General Information
This subject explores the current limits and latest workflows of screen storytelling using Virtual Production environments. It delves into when you should use a virtual environment, how to combine a digital environment with a live one, and the benefits and drawbacks of using a volume stage. You will gain a deep understanding of the latest theories of Virtual Production, develop competencies in the basic tools of operation, learn how to build and develop your own virtual environments, and creatively problem-solve real-world production issues.
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Details
Academic unit: Faculty of Society & Design Subject code: DIGM12-105 Subject title: Virtual Production - Places Subject level: Undergraduate Semester/Year: January 2026 Credit points: 10.000 -
Delivery & attendance
Timetable: https://bond.edu.au/timetable Delivery mode: Standard Workload items: - Forum: x12 (Total hours: 12) - Weekly Forum
- Personal Study Hours: x12 (Total hours: 72) - Recommended Study Hours
- Studio: x12 (Total hours: 36) - Weekly Studio
Attendance and learning activities: N/A -
Resources
Prescribed resources: No Prescribed resources.
After enrolment, students can check the Books and Tools area in iLearn for the full Resource List.iLearn@Bond & Email: iLearn@Bond is the Learning Management System at Bond University and is used to provide access to subject materials, class recordings and detailed subject information regarding the subject curriculum, assessment, and timing. Both iLearn and the Student Email facility are used to provide important subject notifications.
Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student.
To access these services, log on to the Student Portal from the Bond University website as www.bond.edu.au
Class recordings: The majority of this subject's classes will not be recorded due to one of the reasons outlined in the Recording policy.
Students are encouraged to attend all sessions as these recordings will not be available for revision purposes.
For further information please contact the subject coordinator.
| Academic unit: | Faculty of Society & Design |
|---|---|
| Subject code: | DIGM12-105 |
| Subject title: | Virtual Production - Places |
| Subject level: | Undergraduate |
| Semester/Year: | January 2026 |
| Credit points: | 10.000 |
| Timetable: | https://bond.edu.au/timetable |
|---|---|
| Delivery mode: | Standard |
| Workload items: |
|
| Attendance and learning activities: | N/A |
| Prescribed resources: | No Prescribed resources. After enrolment, students can check the Books and Tools area in iLearn for the full Resource List. |
|---|---|
| iLearn@Bond & Email: | iLearn@Bond is the Learning Management System at Bond University and is used to provide access to subject materials, class recordings and detailed subject information regarding the subject curriculum, assessment, and timing. Both iLearn and the Student Email facility are used to provide important subject notifications. Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student. To access these services, log on to the Student Portal from the Bond University website as www.bond.edu.au |
| Class recordings: | The majority of this subject's classes will not be recorded due to one of the reasons outlined in the Recording policy. Students are encouraged to attend all sessions as these recordings will not be available for revision purposes. For further information please contact the subject coordinator. |
Enrolment requirements
| Requisites: |
Nil |
|---|---|
| Assumed knowledge: |
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge. Assumed Prior Learning (or equivalent): |
| Restrictions: |
Nil |
Assurance of learning
Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.
At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.
Program Learning Outcomes (PLOs)
Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.
Subject Learning Outcomes (SLOs)
On successful completion of this subject the learner will be able to:
- Display an understanding of the latest theories of Virtual Production environments.
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Build a small digital asset.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
- Creatively problem solve real-world Virtual Production issues.
Generative Artificial Intelligence in Assessment
The University acknowledges that Generative Artificial Intelligence (Gen-AI) tools are an important facet of contemporary life. Their use in assessment is considered in line with students’ development of the skills and knowledge which demonstrate learning outcomes and underpin study and career success. Instructions on the use of Gen-AI are given for each assessment task; it is your responsibility to adhere to these instructions.
