In environment and sustainability fields, research plays a major role in identifying the response of human and natural systems to spatial and temporal differences, disturbances and management actions. Achieving these research outcomes relies upon establishing research questions and testable hypotheses, applying appropriate data collection and analysis methods, critically assessing results, and effectively communicating the observations. That process is common to all science-based disciplines.

ENVS1003 uses a PPDAC (Problem, Plan, Data, Analysis, Conclusion) cycle to introduce fundamental research concepts. You can expect to develop skills in ecological measurement and sampling, and designing and conducting surveys and experiments. You will also develop analytical skills, including data exploration and effective communication and analysis techniques common to all sciences. The course promotes learning through a combination of lectures, and field-/computer-based practical exercises. During field-based exercises you will gain first-hand experience in collecting ecological and social data.

Honours Pathway Option

This course participates in the Honours Pathway option run by the College of Science. Further information and expressions-of-interest will be provided at the commencement of the semester.

Learning Outcomes

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

1. Demonstrate conceptual understanding of inferential statistics and hypothesis testing.
2. Interpret quantitative research results reported within scientific literature.
3. Summarise data to identify effects and trends.
4. Demonstrate understanding of experimental and research design.
5. Apply the principles of sampling techniques in the environmental and social sciences.
6. Demonstrate a capacity to communicate research results effectively.

Research-Led Teaching

This is fundamentally research based and actively engages students in the conduct of research. The course uses a PPDAC framework throughout with the goal of adding new data and understanding to the body of knowledge associated with Ogmograptis moths. Through delivered content, field activities and assessment tasks, this course aims to embed students within a genuine research practice. In addition, this course includes content that reflects the nature of the Fenner School or Environment and Society. That is, content is delivered within disciplinary fields and current research activities relevant to the course convenorship. That is, learning is founded upon inquiry-based learning and encouraging students to act as researchers. To achieve this, research forms part of learning activities; students contribute to collection of genuine research data and analysis of those data.

Field Trips

Field trips to the Canberra Nature Park, particularly Galambary/Black Mountain Nature Reserve, will occur during scheduled practical times.

Additional Course Costs

No additional costs.

Examination Material or equipment

An undergraduate examination of entire course content focussed on understanding principles and interpreting results will be held during the University’s end-of-semester examination period. In addition to short-answer questions, participants must reflect upon results of analyses conducted during the last week of teaching. The examination will be conducted via Canvas.

Required Resources

No special resources are required.

Recommended Resources

Learning in this course is supported by a set of recommended reading. All referenced texts are accessible via the Readings list the course Canvas site.

The course makes use of JMP and Excel for data analysis and to support learning. JMP has an excellent user interface and reports statistics in a fashion that is both comprehensive and comprehensible. Course participants will receive direct instruction in use of the program. JMP is free to all staff and students via https://www.jmp.com/en/academic/jmp-student-edition. Instructions on creating a MyJMP account, downloading and installing JMP, and using the program are available on the course Wattle site.

Recommended student system requirements 

ANU courses commonly use a number of online resources and activities including:

• video material, similar to YouTube, for lectures and other instruction
• two-way video conferencing for interactive learning
• email and other messaging tools for communication
• interactive web apps for formative and collaborative activities
• print and photo/scan for handwritten work
• home-based assessment.

To fully participate in ANU learning, students need:

• A computer or laptop.
• Webcam
• Speakers and a microphone (e.g. headset)
• Reliable, stable internet connection. Broadband recommended. If using a mobile network or wi-fi then check performance is adequate.
• Suitable location with minimal interruptions and adequate privacy for classes and assessments.
• Printing, and photo/scanning equipment

For more information please see https://www.anu.edu.au/students/systems/recommended-student-system-requirements

Staff Feedback

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

• Written comments, marked rubrics and verbal discussion on assignments;
• Verbal feedback to the whole class on field exercises, data outcomes, analysis tasks, quiz answers exercises and on assignments;
• General online feedback on quizzes
• Additional, individual feedback on request.

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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Honours-Pathway and Advanced-Studies (HP/AS) activities, comprising active research opportunities conducted under direct supervision of the course convener, complement the content delivered in this course. Students wishing to participate in HP/AS activities must express their interest within the first two weeks of the semester.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Students should refer to the Canvas site for a detailed weekly schedule of teaching activities including all readings. Lectures Introduction and Ogmograptis Galambary/Black Mountain Practical Independent measurement task	Blue-gum data submission
2	Lectures Data and error Sampling and bias Practical Computer session: Data exploration
3	Lectures Quantitative summary Central limits theorem Practical Field measurement: Overstorey and scribbles (north v south)	Quiz 1: Description Post-practicum data submission
4	Lectures Confidence intervals: theory Confidence intervals: application Practical Computer session: Summarising diameter data
5	Lectures Experimental design I Experimental design II Practical Computer session: Field measurement: Overstorey and scribbles (western face)	Quiz 2: Inference Post-practicum data submission
6	Lectures Hypothesis tests Fisher's protocol Practical Computer session: One-sample and paired two-sample hypothesis testing
7	Lectures The problem with normality Rescaling data Practical Computer session: Field measurement: Overstorey and scribbles (lower slopes)	Quiz 3: Hypothesis testing Post-practicum data submission
8	Lectures Independent two-sample hypothesis testing: theory Independent two-sample hypothesis testing: application Practical Computer session: Two-sample hypothesis testing
9	Lectures ANOVA: theory ANOVA: application Practical Computer session: ANOVA and anthropoda	Quiz 4: Two-sample tests
10	Lectures Non-parametric comparison and x²: theory x² and contingency: application Practical Computer session: Research-proposal support
11	Lectures Linear association: theory The limits of hypothesis testing Practical Computer session: x², association and experimental-effects summary	Quiz 5: Effects and relations
12	Lecture Non-parametrics and p	Research proposal and interview

Tutorial Registration

This course includes weekly 3-hour practical sessions. These sessions connect measurement and data-analysis theory with practice. Registration is via MyTimetable.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Quiz - Description	10 %	09/08/2026	16/08/2026	1, 2
Quiz - Inference	10 %	23/08/2026	31/08/2026	1, 2, 3
Quiz - Hypothesis testing	10 %	20/09/2026	27/09/2026	1, 4, 5
Quiz - Differences	10 %	05/10/2026	11/10/2026	1, 2, 3
Quiz - Effects and association	10 %	25/10/2026	30/10/2026	1, 2, 3, 4
Data submissions	10 %	*	*	1, 2
Research proposal and interview	20 %	30/10/2026	14/11/2026	1, 2, 4, 5, 6
End-of-semester exam	20 %	*	*	1, 2, 3, 5, 6

* 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 Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

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 Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Canvas’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

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

Some practicals within this course will be conducted in field locations on Black Mountain. In-person participation is mandatory for all practical sessions

Examination(s)

This course includes a final examination conducted via Canvas

Please note, that where a date range is used in the Assessment Summary in relation to exams, the due date and return date indicate the approximate time-frame in which the exam will be held and results returned to the student (official end of Semester results released on ISIS). Students should consult the course Canvas site and the ANU final examination timetable to confirm the date, time and venue of the exam.

Assessment Task 1

Quiz - Description

Online quiz

Assessment Task 2

Quiz - Inference

Online quiz

Assessment Task 3

Quiz - Hypothesis testing

Online quiz

Assessment Task 4

Quiz - Differences

Online quiz

Assessment Task 5

Quiz - Effects and association

Online quiz

Assessment Task 6

Data submissions

Audits of primary field datasets collected in Weeks 3, 5 and 7 (scheduling weather dependent)

Assessment Task 7

Research proposal and interview

Black Mountain Nature Reserve (BMNR) is an important and well-known part of the Canberra Nature Park. Eucalyptus rossii (syn. E. racemosa ssp. rossii) is one of the best-known species within the reserve and is widely recognised for the scribbles present on the bark. These scribbles are common on stems of the species and are often used as a trait to distinguish the species from species similar in appearance (e.g., E. mannifera). Scribbles on E. rossii are the product of the larvae of a moth species (Ogmograptis racemosa). The literature that exists for Ogmograptis suggests scribbles are concentrated on the southern side of tree boles.

Although previously ubiquitous in BMNR, O. racemosa scribbles suddenly disappeared in 2020/21. Although they have re-accumulated, few prior data existed at the time, making it impossible to interpret the dynamics of scribbles and the moths that make them. Pook and Moore (1966) showed that aspect governs overstorey composition on Galambary and Cooke and Edwards (2007) described aspect-related patterning of scribbles within stems. While the former study used a systematic sample to understand aspects, the latter was based upon selective sampling. Neither study attempted to isolate the direct effect of abiotic variables. Thus, while Cooke and Edwards (2007) attributed scribble patterning to astronomical and meteorological phenomena, the actual impact of wind, temperature or another correlate of aspect remain untested. While experimental treatments might reveal insect behaviours, the cryptic nature of Ogmograptis makes that difficult. 

This semester's field measurement program aimed to break the impasse of understanding the drivers of scribble patterning. Our structured surveys across contrasting landscape positions and bole aspects recorded scribble occurrence, density and orientation alongside the site- and tree-level variables needed to interpret them. Your analysis throughout the semester has generated results that, although still restricted to a single location, offer a starting point to establish a pattern (or its absence), and point to, but not resolve, a possible driver.

