Student engagement in higher education is strongly associated with persistence and academic success, with engagement closely tied to students’ academic self-efficacy and sense of belonging within their institution (Tinto, 2023). Academic self-efficacy, grounded in Bandura’s (1977) social cognitive theory, influences the effort expended, whether coping strategies are initiated and the degree to which effort is sustained in the face of challenges. Alongside this, students’ social and affective connections with peers and faculty significantly shape progression and engagement (Tinto, 2023; Carrell, 2009). In blended higher education contexts, where interactional patterns differ from traditional face-to-face delivery, these dimensions of self-efficacy and belonging warrant closer examination.

This study explores student self-efficacy within a blended Professional Masters of Education programme in Ireland. In this context, “blended learning” is defined as programme delivery that combines online asynchronous and synchronous components with face-to-face elements. As blended delivery becomes increasingly prevalent in higher education in Ireland and internationally (Wiggers et al., 2023), further research into effective blended design and the measurement of student engagement is needed (Dixson, 2015; Muller et al., 2023). Engagement in blended contexts cannot be assumed; rather, it must be intentionally designed and critically examined (Brujin-Smolders & Prinsen, 2024 Garrison & Vaughan, 2008; Hutchings et al., 2011; Means et al., 2013).

While debates comparing blended and face-to-face modalities are often unproductive (Dyment & Downing, 2020), evidence suggests that blended learning can be as effective as, and sometimes more effective than, traditional delivery (Bernard et al., 2014; Boelens et al., 2017; Means et al., 2013; Strelan et al., 2020). Central to this argument is the notion that blended learning offers “the best of both worlds” (Arbaugh, 2014), particularly when asynchronous elements support flexible knowledge acquisition and synchronous face-to-face sessions facilitate higher-order thinking, application, and rich interaction (Akçayır & Akçayır, 2018; Buhl-Wiggers, 2023; O’Flaherty & Phillips, 2015). However, how students experience this “blend” and how it shapes their academic and social self-efficacy remain underexplored in postgraduate contexts in Ireland.

In this mixed-methods study, quantitative data was collected using the General Self-Efficacy Scale (GSE; Schwarzer & Jerusalem, 1995) and the Self-Efficacy Questionnaire for Online Learning (SeQoL; Tsai et al., 2020), the latter of which measures domain-specific self-efficacy related to online academic tasks and social interactions. Descriptive and inferential analyses were conducted to examine levels of self-efficacy across social and academic domains. Qualitative data was gathered through semi-structured interviews with a purposive sample of students and analysed thematically to explore lived-experiences of blended teaching, learning, and assessment.

Findings indicate variation across domains of self-efficacy. While many students report confidence in managing academic tasks and independent study, lower levels of confidence are associated with initiating and sustaining peer interaction in online spaces. Students identify structured synchronous small-group sessions, timely peer and faculty feedback and peer support as critical supports for engagement and self-efficacy. Conversely, technical challenges, competing professional and academic commitments, and ambiguity in online communication are perceived as barriers. Importantly, students’ accounts underscore the relational dimension of self-efficacy: feelings of belonging and perceived faculty presence and feedback significantly shape confidence and persistence.

By integrating quantitative measures of self-efficacy with qualitative accounts of student experience, this study contributes nuanced insight into how blended programme design can either support or constrain engagement in higher education. The findings have implications for intentional design of blended programmes that foster both academic competence and social belonging.

The COVID-19 pandemic precipitated an unprecedented, system-wide shift to technology-enhanced learning (TEL), compelling higher education institutions (HEIs) to adopt digital tools at speed and scale (Byttebier, 2022), under conditions of necessity rather than choice. In its wake, key changes have emerged, including expanded technical fluency among educators (Damşa et al., 2021), intensified institutional support and professional development (Sia et al., 2023), normalisation of digital teaching practices (Moorhouse et al., 2023), diversification of delivery modes (Imran et al., 2023) and significantly increased workload and stress (Watermeyer et al., 2021). These pandemic-mediated changes have important implications for current TEL adoption models and frameworks because they disrupted the conditions under which technology adoption and use in higher education was previously understood, most notably voluntariness, gradual uptake, and stable teaching environments. This has prompted questions about whether pre-pandemic TEL adoption models and frameworks remain fit for purpose in the post-pandemic context and whether they require extension and modification to reflect fundamentally changed conditions and technology use in higher education, especially in an era of significant disruptive technologies, including Generative AI (Nunez et al., 2026; O'Dea et al., 2024).

