A try-out data visualization

Hello, everyone! A managerial position in a global IT company suggests working with a plethora of reports, learning analytics and stats of all sorts on a daily basis. Hence, looking into numbers, discussing them with my colleagues and taking decisions relying on what I see is part-and-parcel of my daily routines. That’s why for my ‘practise visualization’ I opted for tracking instances when I interact with the in-company analytics. Have I discovered anything revolutionary? Not really. The data show that, indeed, analyzing numbers is a regular activity for me. Most often I read reports or discuss the insights with colleagues. Perhaps last week was more data intense than usual, since I’m getting ready for promoting some of my team-members, hence I had to check many reports.

The topic for my first visualization may also explain why this course is of particular interest to me. I’m working in the environment where data are considered to be the supreme good for all spheres, and education is no exception. Thus, I feel it is crucial to develop a critical understanding of what data really are and what benefits and risks they offer. Working with teachers and students, I would really want to understand how I could empower them with the data we have at our disposal rather than use the analytics as a stick, something that Selwyn and Gasevich were talking about. As a learner myself, a teacher and a manager, I’m looking forward to considering datafication from all the 3 standpoints, and looks like the upcoming blocks will give us an excellent chance to do that.

6 thoughts on “A try-out data visualization

  1. A great visualisation, very clear to understand!

    I am curious to see your views and learning on the topic over this module. I work in IT also so maybe the view of dashboards and data becomes rather tedious or part of every day life and does not have the same impact as other professions. The reason I say this is the following statement “Have I discovered anything revolutionary? Not really.”

    Also isn’t big data meant to take away the need for us to read all these dashboards but it seems as though from your week, this was definitely not the case.

    I am curious is the reason for you doing this Masters to help the people you manage improve more and understand how to guide them or is it to possibly transition into education at some point?

    Looking forward to seeing the upcoming visualisations.

    • Thanks for your comments, cwalsh! In fact, I’m an educator by training and by vocation, but for the past 8 years I’ve been working in corporate training in an IT company, which has had a certain effect on my mindset, the tools I use and the way I see learning and teaching. Answering your question re my motivation for this master’s program, in simple words, I would like to better understand how technology and education could ‘synergize’. Besides, I aim to develop better critical thinking in relation to the omnipotence of the tech progress – the context I’m working in.

      You make a great point saying that big data is probably expected to help us with ready-made decisions rather than provide calculations or summaries. Frankly, at this stage I would never feel safe about those decisions. Technology is still a black-box in many ways, and finding bugs here and there is a norm. Very often the stakes are too high.

      What about your IT environment? Do you feel the spirit of ‘solutionalism’ in educational discourses?

  2. Hi Iryna,

    I will be interested to hear of your comparison of experiencing possible datafication in your three different roles. For instance, how much you want to know about others, but see that information in an easy to read manner, against how you feel about yourself being represented in a simplified manner

    • That’s deep, Tracey! And I think I see your point. That’s why when evaluating teachers’ performance, for instance, I consider observing their lessons, talking to teachers as well as their students, being aware of their hobbies, families, developmental activities no less important than analyzing dashboards and measuring their success. We are people after all, we are complicated…

  3. Great visualisation and good choice of topic. I think, like me, you deal with a lot of data but mostly in a manual way, is that right? That’s how interpreted the single instance of bot presented data anyway. It reminds me og a job I once had, doing business analysis; I was staggered how un-automated data often is.

  4. Thanks for raising this question, Matt. Indeed, although I’m sure that my professional life is much more automated than that of millions of my colleagues, it is still a great deal of manual and brain work. The reports are pretty scattered as well as the stakeholders, so it takes time and effort to make the numbers work.

    As for this bot interaction, I mentioned, in fact, it’s the so-called ‘nudge’-mail that summarizes relevant data for me and offers action points and relevant resources. It can be handy at times, but needs decoding and consideration anyway.

    Interestingly, big data saves our resources as well as wastes them. Hopefully, bringing value…

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