Computer science (CS) education prepares knowledge and insights from computer science for the education of children and adults in diverse contexts. Research in this domain is concerned with the analysis and reflection of educational settings, processes and results of learning in CS and the design, development, testing and evaluation of educational concepts, methods, subject-related teaching and learning processes, resources and media.
Concerning media, hardly any other school subject is shaped as much by its tools as computer science. Presumably there is also no other subject that can make use of such a large variety of available tools to introduce new topics, clarify facts or as a subject of instruction. Numerous tools are available that facilitate the understanding of complex and difficult topics, help to explain concepts with visualization, illustrate application scenarios in simulations, support learning with experimentation platforms or in interactive eBooks, learning tutorials, etc. Additionally, there are also many tools available that empower even the youngest learners to model, design and create their own animations, applications, tools, games, toys or smart devices.
Early successful attempts of using dedicated learning environments for teaching stem from the late 1960s and have influenced the development of educational tools until today. The main idea was to take away unnecessarily complex aspects of programming languages and only provide those elements that support learning in the desired domain. Especially the Logo microworld and the corresponding constructionist approach to learning  in the following years had a tremendous impact on both, learning in computer science and in other subject areas. As Papert argues, “[learning] happens especially felicitously in a context where the learner is consciously engaged in constructing a public entity, whether it’s a sand castle on the beach or a theory of the universe” . Hence, the construction of knowledge is based on an active construction process. In such a way, a meaningful artifact is created, which the learner can try out, show around, discuss, analyse and receive praise for. It is the examination of such an artifact that leads to the understanding of a particular phenomenon. Microworlds are computer assisted learning environments in which such learning can happen unhindered by the complexities of the world . This approach was adopted for computing education: Microworlds and virtual interactive robots have been commonly used in introductory courses. With tools like Kara1 and Karel the Robot,2 students in computing education are exposed to programming and basic CS concepts at very early learning stages.
Modern learning environments suitable for novices in computer science and especially programming, for instance, empower their users to create animations and games (e. g. Scratch3 and Greenfoot4), to control robots (e. g. LEGO Mindstorms5), to develop smartphone apps (e. g. AppInventor6) or to create interactive objects and smart devices with physical computing platforms (e. g. Arduino,7 Raspberry Pi8 or BBC MircoBit9). These tools may not only have a strong impact on the motivation of the students, but also affect the extent to which they can contribute creatively in the classroom.
In the following, we give an overview of computer science education research related to tools and media to be used in educational settings. We analyse different types of tools and possible characterizations and adapt them to current developments. A special focus is set on tools for physical computing activities in the classroom. In the second part of this article, we present research around the development and evaluation of tools and learning resources in the domain of physical computing. With the example of “My Interactive Garden”, a constructionist learning and programming environment, we introduce a concept related to design research and explain how the results from empirical studies are integrated in the continuous development of the learning material.
2 Soft- and hardware tools for empowering learners
In their taxonomy of programming environments for novices, Kelleher and Pausch  identified two main categories: tools that teach learners how to program for its own sake (“teaching systems”) and those that empower learners to use programming languages in the pursuit of other goals (“empowering systems”). The core idea of this taxonomy can be transferred to computer science learning environments in general: teaching systems for CS education pursue the goal of facilitating learning, understanding and application of CS concepts, methodology and content, such as programming languages, encryption algorithms or logic circuits. Typical tools guide students through exercises, simulations, visualizations or allow experimentation. Empowering systems, in contrast, enable learners to make use of their CS competencies pursuing other goals, i. e. that they apply their knowledge and skills to solve problems, to create systems according to specific goals or even to invent new systems and devices (e. g. apps, games, websites or smart objects).
