This course aims to provide students with the knowledge and skills necessary to successfully undertake information systems analysis. The course provides coverage of the concepts, skills, methodologies, techniques, tools and perspectives considered essential for systems analysts working with modern information systems and their development.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Explain the organizational context in which information systems development is undertaken;
2. Explain basic systems theory and the role of the systems analyst;
3. Model the systems analysis and development process;
4. Elicit information system requirements;
5. Construct process, logic, and data models using traditional modelling techniques;
6. Communicate an understanding of basic object-oriented modelling using UML;
7. Communicate an understanding of “soft systems” aspects and techniques in systems analysis; and
8. Apply principled investigation and ethical judgment in systems analysis, consistent with the ACS Code of Ethics.

Research-Led Teaching

This course has readings that are a mix of research and industry publications that cover both theoretical concepts and practical application of the

content.

Field Trips

Not relevant

Additional Course Costs

No additional cost

Examination Material or equipment

There will be a centrally timetabled, invigilated exam. Further advice to be provided by Week 12.

Required Resources

Kendall, K. & Kendall, J. (2019) Systems Analysis and Design, Global Edition, Prentice-Hall, ISBN 9781292281452

Read Online options are available in ANU Library

Staff Feedback

Students will be given feedback in the following forms in this course:

• Written comments
• Verbal comments
• Feedback to the whole class, to groups, to individuals, focus groups

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Lecture - Week 1: Course Administration & Introduction to Systems Analysis	Read Chapter 1 of text and lecture notes Week 1
2	Lecture - Week 2: Elements of Systems Theory & Concepts of Information	Read lecture notes Week 2
3	Lecture - Week 3: Project Selection, Feasibility and Management	Read Chapter 1 of text, lecture notes Week 1 & 2, do assessment work for Assignment 1
4	Lecture - Week 4: “Soft” Techniques	Read lecture notes Week 4
5	Lecture - Week 5: Requirements Determination	Read Chapters 4 & 5 of text & lecture notes Week 5, do assessment work for Major Project Assignment 2.1
6	Lecture - Week 6: Process Modelling	Read Chapter 7 of text & lecture notes Week 6
7	Lecture - Week 7: Process and Logic Modelling	Read Chapter 7 & 9 of text, lecture notes Weeks 6 & 7, do assessment work for Major Project Assignment 2.2.
8	Lecture - Week 8: Data (Entity-Relationship) Modelling - Part 1	Read Chapter 8 of text and lecture notes Week 8
9	Lecture - Week 9: Data (Entity-Relationship) Modelling - Part 2	Read Chapter 8 of text & lecture notes Weeks 8 & 9, do assessment work for Major Project Assignment 2.3.
10	Lecture - Week 10: Object-oriented analysis & UML - Part 1	Read Chapter 2 & begin reading Chapter10 of text & lecture slides Week 10, do assessment work for Major Project Assignment 2.4.
11	Lecture - Week 11: Object-oriented analysis & UML - Part 2	Continue reading Chapter 10 of text & lecture slides Week 11, do assessment work for Major Project Assignment 2.5.
12	Lecture - Week 12: Moving from Analysis to Design & System Development Methodologies	Re-read Chapter 2 & Chapter 6, do assessment work for Assignment 3.
13	End of Semester Examination Period	do study for Assignment 4 (Final Examination)

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. A Zoom tutorial or a pre-recorded tutorial will be available for all students.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Major Project Proposal & Ethics (Individual - 10%)	10 %	14/08/2026	31/08/2026	1,2,3,4,5,6,7
Major Project Assignments (Individual - 45%)	45 %	*	*	1,2,3,4,5,6,7
Reflection (Individual - 5%)	5 %	30/10/2026	13/11/2026	1,2,3,4,5,6,7
Final Examination (Individual - 40%)	40 %	*	*	1,2,3,4,5,6,7

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Policy and General Information
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Please note that lecture slides and readings for each lecture will be uploaded on Canvas on weekly basis. Students are advised to read them before the lecture.

Weekly lecture will be two hours long, while each tutorial will be an hour long. 

