ENV BIOL 3510 - Research Methods in Ecology III
North Terrace Campus - Semester 1 - 2022
General Course Information
Course Code ENV BIOL 3510 Course Research Methods in Ecology III Coordinating Unit School of Biological Sciences Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 7 hours per week Available for Study Abroad and Exchange Y Incompatible ENV BIOL 3006, ENV BIOL 3520, ENV BIOL 3540, ENV BIOL 3530 Assumed Knowledge 6 units Level II ENV BIOL courses & STATS 1000 or STATS 1004 or equivalent Course Description An introduction to systematic methods of collection, analysis and reporting of field and laboratory ecological data, and basic experimental design in ecology. Lectures outline the quantitative nature of ecological research and the value of robust experimental methods. Some knowledge of basic statistics is required. Experimental design will be emphasised, and the elements of statistical tests, particularly linear modelling, will be considered in a variety of ecological contexts. Practical work involves use of computers and software, and will complement methods introduced in lectures. Workshops will be used to collect field-type ecological data and provide specialised expertise in ecological techniques and analysis.
Course Coordinator: Dr Camille Mellin
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes
scientifically based sampling and experimental skills in ecology and
logical observations, models and hypotheses to shape environmental research
questions, both orally and written
an understanding of different types of sampling, apply basic statistical
techniques to real biological, environmental and ecological data and correctly
interpret the outcomes
rigorous sampling designs and apply them to real world ecological problems
appropriate conventions in technical writing and graphical methods for
presenting data in ecology
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
1, 3, 5
Attribute 8: Self-awareness and emotional intelligence
Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.
Learning & Teaching Activities
Learning & Teaching Modes
Lectures are supported by online material. Some lecture material will seek to ‘flip the
classroom’ where the lecture room is the forum for exploring ideas and
creativity to problem solving, recognising alternate cultures have different
perspectives of the generation of knowledge and the ethics of scientific
discovery and quantitative analysis.
Simulations of field conditions and field work will build student knowledge and experience in action-based leaning to develop the
application of theoretical knowledge to practical problems that face industry.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
A student enrolled in a 3
unit course, such as this, should expect to spend, on average 12 hours per week
on the studies required. This includes both the formal contact time required to
the course (e.g., lectures and practicals), as well as non-contact time (e.g.,
reading and revision).
Learning Activities SummaryThis course will be delivered by the following means:
Teaching is through a combination of lectures (1 x 2 hours per week during semester), practicals (1 x 3 hours per week [8 weeks]), workshops (1 x 4 hours per week [4 weeks]), and tutorials (1 x 1 hour per week [8 weeks])
Lectures will cover Fundamentals of logic, experimental design and variation in data;Sample design, hypothesis testing, t-tests;chi-squared tests, power analysis;Correlations, One-way ANOVA; Two-way ANOVA, BACI;Multivariate statistics;Linear models;Likelihood models;Generalised linear models; and Bayesian statistics.
The practicals, tutorials and workshops will support the lecture topics.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Task Type Due Weighting Learning Outcome Quizzes Formative and Summative
30% 1,4 Assignments Formative and Summative Weeks 5 & 10 40% 1-6 Final Exam Summative Exam Period 30% 1, 3-6
1. Lab Quizzes (30%)
There will be four
lab quizzes in practical sessions that will be worth 5% (x2) and 10% (x2)
each. Quizzes will be short-answer written quizzes of 20 minutes in duration.
Written feedback will be provided in the following practical.
2. Assignments (40%)
will be two assignments worth 15% and 25% respectively. Each assignment will
consist of several problem-based questions that will require some computing
work for data analysis and short answer type responses (half
to one page).
3. Final Exam (30%)
2 hour exam in the end of semester exam period that will draw on material from
both lectures and practicals. It will require simple calculations but will not
SubmissionIf an extension is not applied for, or not granted then a penalty for late submission will apply. A penalty of 10% of the value of the assignment for each calendar day that the assignment is late (i.e. weekends count as 2 days), up to a maximum of 50% of the available marks will be applied. This means that an assignment that is 5 days late or more without an approved extension can only receive a maximum of 50% of the marks available for that assignment.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
- Academic Support with Maths
- Academic Support with writing and speaking skills
- Student Life Counselling Support - Personal counselling for issues affecting study
- International Student Support
- AUU Student Care - Advocacy, confidential counselling, welfare support and advice
- Students with a Disability - Alternative academic arrangements
- Reasonable Adjustments to Teaching & Assessment for Students with a Disability Policy
- LinkedIn Learning
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangement Policy
- Academic Honesty Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Elder Conservatorium of Music Noise Management Plan
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.
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