Throughout my projects, I learned that different strategies are necessary to achieve both sides of the engagement coin: initiating and persisting.
For instance, the early game instructions in Pollinator Protectors produced frustration and confusion among learners, delaying and detracting from the intended learning: key information was omitted and what was included was often overly-complicated. Testers of our earlier prototypes leaned on our design team to answer their questions related to their understanding of the instruction ("how do we set up the board?"), and it consequently took them two-hours to play through the game. The "learning" in these versions was more focused on the game itself rather than ideas about pollinators and pollination.
Once the game instructions were more effectively simplified and addressed common gameplay scenarios, the youth game testers were able to play successfully with little to no adult support, much like how they would expect to play the game with their friends or siblings. With these updates, playing time was cut to 30 minutes. Through this process, I learned that inviting engagement requires that there are "low-floors" to the design interaction and that the extraneous load of the experience is minimized.
The images to the right show how the game instructions evolved over time to "lower the floors" for learning.
When developing Artful Analytics, my prototype testers at the Boys & Girls Club were mostly in 3rd and 4th grade, with a few in 2nd and 5th grades. I knew that learners in these grades likely haven't encountered "data science" outright in school, so I wanted to be cognizant that I was introducing them to an unfamiliar content area. However, children at this age are interested in and enjoy making artistic creations, so my target learners were children who like to make art and may be unfamiliar with data science. I was also aware that it's important to combat rising math-phobia among this age-group by ensuring that early math experiences are positive and fun.
With these factors in mind, I wanted to center art, creativity, and expression as a vehicle through which learners could encounter data science concepts and apply them. Indeed, those who returned every week were the ones who enjoyed art the most. These learners were excited to apply their skills in a new way and constantly went above and beyond what I had anticipated in terms of engagement.