Attendance at lectures and tutorials, while not compulsory, is expected in line with 'Code of Practice for Teaching and learning", clause 2 paragraph (b)

Examination(s)

There will be a centrally timetabled, invigilated exam. Further advice to be provided by Week 12.

Assessment Task 1

Major Project Proposal & Ethics (Individual - 10%)

The Assessment Task 1:

The Assessment Task 1 (i.e., Assignment 1: Major Project Proposal & Ethics) work comprises 10% of the final course mark.

Assignment 1 is designed to serve two complementary purposes. First, it assesses students' understanding and application of key concepts, techniques, and ethical considerations introduced during the first three weeks of the course. Second, it supports students in making an informed and well-justified selection of a topic for their five major project assignments (see Assessment Task 2), which constitutes 45% of the overall course grade.

As part of this assessment, students are required to identify and propose two potential project topics. For each topic, they must provide relevant organisational background information and a clear rationale explaining why the topic is suitable and worthy of investigation.

The students will receive feedback on the two topics before committing to a final project direction. This early feedback process is intended to improve topic selection, enhance project feasibility, and provide a stronger foundation for the subsequent major project assignments.

Assessment Criteria:

Each Part within the assignment will be assessed independently using the 0–4 performance descriptors below. Rather than a single fixed mark, each descriptor corresponds to a range of marks, expressed as a percentage of the marks allocated to that Part. Markers will award a specific mark within the corresponding range based on the demonstrated quality of the work. The overall assignment mark will be the sum of the marks awarded across all Parts. Because each Part carries its own mark allocation, Parts with a higher mark allocation contribute proportionally more to the overall assignment mark.

For each Part of the Assessment Task submission:

• 4 (80–100%) = Attempted, and the quality of the work is, on the whole, excellent. Concepts, techniques, and notations are applied correctly and with sophistication. Analysis is well-reasoned, justified, and demonstrates independent thinking beyond the minimum required. Work is complete, accurate, and professionally presented. No errors.
• 3 (70–79%) = Attempted, and the quality of the work is, on the whole, good. Concepts and techniques are applied correctly in most instances. Analysis is generally sound and supported with adequate reasoning. Work is substantially complete with one error or omission at most.
• 2 (60–69%) = Attempted, but the quality of the work does not significantly exceed a barely acceptable standard. Some concepts or techniques are applied with reasonable accuracy, but gaps, errors, or insufficient justification are evident across the submission, with 2–4 errors.
• 1 (50–59%) = Attempted, but contains several flaws in the application of concepts, reasoning, or the quality of work. The work demonstrates a minimally acceptable, pass-level understanding, with errors or omissions evident throughout.
• 0 (0–49%) = Not attempted, or the submitted work contains significant or serious flaws in the application of concepts, reasoning, or the quality of deliverables such that it falls below a pass-level standard (up to 49%, reflecting the extent to which any requirement was met).

Important notes for students:

• Detailed written feedback will not be provided on every submission. You are expected to seek and obtain this feedback yourself through lecture discussions, tutorials, and consultation opportunities.
• The rating for each Part reflects the overall quality of your demonstrated understanding of ethical considerations, IS analysis concepts, techniques, and professional practice as taught in this course, applied to that Part.
• A rating of 4 represents full achievement of the expected standard for a Part. Lower ratings indicate progressively lower levels of achievement. Within each rating band, the specific mark awarded reflects where your work sits relative to the expectations of that band, with the resulting marks allocated proportionally according to the Part's weighting.

Once the assessment has been marked, results will be released via the gradebook feature on Canvas.

Mandatory Assessment

Consider the assignment as being mandatory (i.e. submission is expected), but non-submission of the assignment will not result in a grade of NCN.

All students will receive feedback on this assessment by Monday, Week 6.

