A Guide for VET Teachers with a Focus on Aquaculture: Using Student Rapid Response Systems (SRRS) for Formative Assessment and for Recognition of Prior Learning (RPL)

Introduction: This Optimal Guide is organised into 6 Parts as illustrated below. The reader is free to follow the sequence of parts or simply go to the parts of relevance

A Guide for VET Teachers With a Focus on Aquaculture: Using Student Rapid Response Systems (SRRS) for Formative Assessment and for Recognition of Prior Learning (RPL)

Optimal was a European Commission funded Erasmus+ Key Action 2 Strategic Partnership Project KA2-SP, titled – ‘Optimised Training: Innovative Methods and Tools for Acceptance of Prior Learning in Qualifications and Workplace Training’. It started in 2016 and ended in October 2019. The Optimal project involved a consortium of partners as follows: Norway - Blue Competence Centre and Guri Kunna VET School, Hitra and Froya Belgium - Federation of European Aquaculture Producers (FEAP) Scotland - Pisces Learning Innovations (PLI) Ltd Ireland - Teachers’ Union of Ireland (TUI). The partnership investigated the delivery of VET to work-based learners through the application of Student Rapid Response Systems (SRRS), Recognition of Prior Learning (RPL) and teaching methodologies and tools, considering how teachers and/or instructors could optimise their approach to training adult workbased learners about relevant industry knowledge and skills in the classroom and during self-directed learning. The project built on the partners’ expertise and experience of different VET teaching and training methodologies and methods, exploring approaches to both formal and non-formal learning and the range of assessment and qualifications used in each partner’s system. This included reviewing different curriculum structures and learning outcomes. The project also engaged with industry to explore current needs and demands for training and qualifications. The partners looked at the practical application of using different types of questions and feedback in the classroom. The partners validated project material and outcomes through peer review engagement during transnational meetings. The project outcomes are based on the collaborative participation of all the project partners. The project piloted and tested several combined teaching and learning methodologies and methods in a VET school with adult learners studying fish farming. The project was aware of the aquaculture and fish farming sectors need to both upskill workers and to provide accredited training for new workers

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe