GEOG 1005 - Social Science Techniques I

North Terrace Campus - Semester 1 - 2020

The course aims to provide students with a perspective on the role of social sciences within contemporary society, especially in Australia, and teach a number of fundamental skills which are expected of professional social scientists in the contemporary world. These skills are an important acquisition for students, whether they seek to gain employment in the public and private sectors or to proceed to higher level research within their chosen social discipline. Students of this course should emerge from it with a sound background in the main sources of social science information and data available in Australia, and the major methods of analysing information from these sources. Topics include measurement, exploratory data analysis, descriptive statistics, data collection, hypothesis testing, regression analysis, correlation, and graphical procedures. Computer Workshops provide hands-on training and skills in data analysis. No prior background or knowledge in computing, mathematics or statistics is assumed. The aim is to teach students a range of data analysis techniques and how to interpret the results.

  • General Course Information
    Course Details
    Course Code GEOG 1005
    Course Social Science Techniques I
    Coordinating Unit Geography, Environment and Population
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange N
    Incompatible GEOG 2132, SOCI 2002, GEST 2100
    Course Description The course aims to provide students with a perspective on the role of social sciences within contemporary society, especially in Australia, and teach a number of fundamental skills which are expected of professional social scientists in the contemporary world. These skills are an important acquisition for students, whether they seek to gain employment in the public and private sectors or to proceed to higher level research within their chosen social discipline. Students of this course should emerge from it with a sound background in the main sources of social science information and data available in Australia, and the major methods of analysing information from these sources. Topics include measurement, exploratory data analysis, descriptive statistics, data collection, hypothesis testing, regression analysis, correlation, and graphical procedures. Computer Workshops provide hands-on training and skills in data analysis. No prior background or knowledge in computing, mathematics or statistics is assumed. The aim is to teach students a range of data analysis techniques and how to interpret the results.
    Course Staff

    Course Coordinator: Associate Professor Yan Tan

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    1 Understand basic methods and techniques of data analysis in the social sciences and the ways in which they can be used in research.
    2 Develop skills in analysing and interpreting social, demographic and economic data, such as the Australian Census of Population and Housing, to competently present data by means of tables and graphs.
    3 Perform descriptive statistics, statistical testing, and multiple regress analysis of survey data using SPSS software.
    4 Develop an awareness of the social applications of geographical information systems (GIS) in mapping and interpreting spatial variations in social, demographic and economic data.
    5 Develop skills in selecting the appropriate techniques for various types of data, and presenting results of data analysis with high quality written skills.
    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, 4, 5
    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, 2, 3, 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, 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
    2, 3, 4
    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
    5
    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, 5
  • Learning Resources
    Required Resources

    Publications relating to the content of the census and other information relating to surveys and data sources provided by the Australian Bureau of Statistics (ABS) can be found on the ABS website at: http://www.abs.gov.au



  • Learning & Teaching Activities
    Learning & Teaching Modes
    Detailed online teaching/learning materials (including learning objectives, concepts, and readings suggested) will be delivered via MyUni on a weekly basis. Online materials will provide fundamental information on data and techniques of analysis in the social sciences, introducing social and demographic issues, measurement, sources of data, analysis, interpretation and presentation. Such materials will also reflect layered levels of students in terms of their knowledge basis, disciplinary diversity, and skill levels. Two-Hour Practical Workshops at a computer per week are built upon basic understandings of online teaching/learning materials and follow a sequence of 3 Modules. The first module, based on 2016 Census data, examines population and socio-economic trends using EXCEL to show social indicators, tables and graphs. The second module is based on the collection of survey data and analysis using SPSS to provide descriptive statistical analysis
    and explanation. The third module focuses upon regression analysis of survey data using SPSS to develop skills in regression analysis and interpretation of results.


    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    WORKLOAD – STRUCTURED LEARNING TOTAL HOURS
    1 x 1-hour online teaching/learning per week 12 hours per semester
    1 x 2-hour computer workshop per week 22 hours per semester
    WORKLOAD – SELF-DIRECTED LEARNING TOTAL HOURS
    6 hours reading per week 72 hours per semester
    2 hours research per week 24 hours per semester
    2 hours assignment preparation per week 24 hours per semester
    TOTAL = 160 hours per semester
    Learning Activities Summary
    Schedule
    Week 1 Social Science research: Introduction;
    Secondary data sources 
    Week 2 The Australian Census: applying census data to social sciences study;
    Data analysis, research report writing and presentation
    Week 3 Demographic applications in Social Science research: family and household change;
    Social indicators
    Week 4 Quantitative and qualitative measurement
    Week 5 Survey techniques: sampling and questionnaire design;
    Ethics in research
    Week 6 Descriptive analysis of survey data I
    Week 7 Descriptive analysis of survey data II
    Week 8 Bi-variate analysis and hypothesis testing using SPSS
    Week 9 Correlation and linear regression as analytical techniques;
    Multi-variate analysis
    Week 10 Non-linear regression;
    Mixed methods
    Week 11 Doing Qualitative Research: Discourse Analysis, Focus Group and Interviews;
    GIS & social sciences: examples
    Week 12 Course summary & Exam preparation
    Specific Course Requirements

    A course requirement is that students submit all three Workshop Assignments. Attendance and satisfactory participation in the Workshops is a major component of the course. Failure to attend them will make it very difficult to pass this subject and could preclude you from undertaking the exam.



    Small Group Discovery Experience

    This course is designed to encompass focussed computer workshops to develop skills in data analysis and presentation with small group discovery around interpretation of the outcomes.



  • 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 Task Type Weighting Learning Outcome
    Workshop participation Formative and Summative 10% 1-5
    Workshop assessment tasks Formative and Summative 50% 1-5
    2-hour take-home final exam Summative 40% 1-5
    Assessment Related Requirements
    N/A
    Assessment Detail
    Ongoing Workshop Participation (10%):
    Students MUST attend and participate in practical workshops. Students are required to notify the Course Co-ordinator as soon as possible if they have to miss a workshop. You need written evidence (e.g. medical certificate; note from employer; counsellor’s letter) if you have to miss more than one. Students are expected to be well prepared for each workshop and to actively participate. 

    During the online teaching/learning process, students have opportunities to self-manage and undertake a range of learning activities which will be designed to assess ongoing learning of what are the key concepts, techniques, and issues discussed throughout the course. Development of oral and aural skills will be an important part of this assessment.

    Importantly, please note that although this allocation is 10% only, evidence shows that students who commit to regular attendance and engage with the course via active participation, often get up to 10/10 for this assessment component and that this can make the difference of up to a grade level if done well (i.e. Pass to Credit, Credit to Distinction, Distinction to High Distinction). 
     

    Workshop Assessment Tasks (50%):
    The Workshops are of 2-hour duration per week and are based on basic understandings of self-managed online learning/teaching materials. It is advisable that you regularly read online teaching/learning materials and attend required Workshops. Some weekly workshops will include an assessment task which allows students to demonstrate both the successful completion of the workshop
    tasks, and their understanding and application of the techniques and skills which they learn each week.  Students need to submit all 3  Workshop Assessment Assignments on the following: (1) Analysis of Census data; (2) Statistical descriptive analysis of survey data using SPSS; (3) Regression analysis of survey data using SPSS. Full details of the Workshop Assessments will be provided at the start of each
    workshop. All assignments in this course must be submitted online via the relevant course site. Assignment files must be converted to PDF before being submitted to MyUni.

     
    The DUE dates are as follows:

    1. Analysis of Census data           (20%)      Workshops 1-5     Monday, 6 April

    2. Statistical descriptive analysis of survey data using SPSS (10%)      Workshops 6-8      Monday, 11 May

    3. Regression analysis of survey data using SPSS (25%)      Workshops 9-11    Monday, 18 June

     
    Submission of assignments must be lodged by the given DUE date to avoid penalty.  If an assignment is submitted late there must be an adequate reason given to the Course Coordinator. Students will receive feedback on or grades for their work by the end of week after the due date of each submission.

     
    Take Home Final Exam (40%):
    This exam will be delivered and completed during the week from 8th June to 12th June. It will be a take home exam that students will submit to MyUni by the DUE date of mid-night 12th June. Students will be provided with online guidance that takes them through the exam and practice what a good answer looks like.

    Submission

    Online submission MyUni for assignments - Information available on enrolment.

    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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