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== Agenda ==
 
== Agenda ==
* Presentation by Vinay K. Chaudhri
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* '''Vinay K. Chaudhri''' ''Textbook Open Knowledge Network''
* Discussion
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** 10 minute presentation giving an overview of our progress and proposed research for the Phase II of the Textbook Open Knowledge Network (TOKN) project.
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*** We ask that participants read the [https://go.aws/3cJZWhW TOKN Executive Summary]
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** 15 minute feedback and discussion of the overview
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** 20 minute follow up presentation
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** 15 minute general discussion
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Abstract:
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College students today face the challenge of mastering concepts in the new subject areas, relating those concepts across multiple disciplines, and one size fits all nature of textbooks. Intelligent Textbooks (ITB) using Artificial Intelligence (AI) and knowledge graphs (KG) solve these problems by allowing students to dynamically interact with the textbook content, increasing their ability to understand concepts, increasing engagement, and thereby, improving academic performance. ITBs offer students easy access to definitions and descriptions of concepts, make connections across different sections of the syllabus, and allow students to pose their own questions. Initial trials of ITBs that utilize KGs have been found to improve student grade outcomes by a full letter grade over the control group that was using a conventional textbook. ITBs have been found especially helpful for underperforming students, thus, broadening participation.         
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The potential of ITBs to facilitate better learning has been extremely difficult to realize without major investments of time, money, and expertise. The reason is that KGs are currently constructed using human subject-matter experts in a process that is extremely expensive and time consuming. Due to the large investment required, publishers and ed tech providers keep their KGs proprietary, eliminating their utility outside of the scope of the project for which they were created. I will discuss our efforts to create an open source Textbook Open Knowledge Network (TOKN) that can be freely used for creating ITBs and a variety of education technology applications. We are also working towards a novel process and tools for creating the KGs that combine automatic construction of a KG with validation by humans to ensure high accuracy. We envision a community of educators who would co-create TOKN, and eventually take the ownership for its future development and evolution.
  
 
== Conference Call Information ==
 
== Conference Call Information ==
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== Resources ==
 
== Resources ==
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* Vinay Chaudhri is running a Knowledge Graphs Seminar (CS 520) at Stanford
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** Sessions are on Tuesdays from 4:30PM to 6:20PM PDT (For the time in your timezone see [http://www.timeanddate.com/worldclock/fixedtime.html?month=05&day=19&year=2020&hour=19&min=30&sec=0&p1=179 World Clock])
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** Connection URL: https://stanford.zoom.us/j/620240910
  
 
== Previous Meetings ==
 
== Previous Meetings ==

Revision as of 20:21, 18 May 2020

[ ]
    (1)
Session Vinay K. Chaudhri
Duration 1 hour
Date/Time 20 May 2020 16:00 GMT
9:00am PDT/12:00pm EDT
5:00pm BST/6:00pm CEST
Convener KenBaclawski
Track Whither

Contents

Knowledge graphs, closely related to ontologies and semantic networks, have emerged in the last few years to be an important semantic technology and research area. As structured representations of semantic knowledge that are stored in a graph, KGs are lightweight versions of semantic networks that scale to massive datasets such as the entire World Wide Web. Industry has devoted a great deal of effort to the development of knowledge graphs, and they are now critical to the functions of intelligent virtual assistants such as Siri and Alexa. Some of the research communities where KGs are relevant are Ontologies, Big Data, Linked Data, Open Knowledge Network, Artificial Intelligence, Deep Learning, and many others.     (2A)

Agenda     (2B)

Abstract: College students today face the challenge of mastering concepts in the new subject areas, relating those concepts across multiple disciplines, and one size fits all nature of textbooks. Intelligent Textbooks (ITB) using Artificial Intelligence (AI) and knowledge graphs (KG) solve these problems by allowing students to dynamically interact with the textbook content, increasing their ability to understand concepts, increasing engagement, and thereby, improving academic performance. ITBs offer students easy access to definitions and descriptions of concepts, make connections across different sections of the syllabus, and allow students to pose their own questions. Initial trials of ITBs that utilize KGs have been found to improve student grade outcomes by a full letter grade over the control group that was using a conventional textbook. ITBs have been found especially helpful for underperforming students, thus, broadening participation.     (2B2)

The potential of ITBs to facilitate better learning has been extremely difficult to realize without major investments of time, money, and expertise. The reason is that KGs are currently constructed using human subject-matter experts in a process that is extremely expensive and time consuming. Due to the large investment required, publishers and ed tech providers keep their KGs proprietary, eliminating their utility outside of the scope of the project for which they were created. I will discuss our efforts to create an open source Textbook Open Knowledge Network (TOKN) that can be freely used for creating ITBs and a variety of education technology applications. We are also working towards a novel process and tools for creating the KGs that combine automatic construction of a KG with validation by humans to ensure high accuracy. We envision a community of educators who would co-create TOKN, and eventually take the ownership for its future development and evolution.     (2B3)

Conference Call Information     (2C)

Attendees     (2D)

Discussion     (2E)

Resources     (2F)

Previous Meetings     (2G)


Next Meetings     (2H)