Big-Data Learning Analytics for Online Higher Education
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289). This special issue belongs to the section "Big Data".
Deadline for manuscript submissions: 14 June 2027 | Viewed by 163
Editor
Interests: data science; computational social science; sentiment analysis; text mining; higher education; well-being research; happiness; disability studies
Special Issue Information
Dear Colleagues,
The digital transformation of higher education has generated an unprecedented volume of data from online learning environments. This data holds the potential to revolutionize pedagogical strategies and enhance student outcomes, yet its sheer scale and complexity present significant challenges. Traditional analytical methods often fall short in extracting the deep, actionable insights needed for meaningful improvement.
This Special Issue aims to bridge this gap by exploring the intersection of big data, learning analytics, and advanced computational methods in the context of online higher education. We invite high-quality, original research that showcases innovative techniques for analyzing large-scale educational datasets. The goal is to move beyond conventional metrics and uncover nuanced patterns in student engagement, learning behaviors, and success factors.
We welcome submissions on topics including but not limited to predictive modeling for at-risk students, personalized learning pathways, ethical considerations in educational data mining, and the application of cognitive computing to understand learning processes. This collection will supplement existing literature by providing a focused look at scalable, data-driven solutions that can shape the future of effective and sustainable online education.
Prof. Dr. Eyal Eckhaus
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- big data
- learning analytics
- online higher education
- educational data mining
- artificial intelligence in education
- predictive analytics
- student engagement
- personalized learning
- cognitive computing
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