Section 5.0.0

DAT-2.A: Describe what information can be extracted from data. 

• • DAT-2.A.1 Information is the collection of facts and patterns extracted from data.

  • DAT-2.A.2 Data provide opportunities for identifying trends, making connections, and addressing problems. 

  • DAT-2.A.3 Digitally processed data may show correlation between variables. A correlation found in data does not necessarily indicate that a causal relationship exists. Additional research is needed to understand the exact nature of the relationship. 

  • DAT-2.A.4 Often, a single source does not contain the data needed to draw a conclusion. It may be necessary to combine data from a variety of sources to formulate a conclusion.

DAT-2.B: Describe what information can be extracted from metadata. 

• • DAT-2.B.1 Metadata are data about data. For example, the piece of data may be an image, while the metadata may include the date of creation or the file size of the image. 

  • DAT-2.B.2 Changes and deletions made to metadata do not change the primary data. 

  • DAT-2.B.3 Metadata are used for finding, organizing, and managing information.

  • DAT-2.B.4 Metadata can increase the effective use of data or data sets by providing additional information. 

  • DAT-2.B.5 Metadata allow data to be structured and organized.

DAT-2.C: Identify the challenges associated with processing data. 

• • DAT-2.C.1 The ability to process data depends on the capabilities of the users and their tools. 

  • DAT-2.C.2 Data sets pose challenges regardless of size, such as: § the need to clean data § incomplete data § invalid data § the need to combine data sources

  • DAT-2.C.3 Depending on how data were collected, they may not be uniform. For example, if users enter data into an open field, the way they choose to abbreviate, spell, or capitalize something may vary from user to user. 

  • DAT-2.C.4 Cleaning data is a process that makes the data uniform without changing their meaning (e.g., replacing all equivalent abbreviations, spellings, and capitalizations with the same word). 

  • DAT-2.C.5 Problems of bias are often created by the type or source of data being collected. Bias is not eliminated by simply collecting more data.

  • DAT-2.C.6 The size of a data set affects the amount of information that can be extracted from it. 

  • DAT-2.C.7 Large data sets are difficult to process using a single computer and may require parallel systems. 

  • DAT-2.C.8 Scalability of systems is an important consideration when working with data sets, as the computational capacity of a system affects how data sets can be processed and stored. 

DAT-2.D: Extract information from data using a program. 

• • DAT-2.D.1 Programs can be used to process data to acquire information.

  • DAT-2.D.2 Tables, diagrams, text, and other visual tools can be used to communicate insight and knowledge gained from data. 

  • DAT-2.D.3 Search tools are useful for efficiently finding information. 

  • DAT-2.D.4 Data filtering systems are important tools for finding information and recognizing patterns in data. 

  • DAT-2.D.5 Programs such as spreadsheets help efficiently organize and find trends in information.

  • DAT-2.D.6 Some processes that can be used to extract or modify information from data include the following: § transforming every element of a data set, such as doubling every element in a list, or adding a parent’s email to every student record § filtering a data set, such as keeping only the positive numbers from a list, or keeping only students who signed up for band from a record of all the students § combining or comparing data in some way, such as adding up a list of numbers, or finding the student who has the highest GPA § visualizing a data set through a chart, graph, or other visual representation

DAT-2.E: Explain how programs can be used to gain insight and knowledge from data.

• • DAT-2.E.1 Programs are used in an iterative and interactive way when processing information to allow users to gain insight and knowledge about data.

  • DAT-2.E.2 Programmers can use programs to filter and clean digital data, thereby gaining insight and knowledge. 

  • DAT-2.E.3 Combining data sources, clustering data, and classifying data are parts of the process of using programs to gain insight and knowledge from data.

  • DAT-2.E.4 Insight and knowledge can be obtained from translating and transforming digitally represented information. 

  • DAT-2.E.5 Patterns can emerge when data are transformed using programs.

AAP-3.F For simulations: 

1. Explain how computers can be used to represent real-world phenomena or outcomes

2. Compare simulations with real-world contexts

   • AAP-3.F.1 Simulations are abstractions of more complex objects or phenomena for a specific purpose. 

   • AAP-3.F.2 A simulation is a representation that uses varying sets of values to reflect the changing state of a phenomenon. 

   • AAP-3.F.3 Simulations often mimic real-world events with the purpose of drawing inferences, allowing investigation of a phenomenon without the constraints of the real world. 

   • AAP-3.F.4 The process of developing an abstract simulation involves removing specific details or simplifying functionality. 

   • AAP-3.F.5 Simulations can contain bias derived from the choices of real-world elements that were included or excluded. 

   • AAP-3.F.6 Simulations are most useful when real-world events are impractical for experiments (e.g., too big, too small, too fast, too slow, too expensive, or too dangerous). 

   • AAP-3.F.7 Simulations facilitate the formulation and refinement of hypotheses related to the objects or phenomena under consideration.

IOC-1.E: Explain how people participate in problem-solving processes at scale.

• IOC-1.E.1 Widespread access to information and public data facilitates the identification of problems, development of solutions, and dissemination of results. 

• IOC-1.E.2 Science has been affected by using distributed and “citizen science” to solve scientific problems.

• IOC-1.E.3 Citizen science is scientific research conducted in whole or part by distributed individuals, many of whom may not be scientists, who contribute relevant data to research using their own computing devices. 

• IOC-1.E.4 Crowdsourcing is the practice of obtaining input or information from a large number of people via the Internet. 

• IOC-1.E.5 Human capabilities can be enhanced by collaboration via computing. 

• IOC-1.E.6 Crowdsourcing offers new models for collaboration, such as connecting businesses or social causes with funding.