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Nazanin Nezami; Parian Haghighat; Denisa Gándara; Hadis Anahideh – Grantee Submission, 2024
The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…
Descriptors: Evaluation Methods, College Students, Success, Predictor Variables
Majdi Beseiso – TechTrends: Linking Research and Practice to Improve Learning, 2025
Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…
Descriptors: Prediction, Success, Academic Achievement, Artificial Intelligence
Valeria Damiani; Bruno Losito; Gabriella Agrusti; Wolfram Schulz – International Association for the Evaluation of Educational Achievement, 2024
The IEA's International Civic and Citizenship Education Study (ICCS) investigates the ways in which young people around the world are prepared to undertake their roles as citizens. This report presents the European results from the third cycle of the study (ICCS 2022). Eighteen countries and two benchmarking participants (the German states of…
Descriptors: Citizen Participation, Foreign Countries, Grade 8, Grade 9
Carrie Klein; Jessica Colorado – State Higher Education Executive Officers, 2024
Since 2010, the State Higher Education Executive Officers Association's (SHEEO) Strong Foundations survey has reported on the evolution and value of postsecondary student unit record systems (PSURSs) by illuminating the condition of state postsecondary data in the U.S. In the "Strong Foundations 2023" survey, which was administered from…
Descriptors: College Students, Student Records, Data Collection, Databases
Data Quality Campaign, 2023
The Data Quality Campaign (DQC) has been reviewing state report cards for the past seven years. They continue to examine the landscape of state report cards because they believe states must increase transparency and build trust by sharing information. But after many years, it was time to look at state report cards with fresh eyes. In addition to…
Descriptors: Parent Attitudes, Data Collection, Information Dissemination, Parents
Miranda Kucera; K. Kawena Begay – Communique, 2025
While the field advocates for a diversified and comprehensive professional role (National Association of School Psychologists, 2020), school psychologists have long spent most of their time in assessment-related activities (Farmer et al., 2021), averaging about eight cognitive evaluations monthly (Benson et al., 2020). Assessment practices have…
Descriptors: Equal Education, Student Evaluation, Evaluation Methods, Standardized Tests
Miranda Kucera; K. Kawena Begay – Communique, 2025
In Part 1 of this series, the authors briefly reviewed some challenges inherent in using standardized tools with students who are not well represented in norming data. To help readers clearly conceptualize the framework steps, the authors present two case studies that showcase how a nonstandardized approach to assessment can be individualized to…
Descriptors: Equal Education, Student Evaluation, Evaluation Methods, Standardized Tests
Kearney, Christopher A.; Childs, Joshua – Preventing School Failure, 2023
School attendance/absenteeism (SA/A) is a crucial indicator of health and development in youth but educational policies and health-based practices in this area rely heavily on a simple metric of physical presence or absence in a school setting. SA/A data suffer from problems of quality (reliability, construct validity, data integrity) and utility…
Descriptors: Attendance, Educational Policy, Health, Improvement
Ford, Karly S.; Rosinger, Kelly; Choi, Junghee – Policy Futures in Education, 2022
Policy researchers have difficulty understanding stratification in enrollment in US higher education when race and ethnicity data are plagued by missing values. Students who decline to ethnoracially self-identify become part of a "race unknown" reporting category. In undergraduate enrollment, "race unknown" students are not…
Descriptors: Admission (School), Competitive Selection, Race, Ethnicity
Díaz, Victoria E.; McKeown, Stephanie; Peña, Camilo – British Columbia Council on Admissions and Transfer, 2023
This project reviews data collection practices regarding race, ethnicity and ancestry (REA) in post-secondary institutions (PSIs) in Canada, as well as in other relevant sectors (e.g., health, K-12 education, government agencies). The goal of the project was to identify promising practices and to develop recommendations to guide REA data…
Descriptors: Data Collection, Data Use, Student Characteristics, Race
Galles, Elyse; Gannon, Jamie; Noniyeva, Yuliana; Schweikert, James; Downs, Nancy – Journal of American College Health, 2023
Objective: College students who receive an acute care visit (ACV) from an emergency or inpatient unit require mental health follow-up (MHF) to improve long-term outcomes. This study describes tracking ACVs and MHF, while identifying characteristics of multiple vs. single ACVs. Participants: 191 students who received an ACV (N = 231) at one public…
Descriptors: College Students, Mental Health, Hospitals, Access to Health Care
Kipton D. Smilie – Paedagogica Historica: International Journal of the History of Education, 2025
In the 1930s schooling in the United States underwent fundamental transformations, ultimately responding to the profound social, economic, and technological changes taking place in the early decades of the twentieth century. Students' social and emotional health needed support, especially for entry into a rapidly changing nation and world. One…
Descriptors: Educational History, Professional Autonomy, Data Collection, Student Characteristics
Bhavik Anil Patel – Journal of Chemical Education, 2022
Accuracy and precision are measures of experimental error and are fundamental to most chemical analysis laboratory classes. Assessment of accuracy and precision is often based on the comprehension of the results generated by students rather than on the quality of the data generated. This activity focused on developing a chemical analysis…
Descriptors: Chemistry, Science Laboratories, Accuracy, Data
Construction and Analysis of a Decision Tree-Based Predictive Model for Learning Intervention Advice
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Casey Gogno; Scott Burden; Wyntre Stout – Association for Institutional Research, 2024
Creating a welcoming community is key for an academic environment to thrive. This approach includes accurately representing community members' identities to understand their experiences, and establishing procedures for recording and utilizing individuals' names to support their ability to express their identities freely and without fear of…
Descriptors: Data Collection, Information Storage, Student Characteristics, Identification