The Learning Engineering Research Network (LERN) Convening is an ongoing conference dedicated to fostering top-quality research in Learning Engineering. The conference offers an interdisciplinary outlet for research in cognitive science, educational science, and design sciences, with a focus on developing effective learning ecosystems.
The 2026 convening, themed “From Insights to Implementation: Learning Engineering in Action,” brings together researchers, practitioners, and innovators to advance the interdisciplinary field of Learning Engineering. Building on work from cognitive science, education, design sciences, and beyond, the convening emphasizes translating research insights into practical solutions that strengthen learning ecosystems.
Hosted by the ASU Learning Engineering Institute, this collaborative event features keynotes, panels, and research presentations that showcase how data, technology, and design can drive innovation in education. From exploring generative AI to advancing inclusive practices, the LERN Convening highlights actionable approaches to addressing critical challenges and promoting equity in learning.
Held from February 3-4 in 2026, LERN2026 brought together over xxx educators, researchers, technologists, and learning professionals from public, private, and academic sectors. The LERN proceedings includes 70 examples of research within the learning engineering field from 95 submissions. These papers span from core papers on the Learning Engineering Process (LEP), human-centered evaluations within LEP, educational technology systems informed by the LEP, and the largest group, Artificial Intelligence in Education.
Of these submissions, we awarded two best paper awards. The awards were selected based on recommendations from reviewers and approval by our award committee.
Human-Centered Learning Ecosystems: Reimagining Water Education for Real Estate Professionals |
Danielle Storey, Poorva Ketkar, Emma Noble, & Harry Cooper |
Coaching, Not Autocomplete: Early Evidence from ConnectInk’s AI-Supported Personal Narrative Pilot |
Julio Intriago-Izquierdo & Rahul Patel |
At this convening, we established our LERN Distinguished Fellows. The hard work and dedication of our three inaugural fellows have provided guidance and wisdom, and made the field of learning engineering what it is today, while setting it up to continue into the future. Our awardees this year are Sae Schatz, Jim Goodell, and Chris Dede.
Sae Schatz has been a key contributor to the evolution of learning engineering, especially through her work at the intersection of learning science, data‑informed design, and advanced training technologies. As the former director of the Advanced Distributed Learning (ADL) Initiative for the U.S. Department of Defense, she helped shape modern learning ecosystems—championing interoperability standards, learner‑centric design, and evidence‑based approaches to large‑scale training. Her leadership has pushed the field toward more adaptive, data‑rich, and connected learning environments that embody the core principles of learning engineering.
Jim Goodell has been one of the central architects of learning engineering as a formal discipline, especially through his leadership in defining its frameworks, standards, and professional practices. As editor of Learning Engineering Toolkit and a longtime leader within the IEEE Learning Technology Standards Committee and ICICLE, he has advanced the field’s focus on evidence‑based design and continuous improvement. His work has helped establish learning engineering as a rigorous, systems‑oriented approach to designing.
Chris Dede has been one of the most influential voices shaping the modern field of learning engineering. A longtime Harvard professor and pioneer in learning technologies, he helped define learning engineering as the systematic use of data, design, and iterative experimentation to improve learning at scale. His work spans immersive learning (AR/VR), digital ecosystems, and large‑scale research–practice partnerships, and he co‑edited Learning Engineering for Online Education, a foundational text that formalized the discipline’s methods and principles.
Ruben Acuña, Arizona State University, School of Computing and Augmented Intelligence
Tracy Arner, Learning Engineering Institute, Arizona State University
Christine M. Covas-Smith, Ph.D., Air Education and Training Command
Dr. James Dunnigan, Mary Lou Fulton College
Ariah Elmore, iPerformX
Md Biplob Hosen, University of Maryland Baltimore County
Tanya Churaman, University of Missouri-Columbia; Pearson Education
Linh Huynh, Learning Engineering Institute
Mina C. Johnson-Glenberg, Arizona State University
Heather C. Lum, Arizona State University
Mei Mei Li, Learning Engineering Institute, Arizona State University
Li (Lee) Liang, EvalMate.AI and Lee Vision
Janice Mak, Learning Engineering Institute, Arizona State University
Bryan Matlen, WestEd
Sarah Martin, Arizona State University
Kathryn S. McCarthy, Department of Learning Sciences, Georgia State University
Danielle S. McNamara, Learning Engineering Institute, Arizona State University
Chenyou Nicole Wu, NA
Catheryn Reardon, Learning Engineering Institute, Arizona State University
Henry Ryng, inXsol LLC
Anqi Shao, Arizona State University
Abigail Stein, Carnegie Mellon University
Danielle Storey, Arizona State University, Arizona Water Innovation Initiative
Yu Tian, Learning Engineering Institute, Arizona State University
Vipin Verma, Learning Engineering Institute, Arizona State University
Dr. Wendy Walsh, SL, DAFC, Chief Learning Officer HQ Air Education & Training Command
Yiqiao Xu, MetLife, Inc.
CEO and Founder, the Knowledge Forge LLC
Thriving in the Age of Acceleration
We stand at a pivotal moment in the “Fourth Industrial Revolution,” our modern age, which isn’t simply defined by technological breakthroughs but also by the profound societal ripples they create. This keynote explores three defining characteristics reshaping how we work, live, and learn, and it provides a forward-looking framework for how Learning Engineering principles can help us build systems that match the pace of change.
About Sae
Sae works at the intersection of cognition, technology, and data. She formerly directed the Advanced Distributed Learning (ADL) Initiative, a government program for researching learning technologies, and before joining the civil service, Sae worked as an applied human–systems scientist in both business and academia, including as an assistant professor with the University of Central Florida’s Institute for Simulation and Training. Sae is a prolific writer and professional presenter; for example, she recently released Engines of Engagement: A Curious Book About Generative AI (2023) and contributed to the National Academies report on Adult Learning in the Military Context (2024).
Learning Engineering Research Network Convening Schedule | ||
Welcome, Awards & Panel | Taking Human-Centered Learning Innovation to Scale | Moderator: Danielle McNamara, Executive Director of the ASU Learning Engineering Institute |
Best Paper | ||
Human-Centered Learning Ecosystems: Reimagining Water Education for Real Estate Professionals | Danielle Storey | |
Coaching, Not Autocomplete: Early Evidence from ConnectInk’s AI-Supported Personal Narrative Pilot | Julio Intriago-Izquierdo | |
Designing AI for K–12 | ||
Agentic PAL: Designing Human-Empowered AI Partnerships for Early Childhood Mathematics Learning | Anastasia Betts | |
Multiple-Document Comprehension in High School Science: A Learning-Engineering Pilot Study | Andrew Potter | |
Socio-Emotional Learning in AI K-12 Guidance and Policy Documents: A Gap Analysis | Emmanuel Adeloju | |
Applications of Learning Engineering | ||
Teacher Education through Learning Engineering: An Action Research on Faculty Transformation | Kürşat Çağıltay | |
eBuku: AI-Driven Mentorless Learning for STEM Education in Humanitarian Contexts of the DRC | Narcisse Mbunzama | |
The Writing Analytics Tool: A Learning Engineering Approach to Designing AI-Supported Writing Instruction | Danielle McNamara & Andrew Potter | |
