The SchoolWide Lab middle school curriculum units are anchored in phenomena, aligned to the Next Generation Science Standards(NGSS) and purposefully integrate Computational Thinking (CT). To date, four units have been developed by a team of researchers from the University of Colorado Boulder in collaboration with middle school teachers from Denver Public Schools. The teachers also piloted the units and have taken part in the revision process.
Engaging in computational thinking means examining problems using the strategies and approaches employed by computer scientists. As computational tools have become increasingly ubiquitous in the 21st century, exposing students to these tools and ways of thinking is critical to the development of a well educated society. In science classrooms, students engage in computational thinking as they become aware of the available computational tools and develop an understanding of when those tools are appropriate to use. Students generate scientific questions and consider whether computational tools can be used to help answer those questions. Students plan investigations or engage in design challenges in an algorithmic (discrete step-by-step) fashion utilizing relevant computational tools. Students collect and analyze data using computational tools or construct and execute a simulation. Lastly students communicate their findings in a variety of formats that involve computational concepts, such as models, infographics, visualizations, or other intentional displays of their data.
Each unit is organized around a coherent storyline, in which students ask and investigate questions related to an anchoring phenomenon or design challenge. Students engage in CT and use the science and engineering practices to figure out disciplinary core ideas and crosscutting concepts needed to make sense of and explain the phenomena or solve the problem presented in the challenge.
The phenomena that students work together to explain differs in each unit and were chosen with input from middle schoolers as to what would be interesting and engaging to students like them. As they take part in the units, students engage in the eight science and engineering practices with a focus on computational thinking practices. For example, students in practices where they investigate, make sense of phenomena and problems using CT and programmable sensors, construct and critique models, and develop explanations.
The phenomena that students work together to explain in these CT-integrated middle school units are how Maglev Trains use invisible forces to float and move (Forces at a Distance), environmental conditions that lead to mold growth (Mold), the existence of food deserts and how urban farming and vermicomposting a.k.a. worm composting can be a way to grow food in urban spaces (Ecosystems: Urban Farming and Composting). Each has been chosen with input from Denver students as to what would be interesting and engaging to students like them.
Each unit is designed to support students in becoming more sophisticated in their use of science and engineering practices and CT over the course of the unit. Design challenges help students integrate and apply knowledge and they are expected to take more and more responsibility in problem solving within them. Students engage with all eight science and engineering practices, becoming more proficient in learning when and how to use the practices. Lessons engage students in practices where they investigate, make sense of phenomena and problems, construct and critique models, and develop explanations and arguments. The units are designed to support students in becoming more sophisticated in their use of practices over the school year. Design challenges help students integrate knowledge across units; over time, students are expected to take more and more responsibility in problem solving within them.
There are multiple assessments embedded in the materials that can be used for formative and summative purposes. These include exit tickets with multiple-choice questions that assess both student experience and understanding, student models of phenomena, and 3D transfer tasks in which students apply what they have learned to a new phenomenon. The modeling tasks are accompanied by Student Learning Objectives (SLO) rubrics that can be used to build a portfolio of evidence of student progress.
The sensing technology is integrated into a series of lessons that address identified performance expectations in the Next Generation Science Standards (NGSS) as well as science, engineering and computational thinking practices. Each instructional unit is referred to as a storyline -- a set of lessons that are driven by student questions about a specific design challenge or scientific phenomena. These storylines use students’ questions and ideas to ground the sensing investigation and drive the class forward.
The micro:bit and gator:bit sensors (pictured above) are affordable and built specifically to be used by youth in educational environments. The micro:bit sensor has onboard light, temperature, accelerometer, and magnetometer sensors. The gator:bit works with the micro:bit by adding an LED display for output and the capacity to attach a wider range of sensors, using alligator clips that are easy for small fingers to manipulate. Environmental sensors that can attach to the gator:bit include sensors to measure temperature, sound, carbon dioxide, humidity, and total volatile organic compounds. The micro:bit and gator:bit can broadcast data streams to a paired micro:bit connected to a computer, allowing youth to see and analyze data in real time. The sensor systems are programmable using MakeCode (MakeCode Editor, 2019) which supports either text coding or graphical block programming that is easier for novices.
Sensors are authentic tools for work and science. Youth use these technologies to collect and analyze a variety of indoor and outdoor environmental data. Arrays of sensors, connected with computer networks, provide students the opportunity to collect and investigate rich sets of "big data" streams that many workplaces are using to improve productivity or understand their use of resources. Youth who have experience collecting and analyzing data from sensor systems will be prepared for future workplaces that rely on computer and network technologies, sensor systems, and big data. Programming enables youth to build and communicate models and explanations of phenomena through developing and refining computational representations (e.g., programs) and customizable interactive data visualizations of their data (Weintrop et al., 2016). These practices are key in knowing and doing science and engineering (NRC, 2012) and provide opportunities for youth to investigate phenomena relevant to local STEM occupations (Strom, 2019). Together these features support youth to engage in authentic learning experiences directly related to local STEM and computing careers.
In each unit students use programmable sensor technology to conduct a variety of data-enabled science and engineering investigations that are rooted in personally relevant questions about their community and their lives. This sensor technology enables teachers and students to envision a new type of “school-wide science lab” - moving beyond specialized classrooms where students go to conduct experiments to imagining the entire school and neighboring environment as a potential space for scientific inquiry. As such, this expanded environment for “doing science” enables teachers to creatively integrate CT activities into their disciplinary instruction.
The Sensor Immersion unit (one week) introduces students to the sensor technology and students investigate how sensors work and how to control them. It is recommended that teachers start with this unit, especially if they students are unfamiliar with sensors and coding. The other four units examine mold growth (2 weeks), maglev trains (3 weeks) and vermicomposting (3 weeks). These units can be used in any order, in combination or on their own.
We recommend classrooms have a student:micro:bit kit ratio of 4:1 or lower. In classroom field tests, many classrooms had students work in groups of 4 or smaller depending on the investigation and the data being collected. Students use an online programming platform called Makecode to program the micro:bit. Many classrooms that utilized this curriculum used a ratio 3:1 Chromebooks:students.