AAAI2022 Artificial Intelligence for Education

AAAI2022 Artificial Intelligence for Education

UPDATES

  • Due to the COVID-19 Pandemic, the 3rd AI4Edu workshop will be held virtually on Feb 28, 2022.
  • To avoid connectivity issues in real time, we choose to use the pre-recording option. Live Q & A is optional.
  • This year, we have speakers from North America, Asia and Europe. Therefore, we will have two sessions to make sure people from different time zones can join. Specifically, we will have
    • Session One at
      • Vancouver/San Francisco 05:00 - 08:00
      • New York 09:00 - 12:00
      • London 13:00 - 16:00
      • Beijing 21:00 - 00:00
    • Session Two at
      • Vancouver/San Francisco 17:00 - 20:00
      • New York 20:00 - 23:00
      • London 00:10 - 04:00
      • Beijing 08:00 - 11:00
  • November 30, 2021: Notification of final acceptance. All accepted paper can be found at here.

Workshop Schedule

We outline the tentative schedule for the proposed workshop. All the time slots are in PST (Vancouver/San Francisco local time).

Feb 28 Session One

  • 05:00 - 05:15 Opening
  • 05:15 - 06:00 [Keynote Talk] [Title TBD], Speaker TBD
  • 06:00 - 06:15 [Paper Presentation] [A Multi-task Model for Structural Recognition in Educational Scenario], Yajun Zou, Yixin Li, Lei Shen, Shiqi Dong, Hui Lin, Jinwen Ma and Yitao Duan
  • 06:15 - 06:30 [Paper Presentation] [ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning], Roberto Daza, Daniel DeAlcala, Aythami Morales, Ruben Tolosana and Julian Fierrez
  • 06:30 - 06:45 [Paper Presentation] [Assistive Accessible Charts for Visually Impaired Students: An Automated Learning System], Prerna Mishra, Santosh Kumar and Mithilesh Chaube
  • 06:45 - 07:00 [Paper Presentation] [DIY Graphics Tab: A Cost-Effective Alternative to Graphics Tablet for Educators], Mohammad Imrul Jubair, Tashfiq Ahmed, Hasanath Jamy, Arafat Ibne Yousuf, Foisal Reza and Mohsena Ashraf
  • 07:00 - 07:15 [Paper Presentation] [FreeTalky: Don’t Be Afraid! Conversations Made Easier by a Humanoid Robot using Persona-based Dialogue], Chanjun Park, Yoonna Jang, Seolhwa Lee, Sungjin Park and Heuiseok Lim
  • 07:15 - 07:30 [Paper Presentation] [Improving Controllability of Educational Question Generation by Keyword Provision], Ying-Hong Chan, Ho-Lam Chung and Yao-Chung Fan
  • 07:30 - 07:45 [Paper Presentation] [Incremental Knowledge Tracing from Multiple Schools], Sujanya Suresh, Savitha Ramasamy, P.N Suganthan and Cheryl Sze Yin Wong
  • 07:45 - 08:00 [Paper Presentation] [Monitoring the Learning Progress In Piano Playing With Hidden Markov Models], Nina Ziegenbein, Alexandra Moringen and Jason Friedman
  • 08:00 - 08:15 [Paper Presentation] [Pdf2PreReq: Automatic Extraction of Concept Dependency Graphs from Academic Textbooks], Rushil Thareja, Venktesh V and Mukesh Mohania

Feb 28 Session Two

  • 17:00 - 17:45 [Keynote Talk] [Title TBD], Speaker TBD
  • 17:45 - 18:30 [Keynote Talk] [Title TBD], Speaker TBD
  • 18:30 - 19:15 [Keynote Talk] [Title TBD], Speaker TBD
  • 19:15 - 19:30 [Paper Presentation] [Building a storytelling conversational agent through parent-AI collaboration], Zheng Zheng, Ying Xu, Yanhao Wang, Tongshuang Wu, Bingsheng Yao, Daniel Ritchie, Mo Yu, Dakuo Wang and Toby Jia-Jun Li
  • 19:30 - 19:45 [Paper Presentation] [Fine-Grained Classroom Activity Detection from Audio with Neural Networks], Eric Slyman, Chris Daw, Morgan Skrabut, Ana Usenko and Brian Hutchinson
  • 19:45 - 20:00 [Paper Presentation] [Graph-based Ensemble Machine Learning for Student Performance Prediction], Yinkai Wang, Aowei Ding, Kaiyi Guan, Shixi Wu and Yuanqi Du
  • 20:00 - 20:15 [Paper Presentation] [What kind of peer-assessment comments help improve learning outcomes? Evidence from a programming course], Yunkai Xiao, Qinjin Jia and Jialin Cui

Introduction

Technology has transformed over the last few years, turning from futuristic ideas into today’s reality. AI is one of these transformative technologies that is now achieving great successes in various real-world applications and making our life more convenient and safe. AI is now shaping the way businesses, governments, and educational institutions doing things and is making its way into classrooms, schools and districts across many countries.

In fact, the increasingly digitalized education tools and the popularity of online learning have produced an unprecedented amount of data that provides us with invaluable opportunities for applying AI in education. Recent years have witnessed growing efforts from AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in education. For examples, AI tools are built to ease the workload for teachers. Instead of grading each piece of work individually, which can take up a bulk of extra time, intelligent scoring tools allow teachers the ability to have their students work automatically graded. In the coronoavirus era, requiring many schools to move to online learning, the ability to give feedback at scale could provide needed support to teachers. What’s more, various AI based models are trained on massive student behavioral and exercise data to have the ability to take note of a student’s strengths and weaknesses, identifying where they may be struggling. These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. Furthermore, leveraging AI to connect disparate social networks among teachers, we may be able to provide greater resources for their planning, which have been shown to significantly effect students’ achievement.

