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Camacho, Vicente Lopez; de la Guia, Elena; Olivares, Teresa; Flores, M. Julia; Orozco-Barbosa, Luis – IEEE Transactions on Learning Technologies, 2020
Increasing school dropout rates are a problem in many educational systems, with student disengagement being one significant factor. Learning analytics is a new field with a key role in educational institutions in the coming years. It may help make strategic decisions to reduce student disengagement. The use of technology in educational…
Descriptors: Learning Analytics, Learner Engagement, Measurement Equipment, Technology Uses in Education
Birch, Heather J. S. – Journal of Online Learning Research, 2022
This case study is about understanding disruptive students who are motivated by a psychological need to invoke change in a learning space. Marczewski's User Types Test, a typology for classifying both intrinsic and extrinsic motivational tendencies, and based on Self-Determination Theory, was administered to 14 participants, aged 9 through 15, to…
Descriptors: Elementary School Students, High School Students, Student Behavior, Behavior Problems
Wagle, Rhea; Dowdy, Erin; Nylund-Gibson, Karen; Sharkey, Jill D.; Carter, Delwin; Furlong, Michael J. – Educational and Developmental Psychologist, 2021
Introduction: The investigation of school belonging is crucial due to its established significant associations with mental health, academic achievement, and risky behaviours coupled with the limited research documenting the configurations of children's school belonging experiences. Objective: This study sought to better understand elementary…
Descriptors: Mental Health, Student School Relationship, Elementary School Students, Student Attitudes
Lai, Song; Sun, Bo; Wu, Fati; Xiao, Rong – IEEE Transactions on Learning Technologies, 2020
Adaptive e-learning can be used to personalize learning environment for students to meet their individual demands. Individual differences depend on the students' personality traits. Numerous studies have indicated that understanding the role of personality in the learning process can facilitate learning. Hence, personality identification in…
Descriptors: Personality Traits, Electronic Learning, Individual Differences, Learning Processes
Kuthe, Alina; Keller, Lars; Körfgen, Annemarie; Stötter, Hans; Oberrauch, Anna; Höferl, Karl-Michael – Journal of Environmental Education, 2019
Under the premise that the young generation of teenagers cannot be considered to be uniform, this study identified groups of teenagers based on their level of climate change awareness. Questionnaires answered by 760 teenagers (13-16 years old) from Germany and Austria were analyzed using a hierarchical cluster analysis. The teenagers were assigned…
Descriptors: Classification, Climate, Environmental Influences, Secondary School Students
Las-Vergnas, Olivier – Online Submission, 2016
The purpose of this paper is to present complementary studies focused on the a posteriori effects of school science categorization (SSC) on adults' relationships to scientific knowledge. This interest of this issue is linked to the fact that specificities of the science secondary school diplomas in many countries such as France make many adults…
Descriptors: STEM Education, Secondary School Students, Foreign Countries, Classification
Suranyi, Zsuzsanna; Hitchcock, David B.; Hittner, James B.; Vargha, Andras; Urban, Robert – International Journal of Behavioral Development, 2013
Previous research on sensation seeking (SS) was dominated by a variable-oriented approach indicating that SS level has a linear relation with a host of problem behaviors. Our aim was to provide a person-oriented methodology--a probabilistic clustering--that enables examination of both inter- and intra-individual differences in not only the level,…
Descriptors: Personality Traits, Behavior Problems, Conceptual Tempo, Individual Differences
Ulmer, Jonathan D.; Torres, Robert M. – Journal of Agricultural Education, 2007
The purpose of this study was to investigate the level of cognitive behavior exhibited by secondary agriculture teachers and compare the behavior to science teachers. Teachers within the two groups were found to have similar attitudes toward teaching at higher levels of cognition. Agriculture teachers spent 83% of their time on lower-order…
Descriptors: Agricultural Education, Science Teachers, Agriculture, Comparative Analysis