2.1 Educational software
Different researchers have attempted to capture an overall picture of the available tools and their peculiarities (e. g.  and ), but, similar to the distinction of teaching and empowering systems, the classification categories are often not clear-cut. For example, Gross and Powers  identified the following categories for programming environments for learning: Microworlds (e. g. Logo,10 Karel the Robot, Alice11), Visual programming environments (iconic and textual) (e. g. RoboLab,12 JPie13), Flow Model Environments (e. g. RAPTOR14), Object workbench environments (e. g. BlueJ,15 jGRASP16) and Algorithm realization environments (kinesthetic, multimedia, animation, graphics) (e. g. Lego Mindstorms). Similarly, based on the analysis of publications about introductory programming courses, Pears et al.  identified the following categories of tools used in this context: Visualization Tools, Automated Assessment Tools, Programming Environments, Programming Support Tools, Microworlds and Other Tools.
In recent years, many learning environments have incorporated the ideas of empowering learners that led to the development of “Scratch”: tools for learners should reduce entrance barriers as far as possible (“low floors”), should not restrict their interests and creativity (“wide walls”) and at the same time allow the (step-by-step) creation of complex, sophisticated projects (“high ceilings”) . While Scratch is suitable for the creation of multimedia projects (animations and stories, games, simulations and many more), adaptations and extensions of this environment integrate Internet services, social media, interfaces to smart phones and 3D printers or sensors and actuators and thus allow for even wider ranges of projects, e. g. mobile applications, data stream analysis and visualization (e. g. , Figure 1), 3D modelling and printing (e. g. , Figure 2) or physical computing (Figure 3). In teaching, the newer tools have proven to bring advantages, among other things, especially for student motivation (see , , ).
2.2 Toolkits for physical computing
In addition to software tools, hardware may add extra motivation due to its tangibility. In recent years, physical computing has grown in popularity for school education. Physical computing, in our understanding, is the creative design and implementation of interactive, physical objects and systems, which are programmed, tangible media that communicate with their environment through sensors and actuators. In physical computing, many methods and ideas of embedded systems, cyber-physical systems and robotics are used . Examples for interactive objects and installations range from interactive sculptures and sweets dispensers over extensive model building projects to interdisciplinary STEAM projects (e. g. Figure 3). Suitable construction kits and learning environments allow children and teenagers to learn basic concepts of embedded systems, cyber-physical systems or robotics in a creative and motivating manner. Since the early days of tool development for classroom use, also the idea of controlling robots with programs or using programmable bricks as parts of constructionist toolkits have been present. Blikstein’s historical overview of constructionist toolkits, robots and physical computing devices dates back as far as the 1980s when the LEGO/Logo platform was developed . In these early stages, such tools were used for scientific investigations in developmental psychology and building on the constructionist ideas. Later, artists and designers used such tools, as they make electronics more easily accessible and bring the benefits of programming to the physical world. Nowadays, most approaches aim at making physical computing accessible to an even broader range of interested people: the findings from development psychology are combined with an easy access to electronics. Thus, current projects often show deep bonds with the constructionist ideas: In physical computing activities, students learn with and about interactive computing systems by creating concrete, tangible products of the real world that arise from their own imagination and that they can show around and be proud of in a constructionist sense. With physical computing, constructionist learning is raised to a level that enables students to gain haptic experience and thereby concretizes the virtual .
As physical computing has only recently been integrated in CS curricula, most teachers are new to the subject. The field is unknown to them and they are often not aware of the different tools that could be used for teaching. Therefore, we systematically analysed tools that were mentioned in selected conference reports, influential research papers or used by different institutions in their physical computing courses with the aim to get an overview of tools and their main characteristics.
By now, there is a large variety of good and affordable hardware on the market, which can be used for physical computing. O’Sullivan & Igoe  classified physical computing tools according to the level of abstraction from technology, so that very high-level tools allow their users to immediately start working on the design and configuration process, while very low-level tools require users to deal with ones and zeros and electric circuits. This classification was used as a starting point to investigate physical computing tools that currently are or earlier were available on the market in order to categorize different types of hardware for physical computing activities. Tools of a very low level were excluded from the investigation, as they are neither designed for educational purposes, nor for physical computing in general. A list of mid- to high-level tools was generated and used to classify different types of hardware for physical computing activities technically. We identified various groups of devices and toolkits, which are described below in ascending order concerning the level of complexity in use.
