DDES9911 Future Immersive Learning Methodologies
The Complete Study & Assessment Guide · T3 2026DDES9911 Overview
- Term 3 2026
- Postgraduate course
- Two individual reports
- Moodle submission
- Immersive learning design
DDES9911 Future Immersive Learning Methodologies is a postgraduate UNSW Sydney course offered in Term 3 2026. It treats immersive learning as an educational design problem rather than a device showcase.
- Assessed by A 40% immersive learning experience report and a 60% instruction and assessment report.
- Hardest step Link each technology and fidelity choice to a learner, outcome, transfer claim and evidence.
- How to prepare Develop one proposal across the weekly tasks, then revise it using feedback and evaluation evidence.
What you get in the full DDES9911 Study & Assessment Guide
- 9 chapters, 40 pages — every assessed topic, week by week
- 24 original practice questions, most with model answers
- 9 worked examples, solved the way DDES9911 marks
- 9 computed figures, redrawn from the course’s own numbers
- Before-you-submit checklist for the Assessment 2 – Instruction and assessment with an Immersive Learning system (60%) — what markers reward, what costs marks
Free on this page: assessment table, chapter map, one worked example, key terms, FAQ. The rest is in the full study & assessment guide.
How DDES9911 is assessed
| Component | Weight | Format |
|---|---|---|
| Assessment 1 – Immersive Learning Experience | 40% | Individual written task submitted as PDF through Moodle; 2,000 to 4,000 words; due 11.59pm Sunday of Week 5 |
| Assessment 2 – Instruction and assessment with an Immersive Learning system | 60% | Individual written report submitted as PDF through Moodle; 2,000 to 4,000 words; due 11.59pm Sunday of Week 11 |
What other students are asking about DDES9911
- Where can I find lecture notes or study guides for DDES9911 at UNSW?
- The DDES9911 study guide in AskSia Library covers Future Immersive Learning Methodologies in 9 chapters, with the assessment table, a chapter-by-chapter topic map, key terms and a worked example, free to read on this page.
- Is there a final exam in DDES9911?
- No final exam is listed in the offering this AskSia Library guide is built from; DDES9911 is assessed by Assessment 1 – Immersive Learning Experience 40%, Assessment 2 – Instruction and assessment with an Immersive Learning system 60%.
- What does DDES9911 cover on learning outcomes and task fit?
- In AskSia Library's DDES9911 guide, the Learning Outcomes and Task Fit chapter explains knowledge, competence, confidence and mastery across technical, non-technical, individual and team tasks.
- What does DDES9911 cover on engagement, fidelity and validity?
- In AskSia Library's DDES9911 guide, the Engagement, Fidelity and Validity chapter explains learner stage, interaction design, relevant realism, face validity, content validity and construct validity.
- What does DDES9911 cover on designing the learner experience?
- In AskSia Library's DDES9911 guide, the Designing the Learner Experience chapter explains experiential learning, cognitive load, accessibility, reflection and varied practice for transfer.
What DDES9911 covers
Nine chapters follow the taught sequence from instructional strategy and learning outcomes through learner experience, implementation, instructor roles, debriefing, assessment and performance analytics.
Instructional Strategy for Immersion
Situated and authentic learning, safe repeatable practice, technology choice and evidence of transferAn immersive learning strategy begins with a learner, an authentic task and an observable transfer goal. This chapter shows how safe, controlled and repeatable practice can support situated learning without making technology the outcome.
- Learner need and context
- Situated and authentic activity
- Safe repeatable practice
- Technology choice and tradeoffs
- Real-world transfer evidence
- Future capability assumptions
Learning Outcomes and Task Fit
Knowledge, competence, confidence and mastery across technical, non-technical, individual and team tasksLearning can mean knowledge, competence, confidence or mastery, and those claims require different evidence. This chapter classifies tasks as technical or non-technical and individual or team based, then converts broad ambitions into observable outcomes.
- Knowledge, competence and confidence
- Technical and non-technical skills
- Individual and team performance
- Learner developmental stage
- Observable end states
- Transfer across varied contexts
Engagement, Fidelity and Validity
Learner stage, interaction design, relevant realism, face validity, content validity and construct validityEngagement can support attention and deliberate practice, but it is not proof of learning. This chapter distinguishes visual, physical, functional, psychological and social fidelity, then links them to learner stage and task validity.
- Engagement as a learning mechanism
- Forms of fidelity
- Learner stage and realism
- Face validity
- Content validity
- Construct validity
Designing the Learner Experience
Experiential learning, cognitive load, accessibility, reflection and varied practice for transferThe learner experience should create a cycle of action, consequence, reflection, revised understanding and another attempt. This chapter applies experiential learning, cognitive load and learner-centred design to immersive environments.
- Experiential learning cycle
- Embodied cognition
- Cognitive load
- Human and psychological factors
- Technology and accessibility
- Merrill instructional principles
Planning an Immersive Program
Task decomposition, scaffolding, repetition, progression, summative performance and retentionA learning management plan explains how learners enter, practise, progress, receive feedback, demonstrate performance and return for retention or retraining.
