Starting a Robotics Program
Below are basic questions to consider that will provide some guidance to starting a robotics program.
Step 1: What are you going to teach?
Robotics provides many rich opportunities to teach Computer Science, Science, Technology, Engineering, and Mathematics (CS-STEM) as well as 21st century skill sets. As you plan your robotics course, one of the first things that you will need to consider is what “Big Ideas” do I want to teach through robotics. At the Robotics Academy we’ve worked with many teachers helping them to develop a scaffolded set of curricular activities to help them to develop a multi-year program. For example, if you are developing a middle school robotics program you may want to foreground grade level mathematics and introduction to programming in Grade 6, intermediate level programming and STEM Robotics applications in Grade 7, and engineering competencies with programming in Grade 8. What we have observed is that without planning schools teach the same competencies in grades 6-8 and there are no measurable learning gains. Robotics as a content organizer can be used to teach many things, including:
• Engineering competencies (design, iteration, prototype development, design reviews, project planning…)
• Programming and computational thinking
• Data-logging and scientific methods
• Contextualized mathematics
• 21st century skill sets (teamwork, cooperation and collaboration, time management, resource allocation, etc.)
One of the first things that a robotics teacher needs to do is to determine what it is that they want to teach (foreground and measure) when they are teaching robotics. The link to the left, foregrounding mathematics, provides an example of Robotics Academy research around using robotics to teach mathematics.
Step 2: What do your students already know and how do you scaffold their learning?
All students come into any course with pre-conceived ideas on how things work. Effective teachers find ways to build on what students already know. This was mentioned above, but worth repeating, if you are planning a multi-year robotics experience decide what it is that you want to teach at each level.
Step 3: How do you evaluate student success?
One of the issues that a robotics teacher faces is that there are many moving parts in a robotics classroom (literally) and often times they find themselves helping students troubleshoot, managing classroom activities, and setting up for the next class; and before they know it the day is over. It is important to build assessment activities to measure what students are learning.
Getting Started Guides
We have developed getting started guides for VEX and LEGO Robotics classrooms. Please select the links below to go to those sections.
Research Example Scenario
Note: In this example we highlight using robotics to teach middle school level mathematics, but we use the same deliberate process to develop computer science and engineering type activities.
Robotics broadly construed inherently involves a rich range of mathematics, stemming from the physical design of the mechanical and electrical components, as well as from the programming/control of the components as the robot executes tasks with or without sensors. Even middle school robotics activities involve a rich range of mathematics concepts: measurement, geometry, algebra, and statistics.
But that inherent mathematics is deceptive, instructionally speaking. First, isolated robotic activities can involve too many mathematical concepts at once to be instructionally useful. We have observed how a single 30-minute robotics activity designed for middle-schoolers can in rapid-fire touch upon measurement, geometry, algebra, and statistics concepts (Silk & Schunn, 2008). In such an activity, there is no time to focus instruction on any one mathematical concept, and we were not surprised that students made no mathematical progress over a full semester of engagement with such activities even though the instructor attempted to focus student attention on the mathematics. The Robotics Academy’s approach is to focus on one foundational mathematical construct for an entire robotics unit, and indeed build it up over multiple robotics units. Proportional reasoning is a foundational mathematics concept that relates to a wide range of situations in everyday life and in the workplace, such as those that involve unit rates, mixtures, or scaling (Cramer & Post, 1993; Langrall & Swafford, 2000). Proportional reasoning is also central in understanding how a robot’s movements can be controlled, as the relationships between the physical construction of the robot, the values used to program the robot, and how the robot actually moves are often proportional in nature (Silk, Schunn, & Shoop, 2009). Moreover, students need to understand rates, ratios, and proportions to develop algebraic ways of thinking.
We’ve observed hundreds of students in robotics classrooms and competitions and have found that students often find ways to solve problems without engaging with the underlying mathematics. Most commonly, the young roboticists use a guess-and-check strategy, even when the activity has been designed to make guess-and-check much more painful to apply than a mathematics-based strategy (Silk, Schunn, & Shoop, 2009). Our approach is to use findings from the problem-based learning community broadly speaking, and the model-eliciting activity community in particular, to create units which engage students with the underlying mathematics in the robotics activity, building from their guess-and-check approaches to develop more sophisticated mathematical intuitions and strategies.
