PurposeMany universities implemented institutional social networking apps as an alternative to in-person social experiences during the COVID-19 pandemic. Therefore, this study aims to explore previously identified factors that influenced intentions to form collective actions, also known as we-intentions, on such social networking apps and their influence on student satisfaction with the app artifact.Design/methodology/approachStudents from across a large university were invited to participate in a survey. Responses from 915 students who reported using the app were analyzed using a maximum likelihood covariance-based structural equation model. Analysis was conducted using the R programming language's psych, lavaan, and semTools packages.FindingsThe authors found that we-intentions are positively associated with recent app use and with student satisfaction with the app. Group norms were found to significantly influence the formation of we-intentions, while social identity is positively associated with both we-intentions and satisfaction.Originality/valueThe paper provides evidence that past research generalizes to the context of university mobile social networks and identifies a relationship between we-intentions and satisfaction in this context. It also provides practical insight into factors that influence we-intentions, and subsequently students' online education experience, in the context of a university's institutional mobile social network.

Algorithmic systems shape every aspect of our daily lives and impact our perceptions of the world. The ubiquity and profound impact of algorithms mean that algorithm literacy – awareness and knowledge of algorithm use, and the ability to evaluate algorithms critically and exercise agency when engaging with algorithmic systems – is a vital competence for navigating life in the 21st century. Professional digital competence (PDC) frameworks for teachers include technological, pedagogical, and social competence areas and are intended to illustrate the necessary knowledge, skills, and attitudes for digitally competent teachers. Using document analysis, we undertook a systematised review and evaluation of selected PDC frameworks through the lens of algorithm literacy. This analysis demonstrated that although some aspects of algorithm literacy could be inferred within the PDC frameworks analysed, there is a need for further explicit integration. Just as the DigComp framework for citizens has been updated to recognise the vital importance of understanding algorithmic systems' impact, so should PDC frameworks be revised. Recommendations are provided for incorporating understandings of algorithmic governance and bias and ensuring digital Bildung development in PDC frameworks. Implications for teacher education programs are also discussed.

Technology education (TE) has the creating, making, and doing aspects of human activity at its foundation. This article presents a comparison of the teaching sense of efficacy (TSE) of practicing TE teachers and teacher candidates (TC) pre/post a forced switch to emergency remote teaching (ERT). In study 1, the effect of the switch to ERT had a significantly negative effect on TE teachers (N = 42; d = 1.77). In study 2, TE TCs (N = 16) were similarly affected (d = 1.16). Results of a two-way mixed ANOVA demonstrate that ERT had a greater negative impact on TE teachers’ TSE for student engagement (partial eta squared = .11) and classroom management (partial eta squared = .19) than it did on TE TCs’ TSE. As novice teachers tend to draw more from contextual factors than mastery experiences, this research demonstrates that experienced teachers were at a greater loss due to the pandemic than TCs.