AI In Science and Education | ||
Comparing Epistemic Emotions and User Experience Across Two AI Instructional Designs in Biology Learning | Yiwen Li | |
REAL CHEM Action Research Through the LearnLab Summer School | Bryan Henderson | |
Designing for Student Engagement with AI in Courseware: Lessons from Iterative Improvements to DOT in REAL CHEM | Kimberly Larson | |
Learning Engineering and Learning Technology 1 | ||
From Course Concept to Lecture Video: An AI-Powered System for Automated MOOC Development | Hua Wei | |
MIRANDA: Real-Time Learning Analytics for Authentic Embedded Assessment | Elina Ollila | |
The Impact on Cognition and Motivation Using Gaming, Simulation, and Visual Learning in Military Flight Training | Ariah Elmore | |
Debate | From Insights to Implementation: Learning Engineering in Action | Moderator: Tracy Arner, Associate Director of the Learning Engineering Institute |
Learning Engineering Distinguished Fellows | ||
What Works When for Whom Under What Conditions: Learning Engineering as an Enabler of Component-based Research | Chris Dede | |
Learning Engineering Body of Knowledge | Jim Goodell | |
Education, Validity, & AI | ||
The Education Tree: A New Theoretical Model for P-20 Education and Development | Maxwell Goshert | |
Implementing Concept Instruction via MCP Server | Thor A. Anderson | |
NLP Validation of Prompt Strategies for Theory-Aligned LLM-Generated Personalization | Linh Huynh | |
Learning Engineering and Learning Technology 2 | ||
“Walk It Out”: An Embodied and Mobile AI Tutor for STEM Education | Mina Johnson-Glenberg | |
A Tiered Framework for Educational Event Data Documentation: Synthesizing Principles and Addressing Gaps | Xin Wei | |
Learning Engineering by Design: An Agentic AI Application for Rapid, Personalized Health & Safety Training in Disaster Response and Hazardous Environments | Henry Ryng | |
AI & Pedagogy | ||
ReQUESTA: A Hybrid Agentic Framework for Generating Cognitively Diverse Multiple-Choice Questions | Yu Tian | |
Towards Automated Detection of Struggling Student Programmers | Sanjita Patwardhan | |
The Promise of Scenario-Based Assessments for College Instruction | Jonathan Cohen | |
Human Centered Applications with Learning Engineering | ||
User experience design of AI-assisted human-technology ecosystem for writing assessment | Li (Lee) Liang | |
A Learning Engineering Approach to Transforming Teacher Practice Through Co-Designing Science Curricular for Multilingual Learners | Yernat Mnuar, Jie Zhang, Iftekharul Chowdhury | |
Currents of Inquiry: Insights From Two Years of Real-World AI-Learner Water Conversations | Stephen Carradini | |
Poster Title | Presenter |
Adaptive Multi-Modal Deepfake Detection for Safer Learning Environments | Syeda Samira Sama |
An Application of Design-Based Implementation Research to Develop a Framework to Support a Community of AI-experience Creators | Janice Mak |
Automated Run-on Sentence Detection and Correction for Educational Writing | Shubham Chakraborty |
Automatic Identification and Evaluation of Revisions in Student Writing Using Large Language Models | Yu Tian |
Automatically Generating Interactive Learning Experience With an LLM-driven Agentic Pipeline | Felix Gröner |
Charm-bots: The Impact of A.I.’s Flattering Language on User Trust | Heather C. Lum |
Engineering a Semantic Topicality Instrument for Multiple-Choice Question Quality Control | Michelle Banawan |
From Measurement to Action: A Learning Engineering Approach to AI-Powered Assessment for Human Power Skills Development | Yigal Rosen |
Integrating AI into Data Sensemaking: Teachers’ Learning and Pedagogical Reflections | Emmanuel Adeloju |
L2-French Learners and Generative AI (GenAI): Challenges, Needs, and Design Guidelines | Jiachen Gong |
Learning-By-Explaining with Generative AI: A Pilot Implementation in Introductory Biology | Kathryn S. McCarthy |
Leveraging Agentic AI for Human-Centered XR Learning Content Standards | Myranda Pina |