Programmable Toys, such as Cubetto17 or the BeeBot18 are mainly used in primary education and offer children a first opportunity to develop an intuitive understanding of algorithms. They learn to precisely formulate and follow commands and become acquainted with basics of algorithms such as iterations and loops. With programmable toys, learners configure actions and reactions, but do not work on hardware assembly.
Input-/Output-Devices are used to extend the possibilities of stationary or laptop computers. New forms of in- and outputs to and from computers are used: instead of keyboard and mouse, all kinds of sensors are utilized as input and in addition to computer displays, e. g. LEDs or motors can be controlled. For instance, SenseBoard19 or Pico Board20 projects are successful and call for a wide range of creative projects , . MaKey MaKey21 is another example with growing popularity. It allows to connect all kinds of electrically conductive material as sensors, e. g. plants or even humans.
Programmable bricks are mainly used in primary education (e. g. LEGO WeDo,22 Pico Cricket23) or for building robots (LEGO Mindstorms) in non-formal educational settings. They are very high-level tools, as users can easily snap the parts together and even program their interactive objects or robots in graphical drag and drop programming environments similar to Scratch.
Standalone microcontroller boards, for example the BBC MicroBit or the Calliope Mini24 have recently found great acceptance because they already contain sensors and actuators. They are particularly suitable for initial teaching, offering an attractive opportunity to discuss the fundamentals of embedded systems in class.
Microcontroller boards with modules simplify the handling of the hardware. When using such modular systems, learners can make use of the complexity offered by microcontrollers such as Arduino Uno and still have the plug and play approach of programmable bricks. This branch of physical computing hardware is particularly interesting for use in school as many tools are developed for exactly this purpose, e. g. Grove Modules,25 TinkerKit26 or MyIG Toolbox.27
Mini computers with modules, e. g. Raspberry Pi with PiFace,28 pursue similar goals, but allow creating even more powerful objects and installations. In addition to the functionalities offered by microcontroller boards, they contain all the features of a multi-purpose computer without taking much space and thus make it a lot easier for their users to integrate cameras, displays, speakers, and many other advanced I/O devices into their projects.
Bare Microcontroller boards can also be used as more demanding mid-level tools that require their users to build the circuits and work on breadboards for prototyping before soldering the parts together manually or ordering manufactured circuit boards.
Mini computers are found in more demanding settings that, similar to the use of microcontroller boards without extension shields and modules, require the user to deal with details of electronics.
Reflecting these findings, we found that the tools we analysed could be sorted into five main categories of physical computing devices and toolkits that are suitable for CS education: programmable toys, input/output devices, programmable bricks, microcontroller boards and mini computers (see Figure 4). Although it is not always possible to assign a tool to a distinct category, taxonomies like the one described above help teachers to reflect on their goals and select the tools that best suit their needs in lesson planning, carefully considering their objectives and intentions, the content in question, competencies and skills to be acquired and external conditions (cf. ). Teachers can choose from a large variety of tools: programmable toys offer the lowest entrance barriers possible but allow only a limited range of projects. Mini computers allow the most flexible projects but require advanced knowledge of computing systems.
3 Physical computing in the classroom with my interactive garden
While tools are one major aspect, also contents and pedagogy play an important role for the success of teaching physical computing. There are almost no text books or teaching materials available that help teachers planning their teaching units at secondary school level. Questions that arise when developing scenarios, resources and media for this target group, include:
How can physical computing be taught at secondary school level?
Which tools are suitable for the intended goals?
Which requirements need to be considered in the concrete setting?
3.1 MyIG toolbox
One important aspect of MyIG was the selection and development of appropriate tools for the purpose of teaching physical computing to students in computer science classes in lower secondary education. In tool development, it is always important to consider the needs of the target group. For school settings, where the aim is to empower learners to design and implement sophisticated physical computing projects, we recommend using microcontroller boards with modules. They combine the flexibility of microcontrollers (wide walls) with low entrance barriers similar to programmable bricks (low floors) and allow for elaborated projects (high ceilings). We decided to use Arduino as a microcontroller platform because it was built for educational purposes and there is a large community of educators working on extensions, classroom material and project examples to get inspired from. However, Arduino components are not easy to handle for novice users, e. g. you need to apply knowledge in the field of electrical engineering. For educational settings, especially when electronics is not in focus, it was therefore necessary to develop components that do not require students to solder or to work with breadboards, which quickly gets confusing. Hence, the items of our construction kit were built considering the following principles that were implemented in the development of the MyIG toolbox and later in the further development of the Arduino TinkerKit , :
Simplicity: Provide easy to use plugs, so that students do not have to handle tiny wires, which break easily or slip off the pins on the Arduino.
