Unit Guide

General Information

Unit convenor and teaching staff	Unit convenor and teaching staff Unit Convenor Dr. Adam Stebbing adam.stebbing@mq.edu.au Contact via Email W6A 824 By appointment Tutor Dr. Ben Manning benjamin.manning@mq.edu.au Contact via Email
Credit points	Credit points 3
Prerequisites	Prerequisites (30cp at 100 level or above including (SOC224 and (SSCI200 or SSC200))) or (admission to BSocSc and 3cp from SOC units at 300 level)
Corequisites	Corequisites
Co-badged status	Co-badged status
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.

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 techniques
Learn how to develop hypotheses for quantitative data analysis
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 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
Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences

General Assessment Information

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.

Assessment Tasks

Name	Weighting	Hurdle	Due
Short Quiz 1	15%	No	7th April
Short Quiz 2	25%	No	Week 9 lecture
Data Analysis Task	50%	No	10th June
Workshop Engagement	10%	No	Ongoing

Short Quiz 1

Due: 7th April
Weighting: 15%

This short quiz will consist of 15 multiple choice questions and you will have 20 minutes to complete it. You will be asked to read each question and select the BEST response from the available options. The short quiz is designed to provide you with an early insight into how you are going in the course. It will draw on course materials from the lectures and workshops.

The online quiz will become available on Monday 3rd April and you can undertake the quiz until Friday 7th April (at 11:59 pm EST). It will become available via the SSCI300 iLearn page. The quiz can only be taken once.

More information will become available in the early weeks of semester. Please follow the Disruptions to Studies policy when applying for an extension.

N.B. In the event of technical difficulties, it is your responsibility to contact the unit convenor before the due date. We advise you to ensure that you can access the link to the quiz on Wednesday 5th April at the very latest (without starting the quiz unless you want to).

On successful completion you will be able to:

Learn how to analyse and interpret data collected from social research using a range of techniques
Learn how to develop hypotheses for quantitative data analysis
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 lecture
Weighting: 25%

This short quiz will be administered in the second half of the week 9 lectures. Students will have 40 minutes to complete the quiz (including 5 minutes reading time). It will focus on course materials from earlier in the course up to week 8. 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 both lectures and workshops.

More information on the quiz will be provided in weeks 7 and 8. Attendance is compulsory. Please follow the Disruptions to Studies policy to apply for an extension.

On successful completion you will be able to:

Learn how to analyse and interpret data collected from social research using a range of 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: 10th June
Weighting: 50%

The major assessment for SSCI300 is a data analysis report of 1,800 to 2,000 words. This task requires you to exercise your social research imagination to analyse secondary data in relation to a specific research topic. Both the research topics and associated datasets for this task will be provided and become available on the SSCI300 iLearn page during the mid-semester break. Each of the options requires a different balance of qualitative and quantitative dataanalysis to be undertaken.

This task will require you to select a research topic (and its related dataset) from the options made available on the iLearn page. You will need to do some background reading on the topic and critically reflect on it. This task will also require you to analyse qualitative and/or quantitative data using appropriate techniques that we cover in the course, and, write up your findings in the format of a report. And, this task will require you to write a reflection on using NVivo to analyse qualitative data as an appendix (this appendix does not have to count toward you word count, but it should be no more than 350 words).

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. 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.

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 and 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 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 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
Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences

Workshop Engagement

Due: Ongoing
Weighting: 10%

The weekly workshops are compulsory. In light of the ambitious nature of this course, we have organised 90 minute sessions for the weekly workshops. 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 based on your 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 techniques
Learn how to develop hypotheses for quantitative data analysis
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 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 W5C 220 Tutorial Room on Mondays from 11am to 1pm.

Workshops in W6B 157 Sociology Computer Lab on Monday at 1pm and 2.30pm as well as Thursday at 10am and 11.30am.

Technology used

The following technologies are used in SSCI300...

iLearn

Important information about the weekly schedule for SSCI300, course readings and assessment are all available on the course iLearn page. 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.

Turnitin and GradeMark

The written assessment for SSCI300 needs 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, you can download a copy of NVivo from the software downloads section of the student portal on the Macquarie University website (note that the Mac version of NVivo has fewer features).

Textbooks

This course draws on one required textbook:

Bazeley, P. and K. Jackson (2013) Qualitative Data Analysis with NVivo, 2nd Edition, Sage: Thousand Oaks.

For those interested in a textbook for the first half of the course, the following is recommended (but not required):

Pallant, J. (2013) SPSS Survival Manual: A step by step guide to data analysis using IBM SPSS, 5th Edition, Allen & Unwin: Sydney.

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	Lecture Topics	Workshop Topics
1	Introduction to SSCI300: The practice of social science research	No workshop
2	From Survey Methods to Quantitative Data Analysis	SPSS 1: Investigating variables
3	Developing Hypotheses: The ‘bread’ and ‘butter’ of quantitative reasoning	SPSS 2: Analysing tables and graphs Activity: Designing hypotheses
4	Making Inferences and Testing Hypotheses	SPSS 3: Confidence intervals & Cross-tabs Activity: Refining hypotheses
5	Testing for Associations	SPSS 4: Gamma & Correlation
6	Introducing Linear Regression	SPSS 5: Linear regression
7	Interpreting Logistic Regression Models	SPSS 6: Binary logistic regression
8	Making Sense of Qualitative Data with Computers	NVivo 1: Exploring data
9	Coding & Writing Memos	NVivo 2: Nodes, memos & annotations
10	Thematic Analysis: The staple of qualitative research	NVivo 3: Going further with nodes & queries
11	Thematic Analysis II: Identifying ‘categories’ and ‘themes’	NVivo 4: Visualising codes
12	Grounded Theory, Discourse Analysis & Analysing Narratives	Major project workshop
13	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_2016.html

Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html

Complaint Management Procedure for Students and Members of the Public http://www.mq.edu.au/policy/docs/complaint_management/procedure.html

Disruption to Studies Policy (in effect until Dec 4th, 2017): http://www.mq.edu.au/policy/docs/disruption_studies/policy.html

Special Consideration Policy (in effect from Dec 4th, 2017): https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policies/special-consideration

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/

Results

Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.

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://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Graduate Capabilities

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
Gain experience in critically analysing data relating to contemporary social issues
Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences

Assessment task

Data Analysis Task

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 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 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 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 techniques
Gain first-hand experience in using SPSS to conduct advanced quantitative data analysis, including how to interpret regression models
Gain first-hand experience in using NVivo appropriately to undertake advanced qualitative data analysis

Assessment tasks

Data Analysis Task
Workshop Engagement

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 techniques
Gain experience in critically analysing data relating to contemporary social issues
Further develop oral and written communication skills for conveying research results in an ethical, responsible and engaged manner to a range of audiences

Assessment task

Data Analysis Task