RASE Learning Design Model

Churchill, King and Fox introduced the RASE model in their 2013 paper Learning Design for Science Education in the 21st Century, published in the Journal of the Institute for Educational Research. Their core argument was grounded in a body of evidence from learning science: access to content is a necessary but structurally insufficient condition for learning. Learners who encounter resources — lectures, texts, multimedia, tools — without a designed activity to apply them, without support structures to address emerging difficulty and without evaluation mechanisms to guide progress and provide feedback, do not reliably achieve the intended learning outcomes.

The RASE model was constructed as a response to what the authors identified as a persistent design failure in technology-enhanced learning: the conflation of content access with learning design. Digital platforms make it easy to deliver resources at scale. They do not, by default, deliver Activity, Support or Evaluation. Organizations that confuse the platform’s content delivery capability with a complete learning design are designing against the evidence — and producing learning programs whose outcomes consistently disappoint against their objectives.

The model has been adopted and applied at the University of New South Wales (UNSW), among other institutions, as a structured course design framework. Its applicability extends directly to corporate learning environments, leadership development programs, digital capability building initiatives and any organizational context in which performance improvement is the intended outcome of a structured learning investment.

Resources

Resources in the RASE model encompass the full range of content and tools that learners engage with: written materials, multimedia assets, case analyses, frameworks, data, software tools and physical materials relevant to the learning domain. Churchill and colleagues were deliberate in their scope: resources are inputs to learning, not learning itself. Their presence in a program establishes the raw material from which understanding can be constructed. Their absence creates obvious gaps. But their presence alone does not produce learning outcomes.

This distinction has a direct implication for how organizations design and evaluate learning programs. A learning program’s resource quality matters — poorly produced, outdated or inaccurate content creates barriers to learning that no amount of Activity, Support or Evaluation can fully compensate for. But resource quality is a hygiene factor, not a differentiating factor. Above a threshold of accuracy and relevance, additional investment in resource production generates diminishing returns. The marginal value of a higher-production lecture video is lower than the marginal value of a well-designed activity in which learners apply the resource’s content to a real problem.

In organizational contexts, the Resource component of a RASE-designed learning program should be evaluated against two criteria: relevance to the performance gap the program is designed to close and accessibility to the learners who need it. Resources that are technically accurate but misaligned to actual job performance demands do not generate the transfer of learning that justifies the investment. Resources that are well-designed but inaccessible to learners at the moment they need them fail the design test on practical grounds.

Activity

Activity is the component that the RASE model identifies as critical for learning achievement. Churchill and colleagues defined activity as a student-centered, authentic experience in which learners use resources in the context of emerging understanding — testing ideas, applying knowledge, generalizing from specific cases and producing demonstrable outputs. Without activity, resources remain inert: learners may read, watch or listen, but they do not internalize, apply or transfer the content to their performance context.

The two defining characteristics of effective activity in the RASE model are student-centeredness and authenticity. Student-centered activity focuses on what learners do, not what instructors present. The learner is the active agent — resources are tools in their hands and instructors or facilitators function as designers and coaches rather than primary knowledge sources. Authentic activity presents learners with real-world scenarios, including ill-defined and ambiguous problems, that resemble the challenges they will encounter in their professional context. Activities that are disconnected from the actual performance demands of the learner’s role produce learning that is academically coherent but organizationally inert.

For organizational learning programs, the Activity component requires the most deliberate design investment. A leadership development program built around RASE principles does not produce learning through keynote presentations, panel discussions or assigned reading lists. It produces learning through structured simulations, case-based decision exercises, live project work, peer coaching cycles and applied problem-solving under conditions that replicate the genuine complexity of executive decision-making. The design question is always the same: what will learners do with this content that mirrors what they need to do in their roles?

Churchill and colleagues specified that effective activities produce artefacts — tangible outputs that demonstrate the learner’s progress and provide material for feedback and evaluation. In organizational settings, artefacts might include strategy memos, financial models, stakeholder communication plans, process redesigns, project charters or structured recommendations to a simulated executive committee. The artefact serves multiple functions: it disciplines the activity by requiring the learner to produce something specific, it creates a basis for feedback and it generates evidence of capability development that both the learner and their organization can assess.

The artefact logic also addresses a chronic failure mode in organizational learning design: the substitution of passive consumption for active production. Programs that assess learning through multiple-choice tests measure only recognition and recall. Programs that require learners to produce artefacts that demonstrate applied judgment, synthesis and professional competence measure learning transfer — the dimension of learning that actually predicts improved job performance.

Support

Support in the RASE model provides the scaffolding that enables learners to navigate difficulty, develop skills and build independence without becoming stuck or disengaged at points where the activity exceeds their current capability. Churchill and colleagues identified three modes of support: learner-instructor, learner-learner and learner-artefact (additional resources, tools and reference materials). Each mode addresses a different dimension of the support need.