LLM Safety in an Educational Context: A holistic approach | Bernice Yeo |
Media Mentor AI: How a SCAMPER-guided AI assistant is helping reimagine media literacy learning | Karina Luna |
Optimizing Language-Focused Writing Feedback from Large Language Models through Prompt Engineering | Yu Tian |
QA Automation of Canvas Courses | Natalia Echeverry |
Quality Assessment Through Learning Engineering: An Evaluation Rubric of LLM-Generated Multiple-Choice Questions | Katerina Christhilf |
Reasoning LLMs are Competent Courseware Reviewers | Ryan Dwyer |
Social and Emotional Dimensions of Generative AI Use | Rebekah Jongewaard |
The Difficult Conversations Bot: Findings on Fostering Empathy and Reflective Communication Among Faculty and Staff | Catheryn Reardon |
The Writing Analytics Tool: A Learning Engineering Approach to Designing AI-Supported Writing Instruction | Danielle McNamara |
Epistemic Cognition and Uncertainty Navigation with a Domain-Specific AI Chatbot in STEM Education | Yiwen Li |
Vibe Coding: How Junior and Senior Developers Use GenAI’s Newest Tool | Selena Evans |
A Learning Strategy Analysis for Guiding the Creation of a Team Training Immersive Reality Environment | Robert F. Siegle |
Advancing Usability of a VR Team Training Environment within a Learning-Engineering Cycle | Parkhi Malhotra |
Co-Designing a Study Platform for ASU Graduate Students to Enhance Learning Productivity and Performance Through Connection | Fiodesy Gemilang Putri |
Co-Designing AI-Enabled Learning in Nursing Education: A Learning Engineering Approach Using Faculty and Student Insights | Mamta Shah |
Design and Pilot Evaluation of a Gamified Narrative Chatbot for STEM Education | maria goldshtein |
Developing Learning Strategy Heuristics for Active Mobile Learning Platforms | Ishrat Ahmed |
How Students Really Use Courseware: Visualizing Student Pathways in Integrated Chemistry Courseware | David J. Yaron |
Understanding Instructor Perspectives and Course Challenges in FSE 100: A Learning Engineering Approach to Improving the Course | Whitney Hansberry |
Case Study: Learning Economy Foundation Competency Graph | Jim Goodell |
IEEE Standards for Scaled Learning Engineering | Jim Goodell |
Open Repository for AI Models as Learning Engineering Components | Jim Goodell |
Bridging Human Intelligence Augmentation (IA) and Classroom Practices via GenAI in Learning Engineering | Li (Lee) Liang |
A Predictive Learning Engineering Framework for Modeling Active Learning | Michelle Banawan |
CoreTrust as a Civic Learning Tool: Community Capital for Inclusive Digital Governance | Mark Roseland |
Design and Development of Two Digital Solutions for Promoting Harmonious Relationships: Buddy Up and Squeez | Kimberly R. M. Osborne |
EdLight Research Portal: An Expert-Annotated Repository of Handwritten Math Student Work | Michel Meneses |
From Immersion to Action: How VR Influences Behavioral Intentions Around Advanced Water Purification | Ketevan Chachkhiani |
Terracotta: Lowering Barriers to Experimental Education Research | Benjamin Motz |
Developing a Model to Support Collaborative Engineering Projects | Yu Ye |
Impact of Varying the Playback Speeds of Educational Content on Learning and Engagement | Tyree Cowell |
NSF: IGE: Transforming Master’s-Level Engineering Education through Industry Partnerships, Principled Engineering, and Experiential Learning | Samantha Brunhaver |
SCALED: A Transferable Learning-Engineering Model for Large-enrollment STEM Courses | Medha Dalal |
Scaling Interleaved Mathematics Practice | Bryan Matlen |
Curiosity Games: Project Mars: An AI-Supported Education Recommendation System | Caila DeAbreu |
We would like to acknowledge our student volunteers for their help with the conference.
Parkhi Malhotra
Whitney Hansberry
Mozhgan Ansari
Fiodesy Gemilang Putri
Emma Streberger
Emily Machniak
Jessica Tan
Emmanuel Adeloju
Rebekah Jongewaard
Sathkeerthi S V
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