36201 Arguments, Evidence and Intuition
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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 2020 is available in the Archives.
Credit points: 8 cp
Subject level:
Undergraduate
Result type: Grade and marksDescription
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 sessions: The content in this subject is delivered online in weekly units. You will participate in online interactivities, quizzes, problem solving, and discussions.
By participating, you will receive opportunities to work towards your assessments and receive formative feedback from tutors to support your work.
Independent learning activities: There may be online activities to complete before each week: reading; completing online quizzes; viewing screencasts and videos. The online quizzes are used to help you to review your learning.
Participation in all activities is expected.
Content (topics)
The topics covered in each semester will be drawn from:
- Types, and qualities of arguments and evidence
- Contentious Issues
- Descriptive Statistics (Central tendency, dispersion/variability)
- Correlation and Causation
- Visual display of data
- Finding and manipulating data using spreadsheet software
- Telling and evaluating a data story
- 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. This task contributes to the development of Graduate Attributes 1 and 3. |
|---|---|
| Objective(s): | This assessment task addresses subject learning objective(s): 2 and 3 |
| Type: | Exercises |
| Groupwork: | Individual |
| Weight: | 20% |
| Criteria: | Criteria: (1) Make accurate numerical judgements and calculations concerning data in everyday and professional contexts. Criteria: (2) Read, interpret and construct graphs to illustrate numerical data. |
Assessment task 2: Data in the World: A Data Journey
| Intent: | This task requires you to analyse data to tell a story that is of personal or professional interest to you. You will apply the statistical and communication skills developed in the class sessions to the dataset, to tell a story about that data. The purpose of this activity is to give you experience in why and how to find data, how to analyse collected data and how to use the data to tell a story. You should draw conclusions based on analysis of your data. We will provide examples of data stories, and you may find additional authentic examples at the subject’s Diigo site https://groups.diigo.com/group/uts-aei/content/tag/data-story This task contributes to the development of Graduate Attributes 1, 2, 3 and 6. |
|---|---|
| Objective(s): | This assessment task addresses subject learning objective(s): 1, 2, 3, 4 and 5 |
| Type: | Project |
| Groupwork: | Individual |
| Weight: | 35% |
| Length: | Written report 1750 words (excluding appendices and cover sheet) |
| Criteria: | See above re: compulsory formative activities.
|
Assessment task 3: Contentious Issues: Dealing with Disagreement
| 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. This task contributes to the development of Graduate Attributes 1, 2, 3, 4, 5 and 6. |
|---|---|
| Objective(s): | This assessment task addresses subject learning objective(s): 1, 2, 3, 4 and 5 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 45% |
| Length: | Written report 2100 words, Oral presentation in class on 26th May 2020: no more than 10 slides. |
| Criteria: | See above and assessment guide re: compulsory components of the report.
|
Minimum requirements
To pass this subject you are expected to participate in the majority of in-class activities.
Timely completion and submission of assessment tasks, including formative assessments, is expected. Students who anticipate difficulty in submitting on time are encouraged to request extensions at least 24 hours prior to the deadline, through the Special Consideration Process.
A penalty of 10% per day 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.
If we had to recommend one book to everyone (in AEI, and everywhere!) it would be:
Levitin, D. J. (2016) A Field Guide to Lies: Critical Thinking in the Information Age. Penguin Publishing Group. **** Highly recommended. A kindle edition is available.
The following two books are also excellent and cover many of the themes discussed in AEI:
- Kahneman, D. (2011) Thinking, Fast and Slow Penguin
- Sutherland, S. (2013) Irrationality: The Enemy Within, Pinter & Martin Ltd
You may also wish to explore:
Boslaugh, S. & Watters, P. (2008) Statistics in a Nutshell O’Reilly
Bowell, T. & Kemp, G. (2002) Critical Thinking A Concise Guide Routledge
Laing, L. (2014) Math for Writers Limitless Press A kindle edition is available. (Especially chapters 1 - 4)
Singh, S. (2013) The Simpsons and Their Mathematical Secrets Bloomsbury
Tufte, E. (1992) The Visual Display of Quantitative Information Graphics Press
Other resources
All UTS students are welcome to study in the Drop-in Room of the Mathematics and Science Study Centre, CB04.03.331. During session times there are tutors available there to answer your questions about mathematics and statistics.
Some key online resources:
- The Library has created a Subject Guide
- Free short (16) page guide ‘Making sense of statistics’
- A brief visual guide to logical fallacies
- The Book of Bad Arguments (free online guide)
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 will find it useful to bring a laptop, tablet or smart phone to class. Laptops 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.