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Direct linkEmily J. Barnes – ProQuest LLC, 2024
This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…
Descriptors: Artificial Intelligence, Higher Education, Models, Prediction
Peer reviewed
Download full textMd Akib Zabed Khan; Agoritsa Polyzou – Journal of Educational Data Mining, 2024
In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…
Descriptors: Academic Advising, Courses, Data Use, Artificial Intelligence
Meka N. McCammon; Katie Wolfe; Ruiqin Gao; Angela Starrett – Remedial and Special Education, 2025
Data-based decision-making, which involves evaluating students' progress and making instructional decisions, is an integral competency for preservice teachers. Several studies have found that visual aids, such as decision-making models, may be an effective way to train preservice teachers to make instructional decisions. The purpose of this study…
Descriptors: Data Use, Decision Making, Preservice Teacher Education, Teacher Competencies
Saar, Merike; Rodríguez-Triana, María Jesús; Prieto, Luis P. – Journal of Learning Analytics, 2022
Data-informed decision-making in teachers' practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known about how teachers perceive the different steps that analytics-informed teacher inquiry entails. This paper presents the results of a study into…
Descriptors: Learning Analytics, Evidence Based Practice, Data, Decision Making
Samaranayake, Sobitha; Gunawardena, Athula D. A.; Meyer, Robert R. – Athens Journal of Education, 2023
Many students in the Unites States enter college without having decided on a focus for their studies, and thus are faced with choosing from a large number of potential majors and associated very complex sets of degree requirements which can include many courses in other areas of study. Academic advisors use academic planning tools to help students…
Descriptors: College Students, Degree Requirements, Academic Degrees, Decision Support Systems
Athanatou, Maria; Prendes Espinosa, Maria Paz; Gutierrez Porlan, Isabel – Journal of Education and e-Learning Research, 2023
The digital evaluation field is a new area that arises in the core of education and studies highlight the importance of editing data as well as using ICT to drive internal school improvement. Data- Driven Decision Making (DDDM in advance) executes relatively simple models on carefully targeted data extracted through target questionnaires. This…
Descriptors: Foreign Countries, Elementary Education, Decision Making, Data Use
Owen, V. Elizabeth; Baker, Ryan S. – Technology, Knowledge and Learning, 2020
As a digital learning medium, serious games can be powerful, immersive educational vehicles and provide large data streams for understanding player behavior. Educational data mining and learning analytics can effectively leverage big data in this context to heighten insight into student trajectories and behavior profiles. In application of these…
Descriptors: Educational Games, Video Games, Decision Making, Prediction
Prescott, Brian T. – Change: The Magazine of Higher Learning, 2021
A "Cone of Uncertainty" has become ubiquitous in hurricane forecasting, encompassing the likeliest possible path that a storm might take as it approaches landfall. These forecasts are crucial because they help government agencies at all levels prepare even in these far-from-certain future conditions. Although individual institutions have…
Descriptors: Educational Planning, COVID-19, Pandemics, Decision Making
Courtney, Matthew B. – International Journal of Education Policy and Leadership, 2021
Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…
Descriptors: Data Analysis, Data Use, Decision Making, Educational Improvement
Firestone, William A.; Donaldson, Morgaen L. – Educational Assessment, Evaluation and Accountability, 2019
Most recent research on teacher evaluation examines evaluation's measurement properties and accountability uses. Less research studies how evaluation data can improve teaching and student learning. In other contexts, researchers have examined how teachers use data to improve their practice. From general research on teachers' data use, we apply the…
Descriptors: Teacher Evaluation, Data Use, Evaluation Methods, Decision Making
Nasheen Nur – ProQuest LLC, 2021
The main goal of learning analytics and early detection systems is to extract knowledge from student data to understand students' trends of activities towards success and risk and design intervention methods to improve learning performance and experience. However, many factors contribute to the challenge of designing and building effective…
Descriptors: Artificial Intelligence, Undergraduate Students, Learning Analytics, Time Factors (Learning)
Kressler, Benikia; Chapman, Lindsey A.; Kunkel, Amy; Hovey, Katrina A. – Intervention in School and Clinic, 2020
Engaging in culturally responsive practices is considered best practice in classroom instruction, particularly within diverse schools, however, when making data-based decisions, there is little guidance for culturally responsive practitioners on how to engage in this work. This article introduces a model of culturally responsive data-based…
Descriptors: Data Use, Decision Making, Culturally Relevant Education, Problem Solving
Brann, Kristy L.; Naser, Shereen C.; Clough, Mac – Journal of Educational and Psychological Consultation, 2023
The current study describes the process of a participatory consultation framework, the Participatory Culture Specific Intervention Model (PCSIM), to plan and implement a data-based decision-making framework. The framework integrates proactive and systematic identification of emotional and behavioral needs as well as cognitive psychology techniques…
Descriptors: Consultation Programs, Data Use, Decision Making, Intervention
Lana Shklyar Nenide; Kate Sweeney; Gerard Costa; Neal M. Horen; Robert M. Corso; Jordana Ash, Contributor; Lynette Aytch, Contributor; Julie Betchkal, Contributor; Jean Budd, Contributor; Margo Candelaria, Contributor; Corinne G. Catalano, Contributor; Kimberly P. Diamond-Berry, Contributor; Faith Eidson, Contributor; Brandy Fox, Contributor; Keri Giordano, Contributor; Amy Hunter, Contributor; Harleen Hutchinson, Contributor; Nucha Isarowong, Contributor; Ashley McCormick, Contributor; Kelli McDermott, Contributor; Kaitlin Mulcahy, Contributor; Carmen Rosa Noroña, Contributor; Nichole Paradis, Contributor; Rebecca Parlakian, Contributor; Lindsay J. Pearson, Contributor; Thomas Rendon, Contributor; Julia Sayles, Contributor; Jayne Singer, Contributor; Staci Sontoski, Contributor; Kristin Tenney-Blackwell, Contributor; Mary Louise Hemmeter, Contributor – Brookes Publishing Company, 2025
Infant Mental Health (IMH) and the Pyramid Model (PM) are two frameworks with an important common goal: supporting the mental health and social-emotional well-being of infants, young children and their families. For the first time ever, one book integrates these two frameworks to create a more effective, knowledgeable, and responsive early…
Descriptors: Infants, Models, Mental Health, Diversity Equity and Inclusion
Cynthia Estremera – ProQuest LLC, 2019
Since the introduction of the specific learning disability (SLD) classification in federal special education legislation, there has been considerable ambiguity and controversy about the criteria that should be used in the determination of SLD (Kavale & Flanagan, 2007; Zumeta et al., 2014). Various models have been introduced to identify…
Descriptors: School Psychologists, Disability Identification, Learning Disabilities, Trend Analysis
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