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Scott, Marcus W. – ProQuest LLC, 2018
One way that examinees can gain an unfair advantage on a test is by having prior access to the test questions and their answers, known as preknowledge. Determining which examinees had preknowledge can be a difficult task. Sometimes, the compromised test content that examinees use to get preknowledge has mistakes in the answer key. Examinees who…
Descriptors: Cheating, Answer Keys, Tests, Identification
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Savi, Alexander O.; Deonovic, Benjamin E.; Bolsinova, Maria; van der Maas, Han L. J.; Maris, Gunter K. J. – Journal of Educational Data Mining, 2021
In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…
Descriptors: Learning Processes, Cognitive Processes, Error Patterns, Models
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Decuypere, Mathias; Landri, Paolo – Critical Studies in Education, 2021
University rankings have become commonplace in higher education. Traditional quantified rankings do not merely measure educational performance: they equally grant status, enforce competition between institutions, and are emblematic for the ongoing capitalization of higher education. Drawing on the field of Science and Technology Studies, this…
Descriptors: Universities, Institutional Evaluation, Educational Quality, Institutional Characteristics
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Bridges, Eileen – Journal of Marketing Education, 2021
This article looks back over the past two decades to describe how teaching of undergraduate marketing research has (or has not) changed. Sweeping changes in technology and society have certainly affected how marketing research is designed and implemented--but how has this affected teaching of this important topic? Although the purpose of marketing…
Descriptors: Marketing, Undergraduate Students, Educational Change, Teaching Methods
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McFadden, Rory R.; Viskupic, Karen; Egger, Anne E. – Journal of Geoscience Education, 2021
Quantitative literacy is a foundational component of success in STEM disciplines and in life. Quantitative concepts and data-rich activities in undergraduate geoscience courses can strengthen geoscience majors' understanding of geologic phenomena and prepare them for future careers and graduate school, and provide real-world context to apply…
Descriptors: Earth Science, College Science, College Faculty, Mathematics Skills
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Hartong, Sigrid; Piattoeva, Nelli – Critical Studies in Education, 2021
This paper contributes to a growing body of research on the increasing datafication of schooling, which has become a salient topic in comparative education and education policy research. Specifically, we address the rising scholarly concern about the meaning of (comparing) contexts as bounded localities facing an increasingly fluid and generative…
Descriptors: Data Analysis, Comparative Education, Educational Policy, Standardized Tests
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Boaler, Jo; LaMar, Tanya; Williams, Cathy – Mathematics Teacher: Learning and Teaching PK-12, 2021
Over the course of 18 months, teams at the University of Chicago and Stanford University joined with other leaders across the United States and world to consider the issue of the types of mathematics used in the classroom. It quickly became clear that all students--starting from the youngest in prekindergarten to those in college--need to learn…
Descriptors: Mathematics Instruction, Teaching Methods, Kindergarten, Elementary Secondary Education
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Jones, Thomas J.; Ehlers, Todd A. – Journal of Geoscience Education, 2021
The need for geoscience students to develop a quantitative skillset is ever increasing. However, this can be difficult to implement in university-style lecture courses in a way that is both manageable for the instructor and does not involve lengthy, potentially repetitive, question sheets for the students. Here, a method for teaching dimensional…
Descriptors: Earth Science, Science Experiments, Graduate Students, College Science
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Schwortz, Andria C.; Burrows, Andrea C. – Research in Science & Technological Education, 2021
Background: Dataset skills are used in STEM fields from astronomy to zoology. Few fields explicitly teach students the skills to analyze datasets, and yet the increasing push for authentic science implies these skills should be taught. Purpose: The overarching motivation of this work is to understand authentic science learning of STEM dataset…
Descriptors: Authentic Learning, STEM Education, Science Activities, Data Analysis
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Weiss, Charles J. – Journal of Chemical Education, 2021
Scientific computing and computer literacy are increasingly important skills for chemistry students to learn, but despite this need, there is an absence of chemistry-specific texts available for teaching the subject. This article introduces a freely available textbook released under a Creative Commons license for use in an undergraduate scientific…
Descriptors: Science Instruction, Chemistry, College Science, Undergraduate Study
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Ballance, Oliver James – ReCALL, 2021
Narrow reading has the potential to reduce vocabulary load and to provide rich opportunities for developing collocation knowledge, but these benefits rely on narrow reading increasing lexical repetition within a text. Hence, interest in narrow reading has been limited by the relatively small lexical effect of narrowing reading by topic (Nation,…
Descriptors: Cognitive Ability, Vocabulary Development, Predictor Variables, Teaching Methods
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Zieffler, Andrew; Justice, Nicola; delMas, Robert; Huberty, Michael D. – Journal of Statistics and Data Science Education, 2021
Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…
Descriptors: Mathematical Models, Thinking Skills, Teaching Methods, Statistics Education
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Polak, Julia; Cook, Dianne – Journal of Statistics and Data Science Education, 2021
Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…
Descriptors: Artificial Intelligence, Data Analysis, Models, Competition
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Schwab-McCoy, Aimee; Baker, Catherine M.; Gasper, Rebecca E. – Journal of Statistics and Data Science Education, 2021
In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…
Descriptors: Statistics Education, Higher Education, College Students, Teaching Methods
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Gibson, Patrick; Robles, Ashley – Center for Learner Equity, 2021
This technical brief is part of an ongoing series the Center for Learner Equity (CLE) launched in 2015 that examines the enrollment and experiences of students with disabilities in different school settings. Using the 2017-2018 Civil Rights Data Collection (CRDC) data released earlier this year, this brief focuses on the number and percentages of…
Descriptors: Students with Disabilities, Charter Schools, Public Schools, Data Analysis
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