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Rebecka Rundquist; Kristina Holmberg; John Rack; Zeynab Mohseni; Italo Masiello – Journal of Learning Analytics, 2024
The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper…
Descriptors: Learning Analytics, Elementary Secondary Education, Mathematics Education, Data Analysis
Amukune, Stephen; Caplovitz Barrett, Karen; Józsa, Krisztián – Journal of New Approaches in Educational Research, 2022
Precise assessment of school readiness is critical because it has practical and theoretical implications for children's school and life success. However, school readiness assessment mainly relies on teacher reports and a few direct evaluations requiring a trained examiner. Studies indicate that 80% of games and apps target preschool children and…
Descriptors: Game Based Learning, Evaluation Methods, Student Evaluation, School Readiness
Harris, Lois; Wyatt-Smith, Claire; Adie, Lenore – Teachers and Teaching: Theory and Practice, 2020
Data walls are a data use practice increasingly being adopted in western, Anglophone countries to display student academic achievement data. The purpose of data walls is to improve teaching and learning by helping teachers and/or students to identify patterns of growth and achievement, set goals, and plan instructional interventions or…
Descriptors: Academic Achievement, Data Use, Teaching Methods, Goal Orientation
Fischer, Christian; Pardos, Zachary A.; Baker, Ryan Shaun; Williams, Joseph Jay; Smyth, Padhraic; Yu, Renzhe; Slater, Stefan; Baker, Rachel; Warschauer, Mark – Review of Research in Education, 2020
The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with…
Descriptors: Data Analysis, Data Collection, Decision Making, Instructional Effectiveness
Datnow, Amanda; Hubbard, Lea – Teachers College Record, 2015
Background: Data use has been promoted as a panacea for instructional improvement. However, the field lacks a detailed understanding of how teachers actually use assessment data to inform instruction and the factors that shape this process. Purpose: This article provides a review of literature on teachers' use of assessment data to inform…
Descriptors: Data Analysis, Teaching Methods, Information Utilization, Literature Reviews
Lachlan-Haché, Lisa – American Institutes for Research, 2015
Student learning measures have rapidly become common in teacher evaluation systems across the United States. Over half of the country's states have required, recommended, or identified "student learning objectives" (SLOs) as a measure of student growth for use in educator evaluation. Although SLO-type measures vary significantly in terms…
Descriptors: Behavioral Objectives, Synthesis, Program Implementation, Educational Research
Drent, Marjolein; Meelissen, Martina R. M.; van der Kleij, Fabienne M. – Journal of Curriculum Studies, 2013
Worldwide, the interest of policy-makers in participating in studies from the International Association for the Evaluation of Educational Achievement (IEA), such as Trends in International Mathematics and Science Study (TIMSS) has been growing rapidly over the past two decades. These studies offer the opportunity to relate the teaching and…
Descriptors: International Programs, Mathematics Achievement, Science Achievement, Data Analysis
Nelsestuen, Kari; Scott, Caitlin; Hanita, Makoto; Robinson, LeAnne; Coskie, Tracy – Regional Educational Laboratory at Education Northwest, 2009
This study compares the experiences and perceptions of new and experienced teachers in 235 schools in six western states (Alaska, Arizona, Idaho, Montana, Washington, and Wyoming) that have adopted the Reading First school reform initiative. Using previously collected data from surveys and interviews, the study considers four areas of the reform…
Descriptors: Feedback (Response), Teacher Collaboration, Educational Change, Data Analysis
Englert, Kerry; Fries, Dawn; Goodwin, Bryan; Martin-Glenn, Mya; Michael, Sheri – US Department of Education, 2004
This study helps to illuminate how a group of principals use data in light of new state and national requirements for accountability. On a very positive note, the responding principals reported using data to a great extent in their own practices, and they are encouraging their staff to use data in ways that align with the notion of effective…
Descriptors: Federal Legislation, Student Improvement, Rewards, Data Analysis
Appalachia Educational Laboratory at Edvantia (NJ1), 2005
The School Improvement Specialist Project prepared seven modules. School improvement specialists, as defined by the Appalachia Educational Laboratory at Edvantia, are change agents who work with schools to help them improve in the following areas so as to increase student achievement. These modules are intended to provide training materials for…
Descriptors: Specialists, Literature Reviews, Learning Modules, Educational Change

Garfield, Joan – Teaching Statistics, 1995
Summarizes 19 papers presented at the Fourth International Conference on Teaching Statistics held in Morocco, July 1994. Papers presented were in five categories: (1) empirical studies on students' conceptions; (2) theoretical papers on teaching and learning; (3) assessment; (4) using computers in teaching probability and statistics; and (5) data…
Descriptors: Computer Uses in Education, Concept Formation, Data Analysis, Learning Theories

Fuchs, Lynn S. – Remedial and Special Education (RASE), 1986
Formative evaluation focuses on program modification based on ongoing measurement of student progress. The literature on formative evaluation for mildly handicapped students indicates that four measurement dimensions are critical: (1) focus of measurement; (2) frequency of measurement; (3) data display; and (4) data utilization methods. (Author/CB)
Descriptors: Data Analysis, Data Interpretation, Evaluation Criteria, Evaluation Utilization
Pascarella, Ernest; And Others – 1992
This report sought to test the hypothesis that living on campus fosters cognitive growth by estimating the relative freshman-year gains in reading comprehension, mathematical reasoning, and critical thinking of resident and commuter students at an urban university. Data were collected from 210 college freshmen students at a large research…
Descriptors: Academic Achievement, Cognitive Measurement, Cognitive Tests, College Freshmen
Jarvis, Gilbert A.; Adams, Shirley J. – 1979
This introduction to second language program evaluation begins with a rationale outlining the major issues involved in program evaluation. Procedures for evaluation are described, and examples are offered of goal statements, sub-goal statements, curriculum objectives, and learning objectives. Guidelines for judging a statement of aims are listed.…
Descriptors: Classroom Observation Techniques, Data Analysis, Data Collection, Educational Objectives