- Task decomposition
- Scaffolding and prompt fading
- Repetition, frequency and duration
- Formative and summative stages
- Progression evidence
- Retention and retraining
The Instructor in Simulation
Learning authors, facilitators, domain experts, technical support and virtual guidance boundariesInstruction in immersive environments may be distributed across a learning author, facilitator, domain expert, technical specialist and virtual agent.
- Learning author responsibilities
- Facilitator actions
- Domain expert judgement
- Technical support
- Virtual instructor boundaries
- Prompt fading
Reflection, Feedback and Debriefing
Reflection in action, reflection on action, hot and cold debriefs, evidence and revised behaviourReflection and debriefing convert simulation experience into revised behaviour. This chapter compares reflection in action with reflection on action, hot with cold debriefing, and individual with shared review.
- Reflection in action
- Reflection on action
- Hot and cold debriefs
- Event logs and evidence
- Description, understanding and generalisation
- Facilitator and expert roles
Assessment and Evaluation
Technical and non-technical performance, valid measures, transparent judgement and quality controlAssessment judges learner performance, while evaluation examines whether the simulation and learning strategy are effective.
- Assessment versus evaluation
- Technical skill evidence
- Non-technical skill evidence
- Automatic and human measures
- Rubrics and judgement rules
- Reliability and moderation
Learning Systems and Performance Data
Assignment, event capture, access, assessment, reporting, governance and continuous improvementA learning management system surrounds the simulation event with assignment, preparation, resource allocation, scheduling, access, support, capture, assessment, debriefing and reporting.
- Assignment and preparation
- Resource and access management
- Event capture
- Assessment and debrief handoff
- Reporting and analytics
- Data governance
Across the taught weeks, you develop one theoretical or real training application: first defining the learner, authentic task and instructional strategy, then specifying the learning outcome, delivery mechanism, fidelity, validity and value proposition. The middle of the course turns that proposal into a program through task decomposition, scaffolding, repetition, progression, feedback and a learning management plan.
After Study Week, the focus expands to the role of instructors and facilitators, reflection and debriefing, assessment and evaluation, and the learning systems and performance data needed to deliver and improve the experience. The central challenge is keeping those decisions coherent.
A visually convincing simulation is weak if it rehearses the wrong behaviour; an engaging activity is weak if it has no transfer evidence; a detailed dashboard is weak if its measures cannot support the claim. The course is assessed by two connected individual reports. Assessment 1 establishes the strategy and plan.
Assessment 2 revises and extends that work into a complete account of instruction, learner reflection, performance assessment and analytics. The weekly activities are therefore drafting opportunities for the assessed argument. Use this guide to compare alternatives, state design boundaries and practise turning broad claims into observable decisions.
The strongest work tells a non-specialist exactly who is learning, what they must become able to do, why the chosen immersive mechanism adds value, how support and feedback operate, what evidence is collected, and how that evidence changes the next learner or program decision.
Worked example · free
From technology pitch to learning strategy
- 1Define the learner and the authentic decision the supervisor must make.
- 1State the observable outcome and separate it from confidence or enjoyment.
- 1Justify the delivery mode by naming the spatial or interaction feature it adds.
- 1Test transfer in an unfamiliar layout or supervised workplace task.
Key terms
- Authentic learning
- Learning organised around meaningful tasks and conditions that resemble how knowledge or skill will be used.
- Situated learning
- Learning that develops through participation in a relevant social, physical or professional context.
- Deliberate practice
- Focused repeated practice with clear goals, feedback and adjustment directed at a specific performance gap.
- Task fidelity
- The degree to which a simulation preserves the task relationships and cues needed for meaningful performance.
- Face validity
- The extent to which users or experts perceive an activity as recognisable and plausible.
- Content validity
- The extent to which tasks and evidence represent the relevant domain of performance.
- Construct validity
- The extent to which an activity genuinely elicits or measures the capability it claims to address.
- Cognitive load
- The demand placed on working memory by task complexity, presentation and learner activity.
- Scaffolding
- Temporary guidance or structure that supports performance and is reduced as capability develops.
- Reflective practice
- Deliberate examination of experience and action to revise understanding and future behaviour.
- Formative assessment
- Evidence used during learning to guide feedback, adaptation and another attempt.
- Performance analytics
- Interpreted records of learner or program activity used to support defined educational decisions.
DDES9911 FAQ
How difficult is this course?
The difficulty comes from integrating many design decisions into one defensible argument. You must connect learner need, task, modality, fidelity, facilitation, assessment and analytics without treating technology as proof of value. Weekly drafting makes the workload more manageable because each activity develops a section of the two connected reports.
How is the course assessed?
There are two individual written components. The immersive learning experience report is worth 40% and is due in Week 5. The instruction and assessment report is worth 60% and is due in Week 11. The second extends the first into a complete strategy rather than starting a separate project.
