Students

SSCI2020 – Survey Research in the Social Sciences

2021 – Session 2, Weekday attendance, North Ryde

Session 2 Learning and Teaching Update

The decision has been made to conduct study online for the remainder of Session 2 for all units WITHOUT mandatory on-campus learning activities. Exams for Session 2 will also be online where possible to do so.

This is due to the extension of the lockdown orders and to provide certainty around arrangements for the remainder of Session 2. We hope to return to campus beyond Session 2 as soon as it is safe and appropriate to do so.

Some classes/teaching activities cannot be moved online and must be taught on campus. You should already know if you are in one of these classes/teaching activities and your unit convenor will provide you with more information via iLearn. If you want to confirm, see the list of units with mandatory on-campus classes/teaching activities.

Visit the MQ COVID-19 information page for more detail.

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor and Lecturer
Hangyoung Lee
Contact via Contact via Email
Room C311, Level 3 25C Wally's Walk
By appointment
Tutor
Luke Ashton
Contact via Contact via Email
By appointment
Credit points Credit points
10
Prerequisites Prerequisites
SSCI100 or SSCI1000
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

The unit introduces students to the logic of quantitative social inquiry, with a specific focus on social surveys. Social surveys are widely employed in today’s social science workplaces, with an array of uses in policy-making, public debate and social research. Survey methodologies collect systematic information about cases and present this information in a structured ‘data grid’, which can be used to test theoretically informed hypotheses and inferences. Surveys are used in many different types of studies, from quasi-experiments to cross-sectional and longitudinal studies. Building on SSCI1000 and SSCI2010, the unit focuses on linking quantitative research design to data analysis, including the deductive logic of quantitative research and analysis. Students learn how to develop survey questionnaires and collect other forms of quantitative data, as well as how to use computer software to analyse survey data. The unit aims to show that credible findings from survey research are as reliant on collecting valid and reliable data as they are on applying relevant analytic techniques.

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:

  • ULO1: Understand the link between quantitative research design, survey procedure and statistical analysis
  • ULO2: Analyse survey data using appropriate statistical models.
  • ULO3: Carry out a statistical analysis using SPSS.
  • ULO4: Interpret statistical outputs in plain language.
  • ULO5: Conduct original research using quantitative research methods.

General Assessment Information

Academic Integrity

Academic Integrity 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
  • Self-plagiarism (resubmitting your own work - including past assignments for this or other units - without attribution) is an unacceptable academic activity

 

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

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University.

 

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.

 

Special Consideration (Extensions)

The University recognises that students may experience events or conditions that adversely affect their academic performance. If you experience serious and unavoidable difficulties at exam time or when assessment tasks are due, you can consider applying for Special Consideration.

You need to show that the circumstances:

  1. were serious, unexpected and unavoidable
  2. were beyond your control
  3. caused substantial disruption to your academic work
  4. substantially interfered with your otherwise satisfactory fulfilment of the unit requirements
  5. lasted at least three consecutive days or a total of 5 days within the teaching period and prevented completion of an assessment task scheduled for a specific date.

More information about Special Consideration is available in the Policies and Procedures section of the unit guide.

 

Late Penalties

Unless a Special Consideration request has been submitted and approved, a penalty for lateness will apply – ten (10) marks out of 100 will be deducted per day for assignments submitted after the due date (or extended due date in cases where special consideration is granted). No late submissions will be accepted for timed assessments – e.g. quizzes, online tests.

Student Wellbeing

Macquarie University offers a range of wellbeing services (including [but not limited to]: health, welfare, counselling, disability and student advocacy services) that are available to you at any time during your studies. Campus Wellbeing is here to support you and help you succeed, both academically and personally. More information is available in the Policies and Procedures section of the unit guide.

Assessment Tasks

Name Weighting Hurdle Due
Quiz 1 20% No 3/9/2021
Quiz 2 20% No 29/10/2021
Data Analysis Report 40% No 12/11/2021
Active participation 20% No Ongoing

Quiz 1

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 4 hours
Due: 3/9/2021
Weighting: 20%

 

First Online Quiz

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Analyse survey data using appropriate statistical models.
  • Interpret statistical outputs in plain language.

