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No Child Left Behind Act 20011
Showing 1 to 15 of 94 results Save | Export
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Michelle L. Ackerman; Bettina Shapira; Joel B. Goodin; Sunilda A. Andriotis – Online Learning, 2025
Research suggests that supportive programmatic structure can assist online doctoral student success, including time to complete the dissertation. However, completely online doctoral students have unique characteristics and needs and are underrepresented in the research literature; therefore, research exploring programmatic factors as related to…
Descriptors: Doctoral Dissertations, Doctoral Students, Distance Education, Psychology
Jiaqi Jackie Shi – ProQuest LLC, 2024
One of the many impacts of the COVID-19 pandemic has been the increasing prevalence and accessibility of online education. This trend has also introduced challenges for students, instructors, and institutions. This study examines factors affecting online course satisfaction, focusing on individual, instructor, and institutional level…
Descriptors: Prediction, Online Courses, Higher Education, Student Attitudes
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Lu, Binwei – British Journal of Educational Studies, 2023
This study compares the estimated grammar school effect in different regression models, and explains why previous evidence of the effectiveness of grammar school is mixed. Like most studies of school effectiveness evaluation, previous research on grammar school effect usually applies regression to control for confounding between-school factors and…
Descriptors: Value Added Models, School Effectiveness, Academic Achievement, Comparative Analysis
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Lee, Stephen Man-Kit; Cui, Yanmengna; Tong, Shelley Xiuli – Review of Educational Research, 2022
A compelling demonstration of implicit learning is the human ability to unconsciously detect and internalize statistical patterns of complex environmental input. This ability, called statistical learning, has been investigated in people with dyslexia using various tasks in different orthographies. However, conclusions regarding impaired or intact…
Descriptors: Meta Analysis, Effect Size, Dyslexia, Statistics
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Kirksey, J. Jacob; Gottfried, Michael A. – Journal of Research on Educational Effectiveness, 2021
Over the past decade, identifying how schools might reduce student absenteeism has moved to the forefront of education policy. Yet little research has examined whether school type itself is important. We focus on the influence of Catholic schools using data from the past decade--the most relevant policy context for addressing absenteeism. The…
Descriptors: Educational Policy, Attendance, Catholic Schools, Institutional Characteristics
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Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction
Litman, Diane; Zhang, Haoran; Correnti, Richard; Matsumura, Lindsay Clare; Wang, Elaine – Grantee Submission, 2021
Automated Essay Scoring (AES) can reliably grade essays at scale and reduce human effort in both classroom and commercial settings. There are currently three dominant supervised learning paradigms for building AES models: feature-based, neural, and hybrid. While feature-based models are more explainable, neural network models often outperform…
Descriptors: Essays, Writing Evaluation, Models, Accuracy
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Zhou, Yuhao; Li, Xihua; Cao, Yunbo; Zhao, Xuemin; Ye, Qing; Lv, Jiancheng – International Educational Data Mining Society, 2021
In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…
Descriptors: Online Courses, Computer Assisted Instruction, Networks, Learning Analytics
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Ong, Nathan; Zhu, Jiaye; Mossé, Daniel – International Educational Data Mining Society, 2022
Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…
Descriptors: Prediction, Grades (Scholastic), Learning Analytics, Student Characteristics
Kim, Dong-In; Julian, Marc; Boughton, Keith; Phenow, Aurore – Online Submission, 2022
Pandemic-related policies are typically developed by districts and translated to all schools for implementation. Understanding the degree to which the pandemic impacted school-level performance would provide additional perspective for researchers looking to help district and school officials move forward. The main purpose of this study is to…
Descriptors: Pandemics, COVID-19, Academic Achievement, English
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Moore, Rhiannon – School Effectiveness and School Improvement, 2022
Existing research on "school effectiveness" indicates that differences at the school level contribute significantly towards variation in student outcomes; however, less is known about the effectiveness of schooling in low- and middle-income countries (LMICs). This paper addresses this gap using quantitative analysis of data from two…
Descriptors: Comparative Analysis, School Effectiveness, Institutional Evaluation, Foreign Countries
Malkus, Nat; Hatfield, Jenn – American Enterprise Institute, 2017
The charter school movement is premised on the idea that, if independent operators create differentiated and innovative schooling options, families will benefit from making meaningful choices among those options that reflect their preferences. Charters are freed from many of the constraints traditional public schools face, allowing them to…
Descriptors: Models, Charter Schools, Student Characteristics, Vocational Education
Fazlul, Ishtiaque; Koedel, Cory; Parsons, Eric – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2022
Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new…
Descriptors: Academic Achievement, At Risk Students, Prediction, Disadvantaged
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Kilicer, Kerem; Bardakci, Salih; Arpaci, Ibrahim – Contemporary Educational Technology, 2018
For today's societies trying to cope with the current globally increased competition, existence of individuals who can take risks, solve problems and adopt changes an innovation has gained more importance when compared to the past. This situation brings responsibility to educational institutions for increasing the number of innovative individuals…
Descriptors: Predictor Variables, Technology Uses in Education, Innovation, Student Characteristics
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Ashrafioun, Lisham; Bonar, Erin; Conner, Kenneth R. – Journal of American College Health, 2016
Objective: The purpose of this study was to examine whether positive health attitudes are associated with suicidal ideation among university students after accounting for other health risk factors linked to suicidal ideation. Participants: Participants were 690 undergraduates from a large midwestern university during fall semester 2011. Methods:…
Descriptors: Student Attitudes, Undergraduate Students, Health, Suicide
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