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Amane, Meryem; Aissaoui, Karima; Berrada, Mohammed – International Journal of Information and Learning Technology, 2023
Purpose: Together, learning objects (LOs) and e-pedagogical practices have the potential to improve the performance of e-learning systems in several ways. They can make e-learning more personalised and adaptable, providing students with a more engaging and effective learning experience. Design/methodology/approach: The development of LOs and…
Descriptors: Electronic Learning, Resource Units, Metadata, Algorithms
Cingillioglu, Ilker – International Journal of Information and Learning Technology, 2023
Purpose: With the advent of ChatGPT, a sophisticated generative artificial intelligence (AI) tool, maintaining academic integrity in all educational settings has recently become a challenge for educators. This paper discusses a method and necessary strategies to confront this challenge. Design/methodology/approach: In this study, a language model…
Descriptors: Artificial Intelligence, Essays, Integrity, Cheating
Khor, Ean Teng – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of the study is to build predictive models for early detection of low-performing students and examine the factors that influence massive open online courses students' performance. Design/methodology/approach: For the first step, the author performed exploratory data analysis to analyze the dataset. The process was then…
Descriptors: Prediction, Low Achievement, Algorithms, Artificial Intelligence
Ean Teng Khor; Dave Darshan – International Journal of Information and Learning Technology, 2024
Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
Ben Soussia, Amal; Labba, Chahrazed; Roussanaly, Azim; Boyer, Anne – International Journal of Information and Learning Technology, 2022
Purpose: The goal is to assess performance prediction systems (PPS) that are used to assist at-risk learners. Design/methodology/approach: The authors propose time-dependent metrics including earliness and stability. The authors investigate the relationships between the various temporal metrics and the precision metrics in order to identify the…
Descriptors: Performance, Prediction, Student Evaluation, At Risk Students
de Carvalho, Walisson Ferreira; Zárate, Luis Enrique – International Journal of Information and Learning Technology, 2021
Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…
Descriptors: Causal Models, Algorithms, Learning Analytics, Correlation