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Developing Course Materials

Preparation of infrastructure and resources, Online database tools, software and datasets, Data sets, Lecture notes and manual protocols, FAIR
Drawing, illustration of different materials used for learning, such as books, lab equipment, pencils, a microscope books, lab equipment
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In previous sections we discussed case studies of designing training activities for experimental and bioinformatics. This should be accompanied by a set of training materials, documentation, description of equipment, infrastructural resources and how to access them. Here we will focus on developing training materials and preparation of resources.

Preparation of infrastructure and resources

After planning activities, the next step is to itemise resources required and whether pre-course preparation is needed. For a genomics laboratory course, these steps include preparation of reagents, ensuring equipment is functional, and health and safety requirements are considered and well communicated to learners. For a bioinformatics course ensure computers have been set up and appropriate software has been installed.

Online database tools, software and datasets

In Steps 2.8 and 2.9 we discussed the use of one of the largest freely available nucleotide archives. This is convenient and often learners at the introductory or user level of bioinformatics find it user-friendly. Although here the main requirements are a computer which can access the internet, online distance-based learning may be a challenge due to unstable internet connectivity. It is important to have contingency measures. On a face to face course, the database can be shared from a local server connected to the computers used for training. In addition provision of course manuals is helpful for learners taking the training on their own with continued support from the instructors.

Appropriate datasets need to be prepared, preferably related to the subject topic of the course. For example use datasets which are specific for the pathogen of interest, and where possible avoid having to use manipulated or fake sequences. Having one set of sequences related to a specific case study makes it relevant for participants to follow through and connect learning steps. In Step 2.8 Ben Moore relates how he selected a dataset from an existing case study and publication relevant for AMR to give the right context and meaning to the course. In many cases there are many freely available datasets and if needed, permission should be obtained.

Software should ideally be freely available and a list should be made available to learners ahead of the training. For a short course, different software may be required for several steps and this will also require testing. Making the software and datasets centrally available is also a convenient way of ensuring learners can access the materials easily and are well guided. Clear instructions of how to install the software is paramount. Training teams can choose how to provide access to software and tools for a course through a local cluster or network. Other methods include use of virtual machines, which provide a convenient and portable way for ensuring learners have all their software requirements in the same place. An advantage of VMs, is that once installed on the computer, they are not dependent on the internet. Pre-testing and checking with learners can provide sufficient support to fix any errors, or map keyboards if needed.

Lecture notes and manual protocols

Although live lectures are preferred, pre-recording of lectures and provision of lecture slides gives learners options for when they have challenges in attending some sessions. During virtual delivery, this is common especially during the pandemic and with people working from their homes. Pre-filming of laboratory techniques is also recommended where virtual or online courses need to provide demonstrations for key experimental steps.

Providing paper-based training materials is helpful to follow laboratory or computational protocols. However, alternative methods include electronic notebooks which are becoming the norm and more environmentally friendly. Example of a set of training materials can be found here. Github is a commonly used site for developing, sharing and storing training materials which can be accessed freely under the Creative Commons license allowing anyone to share the materials with others and adapt as needed.

Making materials Findable, Accessible, Interoperable and Reusable is becoming a key expectation for genomics and bioinformatics training. This helps to mitigate the increasing demand and the time it takes to prepare training materials. Therefore, if materials are shared and described properly, this enables reuse and adaptation. Garcia et al (2020) share best practices in their article “Ten simple rules for making training materials FAIR”.

In the next step – Nicole Wheeler describes her approaches of provision of materials online on a face to face course, and the materials became accessible to more participants worldwide who are finding this highly beneficial for their skills development and work.

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Train the Trainer: Design Genomics and Bioinformatics Training

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