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Ayad Saknee – ProQuest LLC, 2024
Higher education institutes experience lower success rates in online learning environments compared to traditional learning. Students' engagement within the learning management system (LMS) is one of the main factors affecting students' academic performance and retention. This quantitative correlational-predictive study examined if, and to what…
Descriptors: Learning Management Systems, Academic Achievement, Predictive Validity, Learner Engagement
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Julia L. Ferguson; Amanda M. Rogue; Tracey D. Terhune; Christine M. Milne; Joseph H. Cihon; Maddison J. Majeski-Gerken; Justin B. Leaf; John McEachin; Ronald Leaf – Exceptionality, 2024
This study aimed to extend previous literature comparing continuous methods of data collection to estimation data, but this time implementing the data collection procedures within a group discrete trial teaching format with three individuals diagnosed with autism spectrum disorder. Group discrete trial teaching was conducted in a classroom setting…
Descriptors: Autism Spectrum Disorders, Kindergarten, Elementary School Students, Elementary School Teachers
Aimee Evan; Olivia Szendey; Kelly Wynveen – WestEd, 2025
This paper reports on a study that adopted a systematic approach to school-level early warning. The study examined areas where research consistently shows schools commonly experience decline: (1) leadership stability; (2) talent management; (3) organizational culture; (4) financial operations; and (5) instructional programming. Rather than relying…
Descriptors: Educational Indicators, Educational Quality, Identification, Prevention
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Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
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Kautz, Tim; Feeney, Kathleen; Chiang, Hanley; Lauffer, Sarah; Bartlett, Maria; Tilley, Charles – Regional Educational Laboratory Mid-Atlantic, 2021
The District of Columbia Public Schools (DCPS) has prioritized efforts to support students' social and emotional learning (SEL) competencies, such as perseverance and social awareness. To measure students' SEL competencies and the school experiences that promote SEL competencies (school climate), DCPS began administering annual surveys to…
Descriptors: Social Emotional Learning, Educational Environment, Student Surveys, Teacher Surveys
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Lin, Shuqiong; Luo, Wen; Tong, Fuhui; Irby, Beverly J.; Alecio, Rafael Lara; Rodriguez, Linda; Chapa, Selena – Cogent Education, 2020
Student learning objectives (SLOs) have become an increasingly popular tool for teacher evaluations as an alternative to Value-added Models (VAMs). However, the use of SLOs faces two major challenges. First, the target setting is mostly subjective and arbitrary. Second, there is little evidence on the reliability and validity of the tool. In this…
Descriptors: Student Educational Objectives, Teacher Evaluation, Data Use, Academic Achievement
Pascopella, Angela – District Administration, 2012
Predicting the future is now in the hands of K12 administrators. While for years districts have collected thousands of pieces of student data, educators have been using them only for data-driven decision-making or formative assessments, which give a "rear-view" perspective only. Now, using predictive analysis--the pulling together of data over…
Descriptors: Expertise, Prediction, Decision Making, Data
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Cho, Moon-Heum; Yoo, Jin Soung – Interactive Learning Environments, 2017
Many researchers who are interested in studying students' online self-regulated learning (SRL) have heavily relied on self-reported surveys. Data mining is an alternative technique that can be used to discover students' SRL patterns from large data logs saved on a course management system. The purpose of this study was to identify students' online…
Descriptors: Online Courses, Self Management, Active Learning, Data Analysis
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Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Themes in Science and Technology Education, 2016
Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…
Descriptors: Predictive Measurement, Decision Support Systems, Academic Achievement, Exit Examinations
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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Welsch, David M.; Zimmer, David M. – Education Finance and Policy, 2015
This paper draws attention to a subtle, but concerning, empirical challenge common in panel data models that seek to estimate the relationship between student transfers and district academic performance. Specifically, if such models have a dynamic element, and if the estimator controls for unobserved traits by including district-level effects,…
Descriptors: Transfer Students, Academic Achievement, Feedback (Response), School Districts
Wang, Helen Y.; Zhao, Huafang; Addison, Kecia L. – Montgomery County Public Schools, 2016
The Office of Shared Accountability (OSA) in Montgomery County Public Schools (MCPS) conducted a linking study to examine the relationship of the Measures of Academic Progress (MAP) assessment with the Common Core Consortia Partnership for Assessment of Readiness for College and Careers (PARCC) assessment in the 2014-2015 school year. This is the…
Descriptors: Public Schools, Accountability, College Admission, College Entrance Examinations
Wheatley, Vicki Ann – ProQuest LLC, 2012
The relationship between components of the local school district report card, school district typology, and the outcome of public school tax levy requests were examined in this study. A correlation research design was used to measure the relationship between the independent variables (performance index, average yearly progress, value added,…
Descriptors: School Taxes, Correlation, School Statistics, Student Records
Weber, Elizabeth A. – ProQuest LLC, 2012
The principal plays a key role in student success. The employment interview is a critical element in the principal selection process. This study examined the interview structure and the content of the interview questions that districts used in their principal search for the 2011-2012 school year. The research-based practices for interview…
Descriptors: Academic Achievement, Leadership Responsibility, Measures (Individuals), Leadership
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Ziswiler, Korrin M.; De Luca, Barbara; Stedrak, Luke J. – Educational Considerations, 2013
Although there exists a large body of research concerning the relationship between expenditure and student achievement, a lack of research exists analyzing this relationship as it pertains specifically to students with disabilities. Given the increasing fiscal and academic pressures districts face to allocate resources efficiently, the purpose of…
Descriptors: Expenditures, Federal Programs, Educational Indicators, Special Needs Students
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