Virtual Production - People

General Information

This subject explores the current limits and latest workflows of screen storytelling with Virtual Production avatars. It delves into when you should use a digital actor, whether you can combine a digital performance with a live one and, what processes are involved. You will gain a deep understanding of the latest theories of virtual performance, develop competencies in the basic tools of operation, learn how to build and develop your own digital avatars, and creatively problem-solve real-world production issues.

  • Academic unit: Faculty of Society & Design
    Subject code: DIGM12-107
    Subject title: Virtual Production - People
    Subject level: Undergraduate
    Semester/Year: January 2026
    Credit points: 10.000
  • Timetable: https://bond.edu.au/timetable
    Delivery mode: Standard
    Workload items:
    • Personal Study Hours: x1 (Total hours: 72) - Recommended Study Hours
    • Forum: x12 (Total hours: 12) - Weekly Forum
    • Studio: x12 (Total hours: 36) - Weekly Studio
    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.
Academic unit: Faculty of Society & Design
Subject code: DIGM12-107
Subject title: Virtual Production - People
Subject level: Undergraduate
Semester/Year: January 2026
Credit points: 10.000

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.

Find your program

Subject Learning Outcomes (SLOs)

On successful completion of this subject the learner will be able to:

  1. Display an understanding of the latest theories of Virtual Production avatars.
  2. Demonstrate competency in operating the basic tools of the software required for Virtual Production avatars.
  3. Create a Virtual Production Avatar.
  4. Demonstrate understanding of how to blend animations with avatars to create convincing virtual actors.
  5. 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.

  • Type Task % Timing* Outcomes assessed AI category
    Creative Piece Assessment 1: Digital Human Performance: Students design and animate a custom MetaHuman avatar and deliver a short solo performance within a virtual environment. The scene should demonstrate expressive facial and body animation, lighting, and basic cinematic camera blocking. 30.00% Week 6 1, 2, 3, 4
    Project§ Assessment 2: Ensemble Hybrid Scene with LED and Avatars: In production teams, students plan, rehearse, and deliver a short cinematic scene combining animated MetaHuman avatars with a live actor performance on the LED stage. Teams must demonstrate interaction across real and virtual characters, effective scene blocking, animation blending, camera movement, and lighting integration. 40.00% Week 12 1, 2, 3, 4, 5
    Professionalism Participation and Studio Engagement: Assessed through weekly contribution to workshops, rehearsals, technical setup, peer feedback, and project development. Includes reflection and documentation of both individual progress and team collaboration. 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.

Type Task % Timing* Outcomes assessed AI category
Creative Piece Assessment 1: Digital Human Performance: Students design and animate a custom MetaHuman avatar and deliver a short solo performance within a virtual environment. The scene should demonstrate expressive facial and body animation, lighting, and basic cinematic camera blocking. 30.00% Week 6 1, 2, 3, 4
Project§ Assessment 2: Ensemble Hybrid Scene with LED and Avatars: In production teams, students plan, rehearse, and deliver a short cinematic scene combining animated MetaHuman avatars with a live actor performance on the LED stage. Teams must demonstrate interaction across real and virtual characters, effective scene blocking, animation blending, camera movement, and lighting integration. 40.00% Week 12 1, 2, 3, 4, 5
Professionalism Participation and Studio Engagement: Assessed through weekly contribution to workshops, rehearsals, technical setup, peer feedback, and project development. Includes reflection and documentation of both individual progress and team collaboration. 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.

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

Approved on: Oct 21, 2025. Edition: 1.3
Last updated: Oct 21, 2025