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O'Sullivan, Kathy; O'Meara, Niamh; Goos, Merrilyn; Conway, Paul – Irish Educational Studies, 2021
Our everyday lives have been transformed in 2020. Key features of this transformation have been the significance of COVID-related numeracy in our everyday lives and the realisation of the story it might tell about lives, health and death. In recent years, governments and educators around the world have been advocating for numeracy as an essential…
Descriptors: COVID-19, Pandemics, Numeracy, Misconceptions
Ostermann, Andreas; Leuders, Timo; Nückles, Matthias – Journal of Mathematics Teacher Education, 2018
To teach adaptively, teachers should be able to take the students' level of knowledge into account. Therefore, a key component of pedagogical content knowledge (PCK) is the ability to assume the students' perspectives. However, due to the so-called expert blind spot, teachers tend to misestimate their students' knowledge, such as when estimating…
Descriptors: Difficulty Level, Preservice Teachers, Mathematics, Graphs
Chimhande, Tinoda; Naidoo, Ana; Stols, Gerrit – Africa Education Review, 2017
This article reports on a study of six Grade 11 learners' levels of understanding of concepts related to the function definition and representation. Task-based clinical interviews were used to elicit the learners' interpretations and reasoning when working with these function-related concepts. Indicators for Action-Process-Object-Schema (APOS)…
Descriptors: Grade 11, Mathematics Instruction, Mathematical Concepts, Case Studies
El-khateeb, Mahmoud M. A. – Journal of Education and Learning, 2015
The purpose of this study was to investigate the misperceptions and performance of king Saud University students' about concept and finding the limit of same partial functions given in the form of both graphical and symbolic. In the collection of the data, the researcher employed the open-ended question test consisted of four items. Firstly,…
Descriptors: Foreign Countries, College Students, Student Attitudes, Misconceptions
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
McKnight, Curtis C.; Fisher, Mark A. – 1990
Knowledge representations and mental models from graphically presented information were investigated for 98 college students with different levels of mathematics experience. The subjects were drawn from a remedial algebra course (n=35), a second semester calculus course (n=35), and a calculus-based statistics course (n=28); they were all exposed…
Descriptors: Cognitive Processes, College Students, Comparative Analysis, Concept Formation
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
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

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