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Kimberly Wheeler – ProQuest LLC, 2023
The Vortex School District (VSD) utilized CASE benchmark assessments as their accountability tool to measure students' progress on Tennessee's standardized testing. The researchers sought to determine the predictive relationship between math scores on CASE benchmark assessments and math scores on state-mandated standardized tests within the VSD.…
Descriptors: Benchmarking, Prediction, Standardized Tests, Mathematics Tests
Benjamin Simmons – ProQuest LLC, 2023
The Vortex School District (VSD) utilized CASE benchmark assessments as their accountability tool to measure students' progress on Tennessee's standardized testing. The researchers sought to determine the predictive relationship between math scores on CASE benchmark assessments and math scores on state-mandated standardized tests within the VSD.…
Descriptors: Benchmarking, Prediction, Standardized Tests, Mathematics Tests
Caesar Jude Clemente – ProQuest LLC, 2023
Having a job immediately after graduation is the dream of every IT graduate. However, not everyone can achieve this outcome. The study's primary goal is to develop predictive models to forecast IT graduates' chances of finding a job based on factors such as academic performance, socioeconomic status, academic habits, and demographic data.…
Descriptors: Artificial Intelligence, Prediction, Models, Information Technology
J. Bryan Osborne; Andrew S. I. D. Lang – Journal of Postsecondary Student Success, 2023
This paper describes a neural network model that can be used to detect at- risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accuracy of 88% whether the student will pass or fail…
Descriptors: Identification, At Risk Students, Learning Management Systems, Prediction
David Kaplan; Jianshen Chen; Weicong Lyu; Sinan Yavuz – Grantee Submission, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
Benabbes, Khalid; Housni, Khalid; Hmedna, Brahim; Zellou, Ahmed; Mezouary, Ali El – Education and Information Technologies, 2023
Today, with the extension of learning management systems (LMSs) and the diversity of learners' needs for online learning, instructors have to be assisted to adapt their syllabus to meet learners' needs. Therefore, it is necessary to tailor course instruction to meet individual needs and determine how well they serve the learners using these online…
Descriptors: Learning Management Systems, Student Needs, Cognitive Style, Context Effect
Alexandra L. Vizgaitis; Summer Bottini; Craig P. Polizzi; Eileen Barden; Adam R. Krantweiss – Journal of Attention Disorders, 2023
Objective: Self-report symptom inventories are commonly used in adult ADHD assessment, and research indicates they should be interpreted with caution. This study investigated one self-report symptom inventory for adult ADHD in a clinical sample. Method: Archival data were used to evaluate diagnostic utility of the Conners Adult ADHD Rating…
Descriptors: Adults, Symptoms (Individual Disorders), Attention Deficit Hyperactivity Disorder, Measurement Techniques
Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – Grantee Submission, 2023
Adaptive educational software is likely to better support broader and more diverse sets of learners by considering more comprehensive views (or models) of such learners. For example, recent work proposed making inferences about "non-math" factors like reading comprehension while students used adaptive software for mathematics to better…
Descriptors: Reading Ability, Computer Software, Mathematics Education, Intelligent Tutoring Systems
Eli Ben-Michael; Avi Feller; Erin Hartman – Grantee Submission, 2023
In the November 2016 U.S. presidential election, many state level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the…
Descriptors: Public Opinion, National Surveys, Elections, Political Campaigns
Jianyi Liu; Tengwen Fan; Yan Chen; Jingjing Zhao – npj Science of Learning, 2023
Statistical learning (SL) plays a key role in literacy acquisition. Studies have increasingly revealed the influence of distributional statistical properties of words on visual word processing, including the effects of word frequency (lexical level) and mappings between orthography, phonology, and semantics (sub-lexical level). However, there has…
Descriptors: Semantics, Brain Hemisphere Functions, Language Processing, Reading Processes
Comparison in the Classroom: Motivation for Academic Social Comparison Predicts Academic Performance
Fanny Lalot; Diane M. Houston – Social Psychology of Education: An International Journal, 2025
Reviews of social comparison processes in school contexts have concluded that individual differences in propensity to compare with others are likely to be important in the classroom, but that there is a paucity of evidence testing this key proposition. To address this gap, we developed and validated a new measure of propensity to engage in…
Descriptors: Academic Achievement, Comparative Analysis, Individual Differences, Peer Relationship
Xiaoxiao Liu; Jiahua Liu; Carrie Demmans Epp; Ying Cui – Educational Technology Research and Development, 2025
Parental involvement is essential to children's learning engagement activities and academic performance. Much research revolves around the impact of parental involvement on students' academic performance or the relationship between student engagement and grades. However, few studies have used process data to examine the relationship between…
Descriptors: Parent Participation, Parent Child Relationship, Learner Engagement, Academic Achievement
Robert Shand; Roger D. Goddard – Educational Policy, 2025
There is growing consensus about the importance of teacher collaboration. Less clear are the mechanisms by which teacher collaboration can positively impact student achievement. We address this gap by examining two questions using panel data methods. First, does the degree to which teachers collaborate predict future growth in conditions relevant…
Descriptors: Teacher Collaboration, Academic Achievement, Prediction, Educational Practices
Seyhan Eryilmaz Toksoy; Emine Bulut – Journal of Science Education and Technology, 2025
In this research, it was aimed to determine the effect of Simulation-Supported Prediction Observation Explanation (SSPOE) activities related to solid and liquid pressure on the conceptions of learning physics of 10th grade students. In the research, a quasi-experimental design with pretest-posttest control group, which is one of the quantitative…
Descriptors: Simulation, Prediction, Observation, Student Attitudes
Tina Eckstein-Madry; Bernhard Piskernik; Thilo Schmidt; Wilfried Smidt – European Early Childhood Education Research Journal, 2025
Leadership in early childhood education and care (ECEC) undoubtedly plays a crucial role in preschool quality, yet it is seldom discussed in studies. This study aims to identify various leadership profiles of preschool leaders using a person-centered approach and predict these profiles based on leaders' characteristics and the preschools they…
Descriptors: Preschools, Administrator Characteristics, School Administration, Educational Quality

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