Quiz 2

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 4 hours
Due: 29/10/2021
Weighting: 20%

 

Second Online Quiz

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Analyse survey data using appropriate statistical models.
  • Interpret statistical outputs in plain language.

Data Analysis Report

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 42 hours
Due: 12/11/2021
Weighting: 40%

 

1,800 to 2,000 word research report

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Analyse survey data using appropriate statistical models.
  • Carry out a statistical analysis using SPSS.
  • Interpret statistical outputs in plain language.
  • Conduct original research using quantitative research methods.

Active participation

Assessment Type 1: Participatory task
Indicative Time on Task 2: 11 hours
Due: Ongoing
Weighting: 20%

 

Active participation in unit sessions

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Carry out a statistical analysis using SPSS.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Lecture and workshop times

Lectures are delivered online due to the COVID-19 restriction. Lecture recordings will be uploaded every Monday. Students can access lecture recordings and lecture presentation files on the course iLearn page.

Workshops will take place on Tuesdays and Wednesdays in  25 Wallys Walk - B237 Digital Laboratory(On-campus workshop) or via Zoom(Online workshops). The links to Zoom online workshops are available on the course iLearn page. Also, the Workshop instructions are available at https://methods101.com. Click SSCI2020 at the left sidebar. You will see 12 workshop guidelines. For completing Workshop tasks, students can seek advice and help from tutors in the workshop sessions.

Textbooks

This course draws on one required textbook:

  • Leon-Guerrero, Anna and Chava Frankfort-Nachmias (2018) Essentials of Social Statistics for a Diverse Society, 3rd Edition. Sage: Thousand Oaks.

For those who find the required textbook difficult to read,  the following textbook(optional) is recommended:

  • Wheelan, Charles J. (2014) Naked Statistics: Stripping the Dread from the Data, W.W. Norton & Company.

Technology used

The following technologies are used in SSCI2020:

Email

Make sure that you regularly check your student email for correspondence with teaching staff and course announcements.

iLearn

Important information about the weekly schedule for SSCI2020, 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.

SPSS

SPSS is the primary statistical analytic tool for SSCI2020. Learning SPSS to analyse datasets is an essential component of this unit. SPSS is available in the workshops and some computers in the library and digital lounge (C5C - 17 Wally’s Walk). Students can also access remotely SPSS through AppStream (see below).

AppStream

AppStream is the university's a new application streaming service which provides students access to existing iLab applications via browser from anywhere, anytime, on any device. Students do not need to install a client on their device to access applications. Google Chrome is recommended browser for AppStream. Login to mq.okta.com with your MQ OneID to access AppStream applications.

Methods101.com

Workshop guidelines are available at https://methods101.com/docs/. The website provides easy-to-follow instructions on how to use SPSS to analyse data. In the website, click SSCI2020 at the left sidebar. Then, you can access the guidelines for each workshop. If you do not have access, please contact the unit convenor.

Turnitin and GradeMark

The written assessment for SSCI2020 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 due date of the assessment). Assessments will be marked via GradeMark and returned to students electronically.

Leganto

Leganto is the electronic system for accessing unit readings that can be accessed via the iLearn page. Readings are allocated by weekly schedules. As well as the required readings for each week, you will find recommended and optional readings. The required readings are available in pdf or electronic format. If you are not able to access the readings, please contact the unit convenor via email.

Zoom

Zoom is an online video conferencing software platform. It is used for online workshops, optional meetings, and consultation.

