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Showing 1 to 15 of 31 results Save | Export
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Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
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Nicholas E. Fears; Riya Chatterjee; Priscila M. Tamplain; Haylie L. Miller – Journal of Motor Learning and Development, 2023
Social media platforms are rich and dynamic spaces where individuals communicate on a person-to-person level and to broader audiences. These platforms provide a wealth of publicly available data that can shed light on the lived experiences of people from numerous clinical populations. Twitter can be used to examine individual expressions and…
Descriptors: Social Media, Telecommunications, Psychomotor Skills, Data Collection
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Marwan, Samiha; Shi, Yang; Menezes, Ian; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2021
Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…
Descriptors: Expertise, Models, Feedback (Response), Identification
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Brandon Sepulvado; Jennifer Hamilton – Society for Research on Educational Effectiveness, 2021
Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…
Descriptors: Automation, Data Collection, Data Analysis, Validity
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Sarafoglou, Alexandra; van der Heijden, Anna; Draws, Tim; Cornelisse, Joran; Wagenmakers, Eric-Jan; Marsman, Maarten – Psychology Learning and Teaching, 2022
Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…
Descriptors: Bayesian Statistics, Thinking Skills, Undergraduate Students, Psychology
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
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Larson, Eric C.; Vieregger, Carl – Journal of Information Systems Education, 2019
This teaching case highlights the complex and unique strategic issues facing social media platform companies, using Facebook as the primary, motivating example. The case centers on the breach of trust that occurred when Cambridge Analytica acquired user data from 87 million Facebook accounts and then attempted to sway the 2016 U.S. Presidential…
Descriptors: Social Media, Strategic Planning, Trust (Psychology), Users (Information)
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Wellington, Angela; Easton, Genevieve; Davis, James; Yeh, Andy – Teaching Science, 2020
An important element of STEAM education that teachers struggle with is the adoption and application of digital technologies. Digital technologies have the potential to enhance social inclusion and student-centred learning, and for this reason it is important for teachers across all levels of schooling to develop skills and confidence in this area…
Descriptors: STEM Education, Art Education, Interdisciplinary Approach, Teaching Methods
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Moreno-Marcos, Pedro Manuel; Alario-Hoyos, Carlos; Munoz-Merino, Pedro J.; Estevez-Ayres, Iria; Kloos, Carlos Delgado – IEEE Transactions on Learning Technologies, 2019
One of the characteristics of massive open online courses (MOOCs) is that the overall number of social interactions tend to be higher than in traditional courses, hindering the analysis of social learning. Learners typically ask or answer questions using the forum. This makes messages a rich source of information, which can be used to infer…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
SungYong, Um – ProQuest LLC, 2016
Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among…
Descriptors: Electronic Publishing, Electronic Journals, Ecology, Computer System Design
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Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin – Journal of Learning Analytics, 2016
Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…
Descriptors: Educational Research, Data Collection, Data Analysis, Workshops
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McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2016
Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…
Descriptors: Data Collection, Student Behavior, Academic Achievement, Correlation
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Berland, Matthew; Davis, Don; Smith, Carmen Petrick – International Journal of Computer-Supported Collaborative Learning, 2015
AMOEBA is a unique tool to support teachers' orchestration of collaboration among novice programmers in a non-traditional programming environment. The AMOEBA tool was designed and utilized to facilitate collaboration in a classroom setting in real time among novice middle school and high school programmers utilizing the IPRO programming…
Descriptors: Computer Science Education, Active Learning, Programming, Novices
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Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
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Evale, Digna S. – Journal of Information Technology Education: Research, 2017
Aim/Purpose: This study is an attempt to enhance the existing learning management systems today through the integration of technology, particularly with educational data mining and recommendation systems. Background: It utilized five-year historical data to find patterns for predicting student performance in Java Programming to generate…
Descriptors: Integrated Learning Systems, Technology Integration, Educational Technology, Technology Uses in Education
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