Release & Due Dates:

Assignment 1. Major Project Proposal & Ethics

• Release date: 08 August 2026
• Due date: 14 August 2026 @ 10:00 Canberra Time

Use of Artificial Intelligence (AI): Students are welcome to use generative AI tools (e.g. GPT-4, DALL-E, Copilot) and other tools (e.g. Grammarly) to support their learning in a way that is consistent with the ANU Academic Integrity principles for use of GenAI. As such, please be aware of the following additional conditions for this assessment task:

• Clearly acknowledge the use of Artificial Intelligence in the relevant parts of the assessment task

Submit the deliverable in a format that preserves ‘tracked changes’ (e.g. MS Word, Apple Pages, or similar) that shows the progression of academic effort and contribution towards completing the task.

Form of Submission

For the assignment, your submission MUST include the following three components:

• (1). Following declaration:
• "I declare that this work:
• is original, except where collaboration (for example, group work) has been authorised in writing by the course convenor in the course outline and/or Canvas site;
• is produced for the purposes of this assessment task and has not been submitted for assessment in any other context, except where authorised in writing by the course convener;
• gives appropriate acknowledgement of the ideas, scholarship and intellectual property of others insofar as these have been used;
• in no part involves copying, cheating, collusion, fabrication, plagiarism or recycling.”
• (2). 'Tracked changes' version of the assignment. This version should capture your editing history and progression—including how you have interacted with, refined, or built upon content generated by AI tools.
• (3). Polished version of the assignment (i.e., without tracked changes)

Only submissions in Microsoft Word format (e.g., .doc or .docx) with Tracked Changes enabled will be accepted. Please keep a copy of the submitted work for your records. Unless specifically noted in the instructions, handwritten work will not be accepted or, if submitted, will not be marked. The expected length of the polished version will be mentioned in the description of the assignment.

Failure to include any of the three required components (the declaration form, the tracked-changes version, and the polished version) will result in a mark of zero. Students are responsible for ensuring that all components are submitted together in a single document; page limits apply only to the polished version.

Extension requests.

Extensions may be granted in extenuating circumstances where relevant supporting documentation is provided and the lecturer is notified in a timely manner. Late submissions are accepted but will incur a penalty of 5% per business day unless an extension has been formally approved. Submissions more than 10 business days late will receive zero marks.    

Assessment Task 2

Major Project Assignments (Individual - 45%)

The Assessment Task 2:

The Assessment Task 2 is comprised of five sequentially structured, equally weighted assignments and carries 45% of the student's final mark. Each assignment of this assessment task addresses a distinct aspect of systems analysis as applied to a topic of the student's choosing. Taken together, these assignments are designed to guide students through the progressive application of systems analysis concepts and techniques to their chosen topic, with each assignment building on the work completed in the previous stage.

Early in the course, students will have the opportunity to propose and present two candidate topics, on which they will receive feedback. Based on this feedback, each student will select one topic to carry forward as the focus of their five major project assignments. This process ensures that students enter the substantive assignment work with a well-considered and academically appropriate topic.

Each assignment is structured into a number of Parts, and students should note that individual Parts within an assignment may carry different mark allocations. These weightings reflect the relative importance and expected level of effort for each Part. Students are expected to apportion their effort accordingly. A "Part" refers to a component within an individual assignment and is distinct from Assessment Task 2 as a whole, which comprises all five assignments.

All five assignments are assessed using the following rating criteria, applied independently to each Part. Students are encouraged to read the assessment criteria carefully and to seek feedback through lectures, tutorials, and consultation opportunities as they progress through each assignment.

Assessment Criteria:

Each Part within an assignment will be assessed independently using the 0–4 performance descriptors below. Rather than a single fixed mark, each descriptor corresponds to a range of marks, expressed as a percentage of the marks allocated to that Part. Markers will award a specific mark within the corresponding range based on the demonstrated quality of the work. The overall assignment mark will be the sum of the marks awarded across all Parts. Because each Part carries its own mark allocation, Parts with a higher mark allocation contribute proportionally more to the overall assignment mark.

