GEOG 1005 - Social Science Techniques I
North Terrace Campus - Semester 1 - 2022
General Course Information
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, GEST 2100, SOCI 2002 Course Description The course aims to provide students with skills which are expected of professional social scientists in the contemporary world, 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 available in Australia, and the major methods of analysing information from these sources. This course is designed to provide students with a perspective on the role of social sciences within contemporary society, especially in Australia, and with basic skills in the collection, analysis, interpretation, and presentation of social science data and information. Key topics to learn include measurement, data collection, exploratory data analysis, descriptive statistics, hypothesis testing, correlation, regression analyses, and graphical procedures. No prior background or knowledge in computing, mathematics or statistics is assumed.
Course Coordinator: Associate Professor Yan TanG32, Ground Level, Napier Building
Department of Geography, Environment and Population
School of Social Sciences
The University of Adelaide, SA 5005
P: (61) 08 8313 3976
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes
1 Understand the basic methods and techniques of data collection and analysis in the social sciences and how 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, migration and labour force data, to competently present data using tables and graphs. 3 Perform descriptive statistics, statistical testing, and regression analysis of survey data using SPSS software. 4 Develop skills in selecting the appropriate techniques for various types of data, presenting and interpreting results of data analysis with high-level written skills. 5 Develop an awareness of the social applications of geographical information systems (GIS) in mapping and interpreting spatial variations in social, demographic, economic, and environmental 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)
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.
1, 2, 3, 4, 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.
2, 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.
1, 2, 3, 5
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, 3, 4, 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.
Attribute 6: Australian Aboriginal and Torres Strait Islander cultural competency
Graduates have an understanding of, and respect for, Australian Aboriginal and Torres Strait Islander values, culture and knowledge.
This is not covered in SST course.
Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
1, 2, 3, 4, 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.
- There is no textbook for the course.
- Students will be provided with a comprehensive list of readings, including a suite of refereed journal articles, books, book chapters, and online technical materials on the subject relevant to the lecture and workshops each week. Suggested readings will be made available through MyUni for students’ easy access.
- Students will be expected to do those readings and browse the ABS website, and other websites suggested for relevant data and publications.
- All other required materials (e.g. Lecture recordings, Lecture slides, Assessment information, and video/web links) are provided on MyUni.
Recommended ResourcesPublications 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
Online LearningMyUni/Canvas is a critical learning tool and means of communication and knowledge exchange in this course. Learning materials are available each week in preparation for our workshops. Other course material (e.g. Readings, Assessment information) and many features of MyUni/Canvas (e.g. Announcements and the Discussion Board) will help students organise and manage their studies.
Online learning is facilitated through ECO 360 recording of lectures and getting students to access websites of the Australian Bureau of Statistics (ABS) etc.
Learning & Teaching Activities
Learning & Teaching ModesThe teaching in this course is based on student-centred learning principles and strategies. Students are seen as partners in the learning journey. The course employs a blended approach to teaching and learning: In-class lectures and Small-Group Discovery workshops via face-to-face interactions in the Social Science computer suite are supplemented by effective use of information and communication technologies (ICTs) and the online teaching and learning environment MyUni/Canvas.
The course lectures provide fundamental concepts and information on data and techniques of analysis in the social sciences, introducing social issues, measurement, sources of data, interpretation, and presentation. Focussed practical workshops at a computer suite provide hands-on training to develop data analysis and presentation skills with small group discovery around the interpretation of the results. The Workshops are linked to the lectures and follow a sequence of 3 Modules. Based on Australian population census and migration data, the first module examines population and socio-economic trends using EXCEL and TableBuilder to show demographic and socio-economic indicators, tables and graphs. The second module, using SPSS, develops techniques and skills in doing descriptive statistical analysis of survey data and academically interprets and presents results. The third module, using SPSS, focuses upon regression analyses of survey data and provides a description and explanation of the results. Students have reading material and learning activities on MyUni/Canvas, which need to be done before the workshops to get the most out of these workshops. It is highly encouraged that students attend all Workshops. Please make any arrangements you need with work, family etc., so that you can attend the workshops.
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 lecture per week 12 hours per semester 1 x 2-hour computer-based practical workshop per week 20 hours per semester WORKLOAD – SELF-DIRECTED LEARNING TOTAL HOURS 6 hours reading per week 72 hours per semester 2.5 hours research per week 30 hours per semester 2 hours assignment preparation per week 24 hours per semester TOTAL 158 hours per semester
Learning Activities Summary
Schedule Week 1 Social Science research: Introduction;
Week 2 Analysis of Census data I;
Research results and report writing
Week 3 Analysis of Census data II;
Demographic applications in Social Science research;
Social and economic indicators
Week 4 Analysis of CURF census data III;
Quantitative and qualitative measurement;
Week 5 Sampling methods;
Ethics in research
Week 6 Descriptive analysis of survey data Week 7 Statistical (hypothesis) testing methods Week 8 Correlation and linear regression;
Week 9 Non-linear regression;
Week 10 Qualitative Research: Focus group and in-depth interviews Week 11 Applying GIS in social sciences research Week 12 Course summary & Take-home Final Task preparation
Specific Course RequirementsTo pass the course, students must complete and submit for assessment all the assignments described in this course profile. Attendance and satisfactory participation in the workshops is a significant component of the course. Failure to attend them will make it very difficult to pass this subject.
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 Task Type Weighting Learning Outcome Ongoing workshop participation Formative and Summative 10% 1-5 Workshop practical tasks Summative 60% 1-5 Take-home Final Task Summative 30% 1-5
Assessment Related Requirements
- To pass the course, students must complete and submit all set assignments (on time) as described in this course profile for assessment.
- Students are strongly encouraged to participate in all workshops actively.
- Students are expected to use the Harvard (author-date) referencing system for the written assignments. Their work should include references where needed.
Assessment DetailOngoing Workshop Participation (10%)
Workshop attendance is a compulsory component of the course and is monitored during the course. Students need to notify the Course Coordinator via email (email@example.com) as soon as possible if they have to miss a workshop. They need written evidence (e.g. medical certificate; a note from the employer; counsellor's letter) if they have to miss one. They are strongly encouraged to attend ALL scheduled workshops. Students are expected to be well prepared for each workshop and to participate actively.
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 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 Practical Tasks (60%)
The Workshops are of two-hour duration and are linked to the lecture program. Students should regularly attend Lectures (watch the recordings) and Workshops. Some weekly workshops will include an assessment task that allows students to demonstrate the successful completion of the workshop tasks and their understanding and application of the techniques and skills they learn each week. Students need to submit all Three Workshop Practical Assignments on the following: (1) Analysis of Census data using EXCEL; (2) Statistical descriptive analysis of survey data using SPSS; (3) Regression analysis of survey data using SPSS. Full details of the workshop tasks each week will be provided on MyUni\Modules. 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.
Take Home Final Task (30%)
The final assignment assesses students’ analytical and written communication skills in applying fundamental social science techniques and methods to analyse real-world social, demographic, economic, and environmental issues.
SubmissionAll assignments must be submitted electronically via MyUni/Canvas. To check for plagiarism we use TURNITIN. Last possible time for submission is always midnight on the due date.
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.
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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.
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