Students
SSC 300 – Advanced Social Research Methods
2014 – S1 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Adam Stebbing
Contact via adam.stebbing@mq.edu.au
W6A 824
By appointment
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|---|---|
| Credit points |
Credit points
3
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| Prerequisites |
Prerequisites
30cp including (SOC224 and SSC200) and admission to BSocSc
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit introduces advanced data analysis skills for the social sciences through workshops based on secondary data analysis and project work. The unit will apply all of the skills and capabilities learned through the social science program to the analysis of data in practice. Topics covered include a review of basic quantitative statistics, the development of these skills through forms of regression and the analysis of variance, as well as methods of coding qualitative data for analysis. Practical classes are based on the use of the SPSS statistical package are supported by a choice of secondary data analysis or theoretical library-based projects. Background knowledge of social statistics and social research methods is strongly recommended for prospective students of this unit.
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Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Develop skills using software packages to analyse qualitative and quantitative data in social research
- Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to use and interpret regression models
- Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
- Gain experience in critically analysing data relating to contemporary social issues
Assessment Tasks
| Name | Weighting | Due |
|---|---|---|
| Short Quiz 1 | 15% | Week 6 lecture |
| Short Quiz 2 | 25% | Week 9 lectures |
| Data Analysis Task | 50% | 13th June |
| Workshop Engagement | 10% | Ongoing |
Short Quiz 1
Due: Week 6 lecture
Weighting: 15%
This short quiz will be administered in the second lecture of week 6. Students will have 30 minutes to complete the quiz (and 5 minutes reading time). It will cover materials from weeks 2 to 5 on survey design and quantitative data analysis. It will comprise 15 multiple-choice questions. Marks will be awarded for correct answers, but will not be deducted for incorrect ones. The quiz is designed to provide students with feedback on their progress in the course. It is highly recommended that students attend lectures and workshops, as well as undertake the practical exercises to aid engagement with the course.
More information on the quiz will be provided in week 4.
On successful completion you will be able to:
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
Short Quiz 2
Due: Week 9 lectures
Weighting: 25%
This short quiz will be administered in the second half of the week 9 lectures. Students will have 45 minutes to complete the quiz (including 5 minutes reading time). It will focus on course materials up to week 8, but may also draw on your knowledge from earlier in the course. The main focus of this quiz will be on practical applications of quantitative analysis techniques in the social sciences. Be warned that interpreting SPSS regression output will be tested in this quiz.
The quiz will comprise multiple-choice and short answer questions. Marks will be awarded for correct answers, but will not be deducted for incorrect ones. The quiz is designed to provide students with an indication of how well they are going with the course and offer further incentive to attend lectures.
More information on the quiz will be provided in weeks 7 and 8.
On successful completion you will be able to:
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
Data Analysis Task
Due: 13th June
Weighting: 50%
The major assessment for SSC300 is a data analysis report of 2,000 words. This task requires you to exercise your social research imagination to develop a methodology for social science data that we provide you with and then analyse it using appropriate techniques. In other words, you have to develop an appropriate research question, methodology and data analysis technique that is suitable forthe data you are provided with. That is, using your knowledge from this course, SOC224 and SSC200, you have to assume that you have undertaken this research from start to finish for the purposes of this assessment.
This task requires you to analyse qualitative and/or quantitative data using techniques that we cover in the course, and, write up your results. It also requires you to write up a research report that has the following sections: abstract; background information; aims and objectives; methodology; results/ findings; and, conclusion. And, this task requires you to include a reflection on the software you used to analyse the data as an appendix (this appendix does not have to count toward you word count, but it should be no more than one page).
We have prepared three sets of data relating to three policy issues that you can choose between to analyse for this task. Each of the options requires a different balance of qualitative and quantitative analysis to be undertaken. More information about this task, the three options, how to present it and how to analyse data will be provided in the lectures, workshops and on the iLearn page.
This task should be submitted via Turnitin and it will be marked via GradeMark. Please do not submit hard copies of this task and ensure that you have access to the Turnitin link well before the due date.
N.B. As an important part of this task is to reflect on appropriate uses of computer software in the social sciences, you are required to use SPSS or NVivo to analyse the data you are provided with. More information about how to access these software programs will be provided during the semester.
On successful completion you will be able to:
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Develop skills using software packages to analyse qualitative and quantitative data in social research
- Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to use and interpret regression models
- Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
- Gain experience in critically analysing data relating to contemporary social issues
Workshop Engagement
Due: Ongoing
Weighting: 10%
The weekly workshops are compulsory. You are required to attend at least 80 per cent to meet course requirements. Attendance is particularly important due to the practical focus of this course. But, in addition to attending, you are also expected to actively engage in the workshops. You can demonstrate active engagement by participating in workshop activities (in both the qualitative and quantitative modules of the course). As an incentive, 10 per cent of your final mark will be awarded for participation and engagement.
