“Open Data Training: Education Data Dive” workshop was held on 6-10 October 2014, in Dar Es Salaam, with representatives from Ministry of Education and Vocational Training (MoEVT), Prime Minister’s Office- Regional Administration and Local Government, National Examination Council of Tanzania (NECTA), E-Government Agency (EGA), National Bureau of Statistics (NBS) and National Council of Technical Education (NACTE), Tanzania Education Authority and other institutions.

Group photo for training in Dar es Salaam

This was my first time co-facilitating a workshop of this kind as a School of Data Fellow in Tanzania. And it was a fantastic opportunity for me to sharpen my facilitation skills and also to learn from other facilitators, including the main facilitator and a more experienced among us all, Michael Bauer from the School of Data. It was a wonderful thing seeing all these government agencies responsible for education, in one room, learning and sharing from one another, which even by their own admission is very rare situation. When we were preparing for this workshop we knew that there is an existing expertise and knowledge about specific education datasets, but the challenge is mainly in letting other agencies know this so that they can be able to collaborate between themselves. It was fitting then that we had several datasets from some of the agencies that we used during our workshop to bring participants to a common understanding of open data concepts, teach and practice data wrangling skills and clean and join key datasets that some of them were already familiar with.

We started the workshop by focusing on developing a common understanding of open data and data management with concepts such as improving usability of already available public data providing better metadata and improving data workflows, to open licensing of data. Then we proceeded to introduction of various tools for data cleaning, analysis and visualization, including Open Refine, QGIS, Fusion Tables and Pivot Tables. This was the first time that most of the participants were using these tools, and they were excited to see how these tools opened up a world of possibilities that they did not know that existed with the datasets that they are working with often. An example was clearly illustrated by one participant from the PMO-RALG who was glad to have discovered Pivot Tables, as most of the tasks that he is working on most datasets would be simplified a lot using Pivot Tables skills. These practical hands on sessions were met with enthusiasm by all participants, and despite dedicating two full days, they were still up to spending more time cleaning, merging, analyzing and visualizing their datasets using these tools.

Brainstorming during the workshop

One major discussion that resonated throughout the workshop and how these agencies through working together might be able to come up with solutions about this , was the lack of unique codes that can be used to identify schools by different education stakeholders when dealing with education datasets containing schools. Most participants were of the agreement that merging data sets and coming up with analysis and visualizations during the workshop, would have been much easier, if we had unique codes used by every agency whose data sets were used during the workshop.

The latter part of the workshop was mainly spent, collecting feedback about the workshop and jointly plan the way forward for the implementation of what participants learned in their daily workflows. The follow up plan was drafted in which we will have a bi–weekly sessions with some of the participants to work together to implement what they learned during the workshop and also to revise various techniques about the tools learned and to dive deep into techniques we could not cover during the workshop.

Post-it notes from the workshops

The highlight for me of this workshop was the informal discussions that participants were having during breaks in which most of them were of the agreement that Open Data initiatives need not be seen as a foreign based concept imposed on Tanzania, but rather Tanzanians themselves need to see the benefits and take ownership of this concept.

(photo of Ignasi, Olu and Ketty by Heather Leson, July 2014 (CC-by))

You probably have a skill or knowledge that others would love to acquire… but teaching can be intimidating. Fear not! In this post, we will share a few tips from the School of Data network, which is filled with individuals who hold continuous trainings on all things data worldwide.

Prepare!
It’s not a great idea to improvise when you are frozen by stage fright, nor to realize in the middle of a workshop that you can’t continue as planned because you are missing materials. That’s why formal planning of each workshop can help. Here’s an example you could use.

Michael from School of Data in Berlin has a special piece of advice for your planning: “Be yourself! Find the teaching method you feel comfortable with (I like to do things ad-hoc, Anders prefers slides, e.g.)”

Also, maybe it’s a good idea to partner up. Cédric from School of Data in France makes a great point: “There are two essential things in a workshop: knowledge of methodology and knowledge of the subject. More often than not, it’s better to separate them between two people. One will make sure that the workshop goes smoothly, and the other will help individuals get past roadblocks”.

Be mindful of how you speak
Beyond what you say, the way you speak can have an impact on the success of your workshop. Michael (again) and Heather from School of Data in Toronto recommend that you try to speak a bit slower than you’re used to, with simple sentences, and avoiding jargon or descriptive metaphors.

Make it a friendly environment
Helping people feel comfortable and welcome is necessary in every educational setting. Happy from School of Data in the Philippines explains it: “The point is to keep it as trivial as possible so that people don’t feel intimidated by the skill level of others”.

Codrina from School of Data in Romania has a lot of experience here: she recommends not keeping it too serious, and rather make small jokes; also, “give a little pat on the back for those who ask questions”… And don’t forget to take breaks! Yuandra from School of Data in Indonesia reminds us of something crucial: refreshments and water. People won’t learn if they’re distracted by hunger.

Also, icebreakers. We all love icebreakers, and Olu from School of Data in Nigeria has these in mind.

Try to connect with your audience
We use this phrase a lot, but what does it mean? Ketty from School of Data in Uganda puts it in very practical terms: try to read the learner’s facial expressions for e.g. confusion/tiredness/intent. This will help you find the best ways to continue.

Also, Ketty adds, “sometimes you have to be flexible and allow the learners to change your program… A bit of a give & take approach”.

On a slightly different topic, but still related to your connection with the audience, Olu thinks your audience will be inspired to work harder in your workshop if you tell them stories of what data/open data can be used for. You can find some at the World Bank Open Data Blog, and here on School of Data.

Some other didactic considerations
Heather recommends that you repeat key things 3 times (but not right after each other – spread them throughout the workshop). Also, Codrina recommends repeating questions when they are asked so everyone can hear before the answer is given.

Another recommendation: If you have a really successful workshop, try to replicate it through other media. For example, run it on a hangout, write it out on a tutorial. Multiple content won’t be redundant – it will mean more and more people will have a chance to learn from it.

Happy has a great tip: “When you want to get the group to mingle and pair up (data analysts paired with visualizers, for example) one way to do it is to divide the group, 1 line for data analysts, another for visualizers. Then we ask them to line up according to a range of categories – from technical categories or something as simple as personal information, like the number of house they lived in during their childhood, for example”.

Make an effort to keep track of time and exactly how long you spend on each part, Cédric recommends, as this will help you plan for future trainings.

Communicate
Your audience may well be outside the room where you are doing the training. Cédric adds: “Sometimes good suggestions can come from social media platforms like Twitter, so if you have an audience there, you might want to share some updates during the event. People might answer with ideas, technical advice or more”.

Evaluate
The workshop was fun and people attended. But did they really learn?

Try to evaluate this learning through different methods. Was everyone able to complete the exercises? What did they respond that they learned in your ‘exit survey’? Did you get good responses to your last round of oral questions?

Olu kindly shared a couple of forms that can be used for this purpose both before and after the training. Feel free to use them!

A few resources shared by the School of Data community
Notes from the OKFest How to Teach Data Session (July 2014)
Aspiration Tech has great tips in their guides (via Heather)
PSFK on how people make/learn (via Heather)
Escuela de Datos on our Local LATAM training lessons learned