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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
Nani Teig – Research in Science Education, 2024
The advancement of technology has led to a growing interest in assessing scientific inquiry within digital platforms. This shift towards dynamic and interactive inquiry assessments enables researchers to investigate not only the accuracy of student responses ("product data") but also their steps and actions leading to those responses…
Descriptors: Learning Strategies, Problem Solving, Science Process Skills, Inquiry
Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
De Veaux, Richard; Hoerl, Roger; Snee, Ron; Velleman, Paul – Statistics Education Research Journal, 2022
Holistic data science education places data science in the context of real world applications, emphasizing the purpose for which data were collected, the pedigree of the data, the meaning inherent in the data, the deploying of sustainable solutions, and the communication of key findings for addressing the original problem. As such it spends less…
Descriptors: Holistic Approach, Data Analysis, Statistics Education, Teaching Methods
Cardona Zapata, Mónica Eliana; López Ríos, Sonia – Technology, Knowledge and Learning, 2022
Experimental activity in the physics teaching can be considered as a space in which teachers create contexts for students to approach the way scientific knowledge is constructed. In this sense, the strategies for the integration of Information and Communication Technologies (ICT) in the context of science education, has a wide potential to guide…
Descriptors: Physics, Science Instruction, Teaching Methods, Visual Aids
Chen, Fu; Cui, Ying – Journal of Educational Data Mining, 2020
Effective learning outcome modeling is crucial to the success of learning evaluation in education. In the digital age, the movement towards online learning and computerized assessments has resulted in an explosion of structured and unstructured educational data (e.g., learners' problem-solving process data), which offers new opportunities for…
Descriptors: Models, Outcomes of Education, Data Analysis, Psychometrics
McCarthy, Richard V.; Ceccucci, Wendy; McCarthy, Mary; Sugurmar, Nirmalkumar – Information Systems Education Journal, 2021
This case is designed to be used in business analytics courses; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People's United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize…
Descriptors: Business Administration Education, Data Analysis, Prediction, Crime
Anders Kristian Munk; Anders Koed Madsen; Mathieu Jacomy – New Perspectives on Learning and Instruction, 2019
Data sprints have emerged as a popular way to involve stakeholders in datawork. In this chapter we discuss what it takes to turn a sprint into a productive situation of inquiry (in the sense of Dewey, 1938). We argue that sprint organizers must work actively to counteract an otherwise docile setting where the preference for agreement between…
Descriptors: Data Analysis, Risk, Research Methodology, Research Problems
Nguyen, Huy; Liew, Chun Wai – International Educational Data Mining Society, 2018
Recent works on Intelligent Tutoring Systems have focused on more complicated knowledge domains, which pose challenges in automated assessment of student performance. In particular, while the system can log every user action and keep track of the student's solution state, it is unable to determine the hidden intermediate steps leading to such…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Data Analysis, Error Patterns
Barollet, Théo; Bouchez Tichadou, Florent; Rastello, Fabrice – International Educational Data Mining Society, 2021
In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…
Descriptors: Intelligent Tutoring Systems, Prediction, Internet, Purchasing
Leavy, Aisling; Hourigan, Mairead – Teaching Statistics: An International Journal for Teachers, 2016
We argue that the development of statistical literacy is greatly supported by engaging students in carrying out statistical investigations. We describe the use of driving questions and interesting contexts to motivate two statistical investigations. The PPDAC cycle is use as an organizing framework to support the process statistical investigation.
Descriptors: Statistics, Statistical Analysis, Literacy, Questioning Techniques
Henshaw, Alexis Leanna; Meinke, Scott R. – Journal of Political Science Education, 2018
While data analysis and the related skills of data management and data visualization are important skills for undergraduates in the field of political science, the process of learning these skills can also be used to develop critical thinking, encourage active and collaborative learning, and to apply knowledge gained in the classroom. Drawing on…
Descriptors: Undergraduate Students, Data Analysis, Visualization, Active Learning
Gibson, David C.; Webb, Mary E. – Education and Information Technologies, 2015
This article is the second of two articles in this special issue that were developed following discussions of the Assessment Working Group at EDUsummIT 2013. The article extends the analysis of assessments of collaborative problem solving (CPS) to examine the significance of the data concerning this complex assessment problem and then for…
Descriptors: Educational Assessment, Problem Solving, Cooperation, Psychometrics
Webb, Mary E.; Prasse, Doreen; Phillips, Mike; Kadijevich, Djordje M.; Angeli, Charoula; Strijker, Allard; Carvalho, Ana Amélia; Andresen, Bent B.; Dobozy, Eva; Laugesen, Hans – Technology, Knowledge and Learning, 2018
In this article, we identify and examine opportunities for formative assessment provided by information technologies (IT) and the challenges which these opportunities present. We address some of these challenges by examining key aspects of assessment processes that can be facilitated by IT: datafication of learning; feedback and scaffolding; peer…
Descriptors: Formative Evaluation, Teamwork, Problem Solving, Metacognition
Data Literacy on the Road: Setting up a Large-Scale Data Literacy Initiative in the Databuzz Project
Seymoens, Tom; Van Audenhove, Leo; Van den Broeck, Wendy; Mariën, Ilse – Journal of Media Literacy Education, 2020
This paper presents "the DataBuzz Project." "DataBuzz" is a high-tech, mobile educational lab, which is housed in a 13-meter electric bus. Its specific goal is to increase the data literacy of different segments of society in the Brussels region through inclusive and participatory games and workshops. In this paper, we will…
Descriptors: Data Analysis, Literacy, Program Descriptions, Laboratories