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Showing 1 to 15 of 34 results Save | Export
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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
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Joanna Clifton-Sprigg; Jonathan James – British Educational Research Journal, 2025
Using newly released detailed data on absence from school, we find a 'Friday effect'--children are much less likely to attend schools in England on Fridays. We use daily level data across the whole of England and find that this pattern holds for different schools and for different types of absence, including illness-related authorised and…
Descriptors: Foreign Countries, Attendance Patterns, Student Behavior, Attendance
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Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior
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Rodriguez, Luis A.; Welsh, Richard O. – AERA Open, 2022
The school discipline literature has expanded rapidly in recent decades, yet the conceptualization and measurement of school discipline patterns remains overlooked. In this paper, we present a comprehensive analytic framework to examine school discipline patterns that encompasses school-level metrics that capture the prevalence and disparity in…
Descriptors: Discipline, Outcomes of Education, Incidence, Expulsion
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Knox, Jeremy; Williamson, Ben; Bayne, Sian – Learning, Media and Technology, 2020
This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…
Descriptors: Data Collection, Data Analysis, Artificial Intelligence, Man Machine Systems
Eaton, Sarah Elaine – Online Submission, 2020
Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…
Descriptors: Data Collection, Minority Group Students, Racial Bias, Student Behavior
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Thoutenhoofd, Ernst D. – Studies in Philosophy and Education, 2018
Like other parts of the social system, education is becoming an information-driven venture: data technologies pervade all levels of the system. This datafication of education seems to take place alongside a general turn to learning that Gert Biesta has called learnification: a progressively singular focus on the manipulable features of individual…
Descriptors: Information Technology, Data Analysis, Learning Processes, Intervention
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Chen, Weiyu; Brinton, Christopher G.; Cao, Da; Mason-Singh, Amanda; Lu, Charlton; Chiang, Mung – IEEE Transactions on Learning Technologies, 2019
We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…
Descriptors: Online Courses, Outcomes of Education, Prediction, Course Content
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Kincaid, Don – Journal of Positive Behavior Interventions, 2018
The field of Positive Behavior Support (PBS) has grown and changed significantly in the past 25 years and should be expected to continue that trend for the next 25 years. These changes cannot always be predicted, but they can be managed by considering some current changes to the definition of PBS (Kincaid et al., 2016). This paper discussed how…
Descriptors: Positive Behavior Supports, Student Behavior, Behavior Problems, Evidence Based Practice
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Worsley, Marcelo; Blikstein, Paulo – International Journal of Artificial Intelligence in Education, 2018
This paper presents three multimodal learning analytic approaches from a hands-on learning activity. We use video, audio, gesture and bio-physiology data from a two-condition study (N = 20), to identify correlations between the multimodal data, experimental condition, and two learning outcomes: design quality and learning. The three approaches…
Descriptors: Multimedia Materials, Correlation, Outcomes of Education, Design
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Brown, Neil C. C.; Altadmri, Amjad – ACM Transactions on Computing Education, 2017
Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much…
Descriptors: Novices, Programming Languages, Programming, Error Patterns
Agnihotri, Lalitha; Aghababyan, Ani; Mojarad, Shirin; Riedesel, Mark; Essa, Alfred – International Educational Data Mining Society, 2015
Student login data is a key resource for gaining insight into their learning experience. However, the scale and the complexity of this data necessitate a thorough exploration to identify potential actionable insights, thus rendering it less valuable compared to student achievement data. To compensate for the underestimation of login data…
Descriptors: Data Analysis, Web Based Instruction, Student Behavior, Correlation
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Bohanon, Hank; Wu, Meng-Jia – Preventing School Failure, 2014
On the basis of the implementation of Schoolwide Positive Behavior Supports in high schools, the present study examined the effect of supporting buy-in through conducting needs assessments and focused professional development for high school staff when implementing Schoolwide Positive Behavior Supports. The effectiveness of the 2 additional items…
Descriptors: Secondary School Students, Needs Assessment, Faculty Development, Positive Reinforcement
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Chung, Gregory K. W. K. – Teachers College Record, 2014
Background: Historically, significant advances in scientific understanding have followed advances in measurement and observation. As the resolving power of an instrument increased, so have gains in the understanding of the phenomena being observed. Modern interactive systems are potentially the new "microscopes" when they are…
Descriptors: Online Systems, Data Analysis, Data Collection, Data Interpretation
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Willemsen, Martijn C.; Bockenholt, Ulf; Johnson, Eric J. – Journal of Experimental Psychology: General, 2011
Loss aversion and reference dependence are 2 keystones of behavioral theories of choice, but little is known about their underlying cognitive processes. We suggest an additional account for loss aversion that supplements the current account of the value encoding of attributes as gains or losses relative to a reference point, introducing a value…
Descriptors: Evidence, Cognitive Processes, Comparative Analysis, Self Efficacy
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