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Week 4: Project Plan
Date: September 27, 2023
Completed: Milestone 2
Summary: Create a plan for your project and iterate upon it as the situation changes
1. What did you accomplish last week?
The FastCompany Innovation Festival was not only a lot of fun, but there were a lot of insights I gleaned from the seminars and panels held there. Below is a picture of myself and my friend Titus, a fellow Master's student of Learning Design and Technologies at Columbia's CMLTD program, on the final day of the event.
I also met with and interviewed another professor this past week (Jan Plass) in addition to several industry professionals from the Fast Company conference.
And finally, I set up a rough project plan, which I will continue to iterate upon as my idea becomes more concrete.
2. What obstacles, questions, or surprises did you encounter, if any?
It's been surprisingly difficult to find time to synthesize all the volumes of data I've recently come across. Everything feels quite scattered at the moment. I'm reminded, however, of a lesson from my UX Design course about how designers need to know how to be comfortable in the messiness of things. We naturally want to bring order to chaos, but we should take care not to be in a rush to do so it if will come at the expense of the quality of our insight discovery process.
3. What do you plan to accomplish for next week?
While taking the time to synthesize all the data I recently came across, I'm also scheduled to attend a full-day conference on AI and Education that is being hosted by my EdTech professor Betsey Schmidt. That will take place on Saturday, September 30th, and will feature a good mix of industry professionals, academics, and educators, so I'm very much looking forward to it.
In addition, I will solidify my project plan by next week and submit my M2.
To no one’s surprise, the “thing” on everyone’s minds this year at the conference was AI. Although AI has been around for awhile, the renewed focus on it this year is most likely due to the advances made specifically with Generative AI.
So at the core of a lot of the discussions this week was the question: What is AI’s purpose? It was just one question, but it generated the following thought-provoking answers, all equally-valid and telling of the lived experiences of the people behind them:
"Just create. Don't wait." - Roblox
“Imagine an intern being able to tap into the rich history and knowledge foundations built at Expedia by everyone who came before them through GenAI.” - Expedia Group
"I want AI to know what I'm going to want in 10 years." - Scale AI
1. After being retired from competition, IBM’s Watson AI published a cookbook with 65 unique recipes. It seems even supercomputers feel the need to stay productive during retirement!
2. It’s actually Sales & Marketing that is being MOST disrupted by GenAI (49%) followed by R&D (which most people would assume to be first).
3. Engineers and techies obviously knew the most about how AI actually worked, while Sales & Marketing execs were transparent and upfront about how little they knew. It would seem to me that closing this gap should be a top priority for organizations, since it's Sales & Marketing that are, you know, doing the selling and marketing!
“You want good AI? Be better humans.” - Wesley Eugene, IDEO
“Choose your own tools for building your own product, don’t give in to someone else’s way of doing things. The greatest artists mixed their own paint.” - Sanjiv Yajnik, Capital ONE
The classic approach to a design problem is to utilize the Double Diamond or Design Thinking frameworks, which provide clear direction on when to apply Divergent vs Convergent Thinking as well as clear delineations of when one step in the process is completed and the next begins.
One of my issues with how the thesis project is conducted, however, is that it can be a bit divorced from reality. And that's because of how students are encouraged to come up with an idea and then apply a design process to it. The idea may be a great fit for academic research, but may not have any real-world relevance or it is solving for a problem that nobody really has. Without being grounded in the real world, therefore, these projects can run the danger of being overly academic and/or not very practical.
Again, I would like to point out that I have no problem with how other students decided to pursue their projects. I am just providing a rationale for my own deliberate design choices, which begins with wanting to create a project that is grounded in reality and can have a real-world impact that addresses real needs outside of this master's degree program. And building something that people will pay for grounds it even more solidly in the real world, which is why these are all very important facets of my design rationale.
So with that being said, I am going to be making use of the following Triple Diamond framework below, which includes Strategic Action as a crucial link between the standard Problem and Solution spaces.
The Problem space allows us to identify the problem, and the Solution allows us to ideate and develop a solution for that problem, but where is the mechanism to ensure we are developing a solution that customers will actually pay for? Where is the mechanism that will ensure that your solution will go from a "nice-to-have" to a "need-to-have?"
This Triple Diamond framework grounds the Problem and Solution spaces in reality with the Strategy diamond. And I think this is necessary because it's very easy to get carried away identifying a problem that doesn't really exist and to then deliver a solution that nobody will actually want to pay for. But when they are both grounded in Strategy, it holds those two spaces accountable. It forces you to ask yourself,
This works best for me since I can use the Strategy space to help me filter everything in the Problem space. And then when I'm ready to create a solution, I can again filter my solutions through the Strategy space. In this way, it operates as a very useful tool for both grounding and funneling.
So while this triple-diamond framework is the model I'll be applying to the overall design process, I may also need to incorporate some other form of design model for the actual learning design itself.
This can come in the form of the Kemp model or perhaps ADDIE, SAM, or the Backwards model, but it won't be decided until after the initial assessments (learner, context, needs, etc) can be conducted.
September
The first few weeks are dedicated primarily to Topic Discovery (or, the narrowing down from many possible avenues to just one project idea).
October
Starting from the end of September, my plan is to apportion a generous amount of time towards conducting research...about 5 weeks in total. Week 1 (Sept 28-Oct 3) is focused on developing the plan, Weeks 2-4 will be focused on conducting the actual research, while Week 5 (Oct 26-31) is focused on synthesizing the findings of the research and drawing insights.
I'd like to put a heavy emphasis on research because my past experiences (in previous classes) showed me that there was rarely enough time to conduct this part of the process thoroughly.
November
As my research comes to an end, I will focus most of November on Prototyping, with the first week emphasizing the early prototyping (and feedback) process, which gradually matures into a more fleshed out prototype by November 29th, when I plan to use our class time to test it with my classmates.
December
After conducting a final test of the early prototype, I will focus the remaining weeks on the two deliverables: a video presentation and the S1 end of semester paper.
