What data points are needed to demonstrate learning?

Tweetorial Week

This week, we participated in a Tweetorial as a part of the course. These weeks always come with a bit of dread because I’m not a fan of Twitter. I find the platform chaotic and rude. Rarely, have I opened Twitter and after 20 minutes of scrolling metaphorically walked away enlightened, happy, or relaxed.

I also find the notifications quite distracting throughout the day because in comparison to others like Instagram that often just tells ‘here’s some new accounts to follow’, Twitter notifications have a different sense of urgency and thought weight associated to them.

In this context, I decided to track my actual and emotional engagement with the platform this week. The question I was asking myself was even if I didn’t receive a notification, was I still thinking about Twitter.

Notifications, Reading Tweets, Engaging (i.e. liking, retweeting, or responding), and thinking about Twitter

The image above represents my week in 7 lines with Monday being the first and Sunday the last. The four horizontal lines divide the day up into 6 hour chunks, the bottom being from 00:01 – 06:00.

  • Blue represents a received notification
  • Purple represents reading content in Twitter
  • Turquoise represents engaging (i.e. liking, retweeting, or responding)
  • Yellow represents any time I found myself thinking about Twitter or the activity

Note: I concluded the activity around the time I started writing this blog post and turned off all notifications from Twitter again.

There was little activity on Monday as I read about the Tweetorial late in the evening when checking the course website. The week was quieter as well sine the activity itself had finished, but I had forgotten to turn off all Twitter notifications, so they were still popping up on my phone.

The middle of the week has the most activity as I opened the app every evening to engage with the question posed. What I found was that it took quite some time to read through the tweets from classmates to see what was happening in the conversation prior to engaging with the question myself.

The notifications themselves came in at any time dependent on other student activity and any other ‘older’ notifications that I had set up before creating a new Twitter account for the course. Enabling the notifications opened a can of worms as I had no memory of what I’d previously set up and as a consequence became very distracted as the flood of notifications was constant.

To answer my question – I was thinking about Twitter often throughout the week. This occurred as I saw notifications pop up on my phone, but also when ‘nothing’ was happening. I would think back to a particular response, or if I had anything else to add to the conversation.

In a way, the thinking became a useful way to passively engage with the course as the week progressed. This reflection in particular made me reflect further about the responses posted on what data is collected in learning platforms, and if it actually correlates to learning.

For example, if a student is thinking about a video watched and has a conversation about it outside of the platform, how would the teacher (or data collector know) if this was not recorded in the platform? They would only have access to the fact that the student watched the video, how many times they watched it, and if they answered any questions, commented, etc about. Nothing outside of the platform would be tracked, yet that doesn’t mean the student is not learning while engaging in the outside conversation.

Overview Reflections

First Data Visualisation

Last week, I decided to track my music habits. Music is something that I listen to every day. It keeps me focused, lifts me up when I need a mood or energy boost, and often is selected based on what I’m doing.

Throughout the week as I was adding the data points, I kept coming back to the following in Chapter 2 of Big data in education: the digital future of learning, policy and practice:

From the eighteenth-century perspective, ‘data are apparently before the fact: they are the starting point for what we know, who we are, and how we communicate’, and were often perceived as transparent, self-evident, neutral and objective, ‘the fundamental stuff of truth itself’ (Gitelman and Jackson 2013: 2-3).

Williamson 2017 (p. 29)

Music in the same way as data is described above is what I know, who I am, and how I communicate to myself. What I was not expecting, was that the visualisation of something that was meant to be ‘transparent’ or ‘objective’ would feel personal. When looking at the visualisation, I’m looking at what I needed, or how I felt at a certain point in time through the perspective of music.

In the uploaded image, I tracked on what device I listened on and the four playlists that were on rotation this week. I have Spotify on every device I own. I also decided to include a data point for any other time that I was wearing my headphones and not listing to music – when I sat in meetings.

In looking at this image and analyzing the week, I find that almost 50% of my days last week were filled up by meetings, and I wear my headphones more than I probably should… I also heavily rely on faster paced music to get me motivated for a workout, or when I needed to get something done. Weekends are, however, were filled with slower paced music when I was cooking brunch or cleaning up around the flat.

During working hours, I rely on my headphones. Alexa is rarely, if ever playing music as I work in the same room as my partner. At night, she is queen. My headphones and playlists are a way for me to transport myself to somewhere completely different when my partner is on a call (and I’m not).

As I couldn’t completely tear myself away from my list-focused and scheduled-oriented self, I decided to include a Y and Z-axis for the days of the week and rough waking hours to make it easier to read (as well as track). I knew that I would struggle to remember to jot down when I was listening to music, so I set an alarm on my phone three times a day to help me get into the habit. Maybe by the end of these next 9 weeks, data tracking will become a habit!

Looking through the Dear Data visualisations once more, I am so amazed at how creative Girogia and Stefanie are. It took me a while to come up with the symbols for meeting, phone, computer, and Alexa. I’m secretly hoping this exercise also sparks more creativity as I think through the data over the course.

Overview Reflections

Hello world!

Welcome to Critical Data and Education.

This is the beginning of a data journey. Over the next few months, I’ll be diving into the data collection process and attempting to make sense of data as it relates to education.