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Silva, Valtemir A.; Bittencourt, Ig Ibert; Maldonado, Jose C. – IEEE Transactions on Learning Technologies, 2019
Question classification is a key point in many applications, such as Question Answering (QA, e.g., Yahoo! Answers), Information Retrieval (IR, e.g., Google search engine), and E-learning systems (e.g., Bloom's tax. classifiers). This paper aims to carry out a systematic review of the literature on automatic question classifiers and the technology…
Descriptors: Questioning Techniques, Classification, Man Machine Systems, Information Retrieval
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Strimel, Greg J.; Morehouse, Abby; Bartholomew, Scott R.; Swift, Colin; Woessner, Jonathan – Technology and Engineering Teacher, 2019
Computational thinking is a problem-solving technique traditionally employed by computer scientists to develop computer applications. However, computational thinking practices are now believed to be applicable to other fields (Google for Education, 2018), specifically those related to engineering and technology. Accordingly, the Advancing…
Descriptors: Computation, Thinking Skills, Assistive Technology, Technology Uses in Education
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Pöllänen, Sinikka; Pöllänen, Kari – Design and Technology Education, 2019
Continually increasing demands are being placed on the educational system to prepare students with technical skills due to the exponential implementation of information, technology and automation in the workforce. Students should work with design, problemsolving and computational methods and tools early on in their school lives in basic education…
Descriptors: Computation, Elementary Secondary Education, Programming, Foreign Countries
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Azhikannickal, Elizabeth – Physics Teacher, 2019
Much data, both published and anecdotal, have shown that students grasp scientific concepts more easily when they are directly involved in the learning via lab experiments or other hands-on activities. Hands-on or experiential learning also appears to aid in students' ability to retain scientific theory. One way to engage students in a first-year…
Descriptors: Science Instruction, Physics, Scientific Concepts, Concept Formation
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Ware, Jordan K. – Education and Urban Society, 2019
The effects of poverty on important outcome measures are devastating and well documented, but the conceptualization and operationalization of socioeconomic status (SES) are underdeveloped. Various indicators of SES are useful for different purposes. Free or reduced-price lunch (FRL) status is commonly used because of its convenience and predictive…
Descriptors: Real Estate, Socioeconomic Status, Mathematics Achievement, Low Income Students
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Agoestanto, Arief; Sukestiyarno, Y. L.; Isnarto; Rochmad; Lestari, M. D. – International Journal of Instruction, 2019
The purpose of this research was to describe the positions and causes of students' errors in algebraic thinking based on the cognitive style. This study was qualitative research with subject consisting of twelve students. The results showed that (1) students with Field Independent type tended to make errors at the stage of comprehension,…
Descriptors: High School Students, Cognitive Style, Secondary School Mathematics, Mathematics Education
Lynn S. Fuchs; Amelia S. Malone; Kristopher J. Preacher; Douglas Fuchs; Amber Y. Wang; Rachel Pachmayr – Grantee Submission, 2019
The purposes of this study were twofold. The first was to test the efficacy of two versions of the "Super Solvers" (SS) intervention for fourth- and fifth-grade students at-risk for mathematics learning disabilities (MLD). The second was to test the value of adding an error analysis component to the SS intervention. Students were…
Descriptors: Program Effectiveness, Fractions, Problem Solving, Mathematics Instruction
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Callies, Sophie; Gravel, Mathieu; Beaudry, Eric; Basque, Josianne – International Journal of Game-Based Learning, 2017
This paper presents an architecture designed for simulation serious games, which automatically generates game-based scenarios adapted to learner's learning progression. We present three central modules of the architecture: (1) the learner model, (2) the adaptation module and (3) the logs module. The learner model estimates the progression of the…
Descriptors: Simulation, Educational Games, Models, Computation
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Young, Cristobal; Holsteen, Katherine – Sociological Methods & Research, 2017
Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…
Descriptors: Models, Ambiguity (Context), Robustness (Statistics), Social Science Research
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Savalei, Victoria; Rhemtulla, Mijke – Journal of Educational and Behavioral Statistics, 2017
In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately…
Descriptors: Computation, Statistical Analysis, Test Items, Maximum Likelihood Statistics
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Fitzherbert, John – Australian Senior Mathematics Journal, 2017
Jagadguru Shankaracharya Swami Bharati Krishna Tirtha (commonly abbreviated to Bharati Krishna) was a scholar who studied ancient Indian Veda texts and between 1911 and 1918 (vedicmaths.org, n.d.) and wrote a collection of 16 major rules and a number of minor rules which have collectively become known as the "sutras of Vedic…
Descriptors: Mathematics, Professional Personnel, Mathematics Instruction, Equations (Mathematics)
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Pudwell, Lara – PRIMUS, 2017
In this paper, we discuss the Experimental Mathematics course taught at Valparaiso University since 2009. We focus on aspects of the course that facilitate students' abilities to ask and explore their own research questions.
Descriptors: Inquiry, Mathematics, Mathematics Instruction, Mathematics Education
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Mix, Kelly S.; Smith, Linda B.; Stockton, Jerri DaSha; Cheng, Yi-Ling; Barterian, Justin A. – Journal of Cognition and Development, 2017
Two experiments examined whether concrete models support place value learning. In Experiment 1 (N = 149), 7-year-olds were trained with either a) symbols alone or b) symbols and base-10 blocks. Children in both groups showed significant growth overall, but there were specific effects favoring one training type over another. Symbols-only training…
Descriptors: Symbols (Mathematics), Models, Number Concepts, Mathematics Instruction
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Koopman, Sarah E.; Mahon, Bradford Z.; Cantlon, Jessica F. – Cognitive Science, 2017
Language and culture endow humans with access to conceptual information that far exceeds any which could be accessed by a non-human animal. Yet, it is possible that, even without language or specific experiences, non-human animals represent and infer some aspects of similarity relations between objects in the same way as humans. Here, we show that…
Descriptors: Evolution, Animals, Discrimination Learning, Inferences
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Lockwood, Elise; Erickson, Sarah – International Journal of Mathematical Education in Science and Technology, 2017
Counting problems offer rich opportunities for students to engage in mathematical thinking, but they can be difficult for students to solve. In this paper, we present a study that examines student thinking about one concept within counting, factorials, which are a key aspect of many combinatorial ideas. In an effort to better understand students'…
Descriptors: Undergraduate Students, Mathematical Concepts, Computation, Semi Structured Interviews
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