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The COVID-19 pandemic has had a devastating impact on all facets of education. This led to educational institutions deploying blended and online systems for teaching and learning. The purpose of this study was to assess the role of blended learning in promoting quality education during the COVID-19 pandemic.

The qualitative research design was deployed in this study and enabled the researcher to collect data via in-depth interviews. Twenty-five (25) tertiary institutions accredited by the Ghana Tertiary Education Commission (GTEC) were randomly selected to participate in this study. The registrars of the institutions were purposively selected and served as the participants for the study. Thematic content analysis was used to analyze the data collected via the interview. Ethical considerations were adhered to during the study.

The study established that COVID-19 had a devastating effect on tertiary institutions; multiple technological and open-sourced systems were deployed for teaching and learning; blended learning was adopted to augment the traditional face-to-face mode of teaching and learning due to its ease of use, usefulness and accessibility as it was used for quizzes and assignments, accessing lecture notes, among others. Despite these, the deployment of technological and blended systems was met with challenges that somehow affected effective teaching, learning.

The study was limited to 25 tertiary educational institutions in Ghana. It was again limited to the COVID-19 era.

This research aids in understanding the extent of the impact of COVID-19 on teaching and learning and how blended learning is currently deployed and used in tertiary institutions in Ghana. The findings are relevant to policymakers and management of educational institutions as it informs them of the right method and tools to deploy for teaching and learning during pandemics.

As educational institutions globally are dealing with the effect of the COVID-19 pandemic, it is prudent to look into how tertiary institutions in Ghana deploy blended learning to facilitate teaching and learning. Thus, this paper is original as it fills the relevant literature gap in terms of scope, setting, methodology and findings.

Introduction: The idea of sustainability has become increasingly popular across many industries. To meet the demands of the present without compromising the capacity of future generations to meet their requirements, sustainable organisations prioritise integrating environmental, social, and economic aspects into their operations.

Purpose: To analyse the inter-relationship between sustainable organisations, high-potential employees (HPEs), and blended learning (BL) effectiveness. Organisations can gain a competitive edge, spur innovation, and contribute to a more sustainable and inclusive future by incorporating sustainability into their operations and offering sustainable workspaces.

Design/methodology/approach: This research approach offers a thorough understanding of the connections between sustainable organisations, HPEs, and workspaces by combining a literature review of 77 research papers, case studies, and surveys.

Findings: The dedication to sustainability draws high-potential workers and environmentally aware customers who favour supporting socially conscientious businesses.

Practical implications: The study provides valuable implications and suggestions for businesses looking to improve their sustainability and recruit top talent. These proposals should include the techniques for integrating sustainability into organisational culture, employee engagement programmes, talent recruiting and retention tactics, and designing environmentally friendly workspaces.

Originality/value: This research approach offers a thorough understanding of the connections between sustainable organisations, HPEs, and workspaces by combining literature reviews, case studies, surveys, interviews, and data analysis.

This study explores the consequences of digitalization in the field of education, particularly in relation to teachers’ course processes in higher education institutions. It emphasizes the importance of understanding how information systems (IS) support not only individual tasks but also processes as a whole. The results reveal that process practices have not been considered comprehensively and even core processes may be unseen.

A systematic literature review was conducted to explore the extent to which teachers’ processes are discussed in the literature. A qualitative case study was then conducted at a Finnish higher education institution to identify course processes and their relationships to IS.

Teachers’ processes have scarcely been discussed in the literature, and the process support provided by ISs is remarkably limited. It seems that course processes, which are core to education, are a blind spot in education digitalization. To support evaluating the level of support by IS, novel course process indicators were introduced.

Developing core processes, teachers’ course processes and thesis processes in education field, supports improving service quality. In all industries, organizations should consider whether processes are properly recognized and whether IS support not only individual tasks but also processes as a whole. We recommend recognizing and applying business process management practices to better support teachers’ work and to improve overall efficiency in education.

To the best of our knowledge, this is the first education sector study that attends to teacher’s work as a comprehensive process.

