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Jae Yup Jung; Jihyun Lee – Psychology in the Schools, 2025
In this study, an investigation was conducted into the nature of the attitudes of the general student body (comprising all students) toward gifted students and gifted education, along with the predictors of such attitudes. For this purpose, survey data were collected from 400 secondary students enrolled in a faith-based school system in Australia.…
Descriptors: Student Attitudes, Academically Gifted, Gifted Education, Predictor Variables
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Timo Van Canegem; Mieke Van Houtte; Jannick Demanet – Research Papers in Education, 2024
Across the world, numerous students are being bullied at school. Bullying is often caused by a power imbalance between students. Therefore, identifying potential sources of such a power imbalance can prevent school bullying from happening. Based on the labelling theory, we expect that grade retention can lead to such a power imbalance and,…
Descriptors: Bullying, Grade Repetition, Correlation, Power Structure
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Franz Carrillo-Higueras; T. R. Walton – Journal of Further and Higher Education, 2024
Homesick disposition, an individual's expectation about becoming homesick in the future, has been identified as an important predictor of homesickness. Homesick disposition can be detected and measured even before the separation from home has taken place, making it particularly relevant to understanding feelings and perceptions of rural school…
Descriptors: Foreign Countries, Secondary School Students, Student Adjustment, Psychological Patterns
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Awdry, Rebecca; Ives, Bob – Assessment & Evaluation in Higher Education, 2021
Research on contract cheating usually considers most forms of outsourcing combined, although studies have found that students more commonly obtain work from those known to them, rather than from commercial sites; yet little research exists which explores which variables and motivators may be associated with this type of outsourcing. Strategies…
Descriptors: Cheating, Student Behavior, Outsourcing, Predictor Variables
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Sithole, Seedwell T. M.; Ran, Guang; de Lange, Paul; Tharapos, Meredith; O'Connell, Brendan; Beatson, Nicola – Accounting Education, 2023
This study introduces data mining methods to accounting education scholarship to explore the relationship between accounting students' current academic performance (grades), demographic information, pre-university entrance scores and predicted academic performance. It adopts a C4.5 classification algorithm based on decision-tree analysis to…
Descriptors: Data Analysis, Predictor Variables, Accounting, Educational Attainment
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Larcombe, Wendy; Baik, Chi; Finch, Sue – Higher Education Research and Development, 2022
University students are known to be at heightened risk among their peers for experiencing psychological distress and mental health difficulties. To date, there have been few interventions designed to reduce stressors in the educational environment. This may be due to limited research investigating course-related correlates of students' distress.…
Descriptors: Student Experience, Psychological Patterns, Well Being, Foreign Countries
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Merve Bulut; Yaren Bulbul – Turkish Online Journal of Distance Education, 2024
Even though distance education from the home environment has seemed comfortable and economic for students with disability in formal higher education during the pandemic, insufficiency in their academic self-efficacy, satisfaction and an increasing tendency to drop out were observed. This quantitative research is based on development of the scales…
Descriptors: Self Efficacy, Student Characteristics, Student Satisfaction, Dropouts
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Beswick, Kim; Watt, Helen M. G.; Granziera, Helena; Geiger, Vince; Fraser, Sharon – ZDM: Mathematics Education, 2023
This study examined the extent to which boys fell into clusters comprised of different levels of motivations and costs. In turn, the antecedents of these clusters and associations with engagement and wellbeing outcomes were considered. Based on survey responses from 168 students across Years 5, 7 and 9 from an all-boys' school in Sydney,…
Descriptors: Males, Student Motivation, Grade 5, Grade 7
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Cooper, Grant; Berry, Amanda; Baglin, James – Research in Science Education, 2020
Using the Longitudinal Surveys of Australian Youth (LSAY) data, this paper aimed to examine if, and to what extent, demographic factors predict students' participation in science over the age of 16 (post-16). While all the students participating in this study are attending Australian schools, the comprehensiveness of these datasets, together with…
Descriptors: Predictor Variables, Student Participation, Late Adolescents, Foreign Countries
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Jeffries, David; Curtis, David D.; Conner, Lindsey N. – International Journal of Science and Mathematics Education, 2020
This study investigates factors that influenced the science, technology, engineering and mathematics (STEM) subject enrolment decisions of Year 12 students in Australia. Structural equation modelling (SEM) is used to develop a model using Programme for International Student Assessment (PISA) and Longitudinal Surveys of Australian Youth (LSAY) data…
Descriptors: STEM Education, Grade 12, Secondary School Students, Student Attitudes
Osborne, Kristen – National Centre for Vocational Education Research (NCVER), 2021
Extensive evidence demonstrates a trend of positive outcomes related to learning in the workplace. Despite this, no examination of the outcomes has been undertaken using the available Australian vocational education and training (VET) data. This publication uses VET administrative data to examine trends in the delivery of workplace-based training,…
Descriptors: Incidence, Vocational Education, Foreign Countries, Work Experience Programs
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Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
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Marks, Gary N. – Educational Research and Evaluation, 2019
The literature on the relationship between socioeconomic background (SES) and university education is inconsistent. Some studies conclude SES is important to university entry and course completion, others find trivial SES effects, net of students' prior performance, and a third group concludes that SES effects are important and policy relevant…
Descriptors: Socioeconomic Background, Academic Achievement, Foreign Countries, Longitudinal Studies
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Martin, Andrew J.; Collie, Rebecca J. – Journal of Educational Psychology, 2019
Teacher-student relationships are an important part of students' interpersonal context at school that impacts their academic development. This study extended prior research into teacher-student relationships by exploring the relative balance of negative and positive teacher-student relationships in high school students' academic lives (in each of…
Descriptors: Teacher Student Relationship, Learner Engagement, High School Students, High School Teachers
Osborne, Kristen; Serich, Cameron – National Centre for Vocational Education Research (NCVER), 2020
This report explores, from a variety of perspectives, the volume and nature of recognition of prior learning (RPL) currently granted in the Australian vocational education and training (VET) system. Of particular interest are the areas where most RPL is taking place, including the qualifications being completed with high rates of RPL. The report…
Descriptors: Prior Learning, Vocational Education, Foreign Countries, Educational Trends
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