There has been increasing interest in applying integrative data analysis (IDA) to analyze data across multiple studies to increase sample size and statistical power. Measures of a construct are frequently not consistent across studies. This article provides a tutorial on the complex decisions that occur when conducting harmonization of measures…

Nurturing student artificial intelligence (AI) competency is crucial in the future of K-12 education. Students with strong AI competency should be able to ethically, safely, healthily, and productively integrate AI into their learning. Research on student AI competency is still in its infancy, primarily focusing on theoretical and professional…

Developing effective assessments is a critical component of quality instruction. Assessments are effective when they are well-aligned with the learning outcomes, can confirm that all intended learning outcomes are attained, and their obtained grades are accurately reflecting the level of student achievement. Developing effective assessments is not…

"Data-drive instruction can distort the way reading is taught, harming the students who need high-quality instruction the most," Susan B. Neuman concludes from her research team's two years of observation in nine low-income New York City schools. She describes how some students are reminded that they are "failures" every day by…

In this technical report we document the development and piloting of the Learning Receptiveness Assessment (LRA) Greenhouse for Prekindergarten. This technological tool was designed to prevent reading disabilities by supporting effective "assessment-guided instructional decision-making" by Preschool teachers. The LRA Greenhouse comprises…

Current preservice teacher education practice related to data use has been deemed inadequate, in that it is unevenly distributed and often superficial. In response, this article describes a course-based classroom assessment data-literacy experience for preservice elementary teachers. Grounded in extant theory and research concerning data literacy…

The population of Spanish-speaking preschoolers in the United States continues to increase and there is a significant need to develop psychometrically sound early language and literacy screening measures to accurately capture children's ability in Spanish. In this paper, we describe the innovative design and calibration process of the new…

This pre- and posttest multiple-case study examined the effectiveness and usability of the Sensory Processing Measure-Preschool Quick Tips (SPM-P QT) by key stakeholders (parents and teachers) for implementing data-driven intervention to address sensory processing challenges. The Sensory Processing Measure-Preschool (SPM-P) was administered as an…

As more instructors articulate learning objectives for their students within one course, or academic staff collaborate to articulate learning outcomes for programs, a robust means to assess student performance within these becomes increasingly important. The Examinations Institute of the American Chemical Society (ACS), Division of Chemical…

This dissertation is developed around two studies created with the goal of describing and quantifying current educators' knowledge and perceptions of reading assessment and subsequent data-based instructional decision making. Unique to the field, a critical component of this study is an emphasis on educators' development of "data…

This study explored the data-based decision making of 12 teachers in grades 6-8 who were asked about their perceptions and use of three required interim measures of reading performance: oral reading fluency (ORF), retell, and a benchmark comprised of released state test items. Focus group participants reported they did not believe the benchmark or…