4.1.3 Defining interdependencies

This subtopic covers the identification and analysis of interdependencies between components in the learning system.

From the Learning Engineering Toolkit

Once the parts of a system have been named, the Learning Engineering Toolkit stresses that they never operate alone; whether the whole thing works depends on how they connect. The book explains that interfaces manage the exchanges between modules so the system behaves as intended [LET-04]. It sets out that a system works only when it has modules for every needed function, those modules cooperate through interfaces that function correctly, and each module stays within its tolerances [LET-04].

These dependencies mean that altering one part can ripple across the system. The chapter uses an electronics case: because temperature affects an LCD display, engineers building a phone for hot regions would have to add a cooling module along with a sensor and an interface that governs when the cooling switches on or off, so the new parts mesh properly with the rest of the device [LET-04]. Trade-off analysis is likewise driven by these dependencies; in the solar-cell case, concentrating more sunlight yields more energy but also more heat that can ruin the cells, so the engineer has to weigh the linked effects instead of tuning any single part in isolation [LET-04].

For learning systems, the book makes the dependencies plain through the pandemic case: the elements that had propped up student participation, such as physical space and cultural norms, were tied to the classroom model, and once the surrounding conditions shifted, those coupled elements failed as a group and the system had to be rebuilt [LET-04]. The chapter also casts interdependency in human terms, observing that within a school the learners, instructors, tutors, and tutoring software can all be regarded as parts of one system, with feedback aimed at different parts depending on how they relate [LET-04]. Defining interdependencies therefore means charting how the modules of a learning system cooperate, so that constraints, tolerances, and feedback can be coordinated across the entire system of systems [LET-04].

Further Reading

Source: wrgr/lecommons — curated by the learning engineering community. Confidence: medium — lecommons-curated; not yet independently expert-validated in this context. To validate or challenge any item: use the Edit button on this page. Upgrading confidence from medium → high requires expert sign-off.

Landmark Academic Papers

• Design principles for virtual humans in educational technology environments — Scotty D. Craig, Nicolaus L. Schroeder (2018). International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-017-0148-y · ~150 citations · tier: contemporary

  Synthesized human-factors engineering principles for designing pedagogical agents. Showed that voice, appearance, and persona of virtual instructors systematically affect learner cognitive load and perceived credibility — establishing that LE must integrate psychological design alongside algorithmic design. Source: lecommons/landscape/data/papers.json · ID: LE-LS-AP-009 · confidence: medium · expert-validated: false

• The voice quality of pedagogical agent impacts learning and agent perceptions — Ryan F. Siegle, Scotty D. Craig (2024). Journal of Computer Assisted Learning · doi:10.1111/jcal.12997 · ~20 citations · tier: contemporary

  Empirically demonstrated that voice quality (prosody, naturalness, warmth) of a pedagogical agent significantly affects both learning outcomes and learner perception. Illustrates the meticulous human factors engineering required in modern AI-driven learning systems. Source: lecommons/landscape/data/papers.json · ID: LE-LS-AP-010 · confidence: medium · expert-validated: false

Key People

• Scotty D. Craig (profile), Arizona State University (active 2000s–present) — Human factors researcher; virtual humans and pedagogical agents specialist

  Systematically investigated design principles for virtual humans and pedagogical agents in learning environments Source: lecommons/landscape/data/people.json · ID: LE-LS-PP-014 · confidence: medium · expert-validated: false

Programs & Initiatives

• Human Factors and Ergonomics Society (CO) · link

  Professional society for human factors and ergonomics. Publishes Human Factors journal and organizes the annual HFES conference. The Training Systems technical group directly addresses LE-relevant human factors in instructional systems. Source: lecommons/site/src/data/programs_people_registry.json · ID: LE-PP-133 · confidence: medium · expert-validated: false

• INCOSE Systems Engineering Body of Knowledge (SEBoK) (CO) · link

  Open wiki-based body of knowledge for systems engineering. Includes the Human Systems Integration knowledge area. The SE process framework (requirements, architecture, integration, verification) is the engineering process backbone that LE adapts for learning system development. Source: lecommons/site/src/data/programs_people_registry.json · ID: LE-PP-134 · confidence: medium · expert-validated: false

Lecommons enrichment applied 2026-04-17. All items pending expert validation. See wrgr/lecommons for source data and curation methodology.