Despite gratifying achievements have demonstrated the great potential and bright development prospect of introducing AI in education, developing and applying AI technologies to educational practice is fraught with its unique challenges, including, but not limited to, extreme data sparsity, lack of labeled data, and privacy issues. Hence, this workshop will focus on introducing research progress on applying AI to education and discussing recent advances of handling challenges encountered in AI educational practice.

Topics

We encourage keynote speeches on a broad range of AI domains for education. Topics of interest include (in no particular order) but are not limited to following:

  • Emerging technologies in education
  • Evaluation of education technologies
  • Immersive learning and multimedia applications
  • Implications of big data in education
  • Self-adaptive learning
  • Individual and personalized education
  • Intelligent learning systems
  • Intelligent tutoring and monitoring systems
  • Automatic assessment in education
  • Automated grading of assignments
  • Automated feedback and recommendations
  • Big data analytics for education
  • Analysis of communities of learning
  • Computer-aided assessment
  • Course development techniques
  • Data analytics & big data in education
  • Mining and web mining in education
  • Learning tools experiences and cases of study
  • Social media in education
  • Smart education
  • Digital libraries for learning
  • education analytic approaches, methods, and tools
  • Knowledge management for learning
  • Learning analytics and educational data mining
  • Learning technology for lifelong learning
  • Tracking learning activities
  • Uses of multimedia for education
  • Wearable computing technology in e-learning
  • Smart classroom
  • Dropout prediction
  • Knowledge tracing

Submission

The workshop solicits paper submissions from participants (2–6 pages with unlimited references and single blind). Abstracts of the following flavors will be sought: (1) research ideas, (2) case studies (or deployed projects), (3) review papers, (4) best practice papers, and (5) lessons learned. The format is the standard double-column AAAI proceedings style. All submissions will be peer-reviewed. Some will be selected for spotlight talks, and some for the poster session.

Submission website: https://easychair.org/conferences/?conf=aaai2022ai4edu.

Important Dates

  • November 12, 2021 November 19, 2021: Workshop paper submission due AOE
  • November 30, 2021 : Notifications of acceptance
  • December 15, 2021: Deadline of the camera-ready final paper submission
  • Feb 21, 2022: Workshop Date

Accepted Papers

  • Yinkai Wang, Aowei Ding, Kaiyi Guan, Shixi Wu and Yuanqi Du. Graph-based Ensemble Machine Learning for Student Performance Prediction [PDF]
  • Chanjun Park, Yoonna Jang, Seolhwa Lee, Sungjin Park and Heuiseok Lim. FreeTalky: Don’t Be Afraid! Conversations Made Easier by a Humanoid Robot using Persona-based Dialogue [PDF]
  • Yajun Zou, Yixin Li, Lei Shen, Shiqi Dong, Hui Lin, Jinwen Ma and Yitao Duan. A Multi-task Model for Structural Recognition in Educational Scenario [PDF]
  • Eric Slyman, Chris Daw, Morgan Skrabut, Ana Usenko and Brian Hutchinson. Fine-Grained Classroom Activity Detection from Audio with Neural Networks [PDF]
  • Sujanya Suresh, Savitha Ramasamy, P.N Suganthan and Cheryl Sze Yin Wong. Incremental Knowledge Tracing from Multiple Schools [PDF]
  • Prerna Mishra, Santosh Kumar and Mithilesh Chaube. Assistive Accessible Charts for Visually Impaired Students: An Automated Learning System [PDF]
  • Rushil Thareja, Venktesh V and Mukesh Mohania. [Pdf]2PreReq : Automatic Extraction of Concept Dependency Graphs from Academic Textbooks [PDF]
  • Roberto Daza, Daniel DeAlcala, Aythami Morales, Ruben Tolosana and Julian Fierrez. ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning [PDF]
  • Ying-Hong Chan, Ho-Lam Chung and Yao-Chung Fan. Improving Controllability of Educational Question Generation by Keyword Provision [PDF]
  • Mohammad Imrul Jubair, Tashfiq Ahmed, Hasanath Jamy, Arafat Ibne Yousuf, Foisal Reza and Mohsena Ashraf. DIY Graphics Tab: A Cost-Effective Alternative to Graphics Tablet for Educators [PDF]
  • Nina Ziegenbein, Alexandra Moringen and Jason Friedman. Monitoring the Learning Progress In Piano Playing With Hidden Markov Models [PDF]
  • Yunkai Xiao, Qinjin Jia and Jialin Cui. What kind of peer-assessment comments help improve learning outcomes? Evidence from a programming course [PDF]
  • Zheng Zheng, Ying Xu, Yanhao Wang, Tongshuang Wu, Bingsheng Yao, Daniel Ritchie, Mo Yu, Dakuo Wang and Toby Jia-Jun Li. Building a storytelling conversational agent through parent-AI collaboration [PDF]
  • Ankan Mullick and Suman Kalyan Maity. Conversation for Counseling: A survey [PDF]

Organizers

Beautiful place

  • Zitao Liu TAL Education Group, China
  • Jiliang Tang Michigan State University, USA
  • Lihan Zhao TAL Education Group, China
  • Xiao Zhai TAL Education Group, China