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Ebru Öztürk; Erol Duran – Educational Policy Analysis and Strategic Research, 2024
In this study, it was aimed to develop a rubric to evaluate the creative story writing skill levels of seventh grade secondary school students. The research was designed in quantitative research method and survey model. In the research, convenience sampling technique was used and 270 students studying at the seventh grade level of secondary school…
Descriptors: Scoring Rubrics, Writing Evaluation, Creative Writing, Middle School Students
Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – Grantee Submission, 2023
Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…
Descriptors: Middle School Students, Middle School Mathematics, Reading Comprehension, Intelligent Tutoring Systems
Implications of Bias in Automated Writing Quality Scores for Fair and Equitable Assessment Decisions
Matta, Michael; Mercer, Sterett H.; Keller-Margulis, Milena A. – School Psychology, 2023
Recent advances in automated writing evaluation have enabled educators to use automated writing quality scores to improve assessment feasibility. However, there has been limited investigation of bias for automated writing quality scores with students from diverse racial or ethnic backgrounds. The use of biased scores could contribute to…
Descriptors: Bias, Automation, Writing Evaluation, Scoring
Implications of Bias in Automated Writing Quality Scores for Fair and Equitable Assessment Decisions
Michael Matta; Sterett H. Mercer; Milena A. Keller-Margulis – Grantee Submission, 2023
Recent advances in automated writing evaluation have enabled educators to use automated writing quality scores to improve assessment feasibility. However, there has been limited investigation of bias for automated writing quality scores with students from diverse racial or ethnic backgrounds. The use of biased scores could contribute to…
Descriptors: Bias, Automation, Writing Evaluation, Scoring
Leach, Stephen Michael – ProQuest LLC, 2022
School climate is increasingly recognized by scholars and policymakers as a crucial factor associated with students' educational experiences. Hence, practitioners endeavor to equitably measure and improve school climate to promote favorable student academic and behavior outcomes. Unfortunately, school climate research is fragmented, and a…
Descriptors: Psychometrics, School Surveys, Student Surveys, Middle School Students
Pamela R. Buckley; Katie Massey Combs; Karen M. Drewelow; Brittany L. Hubler; Marion Amanda Lain – Evaluation Review, 2025
As evidence-based interventions are scaled, fidelity of implementation, and thus effectiveness, often wanes. Validated fidelity measures can improve researchers' ability to attribute outcomes to the intervention and help practitioners feel more confident in implementing the intervention as intended. We aim to provide a model for the validation of…
Descriptors: Middle School Students, Middle School Teachers, Evidence Based Practice, Program Development
Jing Liu; Megan Kuhfeld; Monica Lee – Annenberg Institute for School Reform at Brown University, 2023
Noncognitive constructs such as self-efficacy, social awareness, and academic engagement are widely acknowledged as critical components of human capital, but systematic data collection on such skills in school systems is complicated by conceptual ambiguities, measurement challenges and resource constraints. This study addresses this issue by…
Descriptors: Student Behavior, Predictor Variables, Predictive Validity, Academic Achievement
Kathleen Lynne Lane; Wendy Peia Oakes; Mark Matthew Buckman; Nathan Allen Lane; Katie Scarlett Lane; Kandace Fleming; Rebecca E. Swinburne Romine; Rebecca L. Sherod; Emily Dawn Cantwell; Chi-Ning Chang – Grantee Submission, 2024
Introduction: We report predictive validity of the newly defined Student Risk Screening Scale -- Internalizing and Externalizing (SRSS-IE 9, with 9 items) when used for the first time by middle and high school teachers from 43 schools. Methods: The sample included 11,773 middle school-aged students representing four geographic regions, and 7,244…
Descriptors: Predictive Validity, Middle School Students, High School Students, At Risk Students
Klingbeil, David A.; Osman, David J.; Carrigan, Jamison E.; Paly, Benjamin J.; Berry-Corie, Kimberly – School Psychology, 2021
Multiple popular math curriculum-based measures have recently been revised in ways that may improve their utility for universal screening. However, the applied use of these tools has yet to be evaluated independently. We conducted a retrospective analysis of the diagnostic accuracy of prior year statewide test results and aimswebPlus math…
Descriptors: Screening Tests, Elementary School Students, Middle School Students, Curriculum Based Assessment
Carla Wood; Miguel Garcia-Salas; Christopher Schatschneider – Grantee Submission, 2023
Purpose: The aim of this study was to advance the analysis of written language transcripts by validating an automated scoring procedure using an automated open-access tool for calculating morphological complexity (MC) from written transcripts. Method: The MC of words in 146 written responses of students in fifth grade was assessed using two…
Descriptors: Automation, Computer Assisted Testing, Scoring, Computation
Garret J. Hall; Emma Doyle; Edgardo Mejias Vazquez – Learning Disabilities Research & Practice, 2025
Using data from students in Grades 3-8 in school years 2018-2019 (N = 1,871) and 2021-2022 (N = 1,740), we examined the strength of fall math screening using Measures of Academic Progress (MAP) for predicting end-of-year state math assessment performance levels and whether this prediction varied across English language proficiency (ELP). In…
Descriptors: Screening Tests, Mathematics Tests, Achievement Tests, Mathematics Achievement
Christopher Cleveland; Ethan Scherer – Educational Researcher, 2025
Education leaders need valid metrics to predict students' long-term success. We use a unique data set with cognitive skills, self-regulation, behavior, course performance, and test scores for eighth-grade students from a Northeast school district. We link these data to students' high school outcomes, college enrollment, persistence, and on-time…
Descriptors: Middle School Students, Grade 8, Student Surveys, Self Evaluation (Individuals)
Herman, Keith C.; Reinke, Wendy M.; Huang, Francis L.; Thompson, Aaron M.; Doyle-Barker, Levi – School Psychology, 2021
Early adolescence represents a critical developmental period for the identification, prevention, and early intervention of mental health concerns. The Early Identification System--Student Report (EIS-SR) was developed as a user-friendly, accessible, and cost-efficient method for identifying youth at risk for mental health concerns. The present…
Descriptors: Psychometrics, Identification, Screening Tests, Middle School Students
J. Anthony, Christopher; Styck, Kara M.; Cooke, Erin; Martel, Justin R.; E. Frye, Katherine – School Psychology Review, 2022
Behavior rating scales represent one of the most commonly used types of assessments in school psychology. Yet, they suffer from a fundamental limitation: They are an indirect methodology influenced partially by student behavior and partially by rater perspectives. Thus, the current study utilized advanced analytic approaches to evaluate rater…
Descriptors: Behavior Rating Scales, Evaluators, Student Evaluation, Elementary School Students
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables