Open, reproducible, and replicable research practices are a fundamental part of science. Training is often organized on a grassroots level, offered by early career researchers, for early career researchers. Buffet style courses that cover many topics can inspire participants to try new things; however, they can also be overwhelming. Participants who want to implement new practices may not know where to start once they return to their research team. We describe ten simple rules to guide participants of relevant training courses in implementing robust research practices in their own projects, once they return to their research group. This includes (1) prioritizing and planning which practices to implement, which involves obtaining support and convincing others involved in the research project of the added value of implementing new practices; (2) managing problems that arise during implementation; and (3) making reproducible research and open science practices an integral part of a future research career. We also outline strategies that course organizers can use to prepare participants for implementation and support them during this process.
Children learning English as an additional language (EAL) are a diverse and growing group of pupils in England’s schools. Relative to their monolingual (ML) peers, these children tend to show lower receptive and expressive vocabulary knowledge in English, although interpretation of findings is limited by small and heterogeneous samples. In an effort to increase representativeness and power, the present study combined published and unpublished datasets from six cross-sectional and four longitudinal studies investigating the vocabulary development of 434 EAL learners and 342 ML peers (age range: 4;9–11;5) in 42 primary schools. Multilevel modelling confirmed previous findings of significantly lower English vocabulary scores of EAL learners and some degree of convergence in receptive but not expressive knowledge by the end of primary school. Evidence for narrowing of the gap in receptive knowledge was found only in datasets spanning a longer developmental period, hinting at the protracted nature of this convergence.
Training in robust research practices is becoming increasingly common. However, many course participants may encounter challenges in implementation of what they learned after returning to their research groups. In this piece, we summarize insights and "lessons learned" from a group of former course participants. We offer practical tips on implementation and cultural change that may be useful for researchers at any career stage. In addition, we provide a list of considerations for course instructors to help them support course attendees after training is over.
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