Unit Schedule

Week Lecture SPSS Workshop
1 Introduction to Quantitative Research Methods No workshop
2 Quantitative Research Design Introduction to SPSS
3 Univariate Statistics Exploratory Data Analysis 1
4 Statistical Charts and Normal Distribution Exploratory Data Analysis 2
5 Normal Distribution Normal Distribution and Z-scores
6 Sampling and Sampling Distribution Random Sampling Experiment
7 Estimating Confidence Intervals Computing Confidence Intervals 
8 Testing Hypotheses T-test
9 Bivariate Association Cross-table and Chi-square
10 Correlation and Regression Correlation and Regression Analysis
11 Multiple Regression Model Multiple Regression Analysis 1
12 Dummy Variables in Regression Model

Multiple Regression Analysis 2

13 Consultation for Data Analysis Report Consultation for Data Analysis Report

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) 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 or if you are a Global MBA student contact globalmba.support@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 help you improve your marks and take control of your study.

The Library provides online and face to face support to help you find and use relevant information resources. 

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

If you are a Global MBA student contact globalmba.support@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.

Additional Information on Assessment Tasks

Quiz 1

Quiz 1 will be administered online via the course iLearn page. It will consist of 20 multiple-choice or true-or-false questions, and you will have 40 minutes to complete it. You will be asked to read each question and select the BEST response from the available options. This quiz will draw on course materials from the lectures and workshops from week 1 to week 6.

The online quiz will become available on Thursday 3rd September, and you can undertake the quiz until Friday 4th September (at 11:59 pm EST). It will become available via the SSCI202 iLearn page. The quiz can be taken only once, and it is up to you to ensure that you have time available to undertake the quiz.

More information will become available in week 5 lecture. Please follow the Special Consideration policy when applying for an extension. As per the Faculty of Arts policy, no late submissions will be accepted for the online quiz without an extension.

Note) In the event of technical difficulties, it is your responsibility to contact the unit convenor before the due date and follow the instructions on iLearn in notifying the university. We advise you to ensure that you can access the link to the quiz on Thursday 3rd September (without starting the quiz unless you want to).

Quiz 2

Quiz 2 will also be administered online via the course iLearn page. Again, students will have 40 minutes to complete the quiz (which consists of 20 multiple-choice or true-false questions). It will focus on course materials from week 7 to week 12.

The online quiz will become available on Thursday 29th October, and you can undertake the quiz until Friday 30th October (at 11:59 pm EST). It will become available via the SSCI202 iLearn page. The quiz can be taken only once, and it is up to you to ensure that you have time available to undertake the quiz.

More information will be provided in week 11 lecture. Please follow the Special Consideration policy when applying for an extension. As per the Faculty of Arts policy, no late submissions will be accepted for the online quiz without an extension.

Note) In the event of technical difficulties, it is your responsibility to contact the unit convenor before the due date and follow the instructions on iLearn in notifying the university. We advise you to ensure that you can access the link to the quiz on Thursday 29th October (without starting the quiz unless you want to).

Data Analysis Report

The major assessment for SSCI2020 is a data analysis report of 1,800 to 2,000 words. This task is designed to assess students’ overall ability to address social science inquiries using quantitative research skills. It will require you to select a research topic (and its related datasets) from the options made available on the iLearn page. You will need to do some background reading on the topic, critically reflect on it, formulate research hypotheses, analyse the related dataset, and interpret the statistical outcomes. Using SPSS is a must for this task. You will learn all the necessary SPSS skills in the workshops throughout the semester.

Both the research topics and related datasets for this task will be provided and become available on the SSCI2020 iLearn page in week 8. The report 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 before the due date. More information will be provided in week 8 lecture.

Active Participation

Internal students are expected to listen to lecture recordings and review workshop guides (See https://methods101.com. For more details, see the course iLearn page) every week. Also, students are expected to complete Weekly Participation Activities which check the understanding of major topics of lectures and the completion of workshop tasks. The links to Weekly Participation Activities will be available via the course iLearn page (under the section of each week).

Internal students' active participation grade will be based on:

  • listening to the recording of lectures every week.
  • reviewing workshop guides every week.
  • completing Weekly Participation Activities.
  • engaging respectfully with other students in the workshop.

Unit information based on version 2021.01R of the Handbook