For each Part within each Assessment Task submission:

• 4 (80–100%) = Attempted, and the quality of the work is, on the whole, excellent. Concepts, techniques, and notations are applied correctly and with sophistication. Analysis is well-reasoned, justified, and demonstrates independent thinking beyond the minimum required. Work is complete, accurate, and professionally presented. No errors.
• 3 (70–79%) = Attempted, and the quality of the work is, on the whole, good. Concepts and techniques are applied correctly in most instances. Analysis is generally sound and supported with adequate reasoning. Work is substantially complete with one error or omission at most.
• 2 (60–69%) = Attempted, but the quality of the work does not significantly exceed a barely acceptable standard. Some concepts or techniques are applied with reasonable accuracy, but gaps, errors, or insufficient justification are evident across the submission, with 2–4 errors.
• 1 (50–59%) = Attempted, but contains several flaws in the application of concepts, reasoning, or the quality of work. The work demonstrates a minimally acceptable, pass-level understanding, with errors or omissions evident throughout.
• 0 (0–49%) = Not attempted, or the submitted work contains significant or serious flaws in the application of concepts, reasoning, or the quality of deliverables such that it falls below a pass-level standard (up to 49%, reflecting the extent to which any requirement was met).

Important notes for students:

• Detailed written feedback will not be provided on every submission. You are expected to seek and obtain this feedback yourself through lecture discussions, tutorials, and consultation opportunities.
• The rating for each Part reflects the overall quality of your demonstrated understanding of IS analysis concepts, techniques, and professional practice as taught in this course, applied to that Part.
• A rating of 4 represents full achievement of the expected standard for a Part. Lower ratings indicate progressively lower levels of achievement. Within each rating band, the specific mark awarded reflects where your work sits relative to the expectations of that band, with the resulting marks allocated proportionally according to the Part's weighting.

Once the assessment has been marked, results will be released via the gradebook feature on Canvas.

Mandatory Assessment

Consider all assignments as being mandatory (i.e. submission is expected), but non-submission of an assignment will not result in a grade of NCN.

Release & Due Dates:

Assignment 2.1. Systems diagram & requirements analysis

• Release date: 17 August 2026
• Due date: 01 September 2026 @ 23:59 Canberra Time

Assignment 2.2.

• Release date: 14 September 2026
• Due date: 29 September 2026 @ 23:59 Canberra Time

Assignment 2.3.

• Release date: 28 September 2026
• Due date: 13 October 2026 @ 23:59 Canberra Time

Assignment 2.4.

• Release date: 05 October 2026
• Due date: 20 October 2026 @ 23:59 Canberra Time

Assignment 2.5.

• Release date: 12 October 2026
• Due date: 27 October 2026 @ 23:59 Canberra Time

Use of Artificial Intelligence (AI): Students are welcome to use generative AI tools (e.g. GPT-4, DALL-E, Copilot) and other tools (e.g. Grammarly) to support their learning in a way that is consistent with the ANU Academic Integrity principles for use of GenAI. As such, please be aware of the following additional conditions for this assessment task:

• Clearly acknowledge the use of Artificial Intelligence in the relevant parts of the assessment task

Submit the deliverable in a format that preserves ‘tracked changes’ (e.g. MS Word, Apple Pages, or similar) that shows the progression of academic effort and contribution towards completing the task.

Form of Submission

For the assignment, your submission MUST include the following three components:

• (1). Following declaration:
• "I declare that this work:
• is original, except where collaboration (for example, group work) has been authorised in writing by the course convenor in the course outline and/or Canvas site;
• is produced for the purposes of this assessment task and has not been submitted for assessment in any other context, except where authorised in writing by the course convener;
• gives appropriate acknowledgement of the ideas, scholarship and intellectual property of others insofar as these have been used;
• in no part involves copying, cheating, collusion, fabrication, plagiarism or recycling.”
• (2). 'Tracked changes' version of the assignment. This version should capture your editing history and progression—including how you have interacted with, refined, or built upon content generated by AI tools.
• (3). Polished version of the assignment (i.e., without tracked changes)

Only submissions in Microsoft Word format (e.g., .doc or .docx) with Tracked Changes enabled will be accepted. Please keep a copy of the submitted work for your records. Unless specifically noted in the instructions, handwritten work will not be accepted or, if submitted, will not be marked. The expected length of the polished version will be mentioned in the description of the assignment.

Failure to include any of the three required components (the declaration form, the tracked-changes version, and the polished version) will result in a mark of zero. Students are responsible for ensuring that all components are submitted together in a single document; page limits apply only to the polished version.

