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The professional identity of scientists has historically been cultivated to value research over teaching, which can undermine initiatives that aim to reform science education. Course-Based Research Experiences (CRE) and the inclusive Research and Education Communities (iREC) are two successful and impactful reform efforts that integrate research and teaching. The aim of this study is to explicate the professional identity of instructors who implement a CRE within an established iREC and to explore how this identity contributes to the success of these programs. 97 CRE instructors from the Science Education Alliance (SEA) iREC participated in a 2-year, multi-stage, qualitative research project that involved weekly reflective journaling, autoethnographic description, small group evaluation and writing, and large-scale community checking. The resulting description of professional identity consisted of shared values (inclusivity, student success, community membership, ownership/agency, science, overcoming failure, and persistence), specified roles (mentor, advocate, scientist, educator, motivator, collaborator, community builder, learner, evaluator and project manager) and a stated sense of self (dedicated, resilient, pride in students, multiskilled, valued, community member, responsible and overworked). Analysis of individual reflective diary entries revealed how a professional identity underpinned and facilitated the ways in which faculty addressed challenges that arose and worked toward the success of every student. It is the self-concept of the professional identity of the instructor in the context of the CRE classroom that directed the extended commitment and effort that these instructors evidently put into their work with students, which facilitated student engagement, student persistence, and their collective scientific output. The study concludes that a professional identity of STEM faculty in the context of a CRE and iREC combines being a researcher and educator, and that this integrated identity is central for current initiatives aimed at transforming undergraduate STEM education.

ABSTRACTWe explore how organisations working on parenting programmes and other types of family support and violence prevention in low-resource settings experienced the pandemic. In August 2020–May 2021, we interviewed (1) staff from three community-based organisations delivering evidence-informed parenting interventions and other psychosocial services for families in Cape Town, South Africa, (2) staff from a parenting programme training organisation and (3) staff from two international organisations supporting psychosocial services in South Africa. Interviews (22) were thematically analysed, with findings in three areas. First, respondents noted changes in the context, including the job losses, food insecurity, and stress experienced by local communities, and reductions in organisational funding. Second, we found that in response to these context changes, the organisations shifted their focus to food provision and COVID prevention. Parenting and psychosocial programmes were adapted – e.g. by changing the physical delivery settings, reducing group sizes, and taking up digital and phone implementation. Participants reported improved perceptions of remote delivery as a feasible approach for working with families – but internet and phone access remained challenging. Third, the pandemic brought new responsibilities for staff, and both the challenges of working from home and the health risks of in-person work.

Purpose: The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are. Design/methodology/approach: Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT's can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT's suggestions would be successful in avoiding detection by markers when submitting contract-written work. Findings: While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student's ability to distinguish between genuinely viable options and those that appear to be workable but are not. Originality/value: This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

A lack of data hinders effective marine management strategies for developing island states. This is a particularly acute problem for the Commonwealth of Dominica. Here we use publicly available remote sensing and model data to map their relatively unstudied waters. Two study areas were selected; a smaller area focussing on the nearshore marine environment, and a larger area to capture broader spatial patterns and context. Three broadscale landscape maps were created, using geophysical and oceanographic data to classify the marine environment based on its abiotic characteristics. Principal component analysis (PCA) was performed on each area, followed by K-means clustering. The larger area PCA revealed three eigenvalues > 1, and one eigenvalue of 0.980. Therefore, two maps were created for this area, to assess the significance of including the fourth principal component (PC). We demonstrate that including too many PCs could lead to an increase in the confusion index of final output maps. Overall, the marine landscape maps were used to assess the spatial characteristics of the benthic environment and to identify priority areas for future high-resolution study. Through defining and analysing existing conditions and highlighting important natural areas in the Dominican waters, these study results can be incorporated into the Marine Spatial Planning process.