Assumptions underpinning pre-pandemic models require re-assessment in light of post-pandemic conditions. The Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) assume voluntariness, gradual uptake, and stable institutional conditions (Davis, 1989; Venkatesh et al., 2003). Pandemic-enforced TEL adoption was defined by compulsory implementation, compressed timelines, and altered working conditions. The Technological Pedagogical Content Knowledge (TPACK) (Mishra & Koehler, 2006) and the Substitution, Augmentation, Modification, and Redefinition (SAMR) (Puentedura, 2010) models pre-suppose a gradual progression towards an increasingly sophisticated integration of technology in teaching and learning. Yet, in a context where baseline digital competence among teachers has become more widespread (Pérez-Rivero et al., 2023), lower-order stages such as SAMR’s substitution stage are becoming redundant. Furthermore, under pandemic conditions, technology use frequently preceded full knowledge integration and large-scale adoption did not consistently translate into pedagogically meaningful transformation (Rapanta et al., 2021). Similarly, Guskey’s Model of Teacher Change (Guskey, 2002) assumes that changes in practice are preceded by shifts in beliefs and reflective processes but during the pandemic, changes in teaching practice were often enforced rather than internally motivated. Furthermore, existing models and frameworks largely overlook the intensified workload and stress experienced by teachers during and after the transition to TEL, despite the fact that these conditions influence how technology is used in practice, often constraining engagement to more immediate or less pedagogically transformative uses (Gregory & Lodge, 2015).

While the pandemic accelerated pre-pandemic patterns of TEL adoption, it also produced a qualitatively different educational landscape characterised by normalised but uneven practice, where widespread use co-exists with variable pedagogical integration (Mospan, 2023; Scholkmann et al., 2024). This context has prompted renewed questions about the usefulness and contextual adequacy of current TEL adoption models (O'Dea et al., 2024), questions that were already being asked in the pre-pandemic literature, including Kimmons and Hall’s critique of technology integration models (Kimmons & Hall, 2018) and criticism that TPACK is difficult to operationalise in practice (Brantley-Dias & Ertmer, 2013). This paper argues that the post-pandemic TEL landscape cannot be adequately understood through existing models in isolation and instead requires their extension and/or integration to account for compulsory adoption, elevated baseline digital competence, the reduced usefulness of early-stage constructs, and the persistent gap between the breadth of technology use and the depth of educational transformation.

A recent paper on ‘digital humanism’ or how we align technology with our human values indicated a need to revisit theory on Social Identity Theory (Levine & Kordoni, 2026). It also returned attention to Henri Tajfel’s work in the 1970’s and 80’s on Social Identity and Intergroup Relations. Here individuals construct an identity when they engage in practice and social interaction - there is a sense of belongingness in this. It can be viewed as a ‘perception of oneness with or belongingness to some human aggregate’ (Ashforth & Mael 1989, pg. 135) and include a student identity (Kaufman 2014, Nielsen, 2017) for example. Much of the reading in this area points to the importance of communal culture (Erik Erikson, 1968) and its influence on identity. To gain an understanding about the navigation of individuals through development of Social Identity a theory was formulated by Tajfel and Turner in the 1970s, namely Social Identity Theory (SIT). According to SIT individuals engage in social classification, which integrates the process of characterising oneself within a social context (Ashforth & Mael, 1989; Tajfel & Turner, 1986). The dangers that this can bring are very obvious today, in our media and in world affairs. The basis of social identity is that individuals engage in cognitive strategies such as evaluating the status of a group (such as healthcare professionals) and making comparisons between the perceived status of various groups. This evaluation is the basis for individuals to align themselves with an in-group. Although the theory stretches back over four decades it is pertinent today, as SIT provides a useful framework for understanding the process of stereotyping (Ferrucci, 2018). As a result of stereotyping, boundaries are formed between in-groups and other out groups which Hotho describes as the ‘fabric of social practice’ (Hotho, 2008, pg. 728). So, individuals ‘categorised themselves’ as group members they began to display in-group favouritism (Tajfel & Turner, 1986). SIT divides the external environment into elements and provides order to this for an individual. Through this process individuals are provided with a means for defining those within the environment and place themselves within in it, so they find their place and define who they are within a social environment (Ashforth & Mael, 1989). This process involves discriminating individuals and their status as well as stereotyping.

Student Identity Theory and Role Identity (RIT)

SIT considers the meanings attributed to membership within a category of society. Role Identity Theory (RIT) (Farmer, 2003, Mlotshwa 2015) and Student Identity Theory (Kaufman 2014, Nielsen, 2017) are a related theories, which considers the meaning individuals associate with a given role e.g. a University Student. Role Identity Theory (RIT) and Student Identity Theory are a more specific forms of Social Identity, which therefore form as a sub-set of Social Identity as depicted in Figure A1 below:

Figure A1

Digital Identity and other types of relevant identities

What has this to do with Digital Identity?

‘The term digital identity indicates the conversion of human identities into machine-readable digital data’ (Masieroa & Bailurb, 2021). Is it too simplistic to view this form of identity as a sub-set of Social Identity and of our Role Identity? Does our lack of control over our digital identity mean that it is not based on how we ‘stereotype’ ourselves, how we present ourselves online or who we social within a digital environment?