A New Era: Intelligent Tutoring Systems Will Transform Online Learning
for Millions
- URL: http://arxiv.org/abs/2203.03724v1
- Date: Thu, 3 Mar 2022 18:55:33 GMT
- Title: A New Era: Intelligent Tutoring Systems Will Transform Online Learning
for Millions
- Authors: Francois St-Hilaire, Dung Do Vu, Antoine Frau, Nathan Burns, Farid
Faraji, Joseph Potochny, Stephane Robert, Arnaud Roussel, Selene Zheng,
Taylor Glazier, Junfel Vincent Romano, Robert Belfer, Muhammad Shayan,
Ariella Smofsky, Tommy Delarosbil, Seulmin Ahn, Simon Eden-Walker, Kritika
Sony, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova,
Victor Chen, Hossein Sahraei, Robert Larson, Nadia Markova, Andrew Barkett,
Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban, Ekaterina Kochmar
- Abstract summary: AI-powered learning can provide millions of learners with a highly personalized, active and practical learning experience.
We present the results of a comparative head-to-head study on learning outcomes for two popular online learning platforms.
- Score: 41.647427931578335
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Despite artificial intelligence (AI) having transformed major aspects of our
society, less than a fraction of its potential has been explored, let alone
deployed, for education. AI-powered learning can provide millions of learners
with a highly personalized, active and practical learning experience, which is
key to successful learning. This is especially relevant in the context of
online learning platforms. In this paper, we present the results of a
comparative head-to-head study on learning outcomes for two popular online
learning platforms (n=199 participants): A MOOC platform following a
traditional model delivering content using lecture videos and multiple-choice
quizzes, and the Korbit learning platform providing a highly personalized,
active and practical learning experience. We observe a huge and statistically
significant increase in the learning outcomes, with students on the Korbit
platform providing full feedback resulting in higher course completion rates
and achieving learning gains 2 to 2.5 times higher than both students on the
MOOC platform and students in a control group who don't receive personalized
feedback on the Korbit platform. The results demonstrate the tremendous impact
that can be achieved with a personalized, active learning AI-powered system.
Making this technology and learning experience available to millions of
learners around the world will represent a significant leap forward towards the
democratization of education.
Related papers
- From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents [78.15899922698631]
MAIC (Massive AI-empowered Course) is a new form of online education that leverages LLM-driven multi-agent systems to construct an AI-augmented classroom.
We conduct preliminary experiments at Tsinghua University, one of China's leading universities.
arXiv Detail & Related papers (2024-09-05T13:22:51Z) - SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation [54.97931304488993]
Self-improving robots that interact and improve with experience are key to the real-world deployment of robotic systems.
We propose an online learning method, SELFI, that leverages online robot experience to rapidly fine-tune pre-trained control policies.
We report improvements in terms of collision avoidance, as well as more socially compliant behavior, measured by a human user study.
arXiv Detail & Related papers (2024-03-01T21:27:03Z) - Implementing Learning Principles with a Personal AI Tutor: A Case Study [2.94944680995069]
This research demonstrates the ability of personal AI tutors to model human learning processes and effectively enhance academic performance.
By integrating AI tutors into their programs, educators can offer students personalized learning experiences grounded in the principles of learning sciences.
arXiv Detail & Related papers (2023-09-10T15:35:47Z) - A Network Science Perspective to Personalized Learning [0.0]
We examine how learning objectives can be achieved through a learning platform that offers content choices and multiple modalities of engagement to support self-paced learning.
This framework brings the attention to learning experiences, rather than teaching experiences, by providing the learner engagement and content choices supported by a network of knowledge.
arXiv Detail & Related papers (2021-11-02T01:50:01Z) - Comparative Study of Learning Outcomes for Online Learning Platforms [47.5164159412965]
Personalization and active learning are key aspects to successful learning.
We run a comparative head-to-head study of learning outcomes for two popular online learning platforms.
arXiv Detail & Related papers (2021-04-15T20:40:24Z) - Personalized Education in the AI Era: What to Expect Next? [76.37000521334585]
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to meet her desired goal.
In recent years, the boost of artificial intelligence (AI) and machine learning (ML) has unfolded novel perspectives to enhance personalized education.
arXiv Detail & Related papers (2021-01-19T12:23:32Z) - A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM [84.60813413413402]
Korbit is a large-scale, open-domain, mixed-interface, dialogue-based intelligent tutoring system (ITS)
It uses machine learning, natural language processing and reinforcement learning to provide interactive, personalized learning online.
Unlike other ITS, a teacher can develop new learning modules for Korbit in a matter of hours.
arXiv Detail & Related papers (2020-05-06T02:45:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.