The core focus of this week is to continue to engage with the block 2 readings, and to produce your weekly data visualisation.
Our additional (and non-assessed) activity for you to try this week is the ‘build your own teaching dashboard’ task. This will give you the opportunity to reflect on the kind of tools and services one might use to organise data, as well as some of the practical skills involved in setting up and using such systems. However, there is, of course, significant technical expertise involved in building such systems for professional use, and the level at which we can realistically engage with these techniques is very limited. Most importantly, this task is intended for you to gain some additional experiences with organising data for ‘teaching’, primarily for the purpose of supporting your wider reflection on the current theme. Attempting to create a ‘DIY teaching dashboard’ will offer practical insights for questions such as, what kind of data might be useful for teaching? How data might be organised, combined, and visualised for particular kinds of teaching practice? And, how might such ‘dashboards’ impact the day-to-day practices of teaching?
Below are some suggested software tools and services that can be used to create your teaching dashboard. As with our previous task, you are not limited to these particular examples, and are welcome to use additional tools, or to explore different options. Following from the above, the core purpose of this task is to use the practical experience of ‘dashboard design’ to reflect on wider questions about the pedagogical implications of choices about data sources and visual representations. Therefore, the focus of the task is on experimentation, rather than on the final product. We suggest that this task will be more valuable to you if you reflect on the various decisions, options, and constraints, experienced in the use of each tool, rather than being overly concerned with producing a fully functioning dashboard at the end of the task.
The simplest way to approach this task is to use software available to most of us, Microsoft Excel (or you might use another similar spreadsheet -type application). The kind of simple descriptive statistics, charts, and graphs we might produce here are not necessarily representative of the more professional ‘dashboards’ we can find with commercial educational software, but this approach can give us a good sense of the processes and decisions involved in converting data into a useful ‘teaching resource’.
Below are two example, and unrelated, data sets. The first provides some ‘whole class’ data from interaction with a VLE course, and the second provides data for a group of individuals within a particular class. Both data sets are provided as CSV (comma separated values) files, which you will be able to open with spreadsheet software, such as Excel. Your task here is to generate some charts and graphs from this data, with a concern for what a teacher might find useful as a ‘dashboard’. You are free to invent some scenarios here – the context of the class, the subject matter being taught, or the level – as well as deciding what a dashboard might be for – monitoring students regularly, reporting on assessments, or even making predictions (for which you are welcome to add additional calculations). Following from the above, the task here is not to try and produce a fully functioning analytic ‘dashboard’, but rather to gain some experience of the processes and decisions involved: what data should be included, what should be excluded, and for what purposes? It is also primarily an opportunity for you to reflect on how ‘dashboard’ design embodies very specific assumptions about what a teachers ‘needs’ in order to teach.
Note that you need to be logged into Moodle in order to download these .csv files.
Getting a bit more advanced…
If you are interested in something a bit more advanced, you might try Google data studio – a fairly powerful online tool for bring together various data sources – data that you can upload yourself, as well as from a number of online sources – and deriving visualisations from them. The service is free to use, but do be conscious about sharing and private data.
If you’re also interested in playing with more complex datasets, you can search online. Kaggle is one example of an open source data repository, with a ‘Student Performance Data Set’ here, and a ‘Student Performance in Exams’ example here. You can also find public data at KDNuggets here, as well as a number of useful resources from Ewan Klein here.
Your key tasks this week will be to:
- Continue reading the core and secondary literature for this block
- Produce your weekly data visualisation
- Also try some of the ‘build your own dashboard examples’, and post some reflections on the experience in your blog