Towards a KD4LA Framework to Support Learning Analytics in Higher Education

Thi My Hang Vu, Thi My Hang Vu

2025

Abstract

Learning analytics (LAs) involves the process of collecting, organizing, and generating insights from educational data, such as learner assessments, learner profiles, or learner interactions with the educational environment, to support educators and learners in decision-making. This topic has gained attention from the community for many decades. Nowadays, with advancements in data mining and the availability of large amounts of data from various educational environments, learning analytics presents both opportunities and challenges. Especially in higher education, where data is more complex and data analytics is closely integrated with pedagogical activities and objectives, a consolidated framework is crucial to support both educators and learners in their tasks. This paper proposes a comprehensive framework, named KD4LA (Knowledge Discovery for Learning Analytics), which clarifies essential components of common learning analytics tasks in higher education. These tasks include generating statistical insights on student assessments, segmenting students based on their acquired knowledge, or evaluating their proficiency in relation to learning objectives. The proposed framework is validated through several real-world case studies to demonstrate its practical applicability.

Paper Citation

in Harvard Style

Vu T. (2025). Towards a KD4LA Framework to Support Learning Analytics in Higher Education. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 575-582. DOI: 10.5220/0013571000003967

in Bibtex Style

@conference{data25,
author={Thi Vu},
title={Towards a KD4LA Framework to Support Learning Analytics in Higher Education},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={575-582},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013571000003967},
isbn={978-989-758-758-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Towards a KD4LA Framework to Support Learning Analytics in Higher Education
SN - 978-989-758-758-0
AU - Vu T.
PY - 2025
SP - 575
EP - 582
DO - 10.5220/0013571000003967
PB - SciTePress