The NSF PAL Ideation Workshop has ended. The final report is available here, and the workshop recordings and slideshow PDFs are available here.

Personalized Adventures in Learning (PAL):

The Future of AI in Education

Convergence Accelerator Ideation Workshop

Free to attend
Virtual Workshop

October 18, 19, 24 and 25, 2022
1:00PM - 5:00PM EST

An ideation workshop conducted by the University of Massachusetts Amherst, October 18-19, 2022 and October 24-25, 2022.

Supported by the National Science Foundation’s (NSF) Convergence Accelerator Program (Con-Accel), the primary objective is to develop a convincing and compelling rationale for NSF to establish a Con-Accel funding track in 2023 to support creation of smart and integrated platforms, devices and processes for education technology.

We seek projects that address the future potential of AI and Data Science in education through the listed outcomes:

  • A list of projects ideas currently underway that indicate the value and impact to society if a funding track were established and funded by NSF;

  • Engagement of stakeholders from the various PAL-related fields in which participants review and consider identified projects within a potential funding track and the impacts to society

  • A compelling case statement as to why the NSF should establish a funding track to support PAL projects under Con-Accel.

Those who participate in the ideation process, or whose projects are identified as potential exemplars of the PAL theme, may gain special knowledge and insight into future PAL-related projects and will be well-positioned to respond to proposed NSF solicitations.

BENEFITS FOR SOCIETY

U.S. education has a pressing need for improved online education.

  • Low reading and mathematics scores

  • Problems of racism and inequity

  • Student failure in online learning

  • Gaps resulting from Covid

  • Mental health issues

  • U.S. students failing to achieve international standards

Project Rationale

Current educational technologies have many liabilities. They do not leverage basic research on learning, nor have a culture of continuous improvement, nor meet the needs of diverse learners, nor leverage the growing power of computers. Significant technology exists, as does knowledge of what needs to be done. What is needed now is a concerted effort among different sectors to create an agenda that leads to real solutions for immediate use. One issue is the disconnected, fragmented, and often closed nature of different communities: educators, administrators, parents, commercial ventures, not-for-profit organizations, stakeholders, researchers, and government organizations.This workshop will support communities to reason about fruitful near-term (three year) approaches for scaling up innovative pedagogies. Experts in academia (learning science, AI, human-computer interaction, education, psychology), industry and government will identify barriers and solutions to the delivery of high-quality online education; they will use best practices in design, generate plans for future development and testing, and leverage technology and new modes of platform design.They will plan how to increase the number of trials of new products; identify promising interventions; test more often and fail faster; and evaluate conditions and circumstances that increase the probability of successful products.

Scientific Agenda

The scientific agenda is to investigate and augment human learning at large scale in authentic education settings (online, hybrid, and on-the-job). The workshop will establish a framework for new AI, learning science, and education theory and technologies to understand, model, infer, and respond to learning.

It will optimize every point in the education process to understand students, organize what they can learn, and optimize how they learn. It will explore new theory, algorithms, big data, and systems.

The workshop will couple use-inspired AI research with foundational AI and learning science research in a virtuous cycle and forge new partnerships among diverse stakeholders as they bridge the divide with novel tools from engineers, makers, technologists, and designers. It will make a laser focus on projects that present well-defined deliverables within three years.

Broader Impacts

The workshop will have broader impacts where it matters most – with students, adults, informal learners, and workers (many from underrepresented backgrounds) enabling them to more successfully learn, upskill and reskill.

Thousands of instructors will benefit from open-access to AI-driven power tools for differentiated digital instruction and timely professional development. Educational institutions will benefit from the collective use of these tools, ensuring greater continuity in teaching, and thus greater likelihood of student success.

Communities and industry partners will benefit from a significant increase in the number of skilled workers, convenient, timely, low-cost teaching and training, and new tools to identify and remedy skills-based workforce inequities.

