NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
No Child Left Behind Act 20011
Assessments and Surveys
Trends in International…1
What Works Clearinghouse Rating
Showing all 11 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Swist, Teresa; Humphry, Justine; Gulson, Kalervo N. – Learning, Media and Technology, 2023
There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…
Descriptors: Algorithms, Data Analysis, Democracy, Design
Franck Salles; Aurélie Lacroix – International Association for the Evaluation of Educational Achievement, 2024
Digital technologies have the potential to revolutionize education by enhancing quality, fairness, and efficiency. However, equitable access to these technologies remains a challenge. ILSAs (international large-scale assessments) have shown that the relationship between digital use and performance varies across countries and over time. To fully…
Descriptors: Achievement Tests, Elementary Secondary Education, Foreign Countries, Mathematics Tests
Peer reviewed Peer reviewed
Direct linkDirect link
Lester, Jaime; Klein, Carrie; Rangwala, Huzefa; Johri, Aditya – ASHE Higher Education Report, 2017
The purpose of this monograph is to give readers a practical and theoretical foundation in learning analytics in higher education, including an understanding of the challenges and incentives that are present in the institution, in the individual, and in the technologies themselves. Among questions that are explored and answered are: (1) What are…
Descriptors: Educational Research, Data Collection, Data Analysis, Higher Education
Peer reviewed Peer reviewed
Direct linkDirect link
van Halem, Nicolette; Cornelisz, Ilja; Daly, Alan; van Klaveren, Chris – International Journal of Research & Method in Education, 2023
In educational contexts where many domains subject to improvement are interdependent and causal evidence is frequently lacking it is difficult, if not impossible, for policymakers and educational practitioners to decide which domain should be invested in. This paper proposes a new method that uses Conditional Mean Independent Correlations (CMIC)…
Descriptors: Educational Improvement, Evaluation Methods, Decision Making, Growth Models
Lesaux, Nonie K., Ed.; Jones, Stephanie M., Ed. – Harvard Education Press, 2016
"The Leading Edge of Early Childhood Education" aims to support the effort to simultaneously scale up and improve the quality of early childhood education by bringing together relevant insights from emerging research to provide guidance for this critical, fledgling field. It reflects the growing recognition that early childhood…
Descriptors: Early Childhood Education, Academic Achievement, Cognitive Development, Emotional Development
National Forum on Education Statistics, 2015
When properly employed, technology may enhance and support learning opportunities available to any student, at any location, and at any time. Determining which instructional and delivery methods are best for a specific individual, group of students, community, or circumstance demands that high-quality data be available to students, parents,…
Descriptors: Elementary Secondary Education, Educational Technology, Technology Uses in Education, Data Collection
Gold, Thomas; Lent, Jessica; Cole, Rachel; Kemple, James; Nathanson, Lori; Brand, Janet – Research Alliance for New York City Schools, 2012
The federal government, states, school districts, and private foundations are investing hundreds of millions of dollars in educational data management systems. The hope for these investments is that providing better information to teachers and administrators, particularly student performance data, will support school-wide planning, inform…
Descriptors: Educational Technology, Technology Uses in Education, Information Systems, Urban Schools
Gold, Thomas; Lent, Jessica; Cole, Rachel; Kemple, James; Nathanson, Lori; Brand, Janet – Research Alliance for New York City Schools, 2012
The federal government, states, school districts, and private foundations are investing hundreds of millions of dollars in educational data management systems. The hope for these investments is that providing better information to teachers and administrators, particularly student performance data, will support school-wide planning, inform…
Descriptors: Educational Technology, Technology Uses in Education, Information Systems, Urban Schools
Gold, Thomas; Lent, Jessica; Cole, Rachel; Kemple, James; Nathanson, Lori; Brand, Janet – Research Alliance for New York City Schools, 2012
The federal government, states, school districts, and private foundations are investing hundreds of millions of dollars in educational data management systems. The hope for these investments is that providing better information to teachers and administrators, particularly student performance data, will support school-wide planning, inform…
Descriptors: Educational Technology, Technology Uses in Education, Information Systems, Urban Schools
Peer reviewed Peer reviewed
Direct linkDirect link
Karim, Nor Shahriza Abdul; Darus, Siti Hawa; Hussin, Ramlah – Campus-Wide Information Systems, 2006
Purpose: This study seeks to explore the utilization of mobile phone services in the educational environment, explore the nature of mobile phone use among university students, and investigate the perception of university students on mobile phone uses in library and information services. Design/methodology/approach: The study used a review of…
Descriptors: Feedback (Response), Undergraduate Students, Research Needs, Academic Libraries
Hardy, Lawrence – American School Board Journal, 2003
Requirements of the No Child Left Behind Act present school districts with a massive lesson in data-driven decision-making. Technology companies offer data-management tools that organize student information from state tests. Offers districts advice in choosing a technology provider. (MLF)
Descriptors: Academic Achievement, Access to Education, Accountability, Compliance (Legal)