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36200 Arguments, Evidence and Intuition

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2017 is available in the Archives.

UTS: Analytics and Data Science
Credit points: 6 cp

Subject level:

Undergraduate

Result type: Grade and marks

Description

This subject promotes development of numeracy, quantitative literacy and critical thinking skills. Informed citizens need these skills to participate in discussion of significant issues in culture and society. Using primary research materials, governmental reports, and stories and claims drawn from current media and other sources, participants analyse and identify key features of numerical data and graphical illustrations used to support argument. By examining the ways that quantitative data can be collected, used and abused, as evidence for supporting argument, participants have an opportunity to develop habits of mind and lifelong learning skills that can be applied to the questions that should be asked, as informed citizens, of arguments and the supporting data. Participants apply their skills to construct a narrative that uses graphical and numerical data to tell a story, or support an argument, based on the principles explored in the subject.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:

1. Apply appropriate methods to collect and collate data.
2. Identify and apply key concepts in statistics and probability of direct relevance to quantitative literacy.
3. Describe and analyse the key features of the graphical and visual representation of data.
4. Demonstrate effective communication skills to a range of target audiences.
5. Demonstrate the quantitative literacy capacities of informed and ethically aware citizens, through the identification, description, and critique of the use of arguments and evidence, for example in topical or professional contexts.

Contribution to the development of graduate attributes

This subject is available to students in all faculties and undergraduate programs, thus many different graduate attribute profiles could be applied. The Faculty of Science's seven graduate attributes are used here to illustrate how this subject develops key graduate skills.

1. Disciplinary knowledge and its appropriate application
2. An Enquiry-oriented approach

3. Professional skills and their appropriate application

The ability to acquire, develop, employ and integrate a range of technical, practical and professional skills, in appropriate and ethical ways within a professional context, autonomously and collaboratively and across a range of disciplinary and professional areas. For example, time management skills, personal organisation skills, teamwork skills, computing skills, laboratory skills, data handling, quantitative and graphical literacy skills. [Subject Objectives 2 3, 4]

4. The ability to be a Lifelong Learner

The capacity to engage in reflection and learning beyond formal educational contexts that is based on the ability to make effective judgments about one’s own work. The capacity to learn in and from new disciplines to enhance the application of scientific knowledge and skills in professional contexts. [Subject Objectives 4, 5]

5. Engagement with the needs of Society

An awareness of the role of science within a global culture and willingness to contribute actively to the shaping of community views on complex issues where the methods and findings of science are relevant. [Subject Objectives 1, 2, 5]

6. Communication skills

An understanding of the different forms of communication - writing, reading, speaking, listening, visual and graphical - within science and beyond, and the ability to apply these appropriately and effectively for different audiences. [Subject Objectives 3, 4, 5]

Teaching and learning strategies

Interactive Teaching and Learning (T & L) sessions: The content in this subject is delivered in weekly T & L sessions by guest lecturers who are experts in the session’s topic. You will participate in collaborative quizzes, problem-solving, small group discussions and other collaborative learning activities such as benchmarking and in-class presentations with peer-review. To facilitate discussion and to provide you with Q & A and feedback opportunities many of the sessions will be attended by additional tutors.

Independent learning activities: The pre-class preparation in this subject is accessed online. The pre-work includes: reading; completing online quizzes; viewing screencasts and videos. The online quizzes are used to help you to review your learning.

Teaching notes (powerpoint slides) corresponding with each Teaching and Learning Session, including any associated electronic material or links, are uploaded to or linked from UTSOnline.

Attendance at all sessions is expected. Active participation in all in-class interactive activities, as well as attendance, are required in order to successfully complete the subject. Students who are absent from any of the in-class assessment activities are required to submit a request for special consideration.

Content (topics)

The topics covered in each semester will be drawn from:

  • Contentious Issues,
  • Types, and qualities of arguments and evidence
  • Correlation and Causation
  • Descriptive Statistics (Central tendency, dispersion/variability)
  • Visual display of data
  • Finding and manipulating data using spreadsheet software
  • Telling and evaluating a data story/Oral and written communication
  • Probability (including: absolute and relative risk; the normal distribution; polling, populations and estimation; randomness)
  • Data Analytics and data mining

Assessment

Assessment task 1: Formative pre-class and in-class learning activities

Intent:

The purpose of this activity is to give you formative experience across a set of the subject content in AEI, through application of your knowledge and skills in quizzes, collaborative activities, and other exercises.