Flexibility and extensibility: Easily add, remove or exchange items. Provide extension wires to allow users to mount their parts in a distance to the boards.
Black/white boxing: Hide circuits of subordinate relevance in a black box. “Open” the black box with templates and data sheets.
Emphasize computing principles: Visualize computing principles, e. g. the IPO model.
3.2 Learning with MyIG
After the decision for and development of suitable tools for learning computing principles with physical computing, another question to be investigated was “How can physical computing be taught in lower secondary education?” This involves the preparation of new content for the target group and development of suitable teaching methods.
The process in MyIG projects is strongly oriented towards the ideal of physical computing: to focus on ideas, not on the restrictions of tools (cf. ). It also takes into account strategies for raising participation based on :
Focus on themes (not just challenges)
Combine art and engineering
Organize exhibitions (rather than competitions)
Using MyIG, we investigated the possibilities and limits of physical computing in schools and after several iterations, the final lesson plan was structured as follows (cf. ):
Introduction and motivation: Learners are introduced to embedded systems, IoT and physical computing.
Project planning: Learners plan their projects according to the process described in . This bears the danger that students might plan projects that are too hard to realize or intend to use components that are not available in the school’s toolkits they later use. However, our experience shows that students’ projects are a lot more diverse and creative when they are not exposed to the tools first and instead plan their projects according to O’Sullivan and Igoe’s process description , e. g. in first sketching their ideas with pen and paper (Figure 7).
Presentation and discussion: Learners present their project ideas and plans and discuss those with their classmates and teacher.
Learning: In jigsaw classroom and tinkering activities (Figure 8), learners get to know the construction kit and learn about CS concepts and how to program Arduino; they create posters for the classroom; each student group holds one expert for each type of components (analog sensors, digital sensors, servo motors, etc.).
Creating: In groups, pupils work autonomously and create their own interactive objects (Figure 9); classmates and posters help, the teacher only intervenes when necessary.
Exhibition and reflection: Pupils present and explain their projects and discuss their experience with the classmates and their teacher.
This approach to physical computing in the classroom was tested, evaluated and refined in many iterations over a four-year period and adapted by many teachers in various settings. Contexts that teachers used include smart city, smart home, interactive art, interactive games and saving resources, among others.
3.3 Evaluation of the concept
CS education research is concerned with the questions, which competencies learners gain when and how. Besides the educational content preparation of the subject matter, this includes the development of appropriate tools, media and other resources for CS education. Tool development is usually driven by the idea of solving a certain problem, for example reducing the complexity of mighty tools for the purpose of better learning, for other educational reasons, such as supporting a certain paradigm, triggering motivation and creativity or for pursuing methodological goals. CS education research identifies needs and evaluates the success of new developments to ensure that they actually support learning and fulfil their intended purpose.
The accompanying research of the My Interactive Garden project focused on the evaluation of the settings with regard to the original objectives:
minimize entrance barriers
emphasize computing principles and basics of embedded systems
motivate and excite students
Our overarching research on physical computing in general also deals with the following four dimensions: scientific clarification of real-world innovations (e. g. embedded systems, cyber-physical systems, Internet of Things), educational content preparation (e. g. identification of relevant concepts and ideas), development of learning and teaching scenarios (e. g. resources and media, contexts, best practice examples) and investigation in the classroom (e. g. learning outcomes, lesson planning, problems and solutions). Thus, it not only evaluates the setting described above, but investigates the application and effects of physical computing teaching in various settings. For the evaluation of the settings, we focused on the categories of the Berlin Model developed by Heimann, as it is widely accepted and covers many aspects of lesson planning . In this understanding, all decisions for learning scenarios depend on conditional factors and lead to consequences. Pre-conditions often are out of a teacher’s range, although, of course, they need to be considered when planning lessons or teaching units. Thus, in addition to analysing the overall process, as a starting point we investigated how teachers adjusted their lessons with respect to the decision areas intentions, contents, methods and media. We also included context as a category, as learning in authentic contexts helps to motivate students, shows real-world applications for otherwise often abstract topics and offers anchor points to build on prior knowledge . We identified aspects that all teachers included and dimensions of adjustment to the particular classroom settings (Figure 11).
