Learning Sciences and Learning Engineering: Natural or Artificial Distinction? (Lee, 2023)
Scholarly analysis of the relationship between learning sciences and learning engineering, arguing for tighter integration of the two.
T01
Learning Science Foundations
Cognitive load theory; spaced practice; retrieval; worked examples; transfer. The scientific basis for design decisions.
11 resources tagged with this topic
Concepts in this topic
How People Learn: Cognitive Foundations Understand
Builds on: What is Learning Engineering?
Desirable Difficulties & Memory Principles Apply
Builds on: How People Learn: Cognitive Foundations
Cognitive Load Theory Apply
Builds on: How People Learn: Cognitive Foundations
Motivation, Engagement & Self-Regulation Apply
Builds on: How People Learn: Cognitive Foundations
Transfer of Learning Analyze
Builds on: How People Learn: Cognitive Foundations
Resources
Reading List 3
The Science of Remote Learning
Pandemic-era compilation from MIT Open Learning distilling what the learning sciences say about effective remote instruction. Practical, evidence-based, and widely shared during the 2020 pivot.
Practice 1
Learning Design Principles Toolkit (McEldoon)
Toolkit connecting cognitive science principles to practical learning design moves, with examples for day-to-day LE workflow decisions.
Events 3
Learning Engineering: What We Know, What We Can Do — Bror Saxberg keynote
Saxberg's clearest public statement of the learning-engineer role: why instructional design's compliance model falls short at scale, what evidence-based iteration actually looks like in industry, and where the next generation of LEs needs to come from. The canonical 'what is LE' talk for newcomers.
Silver Lining for Learning — The Art and Science of Learning Engineering
Roscoe, Craig, and McNamara on what makes LE distinct from adjacent fields — and where art/intuition still lives inside what's meant to be an engineering discipline. A more philosophical companion to the ICICLE 2024 materials.
Unlock the Learning Engineer in You — pK-12 Context
The Invitation to Learning Engineering webinar held on December 11th, 2024, highlighted a use case from Carnegie Learning on the application of learning engineering in pK-12 context. The case study featured Steve Ritter (Founder & Chief Scientist), Husni Almoubayyed (AI Engineering Manager), and Rae Bastoni (Senior UX Researcher). They showcased insights from the work on facilitating math learning with adaptive reading supports.
Community 4
MIT Integrated Learning Initiative (MITili)
MIT-wide initiative bridging learning science research and practice. Funds cross-disciplinary work on how people learn and publishes actionable guidance — a key academic node in the LE ecosystem.
Playful Journey Lab
MIT lab building playful assessment tools and game-based learning approaches. Runs the 'Schools of Tomorrow' Learning Engineering Project Blueprint — an example of LE applied to K-12 assessment innovation.