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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
15,140 datasets
An ACT-R model provided an excellent quantitative account of data from response signal experiments on associative recognition. The data, from Carnegie Mellon University, examines how associative fan affects the speed-accuracy tradeoff in memory retrieval. It includes results from experiments with both briefly studied and well-learned materials.
Two experiments examined the psychological and biological antecedents of hierarchical differentiation and its consequences for group productivity and conflict. Experiment 1 used a priming manipulation, while Experiment 2 used a biological marker of dominance motivation. The research was authored by Richard Ronay of Columbia University.
Texas high school sophomores and seniors were surveyed to examine post-graduation decision-making, with a target of 33,000 to 35,000 baseline interviews. The dataset, from Princeton University researcher Marta Tienda, includes follow-up surveys tracking college attendance, military enlistment, employment, and life events. Analysis is designed for multiple levels including student, school, and district, with separate examination by racial/ethnic subgroups.
Janet A. Weiss introduces a special issue examining the dual roles of data systems in U.S. public education. The collection of articles explores how data is used both to improve school staff performance and to hold schools and districts accountable for outcomes. This work, from the University of Michigan, analyzes the different logics of action and intervention behind these data strategies.
Approximately 290 primary school teachers in Canton Vaud, Switzerland, responded to two web-based sustainability surveys following a professional development program. The data was used to model the sustainability of a digital education curricular reform that took place from September 2019 to March 2020. Laila El‐Hamamsy from École Polytechnique Fédérale de Lausanne authored this dataset, which is accepted for publication in Education and Information Technologies.
Replication data from Stanford University for a paper introducing a constrained priority mechanism. The mechanism combines machine-learning outcome predictions with preference-based matching, applied to refugee family and kindergarten student assignment. The data likely contains records for agents, preferences, and predicted outcome scores.
Approximately 1200 primary alphabetical entries define terms for chemists and other non-immunologists working in immunotoxicology. The glossary, authored by Douglas M. Templeton of the University of Toronto, includes annexes on common abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents. Its primary objective is to provide a self-contained reference for understanding the literature of immunology in the context of occupational and environmental risk assessment.
A glossary of about 1200 primary alphabetical entries related to immunotoxicology, compiled by Douglas M. Templeton of the University of Toronto. It includes terms from basic and clinical immunology, with annexes covering abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents. The document aims to aid chemists, toxicologists, pharmacologists, medical practitioners, risk assessors, and regulatory authorities in understanding immunology literature.
A glossary of about 1200 terms compiled by Douglas M. Templeton of the University of Toronto to provide clear definitions for non-immunologists working in immunotoxicology. It includes primary alphabetical entries and annexes covering abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents. The document aims to facilitate the use of chemistry in occupational and environmental risk assessment.
A glossary of about 800 terms compiled by Douglas M. Templeton of the University of Toronto. It provides definitions for terms related to basic and clinical neurology, focusing on diagnosing, measuring, and understanding the effects of substances on the nervous system. The resource includes annexes of common abbreviations and examples of chemicals with known neurotoxic effects.
1200 primary alphabetical entries define terms for chemists and other non-immunologists contributing to immunotoxicology studies. The glossary, authored by Douglas M. Templeton of the University of Toronto, includes annexes on common abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents. Its purpose is to facilitate the understanding of immunology literature for occupational and environmental risk assessment.
About 800 primary alphabetical entries define terms for neurotoxicology, basic and clinical neurology, and the effects of substances on the nervous system. The glossary was authored by Douglas M. Templeton of the University of Toronto and includes annexes of common abbreviations and examples of chemicals. It is intended to aid chemists, toxicologists, pharmacologists, medical practitioners, risk assessors, and regulatory authorities.
Douglas M. Templeton at the University of Toronto compiled a glossary of about 800 terms for neurotoxicology. The document provides definitions for non-specialists, especially chemists, and includes annexes with common abbreviations and examples of neuroactive chemicals. Its primary aim is to facilitate the understanding of neurotoxic effects in occupational and environmental risk assessment.
800 primary alphabetical entries define terms for neurotoxicology and related neurology fields. The glossary was authored by Douglas M. Templeton of the University of Toronto to aid non-specialists. It includes annexes with common abbreviations and examples of chemicals affecting the nervous system.
800 primary alphabetical entries define terms for chemists, toxicologists, and risk assessors working in neurotoxicology. Douglas M. Templeton of the University of Toronto compiled this glossary to aid non-specialists in interpreting literature on nervous system effects. The resource includes annexes with common abbreviations and examples of chemicals with known neurotoxic effects.
A glossary of about 1200 terms related to immunotoxicology, compiled by Douglas M. Templeton of the University of Toronto. It provides definitions for chemists, toxicologists, pharmacologists, and medical practitioners to understand the literature of immunology, particularly for diagnosing and measuring effects of substances on the immune system. The document includes primary alphabetical entries and annexes with abbreviations, example chemicals, autoantibodies, and therapeutic agents.
A glossary of about 1200 primary alphabetical entries compiled by Douglas M. Templeton of the University of Toronto. The document provides clear definitions for non-immunologists, especially chemists, contributing to immunotoxicology studies. It includes terms related to basic and clinical immunology, with annexes covering abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents.
1200 primary alphabetical entries define terms for immunotoxicology studies. The glossary includes annexes for common abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents. Douglas M. Templeton from the University of Toronto authored this resource to aid non-immunologists.
A glossary of about 800 terms related to neurotoxicology, compiled by Douglas M. Templeton of the University of Toronto. It provides definitions for terms in basic and clinical neurology, focusing on diagnosing, measuring, and understanding effects of substances on the nervous system. The document includes annexes of common abbreviations and examples of chemicals with known neurotoxic effects.
A glossary of about 1200 primary alphabetical entries related to immunotoxicology, compiled by Douglas M. Templeton of the University of Toronto. It includes terms from basic and clinical immunology, with annexes covering abbreviations, chemicals affecting the immune system, autoantibodies, and therapeutic agents. The primary objective is to provide clear definitions for non-immunologists, such as chemists, contributing to immunotoxicology studies.