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Assessment details
Type Task % Timing* Outcomes assessed AI category Assignment Assessment 1: Digital Twin Cinematic: Individually capture and reconstruct a real-world indoor location, optimise it for real-time use, and produce a short cinematic sequence in Unreal Engine that showcases lighting, composition, and spatial storytelling. 30.00% Week 6 1, 2, 3, 4 Creative Piece§ Assessment 2: Group Cinematic Scene with Actor and VFX Integration: Working in teams, produce a short cinematic scene that combines real-world scanned environments, virtual assets, animated elements, and live actor integration. The final piece must demonstrate narrative intent, visual coherence, and real-time production techniques. 40.00% Week 12 1, 2, 3, 4, 5 Professionalism Participation and Studio Engagement: Assessed through weekly attendance, contribution to discussions and reviews, engagement in peer feedback, and evidence of iterative development in both individual and group work. 30.00% Ongoing 1, 2, 4, 5 - § Indicates group/teamwork-based assessment
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
AI Categories
Ai Prohibited: Learning to develop AI-free knowledge and skills.
Ai Supported: Learning with the help of AI as directed.
Ai Focussed: Learning AI expertise and mastery as directed.
Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.
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Assessment criteria
Assessment criteria
High Distinction 85-100 Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. Distinction 75-84 Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. Credit 65-74 Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. Pass 50-64 Usually awarded to students whose performance meets the requirements set for work provided for assessment. Fail 0-49 Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
| Type | Task | % | Timing* | Outcomes assessed | AI category |
|---|---|---|---|---|---|
| Assignment | Assessment 1: Digital Twin Cinematic: Individually capture and reconstruct a real-world indoor location, optimise it for real-time use, and produce a short cinematic sequence in Unreal Engine that showcases lighting, composition, and spatial storytelling. | 30.00% | Week 6 | 1, 2, 3, 4 | |
| Creative Piece§ | Assessment 2: Group Cinematic Scene with Actor and VFX Integration: Working in teams, produce a short cinematic scene that combines real-world scanned environments, virtual assets, animated elements, and live actor integration. The final piece must demonstrate narrative intent, visual coherence, and real-time production techniques. | 40.00% | Week 12 | 1, 2, 3, 4, 5 | |
| Professionalism | Participation and Studio Engagement: Assessed through weekly attendance, contribution to discussions and reviews, engagement in peer feedback, and evidence of iterative development in both individual and group work. | 30.00% | Ongoing | 1, 2, 4, 5 |
- § Indicates group/teamwork-based assessment
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
AI Categories
Ai Prohibited: Learning to develop AI-free knowledge and skills.
Ai Supported: Learning with the help of AI as directed.
Ai Focussed: Learning AI expertise and mastery as directed.
Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.
Assessment criteria
| High Distinction | 85-100 | Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. |
|---|---|---|
| Distinction | 75-84 | Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. |
| Credit | 65-74 | Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. |
| Pass | 50-64 | Usually awarded to students whose performance meets the requirements set for work provided for assessment. |
| Fail | 0-49 | Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. |
Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Study Information
Submission procedures
Students must check the iLearn@Bond subject site for detailed assessment information and submission procedures.
Policy on late submission and extensions
A late penalty will be applied to all overdue assessment tasks unless an extension is granted by the subject coordinator. The standard penalty will be 10% of marks awarded to that assessment per day late with no assessment to be accepted seven days after the due date. Where a student is granted an extension, the penalty of 10% per day late starts from the new due date.
Academic Integrity
Bond University‘s Student Code of Conduct Policy , Student Charter, Academic Integrity Policy and our Graduate Attributes guide expectations regarding student behaviour, their rights and responsibilities. Information on these topics can be found on our Academic Integrity webpage recognising that academic integrity involves demonstrating the principles of integrity (honesty, fairness, trust, professionalism, courage, responsibility, and respect) in words and actions across all aspects of academic endeavour.
Staff are required to report suspected misconduct. This includes all types of plagiarism, cheating, collusion, fabrication or falsification of data/content or other misconduct relating to assessment such as the falsification of medical certificates for assessment extensions. The longer term personal, social and financial consequences of misconduct can be severe, so please ask for help if you are unsure.
If your work is subject to an inquiry, you will be given an opportunity to respond and appropriate support will be provided. Academic work under inquiry will not be marked until the process has concluded. Penalties for misconduct include a warning, reduced grade, a requirement to repeat the assessment, suspension or expulsion from the University.