While the evaluation of the student data is still in progress, we can already reflect on teachers’ experience. The overall tenor is very positive. Teachers are interested in physical computing and the tools that are available for education. They consider it important that tools are reliable, that technical failure can be ruled out and that resources and media are provided, which teachers can reuse for their purpose. The majority of teachers also considered microcontrollers with modules the most useful tools for secondary schools in computer science teaching.
It is also very important for them that projects can be realized in reasonable time spans – both, concerning preparation and in-class execution. Most teachers aim at motivating their students and not so much to introduce new content. Interestingly, there is a difference between teachers with and without prior experience in this domain: those who had already taught physical computing, focused on programming and algorithms while teachers without physical computing classroom experience intended to address sensing and actuation, embedded systems, Internet of Things, etc. Problems that teachers face in class are mainly related to unreliable tools and organizational efforts during the project phase .
Computer science as a school subject on the one hand is characterized by its tools, but on the other hand also evolves with the innovations outside school. The technological progress of the “digital world” is, of course, also reflected in the tools that are used to teach timely ideas and necessary competencies in school teaching. Modern procedures such as Big Data analysis or 3D printing get into the classroom and prepare today’s students for their future. With physical computing, in particular, aspects of data processing, motivation, creativity and the relevance of computer science in our society become apparent, as the following teachers’ quotes illustrate (cf. ):
“We can recapture the physical world, the students can see what happens, measure their environment, brightness, temperature—that gives [my lessons] a completely different quality. It has really done something, the students can now recognize in real contexts how such things work, discover sensor technology in real computing systems [...] This has a whole new quality.”
“Computer science is not just software. We live in a world shaped by computer science [...]. By this I mean the mobile phone, which contains many sensors. There is also the washing machine, the car, the radio set. Computer science permeates all of these devices nowadays, and computer science teaching has to prepare students to understand these devices. Accordingly, the mechanics or certain mechanical problems belong to computer science.”
Additionally, with physical computing, creative and constructionist learning appears to fit perfectly with the scientific aims of CS education. Modern tools, more than ever, allow students to encounter also the design aspects of computer science in the classroom. One teacher summarized his experience as follows and illustrates that in CS classes, students not only acquire skills and competencies, but also create something personally relevant and meaningful:
“Creativity never was so present in the classroom before. Even with projects we made using Scratch, Snap, etc.–It is only through the students’ efforts to put something together and have a thing that they can touch and look at, that we have this new effect in computer science. It was never visible before, not even when we programmed games. There never was this attachment of the students to their projects.”
Computer science is a dynamic school subject that takes into account recent developments and innovations and thus benefits from its media and tools in many ways. The ideas from the 1960s have matured over the years and thus, today, modern CS education offers students the opportunity to stay motivated by creatively designing and implementing things in computer science education that they can explore, be proud of and share in a constructionist sense.
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Pico Board: https://www.picocricket.com/picoboard.html
Makey Makey: https://www.makeymakey.com
Pico Cricket: https://www.picocricket.com
Calliope Mini: https://calliope.cc/en
MyIG Toolbox: http://www.informatikdidaktik.de/MyIG
The MyIG material is available for download at http://tangible-cs.de
About the article
Mareen Przybylla is research associate and doctoral student at the professorship for Didactics of Computer Science at the University of Potsdam, Germany. Her main research interest is physical computing in computer science education.
Ralf Romeike is the head of the Computing Education Research Group at the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany.
Published Online: 2018-03-22
Published in Print: 2018-04-25