ENV BIOL 3510 - Research Methods in Ecology III

North Terrace Campus - Semester 1 - 2017

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.

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Course Details

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 3530, ENV BIOL 3540
Assumed Knowledge	6 units level II ENV BIOL courses & STATS 1000 or STATS 1003 or equivalent
Assessment	Quizzes (in practicals), assignments, and final exam

Course Staff

Course Coordinator: Professor Sean Connell

Course Timetable

The full timetable of all activities for this course can be accessed from .

Course Learning Outcomes

1.
Demonstrate
scientifically based sampling and experimental skills in ecology and
environmental science

2.
Define
logical observations, models and hypotheses to shape environmental research
questions, both orally and written

3.
Demonstrate
an understanding of different types of sampling, apply basic statistical
techniques to real biological, environmental and ecological data and correctly
interpret the outcomes

4.
Develop
rigorous sampling designs and apply them to real world ecological problems

5.
Demonstrate
appropriate conventions in technical writing and graphical methods for
presenting data in ecology

最新糖心Vlog Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

最新糖心Vlog Graduate Attribute	Course Learning Outcome(s)
Deep discipline knowledge informed and infused by cutting edge research, scaffolded throughout their program of studies acquired from personal interaction with research active educators, from year 1 accredited or validated against national or international standards (for relevant programs)	6
Critical thinking and problem solving steeped in research methods and rigor based on empirical evidence and the scientific approach to knowledge development demonstrated through appropriate and relevant assessment	1,3,4,5
Teamwork and communication skills developed from, with, and via the SGDE honed through assessment and practice throughout the program of studies encouraged and valued in all aspects of learning	2,3,4
Career and leadership readiness technology savvy professional and, where relevant, fully accredited forward thinking and well informed tested and validated by work based experiences	2,5,6
Intercultural and ethical competency adept at operating in other cultures comfortable with different nationalities and social contexts able to determine and contribute to desirable social outcomes demonstrated by study abroad or with an understanding of indigenous knowledges	3,4,5,6
Self-awareness and emotional intelligence a capacity for self-reflection and a willingness to engage in self-appraisal open to objective and constructive feedback from supervisors and peers able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate	1,2,5,6

Learning Resources

Required Resources

CALCULATOR

Online Learning

MYUNI
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.

Workload

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 Summary

This 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 最新糖心Vlog'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 Summary

Assessment Task	Task Type	Due	Weighting	Learning Outcome
Quizzes	Formative and Summative	Weeks 3,5,7,9	30%	1,4
Assignments	Formative and Summative	Weeks 5 & 10	40%	1-6
Final Exam	Summative	Exam Period	30%	1, 3-6

Assessment Detail

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%)
There
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%)
A
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
involve computing.

Submission

If 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.

Course Grading

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 .

Student Feedback

The 最新糖心Vlog 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 最新糖心Vlog 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.
Student Support
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

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鈥檚 disciplinary procedures.

The 最新糖心Vlog of Adelaide is committed to regular reviews of the courses and programs it offers to students. The 最新糖心Vlog of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

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