Feedback on assessment
Feedback on assessment will be provided to students according to the requirements of the Assessment Procedure Schedule A - Assessment Communication Procedure.
Whilst in most cases feedback should be provided within two weeks of the assessment submission due date, the Procedure should be checked if the assessment is linked to others or if the subject is a non-standard (e.g., intensive) subject.
Accessibility and Inclusion Support
Support is available to students where a physical, mental or neurological condition exists that would impact the student’s capacity to complete studies, exams or assessment tasks. For effective support, special requirement needs should be arranged with the University in advance of or at the start of each semester, or, for acute conditions, as soon as practicable after the condition arises. Reasonable adjustments are not guaranteed where applications are submitted late in the semester (for example, when lodged just prior to critical assessment and examination dates).
As outlined in the Accessibility and Inclusion Policy, to qualify for support, students must meet certain criteria. Students are also required to meet with the Accessibility and Inclusion Advisor who will ensure that reasonable adjustments are afforded to qualifying students.
For more information and to apply online, visit BondAbility.
Subject curriculum
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Real-World Environments and the Digital Twin Pipeline
Building on Unreal skills, students are introduced to spatial storytelling, real-world capture methods, and digital twin pipelines. Includes site planning and technical orientation.
SLOs included
- Display an understanding of the latest theories of Virtual Production environments.
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
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Planning and Capturing Built Environments
Students capture an indoor location using scanning or photogrammetry techniques. Emphasis on framing, light consistency, and narrative potential.
SLOs included
- Display an understanding of the latest theories of Virtual Production environments.
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
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Mesh Processing and Cleanup for Production
Students process and clean captured data, generating geometry suitable for optimisation and reuse.
SLOs included
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Build a small digital asset.
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Optimisation and Retopology for Real-Time Integration
Focus on retopology, mesh decimation, UVs, and preparing captured assets for Unreal Engine with high performance.
SLOs included
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Build a small digital asset.
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Reconstructing Place in Unreal Engine
Students import assets into Unreal, apply lighting, composition, and create a short cinematic setup that mirrors the real-world location.
SLOs included
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
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Location Cinematic Submission
Students submit a short individual cinematic showcasing their reconstructed environment, with attention to lighting, camera, and mood.
SLOs included
- Display an understanding of the latest theories of Virtual Production environments.
- Build a small digital asset.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
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Concept Development and Team Roles
Students form groups, pitch creative ideas, and assign production roles. Concepts must integrate scanned and virtual elements, actor presence, and spatial logic.
SLOs included
- Display an understanding of the latest theories of Virtual Production environments.
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Creatively problem solve real-world Virtual Production issues.
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Storyboarding and Blocking for Blended Scenes
Teams storyboard and block their scene, planning for actor movement, camera transitions, and environment interaction across real/virtual space.
SLOs included
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
- Creatively problem solve real-world Virtual Production issues.
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Animation and Environmental Effects
Students animate scene components (e.g. props, lights, environmental FX) and begin layering screen effects (fog, LUTs, lens FX) to enhance cinematic tone.
SLOs included
- Build a small digital asset.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
- Creatively problem solve real-world Virtual Production issues.
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Actor Rehearsal and Performance Integration
Teams rehearse their scene with actors, aligning blocking, lighting, timing, and virtual scene playback. Camera and actor coordination is refined.
SLOs included
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
- Creatively problem solve real-world Virtual Production issues.
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Final Execution and Cinematic Polish
Students complete filming or rendering, incorporating animation, actor presence, and final visual effects for maximum impact.
SLOs included
- Build a small digital asset.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
- Creatively problem solve real-world Virtual Production issues.
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Group Screening and Reflective Documentation
Teams present their final scene. Each student reflects on their role, group collaboration, scene integration challenges, and final creative outcomes.
SLOs included
- Display an understanding of the latest theories of Virtual Production environments.
- Demonstrate competency in operating the basic tools of the software required for Virtual Production environments.
- Demonstrate understanding of how to build and blend a Virtual Production environment with real-world elements.
- Creatively problem solve real-world Virtual Production issues.