36200 Arguments, Evidence and Intuition
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Subject handbook information prior to 2017 is available in the Archives.
Credit points: 6 cp
UndergraduateResult type: Grade and marks
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. For example, the first online quiz will ask you questions on the content in Sessions 1 & 2. In Session 3 you will share your quiz answers in small groups giving and receiving feedback. To support you in developing your report writing skills you will complete a benchmarking activity prior to T & L Session 7. Benchmarking means that you will be given exemplars of the Task 4 report (student work from previous semesters), which you will grade using the task assessment rubric.You will put your grades into SPARKPLUS software on UTSOnline and discuss and justify your grade allocation in Session 7.
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.
The topics covered in each semester will be drawn from:
- The structure of arguments
- Sources and qualities of evidence
- Contentious issues
- Graphs, charts and tables
- Data visualisation
- Probability, odds and risk
- Randomness, variation, coincidences, populations and estimation
- Use and abuse of statistics
- Data analytics and mining
- The narrative of numbers - telling an effective story
Assessment task 1: Formative pre-class and in-class learning activities
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 quizes, collaborative activities, and other exercises.
Assessment task 2: Data in the World: The Quantified Self
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.
Written report 25% (5-8 pages, about 1600 - 2600 words)
Oral presentation 5% (5 minutes)
Assessment task 3: Mini-task on Arguments and Evidence: Analysing the Data Story
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.
|Groupwork:||Group, group and individually assessed|
1 page maximum
Assessment task 4: Arguments and Evidence: The Data Story
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.
Written report (35%) 8 to 10 pages
Oral presentation (5%) 5 minutes
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.
There are no set texts for this subject; however, there are many books that will be of interest to participants.
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