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Frischemeier, Daniel; Schnell, Susanne – Mathematics Education Research Journal, 2023
As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…
Descriptors: Elementary School Students, Context Effect, Data Analysis, Case Studies
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Kim, Eun Mi; Oláh, Leslie Nabors; Peters, Stephanie – ETS Research Report Series, 2020
K-12 students are expected to acquire competence in data display as part of developing statistical literacy. To support research, assessment design, and instruction, we developed a hypothesized learning progression (LP) using existing empirical literature in the fields of mathematics and statistics education. The data display LP posits a…
Descriptors: Mathematics Education, Statistics Education, Teaching Methods, Data Analysis
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Hung, Jeng-Fung; Tsai, Chun-Yen – Journal of Baltic Science Education, 2020
Previous studies on the effectiveness of virtual laboratories for learning have shown inconsistent results over the past decade. The purpose of this research was to explore the effects of a virtual laboratory and meta-cognitive scaffolding on students' data modeling competences. A quasi-experimental design was used. Three classes of eighth graders…
Descriptors: Metacognition, Computer Simulation, Comparative Analysis, Science Laboratories
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Chatti, Mohamed Amine; Muslim, Arham – International Review of Research in Open and Distributed Learning, 2019
Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…
Descriptors: Guidelines, Data Analysis, Learning Experience, Metacognition
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Shen, Huajie; Liu, Teng; Zhang, Yueqin – International Journal of Distance Education Technologies, 2020
This study aims to create learning path navigation for target learners by discovering the correlation among micro-learning units. In this study, the learning path is defined as a sequence of learning units used to realize a learning goal, and a period used for realizing the learning goal is regarded as a learning cycle. Furthermore, the learning…
Descriptors: Correlation, Distance Education, Efficiency, Bayesian Statistics
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
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Maloney, Suzanne; Axelsen, Megan; Galligan, Linda; Turner, Joanna; Redmond, Petrea; Brown, Alice; Basson, Marita; Lawrence, Jill – Online Learning, 2022
Driven by the increased availability of Learning Management System data, this study explored its value and sought understanding of student behaviour through the information contained in activity level log data. Specifically, this study examined analytics data to understand students' engagement with online videos. Learning analytics data from the…
Descriptors: Learning Analytics, Video Technology, Learning Management Systems, Comparative Analysis
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Palit, Shamik; Roy, Chandrima Sinha – International Society for Technology, Education, and Science, 2021
Big Data Technology (BDT) and Analytics have gained immense recognition in recent years. BDT plays an essential role in various sectors. This study intends to provide a review of BDT in the education sector which includes analyzing, predicting learner's results based on behavior patterns, assessing their performance regularly. Education…
Descriptors: Learning Analytics, Data Analysis, Educational Administration, Educational Improvement
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Gervet, Theophile; Koedinger, Ken; Schneider, Jeff; Mitchell, Tom – Journal of Educational Data Mining, 2020
Intelligent tutoring systems (ITSs) teach skills using learning-by-doing principles and provide learners with individualized feedback and materials adapted to their level of understanding. Given a learner's history of past interactions with an ITS, a learner performance model estimates the current state of a learner's knowledge and predicts her…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Feedback (Response), Knowledge Level
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Stanislav Pozdniakov; Roberto Martinez-Maldonado; Yi-Shan Tsai; Vanessa Echeverria; Zachari Swiecki; Dragan Gaševic – Journal of Learning Analytics, 2025
Recent research on learning analytics dashboards has focused on designing user interfaces that offer various forms of "visualization guidance" (often referring to notions such as "data storytelling" or "narrative visualization") to teachers (e.g., emphasizing data points or trends with colour and adding annotations),…
Descriptors: Visual Aids, Learning Analytics, Technological Literacy, Pedagogical Content Knowledge
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Wu, Chao-Jung; Liu, Chia-Yu – Physical Review Physics Education Research, 2021
The purpose of this study was to explore how students with high- and low-prior-knowledge employed multiple representations in argumentation evaluation and generation tasks. The argumentation performance and eye-movement behaviors of 96 college students in these tasks were investigated. The number of participants who proposed complex argumentation…
Descriptors: Eye Movements, Prior Learning, Persuasive Discourse, College Students
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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
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Johnson, Marina E.; Berenson, Mark L. – Decision Sciences Journal of Innovative Education, 2019
AACSB has now mandated that analytics be integrated into the undergraduate business curriculum. Given that the subject of statistics provides the underpinnings of the developing discipline of business analytics, this article focuses on effective course delivery aimed at enhancing the learning of introductory business statistics in the modern world…
Descriptors: Teaching Methods, Introductory Courses, Undergraduate Students, Statistics
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Cunningham-Nelson, Samuel; Baktashmotlagh, Mahsa; Boles, Wageeh – IEEE Transactions on Education, 2019
Contribution: An automated methodology that provides visualizations of students' free text comments from course satisfaction surveys. Focusing on sentiment, these visualizations reveal learning and teaching aspects of the course that either may require improvement or are performing well. They provide educators with a simple, systematic way to…
Descriptors: Student Attitudes, Visualization, Course Evaluation, Teaching Methods
Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2015
This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…
Descriptors: Learning Activities, Learning Processes, Data Collection, Student Behavior
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