This study examined the implementation of an agile-blended learning (ABL) approach in a master-level early childhood research course and assessed its impact on the learning experience. The purpose was to understand how incorporating ABL concepts affected flexibility, learner autonomy, collaboration and technology mediation, the core principles of ABL.

A participatory case study methodology was employed to gather insights from 40 students regarding their experiences in the redesigned research course. Data were collected through interviews, observations and document analysis. Qualitative data were thematically analyzed and quantitative data descriptively analyzed.

ABL fostered flexibility, convenience and learner autonomy. However, students desired richer interpersonal interactions. Technological integration enhanced learning, but social presence was lacking.

The study was limited to a specific master-level early childhood education course and focused on a particular group of students. Further research is needed to examine the generalizability of the findings in different educational contexts and student populations.

Recommendations include ongoing professional development and support systems to optimize ABL realization. Sustaining ABL practices necessitates flexible, empowering institutional structures.

This study contributes to the literature by exploring the potential of ABL in the context of early childhood research education. It provides empirical evidence of the benefits of ABL for increased flexibility, learner autonomy, collaboration and technology mediation. The case study design adds to the originality by offering insights into the practical implementation of ABL in an educational setting.

In 2018, a group of higher education institutions (HEIs) in Switzerland started discussing the future of education. With the COVID-19 pandemic, many of their initial ideas and solutions were tested in the unpredictable, emergency online setting. This study aims to use student and faculty member perceptions to outline the future of higher education.

This research is based on eight surveys from students and faculty members at one Swiss HEI in business studies. While many previous studies focus on one group or one moment in time, this study examines the future of business education from both perspectives and traces the responses throughout the pandemic.

Teaching and learning strategies and perceptions evolved during the COVID-19 pandemic. Nonetheless, despite the potential, many HEIs simply reverted to normal instead of adapting to the “new normal”. Conversely, some HEIs have continued using the same exercises and tools that were used in the emergency remote pandemic-mode, without adapting or reflecting on the current learning environment. Based on the findings, both students and faculty members have increased their interest and proficiency in using digital tools although the students remained more open toward the opportunities of digital teaching and learning.

Based on the results, this study offers a model for the future of education that HEIs could implement when moving forward, whether on campus or online.

This study proposes an integrated Machine Learning and simulated framework for a personalized learning system. This framework aims to improve the integrity of the provided tasks, adapt to each student individually and ultimately enhance students' academic performance.

This methodology comprises two components. (1) A simulation-based system that utilizes reinforcement algorithms to assign additional questions to students who do not reach pass grade thresholds. (2) A Machine Learning system that uses the data from the system to identify the drivers of passing or failing and predict the likelihood of each student passing or failing based on their engagement with the simulated system.

The results of this study offer preliminary evidence of the effectiveness of the proposed simulation system and indicate that such a system has the potential to foster improvements in learning outcomes.

As with all empirical studies, this research has limitations. A simulation study is an abstraction of reality and may not be completely accurate. Student performance in real-world environments may be higher than estimated in this simulation, reducing the required teacher support.

The developed personalized learning (PL) system demonstrates a strong foundation for improving students' performance, particularly within a blended learning context. The findings indicate that simulated performance using the system exhibited improvement when individual students experienced higher learning benefits tailored to their needs.

The research offers evidence of the effectiveness of personalized learning systems and highlights their capacity to drive improvements in education. The proposed system holds the potential to enhance learning outcomes by tailoring tasks to meet the unique needs of each student.

This study contributes to the growing literature on personalized learning, emphasizing the importance of leveraging machine learning in educational technologies to enable precise predictions of student performance.

This paper aims to identify and evaluate resolutions to key learning and teaching challenges in very large courses that involve practical mathematics, such as foundational finance.

A design-based research approach is used across three semesters to iteratively identify practical problems within the course and then develop and evaluate resolutions to these problems. Data are collected from both students and teachers and analysed using a mixed-method approach.

