ENV BIOL 3006 - Research Methods in Environmental Biology III
North Terrace Campus - Semester 1 - 2014
General Course Information
Course Code ENV BIOL 3006 Course Research Methods in Environmental Biology III Coordinating Unit School of Earth and Environmental Sciences Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 6 hours per week Assumed Knowledge 6 units of Level II Environmental Biology courses & STATS 1000 or equivalent Course Description An introduction to systematic methods of collection, analysis and reporting of field and laboratory data, and basic experimental design. Lectures outline the nature of research and the value of experimental methods. Some knowledge of basic statistics is required. Experimental design will be emphasised, and the elements of statistical tests, particularly analysis of variance, will be considered in a biological context. Practical work involves use of computers and software, and will complement methods introduced in lectures.
Course Coordinator: Dr Bayden Russell
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes
A successful student should be able to:
- Identify strategies for asking good questions in biological research
- Demonstrate scientifically based sampling and experimental skills in ecology and environmental science
- Define logical observations, models and hypotheses to shape environmental research questions, both orally and written
- Demonstrate an understanding of different types of sampling, apply basic statistical techniques to real biological, environmental and ecological data and correctly interpret the outcomes
- Develop rigorous sampling designs and apply them to the real world environmental problems
- Demonstrate appropriate conventions in technical writing and graphical methods for presenting data
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) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 2-6 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1, 4, 6 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 1, 3, 4-5 Skills of a high order in interpersonal understanding, teamwork and communication. 2-4 A proficiency in the appropriate use of contemporary technologies. 2, 5-6 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 1, 3, 5-6 A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 1-2, 5-6 An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities. 3-6
The recommended text assigned to this course is:
Zar JH. 2009. Biostatistical analysis, 5th ed. Prentice-Hall International. 944+p. ISBN 0-13-1008465-5.
A more advanced book, suitable for students with more experience, is:
Quinn GP, MJ Keough. 2002. Experimental design and data analysis for biologists. CUP. 556p.ISBN 0-52-1009766
Online LearningAll lecture material for this course will be posted online.
Learning & Teaching Activities
Learning & Teaching Modes
This course will be delivered by the following means:
Teaching is through a combination of lectures (1 x 2 hours per week during semester) and practicals (1 x 4 hours per week)
No information currently available.
Learning Activities Summary
The course content will include the following:
List of course topics:
- Fundamentals of logic, experimental design and variation in data
- Sample design, hypothesis testing, t-tests
- t-tests, chi-squared tests, power analysis
- Correlations, One-way ANOVA
- Two-way ANOVA
- Two-way ANOVA, BACI
- Multivariate statistics
- Linear models
- Likelihood models
- Generalised linear models
- Bayesian statistics.
The topic and activity in practicals will follow what is taught in the lectures each week.
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 Type of assessment Percentage of total assessment for grading purposes Hurdle Learning Outcomes being assess/achieve Approximate timing of assessment Quizzes Formative & Summative 20% No 1,4 Weeks 3,5,7,9 Assignements Formative & Summative
No 1-6 Weeks 5 & 10 Exam Summative 60% No 1, 3-6 Exam period
- Lab Quizzes
No information currently available.
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
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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
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- Coursework Academic Programs Policy
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- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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