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Soyoung Park; Pamela M. Stecker; Sarah R. Powell – Intervention in School and Clinic, 2024
This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…
Descriptors: Student Evaluation, Individualized Instruction, Mathematics Instruction, Progress Monitoring
Steven Snead – ProQuest LLC, 2024
Data-based decision-making has been a frequently used policy and practice intervention used in schools to help inform the decision-making processes of educational practitioners, with the aim of improving student outcomes. Interim benchmark assessments are designed by commercial test developers to support educators in this framework. In fact, the…
Descriptors: Student Evaluation, Data Analysis, Educational Practices, Decision Making
Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
Boesdorfer, Sarah B.; Del Carlo, Dawn I.; Wayson, Jessica – Research in Science Education, 2022
Despite the promotion of data-driven or data-informed instructional practices in teacher education and professional development, past research indicates that teachers use a limited number of sources for student data to make short-term adjustments to their teaching in order to address deficiencies in student learning. Science teachers, with a more…
Descriptors: Secondary School Teachers, Data Use, Teaching Methods, Data Analysis
Maja Hojer Bruun; Thea Engstrøm Vejlin – Discourse: Studies in the Cultural Politics of Education, 2025
How are educational values and pedagogical approaches inscribed into automated education technologies and their data visualizations? In this article we analyze the design process and technical and pedagogical debates of a team of researchers and developers working on an automated scoring tool for primary school students' early writing as part of…
Descriptors: Data Analysis, Visual Aids, Educational Technology, Automation
Regan, Kelley; Evmenova, Anya S.; Hutchison, Amy; Day, Jamie; Stephens, Madelyn; Verbiest, Courtney; Gafurov, Boris – TEACHING Exceptional Children, 2022
The process of analyzing student data to determine an appropriate instructional decision is crucial for student academic growth. This article details how teachers can make data-driven decisions to carefully design writing instruction. Steps are presented for teachers to follow throughout the data driven decision-making process in order to meet…
Descriptors: Writing Instruction, Decision Making, Essays, Data Analysis
Kathy Strunk; Andrew R. Hinkle; Sheryl S. Lazarus; Carol Seay; Kascinda Fleming – National Center on Educational Outcomes, 2024
For many years state education agencies (SEAs) have sought to create assessment systems that include all students, including students with disabilities. In order to improve outcomes for students with disabilities, there is an urgent need for cross-agency collaboration between special education and assessment offices, but other offices (e.g.,…
Descriptors: Agency Cooperation, Student Evaluation, Students with Disabilities, State Departments of Education
Švábenský, Valdemar; Vykopal, Jan; Celeda, Pavel; Tkácik, Kristián; Popovic, Daniel – Education and Information Technologies, 2022
Hands-on cybersecurity training allows students and professionals to practice various tools and improve their technical skills. The training occurs in an interactive learning environment that enables completing sophisticated tasks in full-fledged operating systems, networks, and applications. During the training, the learning environment allows…
Descriptors: Computer Security, Information Security, Training, Data Collection
Taylor V. Williams – ProQuest LLC, 2022
Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…
Descriptors: Multivariate Analysis, Data Analysis, Student Evaluation, Large Group Instruction
Fawcett, Darcy – set: Research Information for Teachers, 2019
This Assessment News article introduces readers to a statistical approach to making sense of student assessment data in order to help teachers understand whether or not changes in practice have made a difference to learning. It Worked! is the brainchild of Darcy Fawcett, HoD Science at Gisborne Boys' High School, and Across-School Teacher for the…
Descriptors: Data Analysis, Data Use, Evidence Based Practice, Communities of Practice
Nathan Helsabeck; Jessica A. R. Logan – International Journal of Research & Method in Education, 2024
Assessing student achievement over multiple years is complicated by students' memberships in shifting upper-level nesting structures. These structures are manifested in (1) annual matriculation to different classrooms and (2) mobility between schools. Failure to model these shifting upper-level nesting structures may bias the inferences…
Descriptors: Academic Achievement, Student Evaluation, Growth Models, Data Analysis
Stephanie Fuchs; Alexandra Werth; Cristóbal Méndez; Jonathan Butcher – Journal of Engineering Education, 2025
Background: High-quality feedback is crucial for academic success, driving student motivation and engagement while research explores effective delivery and student interactions. Advances in artificial intelligence (AI), particularly natural language processing (NLP), offer innovative methods for analyzing complex qualitative data such as feedback…
Descriptors: Artificial Intelligence, Training, Data Analysis, Natural Language Processing
J. Vincent Nix; Yi-Chin Wu; Lan Misty Song; Joseph D. Levy – Research & Practice in Assessment, 2024
Traditionally, assessment professionals use analyses relying upon null hypothesis significance testing (NHST), but those tools have limitations when analyzing small samples or disaggregated data. This study used common NHST analytical techniques, compared their results, and then explored an alternative technique that perhaps allows for a more…
Descriptors: Sample Size, Statistical Significance, MOOCs, Geographic Location
Thomas R. Guskey, Editor; Cassandra Erkens, Contributor; Katie White, Contributor; Mandy Stalets, Contributor; Garnet Hillman, Contributor; Tim Brown, Contributor; Tom Hierck, Contributor; Tom Schimmer, Contributor; Sharon V. Kramer, Contributor; Sarah Schuhl, Contributor; Anthony R. Reibel, Contributor; Joellen Killion, Contributor – Solution Tree, 2025
In "The Teacher as Assessment Leader, Second Edition," editor Thomas R. Guskey and expert contributors offer research-backed strategies for re-envisioning assessment to enhance student learning and teacher instruction. The authors provide actionable steps, practical examples, and strategies for utilizing formative assessments. These…
Descriptors: Teacher Leadership, Formative Evaluation, Data Analysis, Evidence Based Practice
Achmad Bisri; Supardi; Yayu Heryatun; Hunainah; Annisa Navira – Journal of Education and Learning (EduLearn), 2025
In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…
Descriptors: Data Analysis, Models, Academic Achievement, Evaluation Methods

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