The results indicate that key learning and teaching challenges in large foundational finance courses can be mitigated through appropriate consistency of learning materials; check-your-understanding interactive online content targeting foundational concepts in the early weeks; connection points between students and the coordinator to increase teacher presence; a sustained focus on supporting student achievement within assessments; and signposting relevance of content for the broader program and professional settings. Multiple design iterations using a co-design approach were beneficial to incrementally improve the course and consider multiple perspectives within the design process.

This paper develops a set of design principles to provide guidance to other practitioners who seek to improve their own courses.

The use of design-based research and mixed-method approaches that consider both student and teacher perspectives to examine the design of very large, foundational finance courses is novel.

The integration of digital technologies into education has brought about a profound transformation, fundamentally reshaping the learning landscape. The purpose of this study is to underscore the importance of investigating the factors influencing students’ engagement (SE) in this evolving digital era, particularly within formal digital learning environments. To address this need, the study is grounded in self-determination theory (SDT) and presents a comprehensive model comprising interconnected elements: digital competence (DC), smartphone use (SPU), perceived autonomy (PA), digital formal learning (DFL) and SE.

The research conducted an investigation within Saudi Arabian universities, collecting a robust data set of 392 cases. This data set underwent rigorous analysis to validate the proposed model. To untangle the intricate relationships within the framework, the study used partial least squares structural equation modelling. Given the distinct dimensions of the two constructs under study, the researcher used a disjoint two-stage approach to establish reflective-formative higher-order constructs (HOC).

The findings revealed that digital literacy and digital skills (DS) constitute the foundational constituents of DC. Simultaneously, the study identified facilitation, distraction and connectedness as integral components of SPU. Importantly, the study established that DC, SPU, PA and DFL significantly influence SE. Furthermore, the research illuminated the mediating roles played by SPU, PA and DFL in the complex relationship between DC and SE.

This study advances the literature by delineating the dynamic interplay between DC, SPU and SE in digital learning. It extends SDT within educational contexts, emphasizing the role of internal motivations and DS. Methodologically, it innovates through reflective-formative HOCs, deepening the analysis of complex educational constructs. Managerially, it guides institutions in enhancing DC and integrating smartphones effectively into learning, advocating for tailored strategies to foster engaging and autonomous digital learning environments, thereby enriching both theoretical understanding and practical application in education.

Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.

This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.

The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.

The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.

This bibliometric study aims to analyze publication trends, active countries, collaborations, influential citations and thematic evolution in learning analytics (LA) research focused on higher education (HE) during and after the COVID-19 lockdown period.

From the Scopus database, this bibliometric analysis extracts and evaluates 609 scholarly articles on LA in HE starting in 2019. The multidimensional process identifies the scope impacts, advancing the understanding of LA in HE. An analysis of co-citation data uncovers the key influences that have shaped the literature. This study uses the stimulus-organism-response (SOR) theory to suggest future research directions and organizational adaptations to new LA technologies and learner responses to LA-enabled personalized interventions.

Learning analytics are becoming important in the HE environment during and after the COVID-19 lockout. Institutions have used LA to collect socio-technical data from digital platforms, giving them important insights into learning processes and systems. The data gathered through LA has assisted in identifying areas for development, opening the path for improved student success and academic performance evaluation and helping students transition to the workforce.

The study’s concentration on the post-COVID-19 timeframe may lead to paying attention to potential pandemic developments. Nonetheless, the findings provide a thorough picture of LA’s contributions to HE and valuable ideas for future study initiatives. Future research with the SOR framework suggests areas for additional study to maximize LA’s potential in diverse HE situations.

This study adds to the growing corpus of knowledge on learning analytics in HE, especially in light of the COVID-19 lockdown and its aftermath. By using bibliometric analysis, the study provides a complete and evidence-based understanding of how LA has been used to address challenges related to HE. This study uses bibliometric analysis and SOR theory to appraise and map HE learning analytics research. The selected study themes can help scholars, educators and institutions shape their future efforts to improve teaching, learning and support mechanisms through learning analytics.