AGRIC 3515WT - Research Methodology in Agricultural Sciences III

Waite Campus - Semester 1 - 2017

This course provides the applied statistics background for survey and experimental work in typical projects in Agriculture. Case studies and critical examples are used to work through commonly experienced research problems (from sampling designs to the ethical consideration) and to explain how they may be approached, solved or prevented with statistical means. Most common applied statistical techniques in Agricultural research are introduced together with the practical guidance to the statistical software.

  • General Course Information
    Course Details
    Course Code AGRIC 3515WT
    Course Research Methodology in Agricultural Sciences III
    Coordinating Unit School of Agriculture, Food and Wine
    Term Semester 1
    Level Undergraduate
    Location/s Waite Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites STATS1000, STATS1004, ECON 1008 or equivalent
    Course Description This course provides the applied statistics background for survey and experimental work in typical projects in Agriculture. Case studies and critical examples are used to work through commonly experienced research problems (from sampling designs to the ethical consideration) and to explain how they may be approached, solved or prevented with statistical means. Most common applied statistical techniques in Agricultural research are introduced together with the practical guidance to the statistical software.
    Course Staff

    Course Coordinator: Dr Olena Kravchuk

    Course Timetable

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

    The course is timetabled on Fridays, 6 contact hours that equate generally to 2hrs of lectures/discussions, 2hrs of tutorials/data collection and 2 hrs of computer practicals. The order and format of activities are flexible, and it is expected that students are attending the whole day.
    Consultation hours are negotiated with the class in the first week of the semester.
  • Learning Outcomes
    Course Learning Outcomes
    This course aims to help students see the ‘big picture’ of statistical reasoning in agriculture research, where research is taken in a sense much broader than academic research. Working through the course reader, currently based on the text by a famous statistics presenter Bryan Manly, supported with the working examples and case-studies presented in lectures, and applying the principles to simple hands-on problems  in general and agriculturual contexts, working independently and in groups, students will develop:
    1 Understanding of principles and typical designs for data collection in sampling and surveys
    2 Understanding of principles and typical designs of proper, controlled, experiments
    3 Understanding of principles and typical designs of quasi, semi-controlled, experiments
    4 Skills in applying this knowledge in practice to research inquiry
    5 Skills in designing small-scale research studies and interpreting the results statistically
    6 Understanding of the place of statistics in the ethical considerations and overall design of experimentation
    7 Good working knowledge of GenStat as the package of choice
    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)
    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)
    1, 2, 3
    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
    4, 7
    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
    5
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    5
    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
    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
    4, 5
  • Learning Resources
    Required Resources

    GenStat current release, available on the Waite campus and can be downloaded on personal computers of students enrolled in the course.

    ‘The design and analysis of research studies’, by Bryan F.J. Manly, Cambridge Press, 2001. The book is available from the University of Adelaide Library at Waite, but it is highly recommended that the students acquire their own copy to follow the weekly readings for the course and to use this book as a useful research resource afterwards.

    Additional reading and lecture notes are available on MyUni. From 2016, the course reader is also available for download from MyUni.

    Recommended Resources

    To revise the introductory statistics presented in a very relevant manner, the book by Alan G. Clewer and David H. Scarisbrick, Practical Statistics and Experimental Design for Plant and Crop Science, Wiley, 2001, is highly recommended (first five chapters in particular)

    Online Learning

    MyUni: Teaching materials and course documentation will be posted on the MyUni website (http://myuni.adelaide.edu.au/).

  • Learning & Teaching Activities
    Learning & Teaching Modes

    The course is designed to provide students with a broad overview of design and analysis methods for various types of research study. Lectures present the theory, computer tutorials give skills for handling design and analysis in GenStat, and laboratory practicals allow students to design, set up and conduct small-scale studies relevant to the topics discussed in the lectures and demonstrated in the computer practicals

    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

    To follow the course successfully, students will need to come to the class prepared with their weekly reading tasks.
    Learning activities include lectures, computer tutorials for GenStat and problem solving practicals. Every week, all three types of activities are aligned to the common topic.

    The course covers the following topics:

    Types of research studies in agriculture research in Australia
    Sample survey
    Spatial sampling
    Regression models
    Treatment-based experimental designs
    Time series designs
    Typical randomized designs in agriculture studies
    General linear models
    Generalized linear models
    Computation-intensive statistical inference
    Ethical considerations in research study designs
    Synthesis: carrying out a research study

    An emphasis is placed in the course on the development of students' self-learning and team-working skills. Students are encouraged to work in small groups on research studies designs; the course project is based on group-work.

    Specific Course Requirements

    Attendance of contact hours is highly recommended, as all the activities are important for self-learning and team-working. Attendance will be recorded. Students are advised to contact the course staff in advance, if possible, if they are not able to attend certain days, and take the advantage of one-to-one consultations to discuss the material missing.

    Small Group Discovery Experience
    There are two projects during the course, in which students are encouraged to contact their lecturers in special topic courses or research staff for the ideas and/or experimental data. The projects are about designing surveys and controlled experiments.
  • 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
    The assessment is continuing throughout the semester and consists of
    individual student reports, a group mini-lecture and a group project report and
    presentation. The schedule and weighting of the assessment is given on MyUni
    site.

    Technical reports assess the student’s ability to design small-scale
    research studies of various types and complete the analyses in GenStat.

    Mini-lecture assesses the students’ ability to study new material in
    statistics with limited supervision and to present the material to the
    non-professional audience in a clear and engaging way.

    Group project report and presentation assess the students’ ability to
    synthesis the material learned in the course and design, conduct and analyse a
    small-scale scientific investigation with limited supervision and communicate
    the results of the analysis.

    Assessment Task Task Type Due Weighting Hurdle Learning Outcome
    Individual statistical computing reports Formative & Summative

    30% No 1-4, 7
    Individual workbook solutions Formative & Summative 30% No 1-5
    Group mini-lecture Summative 10% No 1-4
    Group research project Summative 30% No 1-7

    Assessment task

    Type of assessment

    Percentage of total assessment for grading purposes

    Hurdle (Yes/No)

    Outcomes being assessed

    Individual statistical computing reports

    Formative/Summative

    30%

    No

    1-4, 7

    Individual workbook solutions

    Formative/Summative

    30%

    No

    1-5

    Group mini-lecture

    Summative

    10%

    No

    1-4

    Group research project

    Summative

    30%

    No

    1-7

    Assessment Related Requirements

    It is compulsory to attempt all the assessment. Group assignments will be weighted in accordance to students’ participation and effort. Students have to negotiate themselves the equal load for the group assignments. All individual reports are strictly individual assignments.

    Assessment Detail

    Statistical computing reports: Six GenStat practical reports will be handed in fortnightly. Prompt written feedback will be provided.

    Workbook solutions: Six problem sets will be handed in fortnightly alternating with practical reports. The problem sets will complement the case-study analyses in practical reports. Prompt written feedback will be provided.

    Group mini-lecture: Students are expected to come to class having read the material assigned for each week. In this assignment, students will be assessed based on answers to the questions that will form the foundation of class discussion on the sampling strategies and analyses. Peer feedback will be promptly provided.

    Design and analysis of a research case-study: Students will design their research study, conduct it and present the design and analysis to the class.

     

    Submission

    Submissions of all assignments are strictly on the MyUni site only. Prompt feedback is guaranteed. For formative assignments, students will be given an opportunity to respond to the feedback in writing with the aim of improving their understanding.

    Late submission of assessments
    Late submissions are not negotiable for the group assignments.

    If an extension is not applied for, or not granted then a penalty for late submission will apply. 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

    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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