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Hamdaoui, Nabila; Idrissi, Mohammed Khalidi; Bennani, Samir – International Journal of Game-Based Learning, 2021
Over the last years there has been a growing interest in the use of educational games as learning tools. Educational games have proven to contribute in enhancing student motivation, increasing their engagement and providing them with personalized and adaptive learning. Learner modeling is a prerequisite when it comes to adaptive learning; it is…
Descriptors: Educational Games, Mathematical Logic, Models, Data Analysis
Ye, Ping; Bautista-Maya, Gildardo – Mathematics Teaching Research Journal, 2021
This paper analyzes the dataset collected from students participating in the Boy With A Ball (BWAB) program, a faith-based community outreach group, through the Hemingway Measure of Adult Connectedness©, a questionnaire measuring the social connectedness of adolescents. This paper first approaches the data in the conventional method provided by…
Descriptors: Outreach Programs, Adolescents, Interpersonal Relationship, Questionnaires
Aksoy, Esra; Narli, Serkan; Aksoy, Mehmet Akif – International Journal of Research in Education and Science, 2018
In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…
Descriptors: Academically Gifted, Talent Identification, Data Collection, Mathematics Instruction
Gniewosz, Burkhard; Gniewosz, Gabriela – International Journal of Behavioral Development, 2018
The present article aims to show how to model longitudinal change in cohort sequential data applying latent true change models using Mplus' multi-group approach. The underlying modeling ideas are described and explained in this article. As an example, change in internalizing problem behaviors between the age of 8 and 13 years is modeled and…
Descriptors: Models, Data, Behavior Problems, Children
Mavroudi, Anna; Giannakos, Michail; Krogstie, John – Interactive Learning Environments, 2018
Learning Analytics (LA) and adaptive learning are inextricably linked since they both foster technology-supported learner-centred education. This study identifies developments focusing on their interplay and emphasises insufficiently investigated directions which display a higher innovation potential. Twenty-one peer-reviewed studies are…
Descriptors: Student Centered Learning, Evidence Based Practice, Technology Uses in Education, Student Diversity
Goldschmidt, Ronaldo; Fernandes de Souza, Isabel; Norris, Monica; Passos, Claudio; Ferlin, Claudia; Cavalcanti, Maria Claudia; Soares, Jorge – Informatics in Education, 2016
The use of computers as teaching and learning tools plays a particularly important role in modern society. Within this scenario, Brazil launched its own version of the "One Laptop per Child" (OLPC) program, and this initiative, termed PROUCA, has already distributed hundreds of low-cost laptops for educational purposes in many Brazilian…
Descriptors: Data Collection, Data Analysis, Computer Uses in Education, Foreign Countries
Jian, Yuheng Helen; Javaad, Sohail Syed; Golab, Lukasz – Informatics in Education, 2016
In this paper, we take a new look at the problem of analyzing course evaluations. We examine ten years of undergraduate course evaluations from a large Engineering faculty. To the best of our knowledge, our data set is an order of magnitude larger than those used by previous work on this topic, at over 250,000 student evaluations of over 5,000…
Descriptors: Course Evaluation, Undergraduate Students, Engineering Education, Data Collection
Pampaka, Maria; Hutcheson, Graeme; Williams, Julian – International Journal of Research & Method in Education, 2016
Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Bendjebar, Safia; Lafifi, Yacine; Seridi, Hamid – International Journal of Web-Based Learning and Teaching Technologies, 2016
In e-learning systems, the tutors play many roles and carry out several tasks that differ from one system to another. The activity of tutoring is influenced by many factors. One factor among them is the assignment of the appropriate profile to the tutor. For this reason, the authors propose a new approach for modeling and evaluating the function…
Descriptors: Electronic Learning, Teaching Methods, Classification, Student Needs
Crick, Ruth Deakin; Knight, Simon; Barr, Steven – Journal of Learning Analytics, 2017
Central to the mission of most educational institutions is the task of preparing the next generation of citizens to contribute to society. Schools, colleges, and universities value a range of outcomes--e.g., problem solving, creativity, collaboration, citizenship, service to community--as well as academic outcomes in traditional subjects. Often…
Descriptors: Educational Improvement, Holistic Approach, Data Collection, Data Analysis
Gray, Geraldine; McGuinness, Colm; Owende, Philip; Hofmann, Markus – Journal of Learning Analytics, 2016
This paper reports on a study to predict students at risk of failing based on data available prior to commencement of first year. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines, n=1,207. Data was gathered from both student enrollment data and an online, self-reporting,…
Descriptors: Prediction, At Risk Students, Academic Failure, College Freshmen
Cafarella, Brian V. – Research & Teaching in Developmental Education, 2016
Due to poor student success rates in developmental mathematics, many institutions have implemented various forms of redesign into their developmental math curricula. Since the goal of redesign is to increase student success, it is salient to explore all aspects of the redesign process. Many studies have focused on the positive outcomes of redesign…
Descriptors: Misconceptions, Instructional Design, Developmental Programs, Mathematics Education
Kuhnel, Matthias; Seiler, Luisa; Honal, Andrea; Ifenthaler, Dirk – Interactive Technology and Smart Education, 2018
Purpose: The purpose of the study was to test the usability of the MyLA app prototype by its potential users. Furthermore, the Web app will be introduced in the framework of "Mobile Learning Analytics", a cooperation project between the Cooperative State University Mannheim and University of Mannheim. The participating universities focus…
Descriptors: Electronic Learning, Higher Education, Data Collection, Usability
Levy, Michal; Gumpel, Thomas P. – Journal of School Violence, 2018
This study explores correlations between bystanders' intervention styles by means of the bullying circle model. Three aims were examined in this study. First, we reevaluated the number and type of bystander intervention styles in aggressive school incidents. Second, we examined the association between reports of relational aggression and…
Descriptors: Audiences, Intervention, Bullying, Prevention
Wook, Muslihah; Yusof, Zawiyah M.; Nazri, Mohd Zakree Ahmad – Education and Information Technologies, 2017
The acceptance of Educational Data Mining (EDM) technology is on the rise due to, its ability to extract new knowledge from large amounts of students' data. This knowledge is important for educational stakeholders, such as policy makers, educators, and students themselves to enhance efficiency and achievements. However, previous studies on EDM…
Descriptors: Educational Research, Information Retrieval, Data Analysis, Educational Technology