Learning engineers apply the learning sciences and engineering methods to iteratively improve learning outcomes at scale.
This site is a practice-centered guide for people doing the work, people curious about the role, and people adjacent to it. It's organized around what you might actually need — not around a graph of citations.
Start from a question, a topic, or a guided tour
- Exploring by topic?Topics →Browse 18 topics across three layers — from learning science foundations to ethics and evidence standards.
- Want a guided tour?Pathways →Five narrative threads through the field — follow the one that matches your question.
Or browse by what you need
- Need something you can use this week?Field Notes (3) →Short practitioner pieces — tips, templates, and lessons from the actual work.
- Figuring out how LEs structure their work?Practice (6) →Process diagrams, maturity models, and analysis methods (Five Whys, Fishbone, task analysis).
- Looking for people or programs?Community (72) →Organizations, degree programs, and practitioners who do this work.
- Planning to attend, present, or catch up?Events (53) →Conferences, recurring series, keynotes, podcasts, and talks from the field.
- Scanning the field or citing the literature?Reading List (79) →Papers, books, articles, and reports that define the evidence base.
- Picking a platform or instrumenting something?Tools (8) →The platforms, systems, and software LEs build on.
What learning engineers do
They work at the intersection of learning science, instructional design, data analysis, and systems thinking. They diagnose why a course or training program isn't producing the outcomes it should, redesign the intervention with evidence in mind, instrument it to collect signal, and iterate. The work spans K–12 classrooms, higher-ed platforms, workplace training, and high-consequence domains like medicine and defense.
What learning engineering adds to instructional design is an emphasis on evidence of impact — and the willingness to treat learning interventions as systems that can be measured, debugged, and improved.
Who this site is for
- Practitioners who already do this work and want a shared vocabulary, practice references, and a way to point colleagues to the field.
- Students and new entrants deciding whether learning engineering is the right path — and where to study or start.
- Adjacent professionals (instructional designers, ML engineers, learning scientists, HR/L&D leaders) who need to understand how this role overlaps with theirs.
About this site
Most entries come from a hand-curated workbook of IEEE ICICLE–adjacent resources, plus original practitioner posts in Field Notes. Items are tagged by format and by curatorial cluster (e.g. "ICICLE resources," "Bror Saxberg," "I/ITSEC"). Sources with incomplete provenance carry a visible source unknown badge — we'd rather show you a promising lead we haven't verified than quietly drop it. More on scope & method →