Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Contribution: Model-based learning improves systems thinking (ST) based on students' prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and…

The results of online learning were not optimal, as evidenced by the unsatisfactory learning outcomes. These issues influenced students who had a poor understanding of concepts and those who were quick to learn. It was the reason for the study that aims to analyze the effectiveness of study, explore, implement, evaluate (SEIE) model e-learning…

Contribution: This study incorporates competition-based learning (CBL) into machine learning courses. By engaging students in innovative problem-solving challenges within information competitions, revealing that students' participation in online problem-solving competitions can improve their information technology, and showcase competitions can…

Implementing a proper learning model during the post COVID-19 pandemic is fundamental for learning quality enhancement, specifically for students' conceptual mastery. The research aims to develop a Complexity Science-Problem Based Learning (CS-PBL) model assisted by the "Sistem Informasi Pengelola Pembelajaran" (SIPEJAR) e-learning…

This paper presents a model for developing research questions that are aligned to research aims for research design in e-learning. The model is proposed as a solution to the on-going problem of heterogeneity of research problems. The model is based on Burrell and Morgan's four social paradigms, and integrates four research aims, namely, explore,…

The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…

The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…

Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…

The recent COVID-19 pandemic has forced many institutes of higher learning across the globe to consider alternative modes of providing quality learning for students. However, developing and implementing safe spaces for academic advisement in online platforms that allow college students to explore their environment in an open and curious manner is…

Traditional professional development is often characterized as being expensive, time consuming, and lacking impact. In contrast, online professional development provides greater flexibility and is becoming increasingly popular for school personnel. In this article, we report the process and outcomes of gathering feedback to adapt traditional…

Traditional professional development is often characterized as being expensive, time consuming, and lacking impact. In contrast, online professional development provides greater flexibility and is becoming increasingly popular for school personnel. In this article, we report the process and outcomes of gathering feedback to adapt traditional…

This study developed an e-resource for six topics and six activities for CHE 242 that could be implemented through the hybrid learning approach. The research employed the analysis, design, development, implementation, and evaluation model but particularly focused on the analysis phase only, in this study. One hundred and two students who enrolled…

Purpose: The purpose of this paper is to focus on assessing individuals' problems in learning groups/teams and should lead to the assessment of the group/team itself as a learning entity. Design/methodology/approach: In this paper, an extension of the IMS-Learning Design (IMS-LD) meta-model is proposed in order to support the assessment of…

The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…