Hardware and software work together to accomplish tasks, such as sending, collecting, receiving, processing and storing units of information. In computing system, information is stored and represented as bits, the basic unit of data. Data is organized, sorted, and transformed to provide clarity and to emphasize aspects. People use data to highlight relationship, make Inferences and prediction.
- Computing Systems (Hardware and Software)
- Data and Analysis (Collection, Visualization & Transformation; Inference & Models)
- Impacts of Computing (Social Interaction)
1B-CS-02 Model how computer hardware and software work together as a system to accomplish tasks. (P4.4)
In order for a person to accomplish tasks with a computer, both hardware and software are needed. At this stage, a model should only include the basic elements of a computer system, such as input, output, processor, sensors, and storage. Students could draw a model on paper or in a drawing program, program an animation to demonstrate it, or demonstrate it by acting this out in some way.
1B-CS-01 Describe how internal and external parts of computing devices function to form a system. (P7.2)
Computing devices often depend on other devices or components. For example, a robot depends on a physically attached light sensor to detect changes in brightness, whereas the light sensor depends on the robot for power. Keyboard input or a mouse click could cause an action to happen or information to be displayed on a screen; this could only happen because the computer has a processor to evaluate what is happening externally and produce corresponding responses. Students should describe how devices and components interact using correct terminology.
1B-DA-06 Organize and present collected data visually to highlight relationships and support a claim. (P7.1)
Raw data has little meaning on its own. Data is often sorted or grouped to provide additional clarity. Organizing data can make interpreting and communicating it to others easier. Data points can be clustered by a number of commonalities. The same data could be manipulated in different ways to emphasize particular aspects or parts of the data set. For example, a data set of sports teams could be sorted by wins, points scored, or points allowed, and a data set of weather information could be sorted by high temperatures, low temperatures, or precipitation.
1B-DA-07 Use data to highlight or propose cause and-effect relationships, predict outcomes, or communicate an idea. (P7.1)
The accuracy of data analysis is related to how realistically data is represented. Inferences or predictions based on data are less likely to be accurate if the data is not sufficient or if the data is incorrect in some way. Students should be able to refer to data when communicating an idea. For example, in order to explore the relationship between speed, time, and distance, students could operate a robot at uniform speed, and at increasing time intervals to predict how far the robot travels at that speed. In order to make an accurate prediction, one or two attempts of differing times would not be enough. The robot may also collect temperature data from a sensor, but that data would not be relevant for the task. Students must also make accurate measurements of the distance the robot travels in order to develop a valid prediction. Students could record the temperature at noon each day as a basis to show that temperatures are higher in certain months of the year. If temperatures are not recorded on non-school days or are recorded incorrectly or at different times of the day, the data would be incomplete and the ideas being communicated could be inaccurate. Students may also record the day of the week on which the data was collected, but this would have no relevance to whether temperatures are higher or lower. In order to have sufficient and accurate data on which to communicate the idea, students might want to use data provided by a governmental weather agency.
Related Resources and Toolkits
Lesson #1 What makes something a computer?
Lesson #2 Hardware and software
Lesson #3 Binary Bracelets
Lesson #4 Binary Images
Lesson #5 What is Data?
Lesson #6 Data and Processing
Lesson #7 Collecting Data
Lesson #8 Data to answer questions
Lesson #9 Data Visualization Project