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Hwang, Wu-Yuin; Utami, Ika Qutsiati; Purba, Siska Wati Dewi; Chen, Holly S. L. – IEEE Transactions on Learning Technologies, 2020
This paper aimed to investigate the effect of a mobile app on mathematics learning in authentic contexts. Authentic contexts contain rich resources wherein students can use authentic objects as aid in advanced educational technology-assisted mathematics learning. We designed Ubiquitous-Fraction (U-Fraction), a mobile application that helps…
Descriptors: Instructional Effectiveness, Mathematics Instruction, Mathematics Achievement, Web Based Instruction
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Han, Feifei; Ellis, Robert – Australasian Journal of Educational Technology, 2020
This study combined the methods from student approaches to learning and learning analytics research by using both self-reported and observational measures to examine the student learning experience. It investigated the extent to which reported approaches and perceptions and observed online interactions are related to each other and how they…
Descriptors: Measurement Techniques, Observation, Learning Analytics, Data Collection
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Nguyen, Quan; Rienties, Bart; Richardson, John T. E. – Assessment & Evaluation in Higher Education, 2020
Although the attainment gap between black and minority ethnic (BME) students and white students has persisted for decades, the potential causes of these disparities are highly debated. The emergence of learning analytics allows researchers to understand how students engage in learning activities based on their digital traces in a naturalistic…
Descriptors: Learning Analytics, Academic Achievement, Achievement Gap, Racial Differences
Karaoglan Yilmaz, Fatma Gizem – Online Submission, 2020
The aim of this research is to examine the relationships between students' community of inquiry, academic self-efficacy, reflective thinking skills, problem-solving skills, and metacognitive awareness in a flipped learning environment supported by personalized recommendation and guidance messages based on learning analytics. For this purpose,…
Descriptors: Blended Learning, Learning Analytics, Feedback (Response), Individualized Instruction
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Dawkins, Roger – Open Learning, 2019
I am a lecturer with professional marketing experience, and this study was motivated by my dismay at university about what I have perceived as oversights in colleagues' typical use of mass email (emailing a single message to a large group of subscribers) for content delivery, in comparison to the communication strategies of major industries (for…
Descriptors: Foreign Countries, Communication Strategies, Electronic Mail, Business Communication
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Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan – International Association for Development of the Information Society, 2019
Learning analytic models are built upon traces students leave in technology-enhanced learning platforms as the digital footprints of their learning processes. Learning analytics uses these traces of learning engagement to predict performance and provide learning feedback to students and teachers when these predictions signal the risk of failing a…
Descriptors: Learner Engagement, Outcomes of Education, Learning Processes, Learning Analytics
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Kohnke, Lucas; Foung, Dennis; Chen, Julia – SAGE Open, 2022
Blended learning pedagogical practices supported by learning management systems have become an important part of higher education curricula. In most cases, these blended curricula are evaluated through multimodal formative assessments. Although assessments can strongly affect student outcomes, research on the topic is limited. In this paper, we…
Descriptors: Formative Evaluation, Higher Education, Outcomes of Education, Learning Analytics
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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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Feng, Shihui; Law, Nancy – International Journal of Artificial Intelligence in Education, 2021
In this study, we review 1830 research articles on artificial intelligence in education (AIED), with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary research field from 2010 to 2019. A novel three-step approach in the analysis of the keyword co-occurrence networks (KCN) is proposed to identify the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Intelligent Tutoring Systems
Solomon, Bonnie J.; Sun, Sarah; Temkin, Deborah – Child Trends, 2021
With the passage of the 2015 Every Student Succeeds Act (ESSA), states were required to add a fifth indicator on "School Quality or Student Success" (SQSS) to their school accountability systems. An analysis of submitted ESSA state plans found that 13 states included measures of school climate as their SQSS indicator or incorporated…
Descriptors: School Districts, Learning Analytics, Educational Environment, Educational Quality
Ian Rosenblum – Office of Elementary and Secondary Education, US Department of Education, 2021
The author writes this letter to provide an update on assessment, accountability, and reporting requirements for the 2020-2021 school year. President Biden's first priority is to safely re-open schools and get students back in classrooms, learning face-to-face from teachers with their fellow students. To be successful once schools have re-opened,…
Descriptors: Letters (Correspondence), Educational Improvement, Accountability, Learning Analytics
Kenneth Holstein; Bruce M. McLaren; Vincent Aleven – Grantee Submission, 2017
Intelligent tutoring systems (ITSs) are commonly designed to enhance student learning. However, they are not typically designed to meet the needs of teachers who use them in their classrooms. ITSs generate a wealth of analytics about student learning and behavior, opening a rich design space for real-time teacher support tools such as dashboards.…
Descriptors: Intelligent Tutoring Systems, Technology Integration, Educational Technology, Middle School Teachers
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West, Deborah; Luzeckyj, Ann; Searle, Bill; Toohey, Danny; Vanderlelie, Jessica; Bell, Kevin R. – Australasian Journal of Educational Technology, 2020
This article reports on a study exploring student perspectives on the collection and use of student data for learning analytics. With data collected via a mixed methods approach from 2,051 students across six Australian universities, it provides critical insights from students as a key stakeholder group. Findings indicate that while students are…
Descriptors: Stakeholders, Undergraduate Students, Graduate Students, Student Attitudes
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Saito, Daisuke; Kaieda, Shota; Washizaki, Hironori; Fukazawa, Yoshiaki – Journal of Information Technology Education: Innovations in Practice, 2020
Aim/Purpose: Although many computer science measures have been proposed, visualizing individual students' capabilities is difficult, as those measures often rely on specific tools and methods or are not graded. To solve these problems, we propose a rubric for measuring and visualizing the effects of learning computer programming for elementary…
Descriptors: Scoring Rubrics, Visualization, Learning Analytics, Computer Science Education
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Michel, Marije; Révész, Andrea; Lu, Xiaojun; Kourtali, Nektaria-Efstathia; Lee, Minjin; Borges, Lais – Second Language Research, 2020
Most research into second language (L2) writing has focused on the products of writing tasks; much less empirical work has examined the behaviours in which L2 writers engage and the cognitive processes that underlie writing behaviours. We aimed to fill this gap by investigating the extent to which writing speed fluency, pausing, eye-gaze…
Descriptors: Second Language Learning, Writing Processes, Cognitive Processes, Writing Skills
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