Unit 1: Applied Computing

Area of Study 1: Data analysis

Outcome 1

Interpret teacher-provided solution requirements and designs, collect and manipulate data, analyse patterns and relationships, and develop data visualisations to present findings.

Examples of learning activities

• Prepare a presentation for the class that contains several examples of data, both qualitative and quantitative. In a whole-class discussion, students classify each example as being either qualitative or quantitative. A Kahoot! activity could be used requiring students to classify statements as being either qualitative or quantitative, such as: ‘28% of households shopped at Aldi last month’ or ‘Many parents feel guilty when buying fast-food’.
• Watch the short video ‘Analytics in the AFL – The Most Data Rich Sport on Earth’. In small groups, students are each assigned a role from the following list: player, coach, football fan, sports journalist. Each group discusses the characteristics of data and information from the perspective of the assigned roles. A spokesperson from each group is nominated to report back to the class, summarising their group’s discussions.
• Assign students to small groups to research sources, methods and techniques for acquiring and referencing primary and secondary data and information. Groups generate American Psychological Association (APA) citations of the websites that their research is based upon, using an online citation tool, such as Citefast, Endnote, etc.
• Introduce students to an e-commerce case study, such as how Amazon’s recommendations have been integrated throughout their purchasing process. Students discuss the impact that this strategy has on a customer’s decision-making and the impact on Amazon’s sales revenue. In a subsequent activity, students work in small groups to analyse data and interpret the resulting information, including arriving at a concluding statement, which is then communicated to the class.
• Discuss the factors affecting the quality of data and information, such as accuracy, bias, integrity, relevance and reliability. Screenshots of sample data featuring these characteristics are shown to the students who identify the issues with the data samples.
• Provide students with a recent newspaper article that features a story of interest to them (e.g. from the fields of nutrition, sport or crime) and which contains several distinct pieces of data. Students are required to analyse the news story and extract all data, assigning each piece of data to an appropriate data type. The activity can be undertaken individually or in a small group and results shared with the class. Following on from this preliminary activity, the class discusses the way in which this data could be stored as data structures in programs (e.g. in arrays, lists or queues) prior to being used in databases and spreadsheets.
• Students research online an ethical dilemma involving data. They discuss and present the legal and ethical issues and include in their discussion the use of data and information. In a separate component of this activity, students create a sample consent form that can be used to collect data from people.
• Students research how physical and software security controls can be used to protect data and information from misuse. The outcome of the research can be presented as an information sheet or checklist.
• Discuss the structural characteristics of spreadsheets and databases in a teacher-prepared presentation. In a follow-up Kahoot! activity students respond to questions and scenarios on the characteristics of spreadsheets and databases, where they identify the main features of the software tools.
• Students complete a series of database exercises:
  • create tables
  • set up validation rules
  • enter data
  • create queries
  • create reports
  • test the database.
• Prepare sample data that is pre-loaded into a database and have students extract the data and import into a spreadsheet. Depending on the database management system used, students might use features within the software tool to extract the required data, or execute a ‘select’ statement against the database and have the output of the ‘select’ statement written to a CSV file and then save it in a spreadsheet.
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  Assign students to work in groups to locate and analyse an online news story that contains a data visualisation. Each group is to report back to the class, via a multimedia presentation, the results of the analysis, such as: target audience, key information presented in the data visualisation, any inaccuracies or ambiguities, and suggested improvements to better inform and persuade the targeted audience.
  
• Provide students with a case study that contains the need for a data solution. Students engage in a whole-class discussion to discuss and critically analyse the scenario, identifying the functional and non-functional requirements of the proposed solution, the constraints imposed and scope of the proposed solution.
  

• Provide students with an authentic set of data, possibly from an area of student interest. Examples of authentic data can be found on websites such as: FiveThirtyEight; Bureau of Meteorology; and Climate Science. Students identify a guiding question and then create annotated diagrams or mock-ups for a spreadsheet, database and data visualisation. As an extention, students can create data visualisations for the annotated diagrams or mock-ups from the activity.

• Prepare a presentation that contains images sourced from a current organisation, such as a government department. Discuss the importance of formats and conventions. Students work collaboratively in small groups, mimicking an organisation, to develop a set of formats and conventions for databases, spreadsheets and data visualisations.
• Assign students to work in small groups to devise three or four questions that can be used to check whether the Australian Privacy Principles are being followed in an organisation. Each group’s list is then combined to create a class list. The questions should relate to the Australian Privacy Principles explicitly mentioned in the study design: Principles 2, 6 and 11.
• Use a reasonably contemporary issue, such as the ‘My Health Record’, as the basis for a case study featuring an ethical issue arising from the acquisition, storage and use of data and information. Students work in small groups, with each student assigned a role from one of the following: doctor, government official from the Department of Health, family member, and the person deciding on whether or not to opt out of the ‘My Health Record’. Students discuss their points of view and present to the class.

Detailed example

Analysis of data visualisations in the media

Data visualisations are important tools to businesses and organisations because they allow the target audience to quickly and easily understand the information being presented. In this activity students are provided with the opportunity to gain an insight into data visualisations in an authentic context, as well as preparing those students planning on undertaking the Units 3 and 4 Data Analytics course. This activity is best suited as a collaborative task, collaboration being a key skill that teachers should foster with their students.

There are two suggested approaches that the teacher can use in running this activity. Firstly, they may provide each student group with the opportunity to search and locate a suitable media article of particular interest to them, and which contains a data visualisation. Alternatively, they can provide the online link to the media article containing the data visualisation.

Note: If the teacher opts for student choice in selecting the media article, an initial check of the data visualisation should be undertaken to ensure that it is appropriate for the activity and the student group.

Sample media articles can be found in a variety of fields and sources, such as:

• medicine and health (e.g. World Health Organisation, Ramon Martinez’s Health Intelligence)
• climate science (e.g. The Australia Institute; Asian Development Bank)
• sport and health science (e.g. Sport Australia)
• business and finance (e.g. IMF, World Economic Forum).

In this activity, students critically analyse the data visualisation and its context, and report back to the class with their findings. This can take the form of a multimedia presentation. Some factors for each group to consider when compiling their response are:

• the intended audience
• key information being presented and how well it achieves this objective
• any inaccuracies or ambiguities
• suggested improvements to better inform and persuade the targeted audience.