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Jessica R. Toste; Marissa J. Filderman; Nathan H. Clemens; Erica Fry – Journal of Learning Disabilities, 2025
Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation…
Descriptors: Preservice Teachers, Data Use, Decision Making, Progress Monitoring
Cynthia C. Massey; Emily M. Kuntz; Corey Peltier; Mary A. Barczak; H. Michael Crowson – International Journal for Research in Learning Disabilities, 2024
Enhancing special educators' data literacy is critical to informing instructional decision-making, especially for students with learning disabilities. One tool special educators commonly use is curriculum-based measurement (CBM). These data are displayed on time-series graphs, and student responsiveness is evaluated. Graph construction varies and…
Descriptors: Special Education Teachers, Preservice Teachers, Progress Monitoring, Information Literacy
Khamisi Kalegele – International Journal of Education and Development using Information and Communication Technology, 2023
Pragmatically, machine learning techniques can improve educators' capacity to monitor students' learning progress when applied to quality data. For developing countries, the major obstacle has been the unavailability of quality data that fits the purpose. This is partly because the in-use information systems are either not properly managed or not…
Descriptors: Artificial Intelligence, Learning Management Systems, Progress Monitoring, Data Use
Kuntz, Emily M.; Massey, Cynthia C.; Peltier, Corey; Barczak, Mary; Crowson, H. Michael – Teacher Education and Special Education, 2023
Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…
Descriptors: Graphs, Preservice Teachers, Accuracy, Decision Making
Randhir Rawatlal; Rubby Dhunpath – Association for Institutional Research, 2023
Although student advising is known to improve student success, its application is often inadequate in institutions that are resource constrained. Given recent advances in large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT), automated approaches such as the AutoScholar Advisor system affords viable alternatives to…
Descriptors: Academic Advising, Technology Uses in Education, Artificial Intelligence, Progress Monitoring
Ishari Amarasinghe; Konstantinos Michos; Francisco Crespi; Davinia Hernández-Leo – Journal of Computer Assisted Learning, 2024
Background: Data-driven educational technology solutions have the potential to support teachers in different tasks, such as the designing and orchestration of collaborative learning activities. When designing, such solutions can improve teacher understanding of how learning designs impact student learning and behaviour; and guide them to refine…
Descriptors: Learning Activities, Educational Technology, Design, Cooperative Learning
Zhi, Rui; Marwan, Samiha; Dong, Yihuan; Lytle, Nicholas; Price, Thomas W.; Barnes, Tiffany – International Educational Data Mining Society, 2019
Viewing worked examples before problem solving has been shown to improve learning efficiency in novice programming. Example-based feedback seeks to present smaller, adaptive worked example steps during problem solving. We present a method for automatically generating and selecting adaptive, example-based programming feedback using historical…
Descriptors: Data Use, Feedback (Response), Novices, Programming
Vasquez, Andrea – MDRC, 2020
Millions of students leave college every year before earning a degree. At community colleges, only a third of full-time students graduate within three years. How can school administrators help students stay in school and eventually graduate? Higher education institutions commonly offer students advising services to help them develop the academic…
Descriptors: Community Colleges, Two Year College Students, Program Design, Academic Advising
Aburizaizah, Saeed Jameel – Journal of Education and Learning, 2021
For many justifications, the collection, analysis, and use of educational data are central to the evaluation and improvement of students' progress and learning outcomes. The use of data in educational evaluation and decision making are expected to span all layers--from the institution, teachers, students, and classroom levels, providing a…
Descriptors: Data Use, Decision Making, Progress Monitoring, Learning Analytics
Vasquez, Andrea; Scrivener, Susan – MDRC, 2020
Colleges support students with advising, counseling, or coaching in academics and other skills they need to succeed in school. Some colleges enhance those services through reduced adviser caseloads and more comprehensive, frequent guidance, which can improve students' semester-to-semester retention and average credits earned. This overview…
Descriptors: Program Design, Academic Advising, Academic Support Services, Community Colleges
Mozahem, Najib Ali – International Journal of Mobile and Blended Learning, 2020
Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two…
Descriptors: Integrated Learning Systems, Data Use, Prediction, Academic Achievement
Gesel, Samantha A.; LeJeune, Lauren M.; Chow, Jason C.; Sinclair, Anne C.; Lemons, Christopher J. – Journal of Learning Disabilities, 2021
The purpose of this review was to synthesize research on the effect of professional development (PD) targeting data-based decision-making processes on teachers' knowledge, skills, and self-efficacy related to curriculum-based measurement (CBM) and data-based decision-making (DBDM). To be eligible for this review, studies had to: (1) be published…
Descriptors: Professional Development, Inservice Teacher Education, Preservice Teacher Education, Elementary Secondary Education
An Early Feedback Prediction System for Learners At-Risk within a First-Year Higher Education Course
Baneres, David; Rodriguez-Gonzalez, M. Elena; Serra, Montse – IEEE Transactions on Learning Technologies, 2019
Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…
Descriptors: Prediction, Feedback (Response), At Risk Students, College Freshmen
Miller, Cynthia; Cohen, Benjamin; Yang, Edith; Pellegrino, Lauren – MDRC, 2020
College students have a better chance of succeeding in school when they receive high-quality advising. High-quality advising, when characterized by frequent communications between advisers and students, early outreach to students showing signs of academic or nonacademic struggles, and personalized guidance that addresses individual student needs,…
Descriptors: College Students, Academic Advising, Technology Uses in Education, Faculty Advisers
Achieving the Dream, 2018
Helping more students achieve their dreams involves identifying a wider set of student needs--including financial challenges and family responsibilities--and offering redesigned support services to meet them holistically. This holistic student supports approach emphasizes the need for colleges to redefine the way they understand, design, integrate…
Descriptors: Holistic Approach, Program Design, College Programs, Academic Support Services
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