\n This project is not for you. I know nothing about you, what you care about, or how you prefer to retain information. So how can I write something that will be meaningful to you? And why, from online courses to courses at top universities, so many of the learning experiences don\u2019t consider how each individual learner prefers to learn? The problem with one-size-fits-all learning experiences is that they leave many learners behind. These learners might think that they are incapable of learning something, while in truth, a different learning environment will allow them to thrive. So what if we could create a learning environment that is tailored to what each learner needs to realize their goals? What if we could provide each learner with individualized support so they never feel like they can\u2019t learn something? Context is an AI-powered learning platform that allows artists and designers to learn creative coding through interactive experiences tailored to their learning goals, needs, and preferences. It ensures effective learning outcomes by using AI to generate the entire educational journey, from learning plans and unique creative exercises to educational content. <\/p>\n
\n Context is a web application that utilizes a large language model (LLM) to generate uniquely tailored learning experiences. It is deployed online so everybody can join from anywhere and engage with interactive learning material facilitated by AI. The LLM is programmed to create a positive environment so every learner can feel encouraged to learn.\n <\/p>\n
\n When I was a teenager, I almost dropped out of high school. I couldn\u2019t fit into the educational system and lost my confidence in my ability to learn. It took me years of learning through alternative methods to regain my confidence and thrive in higher education, but the question remains: why did I have to go through such a frustrating experience?<\/p>\n
I started Context because I realized that many learners are left behind in one-size-fits-all learning experiences, causing them to give up and believe they can\u2019t learn. The absurd reality of the inaccessibility of quality higher education doesn\u2019t make this matter better. With 1.7 trillion student loan debt in the US that takes 20 years to repay on average, it is not surprising that higher education enrollment is dropping by 4.6%-4.9% annually. When seeking accessible education, the lack of support and passive learning experience in online learning make over 90% of learners give up. Based on over 60 interviews, 40 user tests, and immersion in creative coding communities, I understood that most accessible learning options leave most learners behind. <\/p>\n
But what if there was a learning environment that is tailored to each learner\u2019s goals and needs, allowing them to learn by working on projects they are passionate about while receiving constant support? That is the idea behind Context: to leave no learner behind and allow them to learn things that seem out of reach.\n <\/p>\n
\n Influences & references:
\nInterviews with over 60 people from diverse backgrounds and experiences.
\nDiscussions with advisors, educators, and experts in AI and ed-tech fields.
\nUser testing with over 40 people.
\nMollick, Ethan R. and Mollick, Lilach, Assigning AI: Seven Approaches for Students, with Prompts (September 23, 2023). Available at SSRN: https:\/\/ssrn.com\/abstract=4475995 or http:\/\/dx.doi.org\/10.2139\/ssrn.4475995
\nEnkelejda Kasneci, Kathrin Sessler, Stefan K\u00fcchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan G\u00fcnnemann, Eyke H\u00fcllermeier, Stephan Krusche, Gitta Kutyniok, Tilman Michaeli, Claudia Nerdel, J\u00fcrgen Pfeffer, Oleksandra Poquet, Michael Sailer, Albrecht Schmidt, Tina Seidel, Matthias Stadler, Jochen Weller, Jochen Kuhn, Gjergji Kasneci, ChatGPT for good? On opportunities and challenges of large language models for education, Learning and Individual Differences, Volume 103, 2023, 102274, ISSN 1041-6080, https:\/\/doi.org\/10.1016\/j.lindif.2023.102274. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1041608023000195)
\nMilano, S., McGrane, J.A. & Leonelli, S. Large language models challenge the future of higher education. Nat Mach Intell 5, 333\u2013334 (2023). https:\/\/doi.org\/10.1038\/s42256-023-00644-2<\/p>\n
\nACKNOWLEDGEMENTS:<\/p>\n
My mom Ella Sahar
\nMy dad Yanki Margalit<\/p>\n
Alex Wagner
\nAlexander Porter
\nDan O'Sullivan
\nDaniel Shiffman
\nDave Stein
\nEitan Orr
\nEllen Nickels
\nGali Carmel
\nMary Mark
\nMichelle Binyan Xu
\nMimi Yin
\nParth Pawar
\nRory Solomon
\nShawn Van Every
\nSomya Gupta<\/p>\n
ITP Coding Lab
\nLucia Gomez
\nMK Skitka
\nNima Niazi<\/p>\n
100+ user testers and interviewees
\nNYU Entrepreneurial Institute
\nDarren Yee
\nDe-Ann Abraham
\nFrank Rimalovski
\nJen Curtis
\nKeith Mauppa
\nRebecca Silver<\/p>\n
Berkeley Center for Entrepreneurship
\nCynthia Franklin
\nPaul Foster
\nPratha Tanna
\nShay Gaskins
\nStephanie Shyu <\/p>\n","protected":false},"excerpt":{"rendered":"
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