Sandra Baumann, Dominic Harion & Ann Kiefer

The module #Discover Life on Mars with A Rover was developed in collaboration with ESERO Luxembourg (European Space Education Resource Office). ESERO designs pedagogic material for primary and secondary schools, which is adapted to the Luxembourg school curricula for STEM subjects (Science Technology, Engineering and Mathematics), and which is always linked to the theme of space. As part of the University of Luxembourg’s Bachelor in Education Sciences (BScE), ESERO also supports future primary school teachers in developing general scientific knowledge. For example, pupils work on resources developed by ESERO within the framework of the “Teach with Space” project, on the topic of climate change (Andersen et al., 2021).

The current teaching unit #Discover Life on Mars with a Rover deals with the  topic of robots and has been integrated into the space learn setting. The objective is to bring the fascination with space into the classroom, and to use this topic to encourage young people to learn and work independently and to develop their motivation for the learning process: the multifaceted topic of space is a topic that young people find very interesting – particularly when it’s related to the search for extra-terrestrial life. This module draws on the pupils’ imagination and arouses their curiosity and enthusiasm. Furthermore, space supports the topic of robots, and takes programming from a theoretical context to a very applied context.

In an interview conducted at the Esero UK Secondary Space Conference, Tim Peake, an ESA astronaut, highlights the pedagogic potential of the topic of space. Peake is convinced that the fascination with space can be transferred to a lot of areas of learning and scientific subjects within the framework of education. He believes that space and the work of the ESA can be used as unique platforms to interest children and young people in the topics of space and space exploration, as well as to stimulate their interest in the work of astronauts, engineers and scientists. Peake sees a clear advantage in the fact that, when learning about space, the content is relevant to and meaningful for children and adolescents: abstract ideas from mathematics, physics, chemistry or biology thus become concrete and tangible. This is what Peake calls “space as an educational outreach tool” (UK ESERO, n.d.). The module #Discover Life on Mars with a Rover similarly does not aim to integrate coding into a purely virtual environment, where the programmes created by the pupils simply produce a response on the screen (such as programming images that move, sound effects etc.).

Because the command instructions that pupils have programmed are tested on a robot, they get a response that instantly reflects their efficacy, successes and failures. Here, robotisation adds another level by allowing the algorithms the pupils have designed to produce “spatial feedback” – a tangible aspect that enables learner(s) to look for solutions within a less traditional school environment (INRIA, 2020).

In this way, programming allows them to address their error, in class, within the framework of learning through experimentation (Kapur, 2011). “From a neuroscientific perspective, the error is primarily treated as a diversion from an attempt, and therefore constitutes precious information that allows a person to readjust their design and thus to learn.” (INRIA, 2020) Thanks to programming, pupils can experiment with a positive approach to mistakes, because the error message is immediate: an IT programme does not pass judgement, it simply detects the error and flags it up. It gives the pupil the opportunity to keep having another try, until their work achieves the desired result. Consequently, even those pupils with lower attainment levels have the potential to complete their task successfully.

The programme also helps pupils to develop a more in-depth work method, because a programme only works if it is programmed 100% correctly. In this way, it differs from an educational approach in which pupils strive to be “good enough” rather than “good”. For example, a learner’s aim is often to pass a test, but not necessarily to get full marks. This cannot be the case with programming: whereas an exam can be passed with 50%, a programme that has only been halfconfigured is unusable and cannot work (INRIA, 2020).

In addition to the response provided by spatial feedback, dealing with errors in a way that is conducive to learning, and learning a more in-depth way of working, the module ultimately enables the formation of critical thinking. Here, by “critical thinking”, we mean specifically: the ability to form hypotheses, to confirm them and/or to prove them – or to reject them. Mathematics and science can play a fundamental role in the development of this ability in pupils because the hypotheses, the cause-and-effect relationships and the theories are essential elements of modelling within mathematical and scientific frameworks. The awareness that it is possible to change one’s mind plays an equally important role in this. This trial-error loop is not usually achievable within a traditional one-hour lesson because this type of process often takes much more time in a laboratory. However, the trial-error loop is much shorter in information-technology, because a programme flags up an error on the very first attempt. Pupils therefore quickly learn to say, “I thought that…, but I have discovered that…, I am going to try something else” (INRIA, 2020) and can practise a positive error culture.

In the #Discover Life on Mars with a Rover module, robotised vehicles like Opportunity and Curiosity (NASA, 2022) leave for a mission on the planet Mars. For a Martian rover like this to know what it must do, a programmer has to write a series of instructions that the robot carries out, one after the other (for example “deploy the solar panels”, “deploy the wheels” or “turn on the camera”). However, it is not possible to control the rover from Earth because the radio signal takes between 4 and 20 minutes depending on the position of the Earth in relation to Mars. A remote-controlled robot would therefore only work with a long time-delay. This is why the Martian rover must be programmed in advance, so that it can function independently.