The design discipline the RASE model imposes on Support is anticipation. Effective support does not wait for learners to fail and then intervene — it anticipates where learners are likely to encounter difficulty and provides accessible pathways to assistance before those difficulties cause disengagement. In organizational learning contexts, this anticipatory design logic translates into: structured facilitation checkpoints at predictable difficulty thresholds, peer learning cohort structures that create learner-to-learner support through shared experience, curated reference tools available at the point of need and coaching support that responds to demonstrated performance gaps rather than predetermined schedules.

Churchill and colleagues were explicit about the developmental trajectory of support: it should be calibrated to decrease as learner capability increases. Scaffolding that remains constant throughout a program does not develop the independence that performance in a real organizational context requires. A leadership development program that provides intensive facilitation and coaching throughout but graduates participants who cannot apply their learning without continued support has failed its design objective. The Support component’s goal is to enable eventual self-sufficiency, not sustained dependence.

The RASE model’s Support component carries particular weight in the digital and hybrid learning environments that most organizations now operate. Digital platforms can deliver Resources and some forms of Activity at scale. They are structurally less capable of delivering the responsive, relationship-based support that learners need when they encounter genuine difficulty with complex, ambiguous problems. Organizations that migrate learning programs to digital delivery without redesigning the Support component typically see completion rates decline and performance transfer rates fall, because the human support infrastructure that compensated for design gaps in the original program is no longer present.

Deliberate support architecture in digital learning environments includes: structured discussion forums moderated by experienced practitioners, cohort-based peer feedback mechanisms, asynchronous coaching tools that allow learners to submit questions and receive substantive responses within defined timeframes and escalation pathways that connect learners facing acute difficulty to direct human support. These are design choices, not platform features. Organizations that treat them as design choices invest in them accordingly.

Evaluation

Evaluation in the RASE model encompasses both the assessment of learning outcomes and the formative feedback that guides learners’ progress throughout the program. Churchill and colleagues distinguished between formative evaluation — ongoing feedback that helps learners understand where they are relative to the learning outcomes and what they need to do to progress — and summative evaluation, which provides a final assessment of whether the learning objectives were achieved. Both are necessary. Neither alone is sufficient.

Formative evaluation is where the RASE model produces its most distinctive organizational value. Most corporate learning programs are heavy on summative assessment — end-of-program tests, certification requirements, manager ratings of post-program behavioral change — and light on formative feedback during the learning process itself. That design imbalance is consequential. Learners who receive feedback only at the end of a program cannot use that feedback to improve their performance during the program. The feedback arrives too late to change the learning trajectory.

RASE-aligned evaluation design builds feedback loops into the activity structure throughout the program. Artefacts produced during activities are reviewed and commented on by instructors, peers and subject-matter experts, with feedback specific enough to guide revision and improvement. Rubrics are shared with learners before activities are completed, so that learners can self-evaluate their work against the expected standard before submitting it. Progress checkpoints identify learners who are falling behind early enough for the Support component to intervene before the gap becomes irreversible.

The Evaluation component of the RASE model also addresses the organizational governance question that every executive sponsoring a learning investment will eventually face: how do you know whether the program produced its intended outcome? Evaluation designed at the level of learning artefact quality and post-activity performance change provides the evidence base that ROI (return on investment) analysis requires. Programs that collect only completion rates and satisfaction scores generate data that cannot answer the question of whether learning transferred to job performance. Programs that evaluate artefact quality, track behavioral change over time and measure the performance metrics the program was designed to improve generate the evidence that justifies continued investment and guides design iteration.

Churchill and colleagues designed the RASE model’s Evaluation component to close the feedback loop not just for learners but for the learning design itself. Evaluation data that surfaces consistent patterns — activities that consistently produce weak artefacts, support touchpoints that learners consistently bypass, resources that learners consistently find insufficient — provides the signal that enables iterative design improvement. Organizations that treat their learning programs as fixed products rather than evolving designs forfeit this improvement signal and continue investing in programs whose design gaps they cannot see.

RASE in Organizational Practice

The RASE model provides a design audit framework that any executive or talent leader can apply to an existing learning program in a single structured review session. The audit asks four questions: What resources does the program provide and are they relevant to the performance gap the program is designed to close? What activities does the program require learners to complete and do those activities produce artefacts that demonstrate applied capability? What support structures are in place to help learners navigate difficulty and are they anticipatory or reactive? What evaluation mechanisms provide formative feedback during the program and assess performance transfer after it?

Where any component is absent or underinvested, the audit produces a design gap. The gap is not a judgment about the program’s intent — it is a structural diagnosis that identifies where additional design investment will generate the greatest improvement in learning outcomes. Programs that score well on Resources but poorly on Activity can be redesigned by converting passive content into applied exercises without rebuilding the full program. Programs that score well on Activity but poorly on Support can be strengthened by adding facilitated peer cohorts and coaching checkpoints. The RASE model makes the design leverage points visible and actionable.