N.B. Students are encouraged to demonstrate that they have completed the weekly activities.
On successful completion you will be able to:
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Develop skills using software packages to analyse qualitative and quantitative data in social research
- Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to use and interpret regression models
- Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
Delivery and Resources
Lecture and workshop times
Lectures in E5A 120 on Wednesday from 10am to 12pm.
Workshops in W6B 157
Wednesday from 1.30pm to 3.00pm
Wednesday from 3.00pm to 4.30pm
Wednesday from 4.30pm to 6.00pm
Technology used
The following technologies are used in SSC300...
Barcoded Arts coversheets
Written work must be submitted through the Arts Student Centre (in the appropriate SSC box) on Level 1, W6A. Students must print and attach a completed coversheet to all submitted work. A personalised assignment sheet can be generated from the student section of the Faculty of Arts website. No other coversheets are provided by the Faculty.
Information about iLearn
Important information about the weekly schedule for SSC200, course readings and assessment are all available on the courseiLearnpage. If you do not have access, please contact IT help. You are required to check iLearn and your student email regularly for course updates and information.
Information about Turnitin and GradeMark
All written assessments for SSC200 need to be submitted via Turnitin. A link to Turnitin is available via the Assessments tab on the iLearn page. Please contact the convenor if you cannot find it (do not leave it until the day of the assessment). Assessments will be marked via GradeMark and returned to students electronically.
SPSS and NVivo
We will use both SPSS and NVivo in SSC300. Students have access to both programs free of charge on in the workshops, on campus in the library computer labs and off-campus through iLab (search the MQ website for information on this). If you have a PC (or a Mac that runs MS Windows), you can download a copy of NVivo from the software downloads section of the student portal on the Macquarie University website.
Textbooks
This course draws on two required textbooks:
Pallant, J. (2013) SPSS Survival Manual: A step by step guide to data analysis using IBM SPSS, 5th Edition, Allen & Unwin: Sydney.
Bazeley, P. and K. Jackson (2013) Qualitative Data Analysis with NVivo, 2nd Edition, Sage: Thousand Oaks.
Readings on e-reserve
Additional readings for the course should be available free-of-charge via e-Reserve. e-Reserve has been incorporated into the MultiSearch tool that is accessible via the Macquarie University library website.
Changes since the last offering of this unit
Course readings, weekly topics and assessment design have changed since last year.
Unit Schedule
|
Wk |
Date |
Lecture Topics |
Workshop Topics |
|
1 |
5 Mar
|
Introduction to SSC300: Using Computers in Social Research |
No workshop |
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2
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12 Mar |
From Survey Methods to Quantitative Analysis |
SPSS 1: Exploring SPSS |
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3
|
19 Mar |
Univariate Analysis, Sampling Distributions & Confidence Intervals |
SPSS 2: Univariate analysis & confidence intervals |
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4
|
26 Mar |
Hypothesis tests |
SPSS 3: Chi-square and T-tests |
|
5
|
2 Apr |
Bivariate Relationships and Linear Regression |
SPSS 4: Correlation and Linear regression |
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6
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9 Apr |
Multivariate Regression |
SPSS 5: Multiple linear regression |
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7
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30 Apr |
Multivariate Analysis with Categorical Data |
SPSS 6: Binary logistic regression |
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8
|
7 May |
Making Sense of Qualitative Data with Computers |
NVivo 1: Exploring data |
|
9
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14 May |
Coding & Writing Memos |
NVivo 2: Nodes, memos & annotations |
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10
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21 May |
Grounded Theory: How to build theory from data |
NVivo 3: Going further with nodes & queries |
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11
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28 May |
Discourse Analysis: How to analyse language and cultural texts |
NVivo 4: Visualising codes |
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12
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4 Jun |
Narrative Analysis: How to construct narrative through synthesis |
Major project workshop |
|
13
|
11 Jun |
Mixed Methods Social Research |
No workshop |
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Academic Honesty
Academic Honesty is an intergral part of the core values and principles contained in the Macquarie University Ethics Statement. Its fundamental principle is that all staff and students act with integrity in the creation, development, application and use of ideas and information. This means that:
- All academic work claimed as original is the work of the author making the claim
- All academic collaborations are acknowledged
- Academic work is not falsified in any way
- When the ideas of others are used, these ideas are acknowledged appropriately
See the link above for more information from Policy Central.
University Grading Policy
The grade that a student receives will signify their overall performance in meeting the learning outcomes of the unit of study. Graded units will use the following grades
HD High Distinction 85-100
D Distinction 75-84
Cr Credit 65-74
P Pass 50-64
F Fail 0-49
Return of marked work
As per university policy, written assessments will be returned to students within three weeks of the submission date. Early assignments will not be marked early. And, the short class test held during the examination period at the end of semester will not be returned to students.
Extensions and special consideration
In the first instance, extensions for course assessments should be discussed with the unit convenor. Medical certificates or similar documentation will be needed to support requests for extensions. If you have any doubts about whether your situation qualifies for an extension, please contact the course convenor.
Special consideration should be applied for when students experience circumstances of three (3) consecutive days duration (or longer) within a semester that prevents completion of assessment or formal examination. You should apply online to the Faculty of Arts. For an application to be valid, it must include a completed Application for Special Consideration form and all supporting documentation.
The special consideration policy is available online at: http://www.mq.edu.au/policy/docs/special_consideration/policy.html
Late Penalties
For all written assessment tasks, the Department applies the following penalties for late work that does not have an extension:
5 per cent for the first day (or weekend if the assessment is due on Friday and submitted the following Monday); 1 per cent for each subsequent day.
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
IT Help
For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/.
When using the University's IT, you must adhere to the Acceptable Use Policy. The policy applies to all who connect to the MQ network including students.
Graduate Capabilities
Capable of Professional and Personal Judgement and Initiative
We want our graduates to have emotional intelligence and sound interpersonal skills and to demonstrate discernment and common sense in their professional and personal judgement. They will exercise initiative as needed. They will be capable of risk assessment, and be able to handle ambiguity and complexity, enabling them to be adaptable in diverse and changing environments.
This graduate capability is supported by:
Learning outcomes
- Develop skills using software packages to analyse qualitative and quantitative data in social research
- Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to use and interpret regression models
- Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis
Assessment tasks
- Short Quiz 1
- Short Quiz 2
- Data Analysis Task
- Workshop Engagement
Commitment to Continuous Learning
Our graduates will have enquiring minds and a literate curiosity which will lead them to pursue knowledge for its own sake. They will continue to pursue learning in their careers and as they participate in the world. They will be capable of reflecting on their experiences and relationships with others and the environment, learning from them, and growing - personally, professionally and socially.
This graduate capability is supported by:
Learning outcomes
- Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to use and interpret regression models
- Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis
- Gain experience in critically analysing data relating to contemporary social issues
Assessment task
- Workshop Engagement
Discipline Specific Knowledge and Skills
Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
Learning outcomes
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Gain experience in critically analysing data relating to contemporary social issues
Assessment task
- Data Analysis Task
Critical, Analytical and Integrative Thinking
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Learning outcomes
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Gain experience in critically analysing data relating to contemporary social issues
Assessment tasks
- Short Quiz 1
- Short Quiz 2
- Data Analysis Task
Problem Solving and Research Capability
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
Learning outcomes
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to use and interpret regression models
- Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis
Assessment tasks
- Data Analysis Task
- Workshop Engagement
Creative and Innovative
Our graduates will also be capable of creative thinking and of creating knowledge. They will be imaginative and open to experience and capable of innovation at work and in the community. We want them to be engaged in applying their critical, creative thinking.
This graduate capability is supported by:
Learning outcomes
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
- Gain experience in critically analysing data relating to contemporary social issues
Assessment task
- Data Analysis Task
Effective Communication
We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.
This graduate capability is supported by:
Learning outcome
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
Assessment tasks
- Short Quiz 1
- Short Quiz 2
- Data Analysis Task
- Workshop Engagement
Engaged and Ethical Local and Global citizens
As local citizens our graduates will be aware of indigenous perspectives and of the nation's historical context. They will be engaged with the challenges of contemporary society and with knowledge and ideas. We want our graduates to have respect for diversity, to be open-minded, sensitive to others and inclusive, and to be open to other cultures and perspectives: they should have a level of cultural literacy. Our graduates should be aware of disadvantage and social justice, and be willing to participate to help create a wiser and better society.
This graduate capability is supported by:
Learning outcomes
- Actively develop skills in interpreting data and the results generated by social research in an ethical and responsible manner
- Gain experience in critically analysing data relating to contemporary social issues
Assessment tasks
- Data Analysis Task
- Workshop Engagement
Socially and Environmentally Active and Responsible
We want our graduates to be aware of and have respect for self and others; to be able to work with others as a leader and a team player; to have a sense of connectedness with others and country; and to have a sense of mutual obligation. Our graduates should be informed and active participants in moving society towards sustainability.
This graduate capability is supported by:
Learning outcomes
- Learn how to analyse and interpret data collected from social research using a range of vocational analytic techniques
- Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences
- Gain experience in critically analysing data relating to contemporary social issues
Assessment task
- Data Analysis Task
Changes since First Published
| Date | Description |
|---|---|
| 02/03/2014 | '2013' removed from due date of Research Report. |
| 16/01/2014 | The Prerequisites was updated. |