Welcome to the newly-launched AI Pedagogy section of ExpressiveAI.net!
One of the best resources and consultants an educator can have are their students. If you treat your students as future innovators and leaders, they can provide valuable insights and feedback on course design, especially if they know their instructors are invested in the bigger picture of the future of learning. This is why this AI Pedagogies section is being co-developed by students and instructors. If you are an educator, student, scholar, educational technologist, or curriculum administrator and would like to contribute, send us an email at mh193[at]nyu[dot]edu.
Now let’s get to the point. AI is here to stay. We can either vent about it, or accept it as our new reality and learn to thrive in AI-assisted environments. Remember when people thought digital learning was just a gimmicky fad?!? Let’s adapt to the new landscape and make the most of it. In my 20 years as an educator, I wasn’t waiting for AI to come along to challenge and redefine education — I had been doing that all along: questioning divides ranging from the (then) newly digital, to economic, skillset-related, access and accessibility, societal inequities, and more. My main methodologies involve adopting a process-oriented and modular approach to assignments and classroom activities so that students actively reflect on every step of the creative process, and helping students of different backgrounds and learning abilities identify their strengths through multimodal pedagogy. Thinkering (thinking + tinkering)[1]—the playful experimentation with digital tools and technologies that generates new modes of research and praxis— combined with intellectual curiosity are essential motivating forces, especially for younger learners who struggle to find their own authentic expression amidst a barrage of competing social media-amplified voices and influencers. Students feel that their work matters when they are given an active stake in the development of their fields of study, for instance thorugh public-facing scholarship, collaborative projects, and creative experimentation.
My point (and rant) is: If you have been waiting for AI to come along for you to reassess your teaching, learning, assessment methods, AND the entire educational institution, then you are already too late. But better late than never. AI will not revolutionize the future of education, but will be the catalyst to helping us reassess and reconfigure what works and what doesn’t in traditional learning models.
ExpressiveAI.net is launching a new section on AI Pedagogy and Educational Innovation where our founder, professor Marina Hassapopoulou, will be utilizing her nearly 20 years of experience in multimodal learning and innovative pedagogy to generate new creative learning ideas. Recognized with an international Innovative Pedagogy Award by the Society for Cinema and Media Studies as well as other teaching awards and spotlights, Marina’s pedagogy has carried into the AI era the DIY, “hacked,” experimental, and low tech/low budget ethos that set her students apart during the Digital Humanities hype. The unique multimedia work of Marina’s brilliant students has been showcased for the past 15+ years on the Interactive Media Archive, and ExpressiveAI.net’s new AI Pedagogy section hopes to extend this cutting-edge praxis into more AI- and algorithmically-focused contexts.
I will not follow where the path may lead, but I will go where there is no path, and I will leave a trail. ~ Muriel Strode, “Wind-Wafted Wild Flowers.”
Click on the drop-down menu to navigate this section and stay tuned for more soon!
[1] See Erkki Huhtamo’s “Thinkering with Media: On the Art of Paul DeMarinis,” in Paul DeMarinis: Buried in Noise, ed. Ingrid Beirer, Sabine Himmelsbach, and Carsten Seiffairth (Heidelberg and Berlin: Kehrer Verlag, 2010), pp. 33–46. For more recent applications of Huhtamo’s thinkering, see: Tim van der Heijden, and Aleksander Kolkowski. Doing Experimental Media Archaeology (Berlin: De Gruyter Oldenbourg, 2023).
*Header image credit: Yutong Liu & The Bigger Picture / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/
Header alt text: The painting shows a person standing on a staircase made of green and pink cubes, symbolising a Penrose staircase, in a cosmic environment. The person is reaching towards a glowing cross-shaped structure emitting binary code, representing AI’s reach into the future. Surrounding the figure are outlined boxes showing various elements, such as glasses, medical tools, a self-driving car, and financial symbols, interconnected by white lines. The background is dark with star-like dots and features colour-coded boxes which mark different elements as relating to AI, human involvement, a combination of both, or an area uncharted by AI and humans.
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