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van Halema, Nicolette; van Klaveren, Chris; Drachsler, Hendrik; Schmitz, Marcel; Cornelisz, Ilja – Frontline Learning Research, 2020
For decades, self-report instruments -- which rely heavily on students' perceptions and beliefs -- have been the dominant way of measuring motivation and strategy use. Event-based measures based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to…
Descriptors: Independent Study, Learning Motivation, Learning Strategies, Student Behavior
Pennings, Helena J. M. – Complicity: An International Journal of Complexity and Education, 2017
In the present study, complex dynamic systems theory and interpersonal theory are combined to describe the teacher-student interactions of two teachers with different interpersonal styles. The aim was to show and explain the added value of looking at different steps in the analysis of behavioral time-series data (i.e., observations of teacher and…
Descriptors: Teacher Student Relationship, Case Studies, Interpersonal Relationship, Questionnaires
Noroozi, Omid, Ed.; Sahin, Ismail, Ed. – International Society for Technology, Education, and Science, 2022
Education, science, and technology disciplines are closely and extensively connected in all formats and levels. The outbreak of COVID-19 has further squeezed this interconnection where the delivery of education in different scientific fields of studies at all education levels is almost impossible without the presence of technology. Today, there is…
Descriptors: Education, Sciences, Technology, COVID-19
Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – IEEE Transactions on Learning Technologies, 2017
Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…
Descriptors: Student Behavior, Integrated Learning Systems, Personality, Educational Research
Hoekstra, Rosa A.; Vinkhuyzen, Anna A. E.; Wheelwright, Sally; Bartels, Meike; Boomsma, Dorret I.; Baron-Cohen, Simon; Posthuma, Danielle; van der Sluis, Sophie – Journal of Autism and Developmental Disorders, 2011
This study reports on the development and validation of an abridged version of the 50-item Autism-Spectrum Quotient (AQ), a self-report measure of autistic traits. We aimed to reduce the number of items whilst retaining high validity and a meaningful factor structure. The item reduction procedure was performed on data from 1,263 Dutch students and…
Descriptors: Autism, Factor Structure, Foreign Countries, Pervasive Developmental Disorders
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers