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ENV BIOL 3540 - Research Methods in Wildlife Conservation III

North Terrace Campus - Semester 1 - 2022

An introduction to systematic methods of collection, analysis and reporting of field and laboratory data for practical applications in the field of wildlife conservation biology. Lectures outline the quantitative nature of conservation research and the value of robust sampling strategies and experimental methods. Some knowledge of basic statistics is required. Sampling design for field studies will be emphasised, and the elements of statistical tests, including linear modelling, will be considered in the context of their implementation and reporting standards against legislative and industry requirements. Practical work will complement methods introduced in lectures and involves use of computers and software in addition to field data collection at local sites. Workshops will be used to provide specialised expertise in Wildlife Conservation techniques.

  • General Course Information
    Course Details
    Course Code ENV BIOL 3540
    Course Research Methods in Wildlife Conservation 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 N
    Incompatible ENV BIOL 3006, ENV BIOL 3510, ENV BIOL 3520, ENV BIOL 3530
    Assumed Knowledge 6 units of Level II ENV BIOL courses, STATS 1000 or STATS 1004 or equivalent
    Restrictions Available to BSc (Wildlife Conservation) students only
    Assessment Quizzes (in practicals), assignments, and final exam
    Course Staff

    Course Coordinator: Dr Camille Mellin

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes


    1.     Demonstratescientifically based sampling and experimental skills in contemporary conservation science

    2.      Define logical observations, models and hypotheses to shape conservation 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 wildlife conservation problems

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

    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.

    2-5

    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.

    1, 3, 4, 5

    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.

    2-4

    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.

    2, 5

    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.

    3-5

    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.

    1, 2, 5
  • Learning Resources
    Required Resources
    The recommended text
    assigned to this course is:

    Problem-Solving in Conservation Biology and Wildlife Management, 2008
    Blackwell publishing by James P. Gibbs, Malcolm L. Hunter Jr., Eleanor J. Sterling

    ISBN-13: 978-1405152877

  • 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.  Fieldwork, or 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











     







  • 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

     

    Yes
    or No
    Outcomes being assessed / achieved Approximate Timing of Assessment
    Quizzes Formative & Summative 30% No 1, 4 Weeks 3, 5, 7
    Assignments Formative & Summative 40% No 1-5 Weeks 5 & 10
    Final Exam Summative 30% No 1, 3-5 Exam Period
    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 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 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

    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.

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