G
Geneva Haertel
Researcher at SRI International
Publications - 29
Citations - 1022
Geneva Haertel is an academic researcher from SRI International. The author has contributed to research in topics: Educational assessment & Software design pattern. The author has an hindex of 14, co-authored 29 publications receiving 932 citations.
Papers
More filters
Journal ArticleDOI
Implications of Evidence‐Centered Design for Educational Testing
Robert J. Mislevy,Geneva Haertel +1 more
TL;DR: This article describes ECD in terms of layers for analyzing domains, laying out arguments, creating schemas for operational elements such as tasks and measurement models, implementing the assessment, and carrying out the operational processes.
Book ChapterDOI
Evidence-Centered Assessment Design
TL;DR: This chapter reviews the basic concepts of ECD, focusing on evidentiary arguments, and defines the attributes of design patterns, and shows the roles they play in creating tasks around valid assessment arguments.
Journal ArticleDOI
Investigating Links from Teacher Knowledge, to Classroom Practice, to Student Learning in the Instructional System of the Middle-School Mathematics Classroom.
TL;DR: This article examined the relationship between teachers' mathematics knowledge, teachers' classroom decision making, and student achievement outcomes on topics of rate, proportionality, and linear function in prealgebra.
Book
Evaluating educational technology : effective research designs for improving learning
Geneva Haertel,Barbara Means +1 more
TL;DR: This volume outlines research designs, methodologies and types of assessments that can be used to evaluate educational technologies more efficiently and provide critical evidence of the impact of technology upon student learning.
Journal ArticleDOI
A “conditional” sense of fairness in assessment
Robert J. Mislevy,Geneva Haertel,Britte Haugan Cheng,Liliana Ructtinger,Angela Haydel DeBarger,Elizabeth Murray,David H. Rose,Jenna W. Gravel,Alexis M. Colker,Daisy Rutstein,Terry Vendlinski +10 more
TL;DR: In this paper, the authors build on recent research in universal design for learning, assessment design, and psychometrics to lay out the rationale for inference that is conditional on matching examinees with principled variations of an assessment so as to reduce construct-irrelevant demands.