Case Study – Primary – Claver-Jesuïtes & Maristes – Lleida, Spain

In Lleida (Spain), 75 9/10-year-old students investigated during 25 lessons if there was any relationship between weather (such as temperature, wind, pluviometry, foggy, etc.) and chocolate consumption (such as type of chocolate and consumption frequency).

Key data analytic skills were taught such as: define a research question, collect and consider data, interpretation of graphs, graphical data, interpretation of averages and drawing conclusions from data. The students used CODAP (https://codap.concord.org/) to explore and interpret their data. Furthermore, students studied basic statistical concepts, such as appropriate measures of central tendency (mean, mode, median) based on the Catalan national curriculum.

After the implementation of the first pilot project, it was decided that explicit focus was needed on the followings: (1) defining a research question (2) enriching data collection tools (3) acquiring notion of distribution as an aggregate group of data values, (4) using of dot plot representation to visualize distribution shape, and (5) a trial activity for exploring how to use CODAP to organize and analyze data before the actual project.

The project began with the general question: why do we like chocolate so much? After a whole group discussion about their chocolate consumption habits, some more questions were raised: is chocolate consumption related to the weather? Do men and women have the same preferences for chocolate? This motivated students to investigate if the weather and other variables were related.

The students working in groups of four formulated their research questions and hypothesis. Special support was given in order to ensure that young students learn to formulate feasible hypothesis. Students formulated hypothesis such as: a) When it rains, as temperature decreases, the consumption of chocolate is higher; b) if the temperature is high then the consumption of chocolate is lower, and c) women eat less chocolate than men because they want to be healthier and slimmer.

In order to support students understanding of data analytics skills, a roadmap was built in a central area of the class. This roadmap helped students be aware of the different phases of the project and create meaningful knowledge with the data analytics skills that they were implementing.

Data sets were collected by students using on-line questionnaires. Three sessions were devoted to formulate the adequate questions in the on-line questionnaire in order to collect the right data to evaluate their hypothesis. The on-line questionnaires that students created were used to build common understanding on the concept of independent variable (such as:  age, gender, country) and dependent variable (such as type of chocolate; consumption frequency or weather characteristics).  Catalan, Turkish and English people answered the on-line questionnaire. A total of 211 responses were collected (147 from Catalonia, 58 from Turkey and 6 from UK). Students learnt to organise the big data set and imported it into CODAP. The students used CODAP to explore and interpret their data. Thus, the students learned in small groups how to read, interpret and make their inferences and reach conclusions that finally led them to answer their research questions and validate or refute their hypothesis. In the last lessons, groups presented their findings to the class using the smart board and discussed them with the rest of the class.

Some of the conclusions that they reached based on their data analyses in CODAP were as follows:

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  • Chocolate consumption is related with age. 6-12 year-olds have the higher rate of chocolate consumption.

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  • Chocolate consumption is also related with gender. We hypothesized that women could eat less chocolate than men because they want to be healthier and slimmer. But data does not validate this hypothesis because, as it can be seen in the graph, women eat more chocolate than men.

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  • Chocolate consumption is strongly related with temperature. In hot days the consumption of chocolate is lower because it melts. As we can see in the graph, the majority of the sample does not eat chocolate (0 cases) or eats 1 portion of chocolate.

The project helped students with the understanding of the concept of variable and they were able to construct significant meaning to statistical concepts, such as data distribution, mean, mode, and median. Additionally, students were able to organize a big data set and to consider and interpret data to validate and refute their research questions. During the project, we could observe students’ positive attitudes towards learning statistical concepts with technology and higher confidence in using technological tools.

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