In this unit, pupils are therefore given four different and successive programming missions of increasing complexity. Parts of the basic missions can be reused for the more complex tasks. Since the unit is an introduction to programming, pupils don’t need to program all of the missions from scratch. To make the task easier, parts of the programming are given to them in the form of tasks. This also corresponds to the tasks outlined in the ICILS study (International Computer and Information Literacy Study 2018), which was conducted with 6^e pupils (Fraillon et al. 2019). The robots used are mBots from the company MakeBlock. These robots are specially designed for beginners and make it possible to teach and learn robotic programming in a simple and fun way. The programming itself is done using MakeBlock software, a blockbased programming environment based on Scratch.

The #Discover Life on Mars with a Rover module focuses on the development of a specific skill set, which was modelled in the recent ICILS study under the name of Computational Thinking (CT). It refers to a person’s ability to “identify those aspects of real-world problems that lend themselves to IT modelling, to evaluate algorithmic solutions to these problems and to develop their own solutions in such a way that they can be implemented by a computer” (Boualam et al., 2021). The skill set therefore comprises the two key skills “conceptualising problems” and “implementing solutions” (ibid.)¹. 6^e pupils in Luxembourg  are currently below the international average in the area of computational thinking as well as in general computing and IT-related skills (see ibid.).

Access to programming via Scratch within the context of the #Discover Life on Mars with a Rover module gives pupils the opportunity to gain some initial experience with IT systems and lends itself very well to teaching beginners. The programming activity is limited to adapting an existing programming environment to the demands of successive programming tasks, and thus offers an opportunity to create effective products, with very little prior programming knowledge (Schubert & Schwill, 2011). Thanks to these step-by-step instructions, learners become familiar with the basic principles of block-based programming and develop basic CT skills, which can be linked to any experiences they have already had with coding, in the way that it has been designed for primary education.

¹For a critique of the Computational-Thinking model, see for example Nardelli (2019) and Tedre & Denning (2016). From the perspectives of psychology/psychology of learning and epistemology, it is in fact unlikely that CT can define a way of thinking (even a new one) that can be taught. The various skill sets that this comprises are also developed in other disciplines, such as maths and natural sciences, as well as in philosophy and formal logic. For this PITT module, CT is therefore considered to be a group of characteristics, as it is conceptualised within the context of the ICILS 2018 and applied by Boualam et al. 2021. The skills that are grouped together here under the heading of CT, are therefore used in a descriptive rather than a normative way.

Referenzen
Andersen, Katia N., Cornrotte, Fréderic, Trap, Guillaume & Bettelo, Nadia. (2021). Le projet ESERO Luxembourg : conséquences pour la professionnalisation des enseignants sur le thème de l’éducation au développement durable. Rapport national sur l’éducation 2021. https://doi.org/10.48746/bb2021lu-de-19
Boualam, Rachid,  Lomos, Catalina & Fischbach, Antoine. (2021). Compétences en informatique et en information (CIL) et compétences en raisonnement informatique (CT) des élèves de 8e année. Principaux résultats de l’ICILS 2018. Rapport national sur l’éducation 2021. https://doi.org/10.48746/bb2021lu-de-26
Institut national de recherche en sciences et technologies du numérique (INRIA). (2020). Éducation et Numérique : enjeux et défis. Livre Blanc N 04. https://hal.inria.fr/hal-03051329v2/document
Fraillon, Julian, Ainley, John, Schulz, Wolfram,  Friedman, Tim & Duckworth, Daniel. (2019).  IEA International Computer and Information Literacy Study 2018. Assessment Framework. IEA
Kapur, Manu. (2011). A further Study of productive failure in mathematical problem solving : unpacking the design components. Instructional Science, 34(4), 561-579.
Nardelli, Enrico. (2019). Do we really need computational thinking? Communications of the ACM, 62(2), 32-35. https://doi.org/10.1145/3231587.
NASA. (2022). Mars Exploration Rovers. https://mars.nasa.gov/mer/mission/overview/
Schubert, Sigrid & Schwill, Andreas. (2011). Didaktik der Informatik. Spektrum Akademischer Verlag
Tedre, Matti & Denning, Peter J. (2016). The long quest for computational thinking. Proceedings of the 16th Koli Calling Conference on Computing Education Research, 120–129
UK Esero. The benefits of bringing Space to the classroom. The Esero UK Secondary Space Conference. https://www.esa.int/ESA_Multimedia/Videos/2014/11/ESERO_UK_Secondary_Conference_at_Farnborough_with_Tim_Peake/(lang)/en