Extension requests.

Extensions may be granted in extenuating circumstances where relevant supporting documentation is provided and the lecturer is notified in a timely manner. Late submissions are accepted but will incur a penalty of 5% per business day unless an extension has been formally approved. Submissions more than 10 business days late will receive zero marks.

Assessment Task 3

Reflection (Individual - 5%)

Assessment Task 3:

In the Assessment Task 3 (i.e., Assignment 3: Course Reflection), the students are to reflect on their analysis work and discuss what they learned about the analysis process, as well as any difficulties they faced and how they overcame them, and any other interesting points that emerged from their assignment work. Students are also to include their thoughts on the value of the course (e.g., lectures, tutorials, learning activities, individual and group exercises, etc), and any way(s) in which they think it could be improved. Further information on the required components of this assignment will be provided in the second half of the semester.

Assessment Criteria:

Each Part within an assignment will be assessed independently using the 0–4 performance descriptors below. Rather than a single fixed mark, each descriptor corresponds to a range of marks, expressed as a percentage of the marks allocated to that Part. Markers will award a specific mark within the corresponding range based on the demonstrated quality of the work. The overall assignment mark will be the sum of the marks awarded across all Parts. Because each Part carries its own mark allocation, Parts with a higher mark allocation contribute proportionally more to the overall assignment mark.

For each Part of the Assessment Task submission:

• 4 (80–100%) = Attempted, and the quality of the work is, on the whole, excellent. Concepts, techniques, and notations are applied correctly and with sophistication. Analysis is well-reasoned, justified, and demonstrates independent thinking beyond the minimum required. Work is complete, accurate, and professionally presented. No errors.
• 3 (70–79%) = Attempted, and the quality of the work is, on the whole, good. Concepts and techniques are applied correctly in most instances. Analysis is generally sound and supported with adequate reasoning. Work is substantially complete with one error or omission at most.
• 2 (60–69%) = Attempted, but the quality of the work does not significantly exceed a barely acceptable standard. Some concepts or techniques are applied with reasonable accuracy, but gaps, errors, or insufficient justification are evident across the submission, with 2–4 errors.
• 1 (50–59%) = Attempted, but contains several flaws in the application of concepts, reasoning, or the quality of work. The work demonstrates a minimally acceptable, pass-level understanding, with errors or omissions evident throughout.
• 0 (0–49%) = Not attempted, or the submitted work contains significant or serious flaws in the application of concepts, reasoning, or the quality of deliverables such that it falls below a pass-level standard (up to 49%, reflecting the extent to which any requirement was met).

Important notes for students:

• Detailed written feedback will not be provided on every submission. You are expected to seek and obtain this feedback yourself through lecture discussions, tutorials, and consultation opportunities.
• The rating for each Part reflects the overall quality of your demonstrated understanding of IS analysis concepts, techniques, and professional practice as taught in this course, applied to that Part.
• A rating of 4 represents full achievement of the expected standard for a Part. Lower ratings indicate progressively lower levels of achievement. Within each rating band, the specific mark awarded reflects where your work sits relative to the expectations of that band, with the resulting marks allocated proportionally according to the Part's weighting.

Once the assessment has been marked, results will be released via the gradebook feature on Canvas.

Mandatory Assessment

Consider the assignment as being mandatory (i.e. submission is expected), but non-submission of the assignment will not result in a grade of NCN.

Release & Due Dates:

Assignment 3: Course Reflection

• Release date: 19 October 2026
• Due date: 30 October 2026 @ 23:59 Canberra Time

Use of Artificial Intelligence (AI): Students are welcome to use generative AI tools (e.g. GPT-4, DALL-E, Copilot) and other tools (e.g. Grammarly) to support their learning in a way that is consistent with the ANU Academic Integrity principles for use of GenAI. As such, please be aware of the following additional conditions for this assessment task:

• Clearly acknowledge the use of Artificial Intelligence in the relevant parts of the assessment task

Submit the deliverable in a format that preserves ‘tracked changes’ (e.g. MS Word, Apple Pages, or similar) that shows the progression of academic effort and contribution towards completing the task.