Type: Exercises
Groupwork: Individual
Weight: 20%

Assessment task 2: Data in the World: The Quantified Self

Intent:

This task requires you to collect and analyse data to tell a story that is of personal interest to you. For example, you may choose to collect data about your: sleep patterns; exercise regime; time spent on Facebook and so on. Alternatively, you could undertake a new activity to generate data, for example: walking to work; learning a new video game or app. If you prefer, you could choose a set of quantitative data in the world which is of interest to you, for example: data about countries or regions you have visited on holiday.


The purpose of this activity is to give you experience in how to approach a data gathering exercise, how to analyse the data you’ve collected and how to use the data to tell a story. For example, your story could be about how you have improved your fitness. You should draw conclusions based on analysis of your data.

Type: Project
Groupwork: Individual
Weight: 30%
Length:

Written report 25% (5-8 pages, about 1600 - 2600 words) (This could be 800 - 1300 words if you use space for graphs etc.)

Oral presentation 5% (5 minutes)

Criteria:
  • Has applied appropriate methods to collect and collate original and external data.
  • Has applied key concepts in statistics and probability to draw conclusions from analysis.
  • Has created graphical and visual representations of data, which are described and analysed.
  • Has demonstrated effective communication skills appropriate to the written genre.
  • Has critiqued findings and analysis, drawing on relevant external information to demonstrate the quantitative literacy capacities of informed and ethically aware citizens.

Assessment task 3: Mini-task on Arguments and Evidence: Analysing the Data Story

Intent:

The purpose of this assessment is to provide you with a formative opportunity to collaboratively consider the ways data informs, and forms part of, news stories.

Type: Exercises
Groupwork: Group, group and individually assessed
Weight: 10%
Length:

1 page maximum (templates will be provided)

Criteria:
  • Suitability of the individually-selected resource for application of quantitative literacy skills
  • Identification of the key concepts in statistics and probability of relevance in the group-selected resource
  • Application of quantitative literacy capacities to evaluate the use and abuse of data in the resource
  • Identification of how further data would help develop your understanding of the issue

Assessment task 4: Arguments and Evidence: The Data Story

Intent:

The purpose of this assessment is to provide you with an opportunity to apply your quantitative literacy skills to a contentious issue, and to reflect on the way in which you draw on evidence to form your opinions.

Type: Report
Groupwork: Individual
Weight: 40%
Length:

Written report (35%) 8 to 10 pages (About 2600 - 3200 words. This could be 1300 - 1600 words if you use space for graphs etc.)

Oral presentation (5%) 5 minutes

Criteria:
  • Identifies, summarises, analyses and critiques the key arguments and quantitative evidence from the perspectives of the various stakeholders, drawing on a range of sources (standard academic referencing practices apply).
  • Identifies your position on the CI, and give a rationale for it including the independent arguments and quantitative evidence that inform it
  • Evaluates your position, explaining the evidence that would produce a change in your point of view
  • Has told a story about the CI that is engaging and coherent, and appropriate for the designated audience
  • Reflects appropriately on the peer feedback received on oral presentations

Minimum requirements

To pass this subject you are expected to participate in the majority of in-class activities including peer-review of presentations. Timely completion and submission of assessment tasks, including learning plans and progress reports, is expected.

A penalty will be incurred for late submissions (unless an extension has been granted due to extenuating circumstances).

References

There are no set texts for this subject; however, there are many books that will be of interest to participants.

Levitin, D. J. (2016). A Field Guide to Lies: Critical Thinking in the Information Age. Penguin Publishing Group. **** Highly recommended, the book covers many of the same issues as Arguments, Evidence, and Intuition.

Kahneman, D. (2011) Thinking, Fast and Slow Penguin **** Highly recommended

Boslaugh, S. & Watters, P. (2008) Statistics in a Nutshell O’Reilly
Bowell, T. & Kemp, G. (2002) Critical Thinking A Concise Guide Routledge
Singh, S. (2013) The Simpsons and Their Mathematical Secrets Bloomsbury
Tufte, E. (1992) The Visual Display of Quantitative Information Graphics Press
Tufte, E. (1990) Envisioning Information Graphics Press

Other resources

Some key online resources:

UTS offers students a free license for the Mathematica software package. Please see http://www.itd.uts.edu.au/services_facilities/mathematica.html for further details of how to download this if you are interested. Recommended!!

You may find it useful to bring a laptop to class. These can be borrowed from IT Support Centres in Building 10 (Level 2, Room 212 (CB10.02.212)), at time of writing open 9am-5pm Monday to Friday, or Building 5 (Block C, Level 1, Room 41 (CM05C.01.41)), at time of writing open 9am-9.30pm Monday to Friday.