What should the final report contain?
The second brief asks you to revise the first submission using feedback and combine the major course components into a coherent formal report. It should explain the strategy, outcome, mechanism, management, instruction, reflection, assessment and analytics, with an introduction, contents and a concluding recommendation.
Does high fidelity always improve learning?
No. Fidelity must fit the learner stage and the task feature that needs to transfer. Visual realism can add cost or cognitive burden without improving the target performance. Name whether physical, functional, psychological or social fidelity matters, then justify what can be simplified and how validity will be examined.
Can generative AI be used in assessment?
The assessment briefs require you to create the first iteration yourself. They permit later generative assistance when any output used in the submission is fully attributed and referenced. Keep your own reasoning visible, verify suggestions against course evidence, and follow the exact permission statement in the current brief.
How should feedback be used between reports?
Treat feedback as evidence for revising the same project. Identify the claim or design choice being questioned, decide whether the strategy, mechanism or explanation needs to change, and make the revision visible in the complete report. Avoid adding disconnected features merely to show that the document has grown.
What makes a good analytics plan?
A good plan begins with the educational decision, then selects the minimum valid trace, preserves scenario context, limits access and names the person responsible for interpretation. It distinguishes learner assessment from program evaluation and states what pattern will trigger feedback, support, redesign or further investigation.
Questions students ask in each DDES9911 chapter
- Why should technology not come first?
- Starting with technology encourages the proposal to search for a problem. Beginning with the learner and authentic task makes it possible to judge whether immersion adds useful practice, whether a simpler method is better, and what evidence would show that the design transfers to real performance. Chapter 01 · Instructional Strategy for Immersion
- What is the difference between competence and confidence?
- Competence is supported by evidence that a learner can perform to a defined standard. Confidence is the learner's belief or willingness to act. Confidence can influence participation and deserves attention, but it should be paired with behavioural evidence because a learner can feel certain while using an incorrect method. Chapter 02 · Learning Outcomes and Task Fit
- Is more realism always better?
- No. Extra realism can increase cost, discomfort or cognitive burden without protecting the target task. Select the visual, physical, functional, psychological or social features that change relevant performance, and simplify features that do not support the learner or outcome. Chapter 03 · Engagement, Fidelity and Validity
- How does experiential learning shape a simulation?
- The experience must permit meaningful action, make consequences interpretable, create space for reflection and support another attempt in which behaviour can change. A single dramatic event without reflection or retry may be memorable but does not complete the learning cycle. Chapter 04 · Designing the Learner Experience
- How should repetition be planned?
- Repetition should vary relevant conditions and respond to evidence rather than use a universal fixed count. Specify duration, frequency, fatigue safeguards and the behaviour required for progression. Repeating one unchanged scene can reward memorisation instead of adaptable performance. Chapter 05 · Planning an Immersive Program
- Can a virtual instructor replace a human?
- A virtual instructor can deliver consistent orientation, prompts or routine feedback when its rules are valid. It should not imply contextual expertise beyond those rules. Define limits, preserve event evidence and escalate safety, distress or ambiguous judgement to an accountable person. Chapter 06 · The Instructor in Simulation
- When should a simulation be paused for reflection?
- Pause when safety, severe misunderstanding or novice guidance requires immediate intervention and when doing so will not destroy the learning purpose. Preserve whole-event flow when sequence and consequences matter, then review afterwards. The choice should match risk, learner stage and task integrity. Chapter 07 · Reflection, Feedback and Debriefing
- How are assessment and evaluation different?
- Assessment asks how well the learner performed against an outcome or standard. Evaluation asks whether the learning strategy, simulation and delivery worked. The same event may inform both, but a poor result can reflect learner need, interface design, scenario alignment or operational failure. Chapter 08 · Assessment and Evaluation
- What belongs in the learning-system workflow?
- The workflow can include module assignment, preparation, technical resources, access privileges, scheduling, support, the simulation event, selected capture, assessment, debrief, reporting, technical evaluation and program review. Each element should have a purpose and owner. Chapter 09 · Learning Systems and Performance Data
How to prepare for the assessments
Build one live design dossier from the first teaching week. Start with a one-page learner and task definition, then add the observable outcome and transfer test. For each later topic, write a decision, an alternative, the evidence supporting your choice and the limitation that remains.
Keep a traceability table linking outcome, mechanism, fidelity, practice stage, instructor role, debrief evidence, assessment rule and analytics action. Before Assessment 1, check that the learning management plan follows logically from the strategy rather than appearing as a separate schedule.
After feedback, record each revision and the reason for it before extending the project through instruction, reflection, assessment and performance analytics. Rehearse with original cases by explaining why an attractive feature should be rejected when it does not protect the target task.
On the final edit, remove unsupported promises, define specialist terms for a non-specialist reader, verify that every measure supports a real decision and confirm the current Moodle submission details. This approach turns weekly activity into cumulative progress while protecting the coherence that both reports require.
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