Form of Submission

For the assignment, your submission MUST include the following three components:

• (1). Following declaration:
• "I declare that this work:
• is original, except where collaboration (for example, group work) has been authorised in writing by the course convenor in the course outline and/or Canvas site;
• is produced for the purposes of this assessment task and has not been submitted for assessment in any other context, except where authorised in writing by the course convener;
• gives appropriate acknowledgement of the ideas, scholarship and intellectual property of others insofar as these have been used;
• in no part involves copying, cheating, collusion, fabrication, plagiarism or recycling.”
• (2). 'Tracked changes' version of the assignment. This version should capture your editing history and progression—including how you have interacted with, refined, or built upon content generated by AI tools.
• (3). Polished version of the assignment (i.e., without tracked changes)

Only submissions in Microsoft Word format (e.g., .doc or .docx) with Tracked Changes enabled will be accepted. Please keep a copy of the submitted work for your records. Unless specifically noted in the instructions, handwritten work will not be accepted or, if submitted, will not be marked. The expected length of the polished version will be mentioned in the description of the assignment.

Failure to include any of the three required components (the declaration form, the tracked-changes version, and the polished version) will result in a mark of zero. Students are responsible for ensuring that all components are submitted together in a single document; page limits apply only to the polished version.

Extension requests.

Extensions may be granted in extenuating circumstances where relevant supporting documentation is provided and the lecturer is notified in a timely manner. Late submissions are accepted but will incur a penalty of 5% per business day unless an extension has been formally approved. Submissions more than 10 business days late will receive zero marks.

Assessment Task 4

Final Examination (Individual - 40%)

There will be a closed-book, centrally timetabled, invigilated final examination for this course. Only permitted material will be one A4 sheet with handwritten notes on one side.

The three-hour final examination will primarily assess your comprehensive understanding of Intelligent Business Analysis: Models, Processes and Techniques using a case study–based format. You will be required to analyse the case study, develop appropriate diagrams and models, and respond to a range of questions assessing your technical knowledge and critical thinking skills. In addition, the examination may include questions that are not directly related to the case study but assess your ability to apply concepts, analyse scenarios, and make informed decisions based on your learning across all lectures. The questions are designed to evaluate analytical capability and practical systems analysis skills, requiring synthesis and application of knowledge rather than reproduction of course content.

Due Date

The exam will be held during the examination period. Further details will be provided during the semester.

Form of Submission

Students will be given the question paper and an answer book at the start of the centrally invigilated exam.

They are to provide their answers in the answer book and hand them over to the invigilators when finished.

This examination will be closed-book. Students are permitted to bring one A4 sheet of notes, handwritten notes on one side only.

You should not assume that the ability to bring a notes sheet will make the examination straightforward. The examination is designed to assess your understanding and application of course concepts rather than your ability to recall information verbatim. In particular:

• The questions will not be of a type where answers can be directly copied from notes.
• Many questions will require independent reasoning, such as case analysis and the creation or interpretation of models.
• Effective performance will depend on prior understanding of the material, as there will be insufficient time to rely on notes to learn concepts during the exam.
• Accordingly, thorough preparation and conceptual understanding are essential for success.

More information on the examination will be made available on Canvas at least 2 weeks before the examination period.

Marking criteria and Rubrics will be made available on Canvas two weeks prior to Week 1 of the semester.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. 

Hardcopy Submission

No hardcopy submissions will be required for this course.

Late Submission

Late submissions of non-exam assessment are accepted but will incur a penalty of 5% per business day unless an extension has been formally approved. Submissions more than 10 business days late will receive zero marks.

All requests for Assessment Adjustment (including Requests for Extension and for Consideration of Extenuating Circumstances) should be submitted via ANUHub.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Please see relevant assessment task detail above. All assignments will be marked and where appropriate feedback will be provided either: in class, or in person by appointment with the course lecturer, or via the course Canvas site.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Unless specified otherwise in the assignment requirements, resubmissions are permitted up until the due date and time, but not allowed afterwards. 

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information. In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service — including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy. If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes. Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students