Taking an intriguing element of your results as the PPDAC 'Problem' to be addressed, you must argue reasoning for the single most worthwhile question to ask next and set out an experimental - natural or designed - investigation that would address it.

 

From P to C: focusing on a single PPDAC question

This semester's field program was based around a broad set of questions focussed on the frequency and density of scribbles, their variation with aspect, dominance and landscape position, and the basis of their arrangement within a bole. Your proposal need not attempt that breadth. Rather it should focus on one. That is, you need to consider a single, specific, testable question that your own results now make worth asking, and that one focused investigation could answer.

By an individual question we mean a single comparison or test; one question, pitched at the level of those in this semester's activities. For example, if you found scribble density differs between aspects or not, or whether the arrangement of scribbles around a bole follows the distribution of wind directions, your single question might be directed at testing why that is/isn't the case. Avoid anything like a broad research priority such as "what determines scribble patterning?". The latter is a program of work. Your job is to propose something a single field season might resolve. A good individual question is specific enough that you can name three things about it in a sentence: the comparison it rests on, the data that would answer it, and the result that would count as an answer.

Identifying that question is the first action; one that you should keep in the back of your mind as we work through the analyses this semester. The process will necessarily draw from your analytical experience and own results rather than any pre-existing list. Work through it in steps:

1. Start from your results. Document within your JMP journals what you found (effects, directions, and significance) with the figure/s and/or table/s that shows it.
2. Ask what it leaves unresolved. A result rarely closes a question cleanly. More often it creates at least one more. Your effect might be real but confounded, or is simply correlative, or is weak or absent. So the question becomes why, or under what conditions it would appear/disappear.
3. List the questions your result raises.
4. Choose one on of the questions. Take the single question that is both the most worth asking and answerable by one focused investigation. If you cannot state its comparison in a sentence, it is still too broad — narrow it until you can.
5. Build a proposal that reflects your question. That one question is the Problem of your new PPDAC cycle. Everything that follows (the design, the data, the analyses, the prediction) exists to answer it, and nothing more.

The aim here is discipline. The goal of your proposal is not how many questions you can raise, but whether you can take one, justify it from your own evidence, and design something that would actually answer it.

 

What you need to do.

This is a synthesis-and-reasoning task. Don't see it as a test of whether you land on the “right” next investigation. Rather, this task focusses on your ability to reason your way to an investigation and whether, say, the analyses you propose are suited to the question. In short, it's about your ability to build a conceptual framework. You do not need to create a full protocol, a budget, or literature review.

There are two marked components:

• A written 1200-word research proposal due in Week 11, structured as a PPDAC cycle
• A short individual five-minute interview in Week 12, in which you discuss and account for your own proposal.

The interview is not a talk or a presentation and needs no extra preparation. You just bring your proposal and be ready to discuss it. The two components are marked in their own right. The interview does not affect the written mark, and the written proposal is not a script to be read aloud.

For ENVS6103 students this proposal is one component of your graduate assessment. Your interview is included in the combined viva that covers your research synthesis. See the ENVS6103 Research synthesis assessment task for its structure and weighting.

 

Structuring the proposal

Use the following structure for your proposal. Develop each element from the one before; Problem to Plan, Design, Analysis, and Conclusion. The chain from your result (Problem) to your proposed analyses is what is being marked.

• Problem: This is your relevant result, and the question it raises. Begin with the result you are drawing on. State it precisely; the figure, its direction, significance (include the graph or table that shows it adhering to Tufte's principles). Then frame the problem it opens. What does this result leave unresolved, or newly worth asking? Your result is the problem the next investigation exists to address.
• Plan: Outline the design you propose. How you would investigate the Problem? Would you use a natural experiment (contrasting positions the landscape already provides) or a manipulative one? Describe the design, the contrast it sets up, and the specific confounding factor or open question it is built to resolve.
• Data: Describe what you would collect. What would be measured, what is held constant or controlled, and how the data would be organised so the design can do its work.
• Analysis: What method would you use to analyse your data. The analyses you would run, drawn from the methods you have used this semester. You should cover the data summaries, and the hypothesis tests appropriate to your question. Name each analysis and say why it suits the question. This is where you show you can choose the right tool, not merely collect data, and justify your choice.
• Conclusion: Outline what the results would mean. Make a prediction about what would distinguish your competing explanations. What should the analysis show if you're right/wrong? How would you interpret the outcome?

