ENV BIOL 3006 - Research Methods in Environmental Biology III

North Terrace Campus - Semester 1 - 2015

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.

  • General Course Information
    Course Details
    Course Code ENV BIOL 3006
    Course Research Methods in Environmental Biology III
    Coordinating Unit School of Biological Sciences
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange Y
    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 Staff

    Course Coordinator: Professor Sean Connell

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes

    A successful student should be able to:

    1. Identify strategies for asking good questions in biological research
    2. Demonstrate scientifically based sampling and experimental skills in ecology and environmental science
    3. Define logical observations, models and hypotheses to shape environmental research questions, both orally and written
    4. Demonstrate an understanding of different types of sampling, apply basic statistical techniques to real biological, environmental and ecological data and correctly interpret the outcomes
    5. Develop rigorous sampling designs and apply them to the real world environmental problems
    6. 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
  • Learning Resources
    Recommended Resources

    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 Learning
    All 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)

    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

    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.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    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

    20%

    No 1-6 Weeks 5 & 10
    Exam Summative 60% No 1, 3-6 Exam period
    Assessment Detail
    1. Lab Quizzes
    There will be four lab quizzes in practical sessions that will be worth 5% each. Quizzes will be short-answer written quizzes 20 minutes in duration. Written feedback will be provided in the following practical.

     

    1. Assignments
    There will be two assignments worth 10% each. Each assignment will consist of a several problem-based questions that will require some computing work for data analysis and short answer type responses (half to one page). Assignments are to be submitted using TurnItIn.

     

    1. Exam
    A 2-hour exam in the end of semester exam period which will draw on material from both lectures and practicals. It will require simple calculations, but it will not involve computing.
    Submission
    Late 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 Access Adelaide.

  • Student Feedback

    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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

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