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Luiz Rodrigues; Filipe Dwan Pereira; Marcelo Marinho; Valmir Macario; Ig Ibert Bittencourt; Seiji Isotani; Diego Dermeval; Rafael Mello – Education and Information Technologies, 2024
Intelligent Tutoring Systems (ITS) have been widely used to enhance math learning, wherein teacher's involvement is prominent to achieve their full potential. Usually, ITSs depend on direct interaction between the students and a computer. Recently, researchers started exploring handwritten input (e.g., from paper sheets) aiming to provide…
Descriptors: Intelligent Tutoring Systems, Handwriting, Equal Education, Access to Education
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Chance, Beth; Reynolds, Shea – Journal of Statistics Education, 2019
Through a series of explorations, this article will demonstrate how the Kentucky Derby winning times dataset provides various opportunities for introductory and advanced topics, from data processing to model building. Although the final goal may be a prediction interval, the dataset is rich enough for it to appear in several places in an…
Descriptors: Prediction, Statistics, Data Processing, Homework
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Avci, Esat; Coskuntuncel, Orkun – Pegem Journal of Education and Instruction, 2019
The purpose of this research is to examine the views of middle school mathematics teachers about the usability of VUstat and TinkerPlots software in data processing learning in the Curriculum of Mathematics Teaching in Middle School (5th, 6th, 7th and 8th grades). In the study, the phenomenology design from qualitative research patterns was…
Descriptors: Middle School Teachers, Mathematics Teachers, Teacher Attitudes, Computer Uses in Education
Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil – Grantee Submission, 2016
In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…
Descriptors: Intelligent Tutoring Systems, Data, Randomized Controlled Trials, Electronic Learning
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Stapel, Martin; Zheng, Zhilin; Pinkwart, Niels – International Educational Data Mining Society, 2016
The number of e-learning platforms and blended learning environments is continuously increasing and has sparked a lot of research around improvements of educational processes. Here, the ability to accurately predict student performance plays a vital role. Previous studies commonly focused on the construction of predictors tailored to a formal…
Descriptors: Teaching Methods, Academic Achievement, Electronic Learning, Mathematics Instruction
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Koparan, Timur – International Journal of Mathematical Education in Science and Technology, 2015
The purpose of this study is to define teacher views about the difficulties in learning and teaching middle school statistics subjects. To serve this aim, a number of interviews were conducted with 10 middle school maths teachers in 2011-2012 school year in the province of Trabzon. Of the qualitative descriptive research methods, the…
Descriptors: Statistics, Teaching Methods, Barriers, Learning Problems
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Blagdanic, Casandra; Chinnappan, Mohan – Australian Mathematics Teacher, 2013
Numeracy in schools is becoming an increasingly important part of mathematics learning and teaching. This is because educators want students to engage with mathematical concepts more deeply, use mathematics to make sense of their environment and make decisions that are based on the analysis of mathematical information. In order to be numerate,…
Descriptors: Statistical Analysis, Statistics, Data Interpretation, Numeracy
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