Study
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McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2016
Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…
Descriptors: Data Collection, Student Behavior, Academic Achievement, Correlation
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Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
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