PRINCIPAL INVESTIGATORS

University of Massachusetts Amherst
Manning College of Information & Computer Sciences

Beverly Woolf

Research Professor, Emeritus
University of Massachusetts Amherst

Ivon Arroyo

Assistant Professor
Computer Science Department
University of Massachusetts Amherst

Andrew Lan

Assistant Professor
Center for Data Science
University of Massachusetts Amherst

Harvard Graduate School of Education

Chris Dede

Senior Research Fellow
Harvard Graduate School of Education

University System of Georgia

Myk Garn

Assistant Vice Chancellor for New Learning Models
University System of Georgia

PRODUCTION AND TECHNICAL SUPPORT

Burt Woolf

Workshop Facilitator and Producer
University of Massachusetts Amherst

Danielle Allessio

Workshop Manager
University of Massachusetts Amherst

Sai Gattupalli

Research Assistant
University of Massachusetts Amherst

Alex Taubman

Zoom Technical Assistant
University of Massachusetts Amherst

THE NSF CONVERGENT ACCELERATOR (C-ACCEL)

Launched in 2019, the National Science Foundation (NSF) Convergence Accelerator program (Con-Accel) addresses national-scale societal challenges through a convergence approach and innovation processes that are use-inspired.

Con-Accel seeks to transition basic research and discovery into practice in order to solve high-impact national societal challenges aligned with specific research themes (tracks). NSF awards ideation grants for the purpose of identifying topical areas to be considered for funding under Con-Accel.

These ideation processes bring together the full range of stakeholders for a given topical research theme in order to provide the NSF with information, project ideas, and an assessment of impact potential for the given theme being considered. The NSF reviews the output of the ideation processes and selects the two or three topics that it feels should have highest funding priority for funding through the Convergence Accelerator program.

To date, the following research tracks have been selected and funded by Con-Accel:

  • Open Knowledge Networks (2019)

  • The Future of Work at the Human-Technology Frontier (2019)

  • Quantum Technology (2020)

  • AI-Driven Innovation via Data Sharing and Model Sharing (2020)

  • Networked Blue Economy (2021)

  • Trust & Authenticity in Communications Systems (2021)

  • Securely Operating Through 5G Infrastructure (2021)

  • Enhancing Opportunities for Persons with Disabilities (2022)

  • Sustainable Materials for Global Challenges (2022)

  • Food & Nutrition Security (2022)

CALL FOR PROJECT IDEAS

As part of the deliverables, the PAL ideation process seeks to identify research projects that address the future of AI and Data Science in education and that meet certain broad criteria.

SUBMIT YOUR PROJECT IDEAS

If you or someone you know has project ideas that you would like to consider for our final report to NSF, please click on the link below and complete the form to submit the project title, a brief abstract, and contact information.

Projects need to deliver tangible products, resources, or processes that empower students, teachers, parents and stakeholders within a three-year time-frame following funding.

CRITERIA

The following overarching priorities will guide appropriate projects:

Use-inspired AI Research

Projects will entail need-based research that focuses on the practical application of AI/Data Science research to optimize one or more of the many points in the education process, from understanding student needs, to organizing what and how they learn, and how to better impart and integrate knowledge into the student’s consciousness.

Projects will investigate and augment human learning in the full array of authentic education settings (e.g., classroom, remote virtual, hybrid, and on-the-job) and will study and leverage data to establish a framework for new AI theory and methods, learning science and real-world education practices (pedagogies).

Projects will impact a broad range of knowledge systems, including traditional core fields of study, work-related training, applied life skills training, and contextual competencies that can be deployed life-long and life-wide.

Customized Education Systems to Provide Personalized Learning

Projects will develop rich new AI models and inference methods to gain a deeper understanding of students and corresponding analytical methods to infer key student factors from data sets. New models are important for all learners, especially adult learners, who tend to have idiosyncratic attributes and can benefit significantly from personalized learning strategies catered to their individual needs.

AI research issues here include technologies that understand, model, infer, and respond to real human learning through multimodal data integration, generalization of learned models to new tasks, interpretable machine learning, FEATful (fairness, ethics, accountability and transparency) data-driven models, and data-augmented learning science as well as neuro-symbolic modeling, large-scale ML, and natural language processing (NLP).

Strong Multi-Organizational Partnerships

Projects must demonstrate collaboration, engagement and partnership between and among stakeholders and/or by the outcome(s) intended for the project. It will not be sufficient to simply assert that the research will support certain population segments; representatives of the population segments must be genuinely engaged in the development and implementation of project research, testing and findings.

The ideal project will attract and enliven new communities of AI researchers, learning scientists, and instructors who will engage in rapid learning experiments with diverse student populations. Teams are expected to forge partnerships among stakeholders from several disciplines.

