Data Visualisation #3
My week of distractions
My week of distractions proved much harder to track than I originally thought. I was interested in finding out what distracts me from my daily activities but also to look at my focus and motivational state during that distraction. I decided to capture the following:
- my main work/learning activity;
- the distraction; and
- the level of my focus/mental state e.g. relaxed, reflective, alert etc…
Having the awareness to understand when I was distracted and to record it was tricky. It was often when I was returning to the original activity that I then realised I had been distracted in the first place! So, my data ended up being scrawled all over the place on my various notebooks (even on my hand) and at the end of each day, I collated it all in one spot to ensure I didn’t lose any data.
The visualisation itself is very loosely based on an EEG and four different brainwaves (gamma, beta, alpha, and theta) to try and reflect my mental state and level of focus at the time of the distraction. I also wanted to depict how the activities jump from one to the other and the impact this has on my focus and potential performance.
Reflecting on the week, I can see that I am easily distracted and veer off for a multitude of reasons. This is something that I was already aware of, however, it was good to see these distractions on paper and categorise them. It has been helpful to highlight things that I can change in order to refocus and improve my concentration, and hopefully, make a positive impact on my work, such as putting my phone on ‘do not disturb’.
However, some things I wouldn’t change. Before starting this exercise, I assumed that the majority of my distractions would be digital and I was happy to see a relative balance between offline and online activities. At a time where I always feel available and online, my assumptions do not quite match reality.
Equally, I think it is important that I have periods of focus, as well as times of reflection and relaxation. I think this balance is reflected through the visualisation above. While I acknowledge I find it difficult to focus, it would be unrealistic to expect total focus and there are times where daydreaming, scrolling, or even talking out loud to the cats can lead to an idea, greater creativity, and innovation. As depicted above, these periods of time often then lead to a period of refocus and productivity. There is an assumption that a distraction will have a negative impact, however, I think distractions such as daydreaming, chatting with my wife, playing with my cats, and even housework can be positive. Not all distractions are negative and it is ok to be distracted! In the future, I need to be less hard on myself and accept that these distractions not only help my general well being but can also help aid my learning and make a positive impact on my work.
Really interesting visualization and reflection. Several things really caught my attention. Your comments about the messiness of data collection really highlights the complexity of the measuring instruments that are often working behind our backs, without us knowing. The other key thing was your comment about distraction being potentially positive. So much educational work is focused on anti-distraction. A wandering mind would not produce a signal of a focused and concentrated learner — and yes, there are brainwave-reading devices that, it is claimed, can produce EEG signals of student concentration and attention (look up BrainCo). And so your representation of your week of distractions as an EEG is really interesting too, because various organizations are increasingly looking to capture alternative forms of data about learners, including their brain data, as a way of ‘nudging’ students’ attention. Maybe in the next block on ‘teaching with data’ you might consider whether such sources of data would be useful to the teacher.
By the way, don’t forget your overall 500 word commentary on the ‘learning with data’ block. I’ll check in again later in the week to read this.