The intersection of AI and learning analytics: Enhancing institutional performance

Integrating Artificial Intelligence (AI) and Learning Analytics (LA) in educational settings signifies a significant shift in leveraging data to enhance institutional effectiveness. This paper investigates the merging of these technologies, highlighting their capacity to revolutionise educational pr...

Full description

Saved in:
Bibliographic Details
Main Author: Thabisa Maqoqa
Format: Article
Language:English
Published: ERRCD Forum 2025-04-01
Series:Interdisciplinary Journal of Education Research
Subjects:
Online Access:https://pubs.ufs.ac.za/index.php/ijer/article/view/1768
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850149810937528320
author Thabisa Maqoqa
author_facet Thabisa Maqoqa
author_sort Thabisa Maqoqa
collection DOAJ
description Integrating Artificial Intelligence (AI) and Learning Analytics (LA) in educational settings signifies a significant shift in leveraging data to enhance institutional effectiveness. This paper investigates the merging of these technologies, highlighting their capacity to revolutionise educational practices, improve resource management, and better student outcomes. AI-powered learning analytics provide immediate insights into student performance, facilitating tailored learning experiences and prompt interventions. The paper addresses the challenges faced and suggests strategies to overcome these obstacles to ensure the ethical and fair use of AI and learning analytics in education. Underpinned by computational learning theory, which emphasises understanding the performance and resource needs of machine learning algorithms, this study focuses on a sample from a rural university in the Eastern Cape. Data were gathered from the experiences and views of 65 students through questionnaires. Within the framework of a positivist paradigm, it was found that the introduction of AI has fostered the development of robust evaluation and assessment techniques, leading to increased faculty engagement. The research indicates that factors such as perceived risk, performance expectations, and awareness significantly influence work engagement and the adoption of AI in higher education, mediated by attitudes and behaviours. It is recommended that university administration establish clear ethical guidelines and policies governing AI and learning analytics and provide training and professional development for faculty to enhance their data literacy skills.
format Article
id doaj-art-cfdc87f31a424cd08d7a8e553c00dd94
institution OA Journals
issn 2710-2114
2710-2122
language English
publishDate 2025-04-01
publisher ERRCD Forum
record_format Article
series Interdisciplinary Journal of Education Research
spelling doaj-art-cfdc87f31a424cd08d7a8e553c00dd942025-08-20T02:26:46ZengERRCD ForumInterdisciplinary Journal of Education Research2710-21142710-21222025-04-017s1a09a0910.38140/ijer-2025.vol7.s1.091734The intersection of AI and learning analytics: Enhancing institutional performanceThabisa Maqoqa0https://orcid.org/0000-0002-9191-3299Walter Sisulu University, South AfricaIntegrating Artificial Intelligence (AI) and Learning Analytics (LA) in educational settings signifies a significant shift in leveraging data to enhance institutional effectiveness. This paper investigates the merging of these technologies, highlighting their capacity to revolutionise educational practices, improve resource management, and better student outcomes. AI-powered learning analytics provide immediate insights into student performance, facilitating tailored learning experiences and prompt interventions. The paper addresses the challenges faced and suggests strategies to overcome these obstacles to ensure the ethical and fair use of AI and learning analytics in education. Underpinned by computational learning theory, which emphasises understanding the performance and resource needs of machine learning algorithms, this study focuses on a sample from a rural university in the Eastern Cape. Data were gathered from the experiences and views of 65 students through questionnaires. Within the framework of a positivist paradigm, it was found that the introduction of AI has fostered the development of robust evaluation and assessment techniques, leading to increased faculty engagement. The research indicates that factors such as perceived risk, performance expectations, and awareness significantly influence work engagement and the adoption of AI in higher education, mediated by attitudes and behaviours. It is recommended that university administration establish clear ethical guidelines and policies governing AI and learning analytics and provide training and professional development for faculty to enhance their data literacy skills.https://pubs.ufs.ac.za/index.php/ijer/article/view/1768artificial intelligencecomputational learninglearning analyticstechnologytransform
spellingShingle Thabisa Maqoqa
The intersection of AI and learning analytics: Enhancing institutional performance
Interdisciplinary Journal of Education Research
artificial intelligence
computational learning
learning analytics
technology
transform
title The intersection of AI and learning analytics: Enhancing institutional performance
title_full The intersection of AI and learning analytics: Enhancing institutional performance
title_fullStr The intersection of AI and learning analytics: Enhancing institutional performance
title_full_unstemmed The intersection of AI and learning analytics: Enhancing institutional performance
title_short The intersection of AI and learning analytics: Enhancing institutional performance
title_sort intersection of ai and learning analytics enhancing institutional performance
topic artificial intelligence
computational learning
learning analytics
technology
transform
url https://pubs.ufs.ac.za/index.php/ijer/article/view/1768
work_keys_str_mv AT thabisamaqoqa theintersectionofaiandlearninganalyticsenhancinginstitutionalperformance
AT thabisamaqoqa intersectionofaiandlearninganalyticsenhancinginstitutionalperformance