This whole exchange produced immensely valuable pedagogical exchanges that will probably be useful to others for years/decades to come! Thinking crazy thoughts now about borderless classrooms / MOOCs / learning communities 1/n
Importantly, the q came in an unexpected "package" (in terms of demographic and form), a beautiful thing in terms of diversifying how qs can be asked and by whom:
To me this shows the exciting potential of broadening access, not just for students, but *to* students and also *to* educators (and yes, students will also be co-educators!). 4/n
I have a personal stake in this as a #firstgen college student and academic from a non-Ivy-league background, who has immensely benefited from, basically, Twitter as open MOOC, even now:
But I recognize my experience is colored. There are substantial dangers of opening things up to *everyone*. Bad actors are real, foibles can be amplified, little design decisions have outsized impacts. Is a reality of massively open (to all) ed systems desirable or feasible? 6/n
Not even sure it's that different from existing work in online education, learning at scale, (thinking of @chinmay, @houshuang, @bod0ng, @hqz, @imjuhokim, and many others I'm definitely missing). But if it is, what core problems emerge that we need to solve? 7/end
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Can #toolsforthought like RoamResearch, Obsidian, and Notion actually help us think better? If so, how?
In our #UIST2024 paper, we distill hypertext patterns from real-world usage that augment sensemaking by addressing temporal + spatial fragmentation of sensemaking
I see this work as complementary to the rich practical wisdom many have shared in the #toolsforthought community - I hope that connecting this wisdom with research on hypertext and sensemaking can enrich our understanding of how these tools can help us think better
If this sounds interesting to you, dig into the paper here:
And come chat with us during/after the "Learning to Learn" session at 3:35p on Wed 10/16 @ #UIST2024!
I get wonderful shared delight from hearing others talk abt deep insights that influence/delight them.
I'm also curious what constitutes "depth" (broad implications, surprise, difficulty, etc.).
Would you share a deep insight that influences/delights you + explain why?
Thought sparked by this snippet from @Noahpinion's interview w/ @VitalikButerin where they get into the reasoning behind the coming switch of Ethereum from Proof-of-Work to Proof-of-Stake:
#Idea - NLP to do initial clustering/classification of altmetric-aggregated discussion of preprints, to facilitate finding high-signal discussions and critiques of preprints (honestly would want this for any paper!).
Preprint servers already hook into @altmetric to expose mentions of a paper in news/blogs + social media (tweets).
But it links to an undifferentiated list of sources (not titles, citation contexts) - good for signaling "attention", missed opportunity to get real context.
If preprint servers have access to commercial API from @altmetric, classifying (and then clustering, enabling searching by) these mentions is eminently doable (e.g., can frame as a straightforward citation context classification problem, like with @scite and @SemanticScholar)
A striking example of "behind the scenes" of great research: Esther Duflo noted that a crucial enabler of her Nobel-prize-winning work was a masterful synthesis of human resource economics in a handbook chapter.
I... think I tracked down the (141-page!!!) handbook chapter?
And it is indeed wonderful!
What a synthesis indeed of a conclusion!
Clearly identifying progress, and also crucial open problems, deeply grounded in a detailed analysis of the literature.
Started as a "short thread", turned into a longer thing. Hope you find it helpful!
There's been some good discussion on effective search as a core primitive for tools for thought, and the limitations of existing tools, such as @RoamResearch wrt search.