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Sirnoorkar, Amogh; Mazumdar, Anwesh; Kumar, Arvind – Physical Review Physics Education Research, 2020
We elaborate on a new approach of assessing content-based epistemic clarity of college physics students in terms of their ability to discriminate between different epistemic warrants for propositions in a chained argument in physics. A threefold classification (nominal, physical, and mathematical) of warrants is used, with each class split into a…
Descriptors: Physics, Science Instruction, College Science, Measurement Techniques
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Schneider, Kent N.; Becker, Lana L.; Berg, Gary G. – Accounting Education, 2017
Given that the usage and complexity of spreadsheets in the accounting profession are expected to increase, it is more important than ever to ensure that accounting graduates are aware of the dangers of spreadsheet errors and are equipped with design skills to minimize those errors. Although spreadsheet mechanics are prevalent in accounting…
Descriptors: Accounting, Spreadsheets, Error Patterns, Error Correction
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Lewis, Heather A. – PRIMUS, 2015
Teachers often promote care in doing calculations, but for most students a single mistake rarely has major consequences. This article presents several real-life events in which relatively minor mathematical errors led to situations that ranged from public embarrassment to the loss of millions of dollars' worth of equipment. The stories here…
Descriptors: Mathematics Instruction, Error Patterns, College Mathematics, Undergraduate Study
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Spinelli, Giacomo; Goldsmith, Samantha F.; Lupker, Stephen J.; Morton, J. Bruce – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
According to some accounts, the bilingual advantage is most pronounced in the domain of executive attention rather than inhibition and should therefore be more easily detected in conflict adaptation paradigms than in simple interference paradigms. We tested this idea using two conflict adaptation paradigms, one that elicits a list-wide…
Descriptors: Bilingualism, Executive Function, Attention Control, Interference (Language)
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Arzumanyan, George; Halcoussis, Dennis; Phillips, G. Michael – American Journal of Business Education, 2015
This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small…
Descriptors: Business Administration Education, Error of Measurement, Error Patterns, Intervals
Wang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection