You can use this template to summarise your teaching activity. Examples can be found from our case study pages.

For designing your own project based learning, you can use Data Analytic Framework to frame your activity. For example, in below, 9 hours of activities were planned by considering 1. Defining the problem, 2 & 3. Consider and exploring data, 4 & 5. Drawing conclusions and making decisions.

Although there is no perfect way to teach DA, the following points are worth considering when you design your activities:

- Task design – Real world problems are related to students’ interests and require real (multivariate) data to be explored through using various models and representations. Also comparing sets of data will be useful strategies to encourage statistical inferences in their data analytics learning processes.
- Taking a project based approach – problems are complex, and ill-structured. Therefore students have to make sense of problem context, organise and model data so that they can manage and work with, and make decisions and inferences about data and their interpretations.
- Teachers’ roles – teachers enrich, structure and scaffold students’ collaborative inquiry, give specific and planned guidance, be an organiser of the shared knowledge practices and support the dialogue of students to create the shared object.
- Use of technology – use tools such as TinkerPlots or CODAP (Finzer, 2016) which can provide multiple and dynamic representations of data and models.
- Students’ affection towards DA – it is necessary to provide safe and encouraging learning environments to reduce their anxiety levels.

**(a)** Recognising the need for data;

**(b)** Generating specific questions that can be answered with data e.g. “Does weather affect students behaviour?”; Use gap minder etc. to consider what issues can be explored? We used a group discussions to develop what our students were interested in.

**Possible Questions to be Explored**

1. Drag and drop data from the table left to the graphs right, and explore tempratures etc. in 2018 and 2019. For example, is there any relationship between daily temprature and daily radiation?;

2. Explore students’ attendance and day, etc. Can you find any patterns?;

3. Explore attendance and temprature, etc. Do you think there are any relationships between students’ health and weather?;

4. Discuss what measurement such as mean, median etc. can be used to represent data?;

5. Summarise your findings by explicitly stating what evidence can be used to state your conclusions? Also what implications can you make based on your findings?

**(a)** Using data as evidence for generalisations beyond describing the given data;

** (b)** Expressing an articulation of uncertainty;

**(c)** Communicating what has been learned e.g. “Students’ attendance might be worse on Friday”, “there might be a correlation between daily radiation and daily maximum temperatures”, etc.

You can ask students to create a summary video! An example is available from here.

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