The final project at my last role involved extracting seven years of learner data for 80,000 learners from an LMS that was being decommissioned. The shock of our vendor’s £150,000 quote to both extract and host 3TB of learner data led me to explore a robotic process automation (RPA) solution using a low cost browser plugin, UIVision. This article explores how I crafted and fine-tuned a suite of RPA scripts to automate the data extraction and reflects on the challenges faced and lessons learned.
I’ve seen a lot of LinkedIn posts recently about professionals who do voluntary work, and then use those experiences to sell their services. You know what I mean: “Look at me coaching my baseball team, we do such a great job building resilience in our kids. Why not buy some management and leadership training from my company and build resilience in your own team.” I can’t stand that bullshit, it just feels wrong to leverage good deeds for sales.
Following an amazing weekend, I want to share my own volunteering experience, but I won’t try and sell anything off the back of it! Instead, I’d like to ask a reflective question: how much do you invest in your own learning outside work? I’m thinking time, not money.
About five years ago at Brightwave, we worked on a chatbot prototype for The Samaritans. The chatbot was a learning simulation tool, with the chatbot acting out the part of Bella, a bullied teenager. The training was for listening volunteers who were increasingly supporting people via chat channels rather than telephone calls. Bellabot offered a safe place to fail, to hone their responses on a text-only interface.
Bellabot was a completely scripted experience that only had a small range of conversational prompts about how she was being bullied and how that made her feel. As a volunteer, you had to listen to and chat with Bella. Despite the limitations, everyone who ‘talked to’ Bella was astounded at how emotionally engaged they became in the conversation. It was as if Bella was a real person, not a bot. Immersive is a word usually reserved for high tech, virtual reality simulations, but this low tech, text-based experience was one of the most immersive learning experiences I’d ever had. Now that Brightwave has been merged into Capita most of the original online blogs and presentations seem to have been taken offline which is a real loss, but the team ran quite a lot of webinars and conference sessions to talk about this at the time, it was a fantastic learning experience in how to use chatbots as a learning tool.
Fast forward to 2023 and you’d need to have been living under a rock to not know that chatbots have moved on somewhat since then. ChatGPT offers some amazing possibilities. One of the earliest and most intriguing uses of ChatGPT was when some child realised you could use it to generate text based MUD games, where you give the chatbot a scenario to play out and let a text based adventure unfold.
People have been trying to find educational uses for blockchainfor many years now. I try to carve out a little time every year to see if any research projects have matured into industry products but it’s never a productive search. There are always dedicated practitioners (mostly academics) running proof of concepts, and many more edtech commentators weighing in with blogs, ideas and conjecture about blockchain’s potential in education. But over the years things have progressed at such a glacial pace, I had pretty much concluded that blockchain in EdTech was possible just a solution that couldn’t find a problem.
I recently completed the Designing a Feminist Chatbot course on FutureLearn. As a starter course it has a lot going for it, covering areas such as different chatbot uses, how chatbots can become biased, user centred design (UCD) principles, persona creation, conversation design, storyboarding and prototyping. Having studied UCD at degree level and worked on countless software design projects in my career this could have become a bit boring but it’s always good to revisit the basics and is especially interesting to apply existing knowledge to new problems. There were some fascinating new areas to me such as conversation design and chatbot personality design, and the course drew heavily on the Google Conversation Design Process which is a great resource in itself and has some useful canvas-style templates for guiding the development of a chatbot.
This week’s dataset was from European Institute for Gender Equality and shows the proportion of seats held by women in European parliaments and governments. Another great dataviz learning experience and on the whole I’m OK with the finished product this week, I know I still have a big journey ahead of me to create some decent work, but it feels like a big improvement and tangible progress on my previous effort. I used the timeline slider for the first time and explored Tableau’s formatting tools in more depth. I also applied some learnings from last time by going straight for portrait mode, using a decent font size, avoiding cognitive overload and keeping the screen elements to a minimum, leading with the key finding and then fleshing out the detail further down.
I’ve been meaning to take part in Makeover Monday for some time as a way to improve my data storytelling skills. This weekly learning event has been running for a year or so and I love its simple but effective format: a data vizualisation and accompanying dataset is released at the start of each week and you simply read the brief, analyse the dataset and make over the visualisation, submitting your work into the Twitter dataviz community for feedback. I am a big fan learning by doing, so while a 10 week Coursera on Data Vizualisation might be interesting, I don’t think it would be nearly so useful as just getting stuck in with some open data sets and trying things out, getting feedback from the dataviz community and iterating your work. Active and social learning at its best!
Towards the end of 2020 our Head of Learning Design asked me to do a short presentation to her design team about where I thought the main disruptions to the Learning & Development technology market would come from in the year ahead. Usually we would look at startups, niche suppliers or parallel industries to identify potential disruptors. But if 2020 taught us anything, it was to think differently and look elsewhere for what could turn markets upside down!
You don’t need to be on the product design team to have an interest in user experience. Putting the user first is part of all of our jobs in software and product development, as important as putting the customer first is to a business or service. User centered design (UCD) is the beating heart of all good product development so it’s beneficial for everybody in the team to develop a solid understanding of its principals and to put the user first at every opportunity.
Adaptive learning uses competence, behavioural and demographic data to tailor a digital learning experience around each learners unique needs. There’s a lot of hype around this area which might have you thinking its all about Artificial Intelligence (AI), but that’s not the case and there are two types of adaptive learning approaches: AI-based and Rule-based. Each will afford you different features, benefits and outcomes.