High Probability of Deliverables

The workshop has a laser focus on well-defined practical deliverables that will translate research into practice with measurable outcomes and impacts within three years.

WORKSHOP

Personalized Adventures in Learning (PAL): The Future of AI in Education

Convergence Accelerator Ideation Workshop


October 18, 19, 24 and 25, 2022

1:00PM - 5:00PM EST

Free to attend


For more information, contact Burt Woolf at bwoolf at umass dot edu.
This workshop is sponsored by the National Science Foundation.

For each theme, keynote experts will present lightning presentations followed by breakouts for participant input.

Tentative session schedules listed below.

Workshop Schedule:

ENDED: SESSION 1

Tuesday, October 18, 2022
1:00 PM - 5:00 PM EST (See in your local time)

Theme A: Design, Development, and Testing

1:00 - 3:00 PM

Welcome to the NSF Convergence Accelerator Ideation Workshop

By Beverly Woolf, PI

Robots as Social Learning Companions

By Erin Walker

Online Adult Learning: AI Institute

By Myk Garn

AI for Orchestration in the Classroom

By Jennifer Olsen

Q&A

By Myk Garn

Breakouts

Moderators: Keynote Speakers and Chad Lane

Theme Re-Cap

Moderator: Beverly Woolf, PI

Theme B: Assessment of Educational Research

3:05 - 5:00 PM

Social Analytics

By Carolyn Rosé

How AI Can Empower Component-Based Educational Research

By Chris Dede

Opportunities Matter: Hybrid Human-Computer Tutoring Toward Educational Equity

By Ken Koedinger

Breakouts

Theme Re-Cap

Moderator: Beverly Woolf, PI

ENDED: SESSION 2

Wednesday, October 19, 2022
1:00PM - 5:00 PM EST (See in your local time)

Theme C: Learning at Scale

1:00 - 3:00 PM

Future of Stealth Assessment

By Val Shute

Data-driven Item Selection and Generation in Assessments and Learning

By Andrew Lan

Crowdsourcing Paves the way for Personalized Learning

By Neil Heffernan

Q&A

Moderator: Andrew Lan

Breakouts

Theme Re-Cap

Moderator: Beverly Woolf, PI

Theme D: Ethical and Equitable

3:05 - 5:00 PM

Rapid Workforce Development

By Lewis Johnson

Bilingual Tutor

By Ivon Arroyo

Q&A

Moderator: Andrew Lan

Breakouts

Theme Re-Cap

Moderator: Beverly Woolf, PI

ENDED: SESSION 3

Monday, October 24, 2022
1:00PM - 5:00 PM EST (See in your local time)

Theme E: Entrepreneurial, Not-for-profit, and Government Digital Learning Systems

1:00 - 4:00 PM

Aligning Curricula with Skills and Jobs

By Robby Robson

Foreign Language Learning

By Lewis Johnson

Intelligent Game-based Assessment and Tutoring

By Danielle McNamara

Q&A

Breakouts

Theme Re-Cap

Moderator: Beverly Woolf, PI

Large Scale Commercialization

By Steve Ritter

The EdTech Investment Climate

By Max Woolf

Recap of Project Ideas (Part 1)

4:00 - 5:00 PM

Brainstorming Session Part 1: Project Possibilities, Collaboration and Synergy, Engaging Users

Panelists: Beverly Woolf and selected Keynote Speakers

Facilitator: Burt Woolf, Ed.D.

In this session, the panelists and participants will explore three questions:

  • Promising Possibilities: What projects and/or ideas for AI in Education have you heard, are thinking about, or are aware of that would benefit from an NSF Con-Accel Funding Track?

  • Collaboration and Synergy: Which projects overlap or where are we working toward similar impact? What combinations (integration, blending, piggybacking, dovetailing) of research efforts would amplify the impact of AI in education and learning?

  • Realizing our Shared Transformative Vision: In what ways might we engage users to help address and overcome inherent limitations, barriers and biases in our research efforts so that we might be more effective in realizing our vision for AI in the world of education and learning?

