I met with the Interactive Video (IVY) from the Design Intelligence (DI) for the very first time. I was ecstatic to finally meet the group!

In the beginning, before the main meeting begins, the group discussed the latest developments in AI technology, particularly GPT 4.0, and its potential applications in tutoring and education. Dr. Ashok introduces the IVY project and its aim to combine understanding of in-video context with generative AI to generate explanations. Then the GRAs who worked with IVY previously gave a quick presentation on the overall cognitive model framework and the current updates on the paper that will be produced by the group. Then, Dr. Ashok has set an ambitious and challenging timeline for accomplishing IVY by end of summer for use in January 2025 classes. On my end, my goal is to start the onboarding process, starting with the TMKL2 documentation and the Project IVY onboarding documents.

Project IVY Onboarding Documents

I’ve reviewed the documents with IVY’s research questions, hypotheses and assumptions. As well as the poster for the IVY project which has a good overview of the current work and progress of the project. I’ve also watched the video “AI-ALOE Webinar with Professor Mairead Pratschke”. The video discussed learning theories of AI, which are derived from established learning theories (of humans). She delved into the digital ecosystem – from Web 1.0, the Read-write web to now Web 3.0, Semantic Web (Meta Data + Personalization) and then finally, to the future Web 4.0, Symbiotic Web (human + computer). I thought this was an interesting point, I never really thought about the direction of our digital ecosystem. I can see the need to further research and understand human-machine interaction and collaboration, especially in the field of education. The speaker also highlighted the “Community of Inquiry” as a learning model that is more collaborative and constructivist that really ties to the research questions and hypotheses of the project.

Literature Review on Learning Theory

As advised, I started reading the paper titled “The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes” by Michelene T. H. Chi and Ruth Wylie. This paper illuminated the critical concept of cognitive engagement and its relationship to active learning outcomes. It became apparent that doing anything else but receiving learning materials isn’t enough (passive learning); students must ascend to a state of cognitive engagement characterized by overtly active behaviors during learning activities. The ICAP framework introduced in the paper outlines four modes of engagement: Interactive, Constructive, Active, and Passive, with a hierarchy of engagement levels from Interactive to Passive (I>C>A>P).

Each mode has its own definition that can be used to distinguish it from the others. Interactive engagement involves discourse with constructive dialogs, while Constructive engagement entails generating externalized output and fostering new ideas beyond given information. Active engagement, on the other hand, requires some form of manipulation while receiving information, coupled with focused attention, whereas Passive engagement involves merely receiving information without overtly engaging in additional activities. I have understood that the levels of engagement of say, P is encompassed in I, C and A.

I’ve also contemplated on the dichotomy between Constructionism and Instructionism in educational paradigms. Constructionism advocates for learning through discovery and the generation of new ideas from one’s own understanding, rather than following strict instructions. Tutoring tactics aligned with Constructionism often involve prompting, encouragement to construct, and hinting, fostering an environment conducive to active learning. These are the type of tutoring tactic that we want to come from the coaching Agent. However, truly interactive learning goes beyond this. It needs a mutual exchange of novel ideas beyond the given information, with equal participation from all parties involved. This is where the coaching Chatbot really hammers home the message. Ultimately, we want to be able to create a human-machine interaction wherein it sufficiently begets interactive learning.

Literature Review on TMKL2

This week I started reading and getting familiar with the programming language that is being used to model the Agent in our Lab. The TMKL language, developed by Bill Murdock, serves as a crucial tool for the Design Intelligence Lab in modeling knowledge representations. Building upon its predecessor, TMKL, TMKL2 is designed to facilitate reasoning and adaptation within software agents. At its core, TMKL2 retains the teleological nature of TMKL, establishing direct connections between agent goals and the mechanisms required to achieve them. This teleological approach ensures a clear alignment between agent objectives and the means to realize them. TMKL2 comprises three main subnotations: Goals, Mechanisms, and Environment, which are akin to TMKL’s Tasks, Methods, and Knowledge, respectively. Each subnotation provides a framework for defining and organizing essential components within the agent’s operational context.

Creation of the DREAM Web Page

This week I started to work on the summer research webpage, populating the index.html with descriptions about myself, my project, and my advisor. With this post, I’ve created my first blog entry to this website as well. With a few more tweaks, I will be complete here and then I’ll send this over to my advisor for his review.

Other Reading

I started reading the book titled “How to Read a Book: The Classic Guide to Intelligent” by Adler and Van Doren. There are different levels of reading: Elementary, Inspectional, Analytical and Comparative. The authors compare properly reading as catching a baseball, it is a skill. Passively reading is akin to low-effort ball catching and higher levels like analytically and comparatively reading is like catching the baseball but taking into the account the wind direction, analyzing the balance and strength of the pitcher and anticipating the amount of adjustments needed as the ball gets closer etc. I’ve contemplated on the first few chapters and I think this concept is similar to the different levels of cognitive engagements in the ICAP Learning Theory. I’ve also realized how I need to improve my own reading ability, to really dig deep when I don’t understand what the author is saying and what they actually mean and not just what I can interpret from it and leave from there. There needs to be an improvement of merely “kinda” getting it to really getting it.