Use In Your Classroom

Data and Analysis strand:

1. Collection.
A music producer can decide what kinds of data to collect, how often to collect it, and where to collect it from. This relates to the emphasis in the CS K-12 framework on understanding that computing processes can be directed to collect particular variables, at a specific frequency, and from different sources.

2. Storage.
A music producer can choose how to store the data. At the most basic, different data sets store different variables. Further, it may cost more to acquire or store bigger volumes of data. The CS K-12 framework highlights that how you store the data can have a big impact on how you use it — for example, the location of a listener could be stored as a zip code, city name, or geographical coordinate — and this might change how useful the data is.

3. Visualization.
A music producer can visualize data in many forms. Lines may show trends in listeners or followers over time. A map might show where a song is being listened to. A bar chart might show how popular different types of songs are. The CS K-12 framework highlights that the different ways that data is visualized or transferred gives us information that can be used in different ways.

4. Inferences and Modeling.
A music producer will succeed on the basis of insights that use the collected, stored, and visualized data to generate insights that help their artist. In this game we focus on inferences, such as noticing that a particular mood is trending (e.g. sad songs). The CS K-12 framework emphasizes that more data, over time and from different sources (such as more people) helps us identify trends, develop better models of what might happen in the future.

In middle school math, students learn about creating and reading graphs, these skills and knowledge can help them with the game, but they made need teachers to point out the opportunities for transfer. Also, think about the ways in which the game is not just mathematics — for example, in middle school math we don’t normally worry about how data is stored nor about improving a decision-making model through repeated cycles of play.

This game may also offer opportunities to think about decisions about which data set to purchase and the social implications of data.

Alignment with CCSS for Math: Computational thinking with data aligns well with mathematical practices, but the fit is less good on content standards, especially for middle school.

The ‘Construct viable arguments and critique the reasoning of others’ practice involves reasoning inductively about data and making plausible arguments accounting for the context of the data, and bears similarity to the ‘Inference and Models’ CS concept.

The ‘Model with mathematics’ practice involves the ability to identify important quantities in a practical situation and analyze their relationships mathematically using tools like tables, graphs, flowcharts and formulae and bears similarities with the ‘Data transformation’ and ‘Inference and models’ CS concepts.

The fifth grade Measurement and Data concept for Math includes the ‘Represent and Interpret Data (CCSS.MATH.CONTENT.5.MD.B.2)’ concept that bears strong similarities with the ‘Visualization & Transformation’ and ‘Inference & Models’ components of the ‘Data and Analysis’ CS concept. For example, the 5th grade standards include making sense of a coordinate plane, and points and axes on a plane.

The fifth grade Math standards also include solving problems with line plots, and the third grade Math standards include making sense of bar plots – both well aligned to activities in the ‘Beats Empire’ game. While these constitute elementary school content standards, middle school students may still be having some trouble with reading the graphs and making comparisons using them.

Tentative fit to Algebra: There is opportunity for discussing proportional reasoning within a more complicated plot in the game – for example, reasoning about the portion of a line that is steeply sloped versus the portion that is flat can constitute proportional reasoning.

Data and Analysis is a very important computer science and computational thinking concept with strong connections to the Next Generation Science Standards (NGSS).

Alignment with NGSS Practices:

Planning and carrying out investigations involves collecting data from the real world and data about performance of systems and tools in order to produce data to serve as the basis for evidence to answer scientific questions or test design solutions under a range of conditions. It, however, does not encompass the concept of automatic data collection by computers, which is a vital CT concept.

Analyzing and interpreting data relates to multiple aspects of the Data and Analysis CS concept. This NGSS practice bears similarity to CS learning targets in terms of including the ability to analyze data and determine similarities and differences in data, but it also includes the ability to use statistical techniques and engage in error analysis – skills that are not typically defined as part of the CS framework .

Developing and Using Models involves developing, using, and revising models to describe, test, and predict phenomena and design systems. It is closely related to the Inference and models component of the Data and analysis CS concept.

Using Mathematics and Computational Thinking involves recognizing and applying quantitative relationships, predicting behavior of physical systems, and identifying patterns in large data sets – skills that align well with the ‘Visualization and transformation’ and ‘Inference and models’ aspects of the CS Data and Analysis concept.

1. In courses dealing with CULTURE: They will acquire knowledge and understanding of culture through multiple modes, including fiction and non-fiction, data analysis, meeting and conversing with peoples of divergent backgrounds, and completing research into the complexity of various cultural systems.

2. In courses dealing with GEOGRAPHY, REGIONAL STUDIES, AND WORLD CULTURES: Student experiences will encourage increasingly abstract thought as they use data and apply skills in analyzing human behavior in relation to its physical and cultural environment.

3. In courses dealing with PRODUCTION, DISTRIBUTION, AND CONSUMPTION: Students will gather and analyze data, as well as use critical thinking skills to determine how best to deal with scarcity of resources. The economic way of thinking will also be an important tool for students as they analyze complex aspects of the economy.