This open access book maps the role of challenge-based learning (CBL) in the transformation of higher education pedagogy, towards being sector-informed as well as student-driven. CBL democratises the process of learning by repositioning students as drivers, who are empowered to make decisions on course content, assess needs in the real world and…

Balancing the contextual and universal reporting of workplace-based work-integrated learning (P-WIL) to capture, examine and explain sector-wide impacts, remains an unresolved challenge within Australian Higher Education. To address this, an action-research project was tasked with developing a prototype data schema that groups the typical elements…

This study aims to analyze the factors influencing the typology of Turkic words to examine the specifics of the way students learn Turkic languages in higher education institutions. A hypotheticdeductive, survey, and comparative method was used for the study. Results showed that the learners have trouble constructing oral discourse and do not…

Although self-regulation is an important feature related to students' study success as reflected in higher grades and less academic course delay, little is known about the role of self-regulation in blended learning environments in higher education. For this review, we analysed 21 studies in which self-regulation strategies were taught in the…

While studies have shown that additional language (Lx) learners build on knowledge of previously acquired languages (Ringbom 2007), the natural interaction between languages is rarely exploited in Lx classrooms. This study explores the nature of metalinguistic reflections and crosslinguistic connections during plurilingual consciousness-raising…

Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…

With the onset of online education via technology-enhanced learning platforms, large amount of educational data is being generated in the form of logs, clickstreams, performance, etc. These Virtual Learning Environments provide an opportunity to the researchers for the application of educational data mining and learning analytics, for mining the…

Purpose: This study aims to explore how the boundary between science and society can be addressed to support the transformation of higher education towards sustainable development (HESD) in the sense of the whole institution approach. It analyses students' learning experiences in self-led sustainability projects conducted outside formal curricula…

As higher education institutions begin to reemerge from the global pandemic, they are reimagining how multimodal learning environments (MMLE) can be used to help shape future delivery modes. This article explores definitions for multimodal learning environments in terms of pedagogy, implementation, and management. According to this study,…

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

Socio-emotional skills are vital for individuals to thrive academically, personally, and socially in the twenty-first century. However, limited attention has been devoted to the factors that might facilitate or hinder the development of socio-emotional skills among university students. To address this gap, we explored the association between the…

This study proposes a knowledge graph-based big data analysis model for course quality evaluation, aiming to address issues in online education course evaluations such as semantic bias, grammatical deficiencies, vocabulary limitations, false evaluations, information distortion, and imbalanced evaluation categories. The model incorporates three…

In recent years, university teaching methods have evolved and almost all higher education institutions use e-learning platforms to deliver courses and learning activities. However, these digital learning environments present significant dropout and low completion rates. This is primarily due to the lack of student motivation and engagement.…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

The COVID-19 epidemic is affecting all areas of life, including the training activities of universities around the world. Therefore, the online learning method is an effective method in the present time and is used by many universities. However, not all training institutions have sufficient conditions, resources, and experience to carry out online…