Model Eliciting Activities (MEAs)
Model Eliciting Activities were originally designed for middle school mathematics classrooms, but have become popular in many kinds of engineering classrooms, primarily at the college level, but also in middle and high school settings (Lesh, et al., 2000; Reid & Floyd, 2007). This combination of engineering and mathematics is exactly the space that we are operating within. Properly designed and implemented MEAs can support the growth and development of mathematical reasoning in students and teachers. Broadly construed, MEAs are authentic problems that groups of students solve over a few hours and require students to express, test, and revise mental models in order to solve the problem. Mental modeling is a critical component of mathematical thinking and learning (Lehrer, Schauble, Carpenter, & Penner, 2000) that has also been shown to be critical to thinking and learning in science (Schwarz, et al., 2009) and engineering (Lesh, et al., 2000). Thus, modeling is an obvious boundary spanning activity for integration of engineering, technology, and mathematics. Below is our Robot Synchronized Dance MEA example. To begin the lesson, students are told:
Bots-N-Sync is a robot dance team that specializes in doing synchronized dances—many robots doing the same dance moves at the same time. They are hugely popular thanks to the power of the Internet. They record videos of each of their routines and post them on YouTube. Many of their videos have gone viral with millions of views.
The team is growing a large and devoted fan base by encouraging their fans to submit dance routines online on the team’s website. The dance captain likes to see if a routine is good by getting the entire dance team do the routine together. The problem is that each dance routine is designed using a single “standard robot”, but the many robots on the dance team are all different. When the captain first downloads a dance routine to all of the robots, they all do very different things and are definitely not in sync with each other. An example of this happening is shown below with the latest submitted dance routine that the captain is currently working on.
Your job is to create a “how to” toolkit that the captain can use to modify submitted dance routine programs so that all of the dancers do the routines in sync with each other. New dance routines are submitted often and new dancers join the team each season, so your toolkit should work for the current dance routine, but should also be easy to adapt for new routines and new robots. It would also be valuable to know why the toolkit works, so that the captain understands how he might adapt it later for other similar situations.
For students, MEAs involve the practice of mathematical/engineering modeling using physical objects to support problem solving with abstract ideas. The MEA presents opportunities to reveal student thinking to teachers, who then can provide more targeted feedback. Well designed MEAs immediately engage problem solvers with a broad range of mathematical skills, making them an especially powerful form of design-based learning that works for many learners and contexts. A number of principles have been discussed regarding the design of good MEAs, such as: using problems that are personally meaningful, requiring models to be documented, and involving generalization of the model (Lesh, et al., 2000). For teachers/informal educators, MEAs also have the potential to be educative in the two ways identified by Stein and Kim (2009). First, if teachers are made aware of the design rationale for the MEA (through well-designed teacher materials), they will know the purpose of the learning tasks in which students are engaging and how those tasks are expected to lead to a particular learning goal. This provides an important roadmap of the “learning terrain” that becomes especially important if things do not go as planned. Second, by revealing student thinking, teachers have the opportunity to closely monitor students’ solution strategies and (if they have prepared for the lesson by anticipating a variety of student solution strategies using well-designed teacher materials) to steer student thinking toward appropriate and correct conceptual and strategic thinking. We seek to evaluate and refine our to-be-developed MEA units such that they are educative for both students and teacher/informal educators in the ways outlined above.
To learn more about the above activity go to our Robotics in Motion Robot Algebra Project here: Link
Selecting hardware can be a difficult choice for teachers. There are a broad range of options available. The majority of the Robotics Academy development has been around LEGO and VEX robots since they are the dominant solution available in education today. One key factor that you will want to consider:
Are you interested in being involved with robotics competition?
Robotics competitions provide an ideal environment to teach engineering and 21st century skill sets. Robotics competitions allow students to learn about:
– conducting research to determine ideal solutions
– collaboratively working in teams
– giving and receiving constructive criticism
– project planning and utilizing charts (PERT and Gannt)
– dealing with the iterative nature of Engineering
One factor that you might consider is what competitions are available locally for your school or group to compete in? You can find out about robotics competitions at the Robotics Education and Competition Foundation here: Link
What type of environment do you teach in?
Some hardware is conducive to building in a classroom without the use of tools and other hardware requires the use of tools.