The ELIXIR-EXCELERATE Train-the-Trainer pilot programme: empower researchers to deliver high-quality training

F1000Res. 2017 Aug 24:6:ELIXIR-1557. doi: 10.12688/f1000research.12332.1. eCollection 2017.

Abstract

One of the main goals of the ELIXIR-EXCELERATE project from the European Union's Horizon 2020 programme is to support a pan-European training programme to increase bioinformatics capacity and competency across ELIXIR Nodes. To this end, a Train-the-Trainer (TtT) programme has been developed by the TtT subtask of EXCELERATE's Training Platform, to try to expose bioinformatics instructors to aspects of pedagogy and evidence-based learning principles, to help them better design, develop and deliver high-quality training in future. As a first step towards such a programme, an ELIXIR-EXCELERATE TtT (EE-TtT) pilot was developed, drawing on existing 'instructor training' models, using input both from experienced instructors and from experts in bioinformatics, the cognitive sciences and educational psychology. This manuscript describes the process of defining the pilot programme, illustrates its goals, structure and contents, and discusses its outcomes. From Jan 2016 to Jan 2017, we carried out seven pilot EE-TtT courses (training more than sixty new instructors), collaboratively drafted the training materials, and started establishing a network of trainers and instructors within the ELIXIR community. The EE-TtT pilot represents an essential step towards the development of a sustainable and scalable ELIXIR TtT programme. Indeed, the lessons learned from the pilot, the experience gained, the materials developed, and the analysis of the feedback collected throughout the seven pilot courses have both positioned us to consolidate the programme in the coming years, and contributed to the development of an enthusiastic and expanding ELIXIR community of instructors and trainers.

Keywords: ELIXIR; EXCELERATE; Train-the-Trainer; TtT; educational psychology; instructor training; science of learning; training.

Grants and funding

This work was funded by ELIXIR, the research infrastructure for life-science data. ELIXIR received funding from the European Union’s Horizon 2020 research and innovation programme (ELIXIR- EXCELERATE, grant agreement no 676559).