Digital Design and Intelligent Construction

General Information

This subject introduces the evolving trends and technologies that are challenging the traditional methods that constitute architectural and construction practices. Through a combination of lectures, workshops, guest speakers, field visits, and case studies, this subject will facilitate critical thinking about how emerging technologies can be meaningfully deployed in the built environment industries. Case studies of international firms and projects that exemplify new approaches shall be highlighted and examined. Principles and concepts to be introduced include information modelling, lean production, products of service, life cycle analysis, technical nutrients, embodied energy, off-site manufacturing, design for manufacture, blockchains, digital twins, mass customisation, and augmented reality.

  • Academic unit: Faculty of Society & Design
    Subject code: ARCH71-139
    Subject title: Digital Design and Intelligent Construction
    Subject level: Postgraduate
    Semester/Year: September 2022
    Credit points: 10.000
  • Timetable: https://bond.edu.au/timetable
    Delivery mode: Standard
    Workload items:
    • Seminar: x9 (Total hours: 27) - Seminar (Weeks 1-5, 7-8, 11-12)
    • Field Trip: x1 (Total hours: 4) - Field Trip (Week 6)
    • Workshop: x2 (Total hours: 12) - Workshop (Weeks 9-10)
    • Personal Study Hours: x12 (Total hours: 77) - Personal study hours
    Attendance and learning activities: Practical workshop – compulsory attendance; interdisciplinary group activity.
  • Prescribed resources:

    Books

    • Phil Bernstein (2018). Practice Competency in the Era of Computation. n/a, Birkhauser Verlag GmbH
    • McDonough, William and Braungart, Michael (2002). Cradle to Cradle: Remaking the Way We Make Things. n/a, New York : North Point Press 92-117
    • Kieran, Stephen and Timberlake, James (2004). Refabricating architecture : how manufacturing methodologies are poised to transform building construction. n/a, McGraw-Hill
    • Scott Marble (2013). Digital Workflows in Architecture. n/a, Walter de Gruyter 288
    • Randy Deutsch (2017). Convergence. n/a, John Wiley & Sons 240

    Journals

    • Hongxi Yin, Ming Qu, Haiyan Zhang & YeChan Lim (2018). 3D Printing and Buildings: A Technology Review and Future Outlook. TAD: Technology Architecture Design 94-111 Available at: https://doi.org/10.1080/24751448.2018.1420968
    • Knapp (2013). The Hand and the Machine. Proceedings of the 2013 CAADRIA Conference
    • Aitchison (2018). A House is Not a Car (Yet). Journal of Architectural Education
    After enrolment, students can check the Books and Tools area in iLearn for the full Resource List.
    iLearn@Bond & Email: iLearn@Bond is the online learning environment at Bond University and is used to provide access to subject materials, lecture 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
Academic unit: Faculty of Society & Design
Subject code: ARCH71-139
Subject title: Digital Design and Intelligent Construction
Subject level: Postgraduate
Semester/Year: September 2022
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.

General understanding of construction procurement strategies and awareness of conventional construction systems.
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. Understand the different types and classifications of information systems and fundamentals of data modelling management and information extraction.
  2. Analyse predominant procurement methods for construction and evaluate the factors and opportunities to implement new procurement methods.
  3. Assess and explain how stakeholder values in the lifespan of a project are transferred and translated.
  4. Apply and carry out basic operations of digital fabrication and computer aided assembly processes as they might be used in actual application in construction.
  5. Construct and compose graphic and written interpretation of cutting-edge industry exemplars.

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
    Exercise Reflective Exercise 30% Week 1 1,2,3
    Paper-based Test (Limited Open) In-class Quiz 30% Week 8 1,2,3
    Case Analysis§ Case analysis and presentation 40% Week 12 1,2,3,4,5
    • § 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.

  • 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
Exercise Reflective Exercise 30% Week 1 1,2,3
Paper-based Test (Limited Open) In-class Quiz 30% Week 8 1,2,3
Case Analysis§ Case analysis and presentation 40% Week 12 1,2,3,4,5
  • § 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.

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 student who has not established a basis for an extension in compliance with University and Faculty policy either by 1) not applying before the assessment due date or 2) by having an application rejected due to failure to show a justifiable cause for an extension, will receive a penalty on assessment submitted after its due date. The penalty will be 10% of marks awarded to that assessment for every day late, with the first day counted after the required submission time has passed. No assessment will be accepted for consideration seven calendar days after the due date. Where a student has been granted an extension, the late penalty starts from the new due date and time set out in the extension.

Academic Integrity

The University’s Academic Integrity Policy defines plagiarism as the act of misrepresenting as one’s own original work: another’s ideas, interpretations, words, or creative works; and/or one’s own previous ideas, interpretations, words, or creative work without acknowledging that it was used previously (i.e., self-plagiarism). The University considers the act of plagiarising to be a breach of the Student Conduct Code and, therefore, subject to the Discipline Regulations which provide for a range of penalties including the reduction of marks or grades, fines and suspension from the University.

Bond University utilises Originality Reporting software to inform academic integrity.

Feedback on assessment

Feedback on assessment will be provided to students within two weeks of the assessment submission due date, as per the Assessment Policy.

Accessibility and Inclusion Support

If you have a disability, illness, injury or health condition that impacts your capacity to complete studies, exams or assessment tasks, it is important you let us know your special requirements, early in the semester. Students will need to make an application for support and submit it with recent, comprehensive documentation at an appointment with a Disability Officer. Students with a disability are encouraged to contact the Disability Office at the earliest possible time, to meet staff and learn about the services available to meet your specific needs. Please note that late notification or failure to disclose your disability can be to your disadvantage as the University cannot guarantee support under such circumstances.

Additional subject information

Subject curriculum

Approved on: Jul 5, 2022. Edition: 1.6
Last updated: Oct 24, 2022
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