Key elements to consider are that you should;

• Lead with your actual figure(s) and their direction, and refer to your own graph/s or table/s throughout.
• Reason through the specific confounder or open question your result leaves unresolved, and the single variable your design isolates or manipulates to resolve it. Show the logic to your argument, not just the conclusion.
• Choose analyses that fit your own response variable and comparison. Generic “run a t-test” is pretty bland and uninformative, and will earn little. Something like “a paired test of [a variable] between [a contrast], because …” is where the action is and will earn marks.
• Be open to having found little or no pattern. That is a legitimate result and offers a different problem and a different next investigation. A well-argued proposal from a null result would earn full marks. Conversely, there is no advantage in overstating a pattern (bearing in mind we'll know them too).
• ENVS6103 students must identify one assumption or limitation of your proposed design or analysis, and say how you would test or mitigate it.

Your submission must;

• Meet the ANU’s requirements of academic conduct, including a statement regarding use of LLM/AI.
• Include appropriate and correct referencing of supporting literature.
• Be 1000 words in length (submissions exceeding by >10% will be penalised; word counts exclude references) .
• Not include attributes (name or ‘u’ number) that allow the author to be identified
• Not have an ANU coversheet.
• Basic bullet points will not do (and won't be marked).
• Include only result/s generated by JMP. LLM generated graphs/tables are not permitted

 

 

A note on using LLMs (AI). 

We expect you may well use LLM/AI tools. That's OK, they're good at supplying background you have not been taught in this course. For example, your experiment might aim to isolate a direct heating effect on bark but you've no idea how to do that. Use an LLM to help for those elements, but make sure you read and confirm anything they propose. What they struggle with is the part that's actually marked. The part where you reason from your own results to the question worth asking next, and account for that reasoning when asked is yours to write. Background a tool brings in counts only where you put it to work in your argument; on its own it earns nothing. And in the interview, it is your reasoning, not the tool’s, that you will be accounting for.

 The result/s upon which your proposal rests must be generated by JMP. LLM generated graphs/tables are not permitted and will not be marked.

 

 

The interview

Every ENVS1003 student will attend a short individual five-minute interview after submission of the proposal. It is not a presentation. Bring your proposal and be ready to discuss it. The interview is aimed at assessing whether you can account for the reasoning in your proposal — why your result raises this problem, why this design, and why these analyses. You will discuss your proposal with the course convenor and one other marker.

You can expect two or three questions drawn from what you wrote, such as:

• Why did that result point you to this problem, rather than another?
• Why is that the right analysis for the comparison you propose — what would it tell you?
• What would have changed the design, or the analysis, you chose?

The interview is intended to be conversational and is marked on the soundness of the reasoning you can articulate, not swanky delivery or polish. Is this Shark Tank? No, I'm not a funder and I don't like sales pitches. I'm an academic research supervisor, so think of yourself as part of my lab group. The questions are there to check the reasoning is yours and to hear you say it.

 

Marking

The written proposal (12%) and the interview (8%) are marked separately. Each element of the proposal is assessed on how it follows from the preceding one. That is, the chain from your result to your proposed analyses really matters. The interview (and viva for graduates) is marked on the soundness of the reasoning you can account for aloud. Again it will be assessed on how your explanation shows the proposal genuinely reflects your results

Examples of previous assignments are not available. Remember that the strongest proposals are not the ones with the largest effect or the tidiest language, but the ones whose design and analyses could only have been chosen by someone who understood their own result.

 

Feedback

In addition to your mark and a marked rubric, you will receive specific comments on your writing and argumentation.

 

Referencing

Where appropriate, your submission must be supported by in-text referencing. A complete, correctly formatted list consistent with the Harvard referencing style. That style is familiar to most students and uses the author-date system (authors' last name and the year of publication) for in-text citations, and reference list should be ordered alphabetically by the last name of the first author of each work. A link to the Fenner School's referencing style guide is below.

As well as supporting a cite-as-you-write facility, referencing software can dramatically reduce the time involved in correctly formatting reference lists. The ANU owns both site and remote licences to Endnote software. Locally, Endnote can be accessed on all Info Commons machines. Alternatively, copies of earlier versions of Endnote can be borrowed from the ANU Library and installed on personal machines. A link to a plugin Endnote style for the Fenner School is below.

While manually entering referencing data in a library can be time consuming, search engines such as Web of Science and Google Scholar directly export references to Endnote. To get you started an Endnote library is available below.

• Download the Fenner School referencing guideDownload Download the Fenner School referencing guide
• Download the ENVS1003/6103 Endnote libraryLinks to an external site.

 

Assessment Task 8

End-of-semester exam

In-person invigilated exam. See ANU timetabling for exam date

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

Assignments are submitted using Turnitin in the course Canvas site. You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

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 it 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.

Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.

Returning Assignments

Feedback on written assessment will be provided on electronic copies of the electronically-submitted assessment.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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

Resubmission of assignments is not permitted. 

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 Accessibility 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 supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students