Learning analytics: current trends and innovative practices
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Learning analytics can provide an accurate understanding of the learning process.
“e results of recent studies showed that learning analytics can provide an accurate understanding of the learning process.”
From Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022) · cites this paper as [96]
Learning analytics can simplify the assessment of the usefulness of pedagogies and instructional designs for upgrading.
“can simplify the assessment of the usefulness of pedagogies and instructional designs for upgrading”
From Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022) · cites this paper as [96]
Learning analytics helps institutions during formative, summative, peer, and self-assessment processes by utilizing available data efficiently and effectively in decision-making.
“Learning analytics helps institutions during formative, summative, peer, and self-assessment processes by utilizing available data efficiently and effectively in decision-making”
From Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022) · cites this paper as [96]
Learning analytics assists to monitor carefully students' learning process and purpose, detect undesirable learning behaviors and emotional states, and monitors students learning to provide ongoing to students.
“assist to monitor carefully students' learning process and purpose, detect undesirable learning behaviors and emotional states and monitors students learning to provide ongoing to students.”
From Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022) · cites this paper as [96]
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References 14 · Cited by 84
Research works printed but not linked: 1
- Baker, R., & Siemens, G. (2014). Learning analytics and educational data mining. In: Keith-Sawyer R (ed) Cambridge handbook of the leaning sciences (2nd edn). Cambridge University Press: New York, NY, pp. 253-272.
- Authors
- Lee, L.-K., Cheung, S. K. S., & Kwok, L.-F.
- Affiliations
- Hong Kong Metropolitan University (HK)
- City University of Hong Kong (HK)
- Corresponding author
- Lee, Lap-Kei
- Venue
- Journal of Computers in Education
- Published
- 2020-02-11
- Volume
- 7
- Issue
- 1
- Pages
- 1-6
- ISSN
- 2197-9987 (ISSN-L)
- 2197-9995
- OpenAlex
- W3006349874
- Cited by
- 84
- References
- 14
- Citations by year
- 2026: 7 · 2025: 17 · 2024: 13 · 2023: 15 · 2022: 17 · 2021: 13 · 2020: 2
- FWCI
- 10.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Computers in Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Keywords
- learning analytics, educational data mining
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