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Nguyen, Andy; Gardner, Lesley; Sheridan, Don – Journal of Information Systems Education, 2020
Data analytics in higher education provides unique opportunities to examine, understand, and model pedagogical processes. Consequently, the methodologies and processes underpinning data analytics in higher education have led to distinguishing, highly correlative terms such as Learning Analytics (LA), Academic Analytics (AA), and Educational Data…
Descriptors: Learning Analytics, Higher Education, Computer Assisted Instruction, Student Centered Learning
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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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Weiss, Charles J. – Journal of Chemical Education, 2021
Scientific computing and computer literacy are increasingly important skills for chemistry students to learn, but despite this need, there is an absence of chemistry-specific texts available for teaching the subject. This article introduces a freely available textbook released under a Creative Commons license for use in an undergraduate scientific…
Descriptors: Science Instruction, Chemistry, College Science, Undergraduate Study
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Sullivan, Patrick – Mathematics Teacher: Learning and Teaching PK-12, 2022
Probabilistic reasoning underpins much of middle school students' future work in data analysis and inferential statistics. Unfortunately for many middle school students, probabilistic reasoning is not intuitive. One specific area in which students seem to struggle is determining the probability of compound events (Moritz and Watson 2000). Research…
Descriptors: Mathematics Instruction, Thinking Skills, Middle School Students, Data Analysis
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Pence, Harry E.; Williams, Antony J. – Journal of Chemical Education, 2016
The amount of computerized information that organizations collect and process is growing so large that the term Big Data is commonly being used to describe the situation. Accordingly, Big Data is defined by a combination of the Volume, Variety, Velocity, and Veracity of the data being processed. Big Data tools are already having an impact in…
Descriptors: Chemistry, Science Education, Data Collection, Data Analysis
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Bull, Susan; Kay, Judy – International Journal of Artificial Intelligence in Education, 2016
The SMILI? (Student Models that Invite the Learner In) Open Learner Model Framework was created to provide a coherent picture of the many and diverse forms of Open Learner Models (OLMs). The aim was for SMILI? to provide researchers with a systematic way to describe, compare and critique OLMs. We expected it to highlight those areas where there…
Descriptors: Educational Research, Data Collection, Data Analysis, Intelligent Tutoring Systems
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Reich, Justin; Tingley, Dustin; Leder-Luis, Jetson; Roberts, Margaret E.; Stewart, Brandon M. – Journal of Learning Analytics, 2015
Dealing with the vast quantities of text that students generate in Massive Open Online Courses (MOOCs) and other large-scale online learning environments is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as students write in forums, assignments, and surveys. This paper introduces to the…
Descriptors: Large Group Instruction, Online Courses, Data Collection, Data Analysis
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Bull, Susan; Wasson, Barbara – ReCALL, 2016
This paper introduces an open learner model approach to learning analytics to combine the variety of data available from the range of applications and technologies in language learning, for visualisation of language learning competences to learners and teachers in the European language context. Specific examples are provided as illustrations…
Descriptors: Competence, Visualization, Educational Research, Data Collection
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Godwin-Jones, Robert – Language Learning & Technology, 2021
Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…
Descriptors: Data Collection, Academic Achievement, Learning Analytics, Computer Assisted Instruction
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Leblay, Joffrey; Rabah, Mourad; Champagnat, Ronan; Nowakowski, Samuel – International Association for Development of the Information Society, 2018
How can we learn to use properly business software, digital environments, games or intelligent tutoring systems (ITS)? Mainly, we assume that the new user will learn by doing. But what about the efficiency of such a method? Our approach proposes an answer by introducing on-line coaching. In learning process, learners may need guidance to help them…
Descriptors: Intelligent Tutoring Systems, Coaching (Performance), Efficiency, Learning Processes
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Aguilar, Jose; Cordero, Jorge; Buendía, Omar – Journal of Educational Computing Research, 2018
In this article, we propose the concept of "Autonomic Cycle Of Learning Analysis Tasks" (ACOLAT), which defines a set of tasks of learning analysis, whose objective is to improve the learning process. The data analysis has become a fundamental area for the knowledge discovery from data extracted from different sources. In the autonomic…
Descriptors: Data Analysis, Learning Processes, Decision Making, Instructional Improvement
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Ranalli, Jim; Feng, Hui-Hsien; Chukharev-Hudilainen, Evgeny – Language Learning & Technology, 2019
The research literature on L2 writing processes contains a multitude of insights that could inform writing instruction, but writing teachers are constrained in their capacity to make use of these insights insofar as they lack detailed information about how their students actually engage in the processes of writing. At the same time,…
Descriptors: Writing Processes, Second Language Learning, Second Language Instruction, Writing Instruction
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Knight, Simon; Littleton, Karen – Journal of Learning Analytics, 2015
There is an increasing interest in developing learning analytic techniques for the analysis, and support of, high-quality learning discourse. This paper maps the terrain of discourse-centric learning analytics (DCLA), outlining the distinctive contribution of DCLA and outlining a definition for the field moving forwards. It is our claim that DCLA…
Descriptors: Discourse Analysis, Outcomes of Education, Data Analysis, Language Usage
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Kraftmakher, Yaakov – Physics Education, 2013
Two computer-assisted experiments are described: (i) determination of the speed of ultrasound waves in water and (ii) measurement of the thermal expansion of an aluminum-based alloy. A new data-acquisition system developed by PASCO scientific is used. In both experiments, the "Keep" mode of recording data is employed: the data are…
Descriptors: Science Experiments, Computer Assisted Instruction, Motion, Acoustics
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Liu, Ming; Pardo, Abelardo; Liu, Li – International Journal of Distance Education Technologies, 2017
Online collaborative writing tools provide an efficient way to complete a writing task. However, existing tools only focus on technological affordances and ignore the importance of social affordances in a collaborative learning environment. This article describes a learning analytic system that analyzes writing behaviors, and creates…
Descriptors: Collaborative Writing, Learner Engagement, Student Attitudes, Visualization
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