ENDED: SESSION 4

Tuesday, October 25, 2022
1:00PM - 4:00 PM EST (See in your local time)

Recap of Project Ideas (Part 2)

1:00 - 4:00 PM (or earlier)

Innovative Education Technology from the US Department of Education

By Ed Metz

Brainstorming Session Part 2: Project Possibilities, Collaboration and Synergy, Engaging Users

Panelists: Beverly Woolf and selected Keynote Speakers

Facilitator: Burt Woolf, Ed.D.

In this session, the panelists and participants will explore three questions:

  • Promising Possibilities: What projects and/or ideas for AI in Education have you heard, are thinking about, or are aware of that would benefit from an NSF Con-Accel Funding Track?

  • Collaboration and Synergy: Which projects overlap or where are we working toward similar impact? What combinations (integration, blending, piggybacking, dovetailing) of research efforts would amplify the impact of AI in education and learning?

  • Realizing our Shared Transformative Vision: In what ways might we engage users to help address and overcome inherent limitations, barriers and biases in our research efforts so that we might be more effective in realizing our vision for AI in the world of education and learning?

Workshop ends at 4:00 PM

THEMES

The PAL Ideation Workshops will focus on the following five topical themes that will be featured in our workshop sessions, keynote presentations, and project ideas.

THEME A

Design, Develop, and Testing

This theme includes development of educational technologies, intelligent tutors, games, and user interfaces; development of new modules or functionality within existing systems and the design of systems and interfaces currently under development. The skill set includes AI, machine learning, models, UX/UI design including needs analysis, wireframing, prototyping, iterative design research, and human factors.

THEME B

Assessment of Educational Research

This theme includes conducting experimental studies in educational settings. The skill set includes expertise working with teachers and students, analyzing data, and interpreting experimental findings. Research focuses on implementing and testing educational technologies in various educational settings (e.g., classrooms, online).

THEME C

Learning at Scale

This theme includes large scale research, better understanding of learning, predicting learning outcomes, and enhancing learning at scale. The skill set includes expertise in conducting and analyzing experimental studies, A/B/n experimental design, database management, R, Python, advanced statistical methodologies, and learning analytics (e.g., machine learning), use of machine learning to address issues of personalization, equity, cost, customization, usability. How can data be collected, processed, and used responsibly for all communities?

THEME D

Diversity, Equity, and Inclusion

This theme includes development of equitable, supportive, affirming, and beneficial environments for students of all cultures, backgrounds, and identities. We need to directly address pervasive ethnic and racial disparities and examine models and data sets for bias (gender, race, nationality, culture), including advocating for marginalized populations. We focus only on short term pain points, we need to solve for the longer run majority who are facing crucial life conditions that could benefit from better life-long design. This theme will identify benefits that accrue from diversity.

THEME E

Entrepreneurial, Not-for-profit, and Government Digital Learning Systems

This theme will bring AI and the data revolution to businesses, non-profits, and government organizations. For example, organizations will use AI to improve processes that require reading and understanding text; such tools act as performance multipliers that increase speed and accuracy, decrease cost, and enable businesses to make the best use of time/expertise. Supporting such organizations, e.g., through Kickstarter or Venture Capital will put in place mechanisms to translate research and development into products.

RECORDINGS

View recordings for the NSF PAL Ideation Workshop.

DAY 1: OCTOBER 18, 2022

Online Adult Learning: AI Institute

By Myk Garn

AI for Orchestration in the Classroom

Slides (PDF)

By Jennifer Olsen

Social Analytics

By Carolyn Rosé

How AI Can Empower Component-Based Educational Research

Slides (PDF)

By Chris Dede

Opportunities Matter: Hybrid Human-Computer Tutoring Toward Educational Equity

By Ken Koedinger

Robots as Social Learning Companions

By Erin Walker

DAY 2: OCTOBER 19, 2022

Future of Stealth Assessment

Slides (PDF)

By Val Shute

Data-driven Item Selection and Generation in Assessments and Learning

Slides (PDF)

By Andrew Lan

Crowdsourcing Paves the way for Personalized Learning

By Neil Heffernan

Rapid Workforce Development

Slides (PDF)

By Lewis Johnson

Bilingual Tutor

Slides (PDF)

By Ivon Arroyo

DAY 3: OCTOBER 24, 2022

Aligning Curricula with Skills and Jobs

Slides (PDF)

By Robby Robson

Foreign Language Learning

Slides (PDF)

By Lewis Johnson

Intelligent Game-based Assessment and Tutoring

Slides (PDF)

By Danielle McNamara

Large Scale Commercialization

By Steve Ritter

The EdTech Investment Climate

Slides (PDF)

By Max Woolf

DAY 4: OCTOBER 25, 2022

Innovative Education Technology from the US Department of Education

By Ed Metz

KEYNOTE EXPERTS

The following people will be delivering keynote remarks at the PAL Ideation Workshops.

