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Professional Doctorate Thesis - Physiotherapy (061701)

General Information

The Professional Doctorate of Physiotherapy at Bond University offers the opportunity for advanced application of evidence-based physiotherapy research and practice in the industry. Through engagement in a doctoral capstone experience, students will build upon the comprehensive clinical, business, and research skills developed during the Doctor of Physiotherapy program to design and implement an innovative and applied response to a current practice issue through doctoral-level research, contributing to the development of new knowledge in the field. Students will have the opportunity to collaborate and engage meaningfully with industry partners and experienced academic mentors to develop advanced skills and in-depth knowledge in their individual topic of interest in one or more areas, including clinical practice, leadership, program and policy development, advocacy, education, or theory development. The Professional Doctorate of Physiotherapy is a higher degree by research program awarded for a combination of coursework, clinical placement, and internship followed by a doctoral thesis.

In this Professional Doctorate Thesis subject, you will conduct a major, substantially original, theoretical or empirical study of an issue pertaining to your major field of study. Depending on the field of specialisation, you will write a 60,000-word thesis. The thesis may incorporate articles ready for submission or already published in peer reviewed journals or equivalent outputs, demonstrating contribution to new knowledge in the field.

 

  • Academic unit: Faculty of Health Sciences and Medicine
    Subject code: HLSC99-525
    Subject title: Professional Doctorate Thesis - Physiotherapy (061701)
    Subject level: Doctoral Major Thesis
    Semester/Year: September 2026
    Credit points: 0.000
  • Timetable: https://bond.edu.au/timetable
    Delivery mode: Standard
    Workload items:
    Attendance and learning activities:
  • 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 Health Sciences and Medicine
Subject code: HLSC99-525
Subject title: Professional Doctorate Thesis - Physiotherapy (061701)
Subject level: Doctoral Major Thesis
Semester/Year: September 2026
Credit points: 0.000

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.

Restrictions:

Refer to Faculty

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. Apply substantial knowledge of research principles and methods to investigate and contribute to developing new knowledge in one or more areas of professional practice in physiotherapy.

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
    Thesis^ For this task students will write a 60,000 word thesis C In Consultation 1
    Oral Assessment^ For this task students will participate in a VIVA VOCE C In Consultation 1
    • ^ Students must pass this assessment to pass the subject
    • * 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.

    Pass requirement

    Students must attempt and pass all assessment items to pass this subject. If eligible, a reassessment opportunity will be scheduled and conducted as soon as practicable after all of the summative assessments have been completed.

  • Assessment criteria

    Pass Usually awarded to students whose performance meets the requirements set for work provided for assessment.
    Fail 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
Thesis^ For this task students will write a 60,000 word thesis C In Consultation 1
Oral Assessment^ For this task students will participate in a VIVA VOCE C In Consultation 1
  • ^ Students must pass this assessment to pass the subject
  • * 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.

Pass requirement

Students must attempt and pass all assessment items to pass this subject. If eligible, a reassessment opportunity will be scheduled and conducted as soon as practicable after all of the summative assessments have been completed.

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 the total marks available for the 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.

Additional subject information

Subject curriculum

A detailed curriculum has not been published for this subject.

Approved on: Jun 26, 2026. Edition: 1
Last updated: Jul 15, 2026