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Showing 1 to 15 of 33 results Save | Export
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Johnson, Jillian C.; Olney, Andrew M. – International Educational Data Mining Society, 2022
Typical data science instruction uses generic datasets like survival rates on the Titanic, which may not be motivating for students. Will introducing real-life data science problems fill this motivational deficit? To analyze this question, we contrasted learning with generic datasets and artificial problems (Phase 1) with a community-sourced…
Descriptors: Data, Data Analysis, Interdisciplinary Approach, Student Motivation
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Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
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Li, Ak Wai; Sinnamon, Luanne S.; Kopak, Rick – Information and Learning Sciences, 2022
Purpose: The purpose of this study is to explore open data portals as data literacy learning environments. The authors examined the obstacles faced and strategies used by university students as non-expert open data portal users with different levels of data literacy, to inform the design of portals intended to scaffold informal and situated…
Descriptors: Data Collection, Multiple Literacies, Data, College Students
Ko, Jen-Li; Joslyn, Jeff; Lu, Ganhua; Palmer, Jason; Charles, Malcolm; Sanganalu Mattha, Aishwarya; Parsons, Bob; Tatum, Ron; Redmann, Carey; Bialkowski, Walter – Metropolitan Universities, 2022
Feeding America Eastern Wisconsin (FAEW) distributed 84% more food to community members in need during the COVID-19 pandemic than in the prior year. Though systems were in place to manage food receipt and distribution data, social distancing requirements and technological barriers revealed inefficiencies in utilizing this data. In pursuit of…
Descriptors: Hunger, School Community Relationship, Data, Data Analysis
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Ferns, Sonia; Phatak, Aloke; Benson, Susan; Kumagai, Nina – Teaching Statistics: An International Journal for Teachers, 2021
In the contemporary workplace, data scientists who are capable of interdisciplinary collaboration are in high demand. Universities need to provide data science students with a plethora of learning opportunities that involve collaboration in interdisciplinary contexts and engagement with industry partners. Curtin University and Lab Tests Online…
Descriptors: Employment Potential, Data, Statistics Education, Interdisciplinary Approach
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Ping Zhao; Chunling Sun; Baojun Lv; Lan Guo; Jiansheng Gao; Xin Zhao; Fengming Jiao – International Journal of Information and Communication Technology Education, 2024
This paper discusses the application value of the writing teaching mode combined with the mixed teaching mode in college English writing teaching against the background of big data. Focusing on production-oriented approach (POA) theory, this paper proposes a mixed learning writing model for English teaching and applies the POA mixed learning…
Descriptors: Writing Instruction, Blended Learning, Data Analysis, Data Collection
Isaac, James; Velez, Erin; Roberson, Amanda Janice – Institute for Higher Education Policy, 2023
Students, families, colleges, and lawmakers need clearer information on postsecondary outcomes to make informed decisions. By leveraging data available at institutions and federal agencies, a nationwide student-level data network (SLDN) would close information gaps that persist in our higher education landscape to answer critical questions about…
Descriptors: College Students, Data, Information Networks, Program Design
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Van Wart, Sarah; Lanouette, Kathryn; Parikh, Tapan S. – Journal of the Learning Sciences, 2020
Data increasingly mediates how we understand the world. As such, there is growing interest in designing initiatives to help young people learn about data--not only the techno-mathematical skills necessary to work with data, but also the dispositions needed to participate in data-centric ways of knowing and doing. In this article, we argue that as…
Descriptors: Data, Social Problems, Data Collection, Data Use
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Fouh, Eric; Farghally, Mohammed; Hamouda, Sally; Koh, Kyu Han; Shaffer, Clifford A. – International Educational Data Mining Society, 2016
We present an analysis of log data from a semester's use of the OpenDSA eTextbook system with the goal of determining the most difficult course topics in a data structures course. While experienced instructors can identify which topics students most struggle with, this often comes only after much time and effort, and does not provide real-time…
Descriptors: Item Response Theory, Data Analysis, Mathematics, Intelligent Tutoring Systems
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Mahnane, Lamia – Educational Technology & Society, 2017
In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…
Descriptors: Social Networks, Pretests Posttests, Cognitive Style, College Students
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Sole, Marla A. – Mathematics Teacher, 2016
Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…
Descriptors: Statistics, Mathematics Instruction, Data Collection, Teaching Methods
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Angeli, Charoula; Valanides, Nicos – Educational Technology Research and Development, 2013
The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI)…
Descriptors: College Students, Computer System Design, Cognitive Style, Immigration
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Irby, Stefan M.; Phu, Andy L.; Borda, Emily J.; Haskell, Todd R.; Steed, Nicole; Meyer, Zachary – Chemistry Education Research and Practice, 2016
There is much agreement among chemical education researchers that expertise in chemistry depends in part on the ability to coordinate understanding of phenomena on three levels: macroscopic (observable), sub-microscopic (atoms, molecules, and ions) and symbolic (chemical equations, graphs, etc.). We hypothesize this "level-coordination…
Descriptors: Chemistry, Formative Evaluation, Graduate Students, College Students
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Hogue, Candace M.; Pornprasertmanit, Sunthud; Fry, Mary D.; Rhemtulla, Mijke; Little, Todd D. – Measurement in Physical Education and Exercise Science, 2013
Salivary cortisol is often used as an index of physiological and psychological stress in exercise science and psychoneuroendocrine research. A primary concern when designing research studies examining cortisol stems from the high cost of analysis. Planned missing data designs involve intentionally omitting a random subset of observations from data…
Descriptors: Research Design, Statistical Analysis, Costs, Data
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Bülbül, M. S. – Themes in Science and Technology Education, 2015
This article proposes a methodology that could assist teachers in understanding their students' primary needs or interests to decide on the kind of examples or contexts to be used in the classroom. The methodology was tested on 100 volunteers from university (N = 50) and high school (N = 50) in Ankara, Turkey. The participants were asked to write…
Descriptors: Data, Physics, Science Instruction, College Science
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