Ivon Arroyo

Assistant Professor
Computer Science Department
University of Massachusetts Amherst

Chris Dede

Senior Research Fellow
Harvard Graduate School of Education

Myk Garn

Assistant Vice Chancellor for New Learning Models, University System of Georgia

Neil Heffernan

Professor
Computer Science Department
Worcester Polytechnic Institute

Lewis Johnson

Chief Scientist
Co-founder, Alelo

Ken Koedinger

Hillman Professor & METALS Program Director
Carnegie Mellon University

Andrew Lan

Assistant Professor
Center for Data Science
University of Massachusetts Amherst

Danielle McNamara

Professor
Learning Sciences Institute
Arizona State University

Ed Metz

Program Manager
U.S. Department of Education and Institute of Education

Jennifer Olsen

Assistant Professor
Department of Computer Science
University of San Diego

Steve Ritter

Co-Founder & Chief Scientist
Carnegie Learning

Robby Robson

Chief Science Officer & Founder
Eduworks.com

Carolyn Rosé

Professor
Human-Computer Interaction Institute
Carnegie Mellon University

Val Shute

Professor
EdPsych and Learning Systems
Florida State University

Erin Walker

Associate Professor
School of Computing and Information
University of Pittsburgh

Max Woolf

Managing Director
Tyton Partners

REGISTRANT ORGANIZATIONS

Individuals from the following organizations and institutions are currently registered for the PAL Ideation Workshops (List as of October 22, 2022).

Name of the Institution
1EdTech Consortium
3M Health Information Systems
Abilene Christian University
AERDF
AI2ES
Alelo
Apple
Arizona State University
Ateneo de Manila University
AYSET
Bamboo Learning
Barbara Treacy Consulting
Berkeley
Booz Allen Hamilton
Boston College
Building State Capability, Harvard Kennedy School
Carnegie Learning, Inc.
Carnegie Mellon University
Central University of Jharkhand
Columbia University
Cornell University
Crystal Clear
Digital & Beyond
Digital Promise Global
District of Columbia Public Schools
Dublin City University
Educational Testing Service
Eduworks Corporation
Elsevier
ETH Zurich
European parliament
FFHS
Florida State University
George Mason University
Georgetown University
Georgia Institute of Technology
Harvard Graduate School of Education
Harvard Next Level Lab
Harvard University
Harvard-Westlake
HSD2
IIT Bombay
IIT Delhi
Indira Gandhi Delhi Technical University for Women, New Delhi, India
ITCILO
KIPP NYC
KLE Technological University
Know Center Gmbh
Lakehead University
MIT
Nanyang Technological University, Singapore
National Academies of Sciences Engineering and Medicine
National Louis University
National Science Foundation
NCDE
North Carolina State University
NYU
OpenStax, Rice University
Quill.org
Royal Roads University
Saint Louis University
Santa Clara county
Skillprint
SRG Technology LLC
SRI IT Consulting Limited
St John's University
TeachFX
Technical College System Of Georgia
TERC
The Concord Consortium
Trinity College Dublin
University of Massachusetts Amherst
University of Massachusetts - CICS
University of Massachusetts - College of Education
Universidad Tecnológica de Nogales
Universitas Negeri Malang
Universitat Politecnica de Valencia
University College London
University of Alberta
University of Arizona
University of British Columbia
University of Chicago
University of Craiova
University of Denver
University of Florida
University of Illinois, Chicago
University of Illinois, Urbana-Champaign
University of KwaZulu-Natal
University of Louvain
University of Massachusetts
University of North Carolina
University of North Carolina at Charlotte
University of Pittsburgh
University of Pretoria
University of San Diego
University of Sheffiled
University of Southern California
University of State Manado
University of Sussex, Brighton, UK
University of Turku
University of West Georgia
UPenn
Vanderbilt University
WestEd
WPI

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