Publication

Many universities implemented blended and hybrid delivery for the first time during the COVID-19 pandemic, and as such, the use of terms that relate to various manifestations and implementations of blended learning has increased significantly by all higher education stakeholders. However, the meaning ascribed to these terms is often inconsistent and can lead to confusion, making it difficult to set expectations clearly for both staff and students. This study aimed to investigate how higher education staff understand and use these terms and to identify sources of confusion and barriers to adopting standardised definitions. We surveyed 152 higher education staff and asked them to provide definitions of each term as well as completing a categorisation task. An applied thematic analysis identified two factors that were present across definitions: choice (no choice, student choice and choice not specified) and modality (mixed but separate, dual delivery and mixed not otherwise specified). Our findings reveal significant discrepancies in understanding, particularly regarding hybrid learning, which was often conflated with other modalities and involved definitions where neither choice nor modality was clearly specified. Blended learning was most consistently defined and identified as involving separate online and in-person components with no student choice as to the modality in which they could engage with each component. Hyflex learning, despite being less familiar to many participants, was accurately associated with dual delivery and the maximum student choice. Our results underscore the need for clearer terminology and for all stakeholders to provide maximally descriptive definitions. The use of any broad category term should be accompanied by a specific definition that at minimum describes choice and modality, but where best practice would be to encompass additional information based on existing frameworks.

This study aims to investigate the factors influencing teachers’ intentions to integrate Virtual Reality (VR) technology into their educational practices, utilising the Unified Theory of Acceptance and Use of Technology (UTAUT-2) framework. The research involved adapting and validating the ‘Acceptance of Mobile Immersive Virtual Reality in Secondary Education Teachers’ scale to the Turkish context, ensuring cultural relevance and psychometric reliability. Data were collected from 213 in-service teachers with prior experience in using VR in education. The results of the Confirmatory Factor Analysis (CFA) confirmed the validity of the adapted scale. The findings indicate that effort expectancy, social influence, personal innovativeness and hedonic motivation significantly predict teachers’ behavioural intentions to adopt VR technology. However, contrary to expectations, performance expectancy and facilitating conditions did not show a significant impact. These results underscore the importance of focusing on the ease of use and social support mechanisms, as well as fostering a culture of innovation amongst educators, to successfully integrate VR into educational settings.

Learning analytics (LA) provides insight into student performance and progress, allowing for targeted interventions and support to improve the student learning experience. Uses of LA are diverse, including measuring student engagement, retention, progression, student well-being and curriculum development. This article provides perspectives on the uses of LA in the UK through the analysis of an expert-led panel discussion held in June 2022. Two institutional case studies and a general overview from an LA service are presented, outlining examples of LA from both an institutional and national viewpoint. Following this, this article analyses the panel discussion themes in relation to the literature, covering both the data quality procedures and practices for learning, teaching and assessment. Outcomes and benefits from case studies are highlighted, which serve as best practice for other Higher Education institutions.