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ABSTRACT
It is generally accepted that video games are motivating and have the potential to support learning (see Gee 2003; Kirriemuir and McFarlane 2003) however, their introduction into schools and classrooms has not been extensive. Barriers to the introduction of games include, amongst other things, the difficulties of relating games content to formal school curricula and the challenge of playing lengthy games within the segmented school timetable (McFarlane, Sparrowhawk and Heald 2002). The game that we discuss in this paper, Astroversity, was designed to overcome these issues by focusing on the development of skills and competencies closely related to the UK National Curriculum, and by being designed in such a way as to enable small group learning within the time constraints of school settings.
In the game scenario three students at an orbiting academy for astronauts are undergoing search and rescue training, which requires the development of collaboration and scientific enquiry skills when a disaster means that these newly developed skills must be used for real as they rescue their peers the toxic gunk invading the academy. In this paper the success of the game at supporting the development of collaboration, planning and scientific analysis skills for 13-14 year-olds is discussed. It specifically addresses the question: how effectively can one combine the features of a mainstream computer game with scaffolding to encourage reflection on collaboration, planning and analytic processes? The paper describes the iterative approach to software development that led to the introduction of tutors and explicit reflection and the impact these had on a class of 13-14 year-olds who used the software over the course of three weeks.
1. INTRODUCTION
You and two friends are taking the search and rescue course at the Astroversity - an orbiting academy where gifted students are trained to become space explorers. Your robotic tutors guide you on effective methods of data gathering, deductive reasoning on toxic gunk levels, and communication requirements as you patrol empty hangars looking for dummy victims. During this training session disaster strikes - the academy is hit by an alien vessel releasing poisonous toxins into the atmosphere. You and your friends must now put your new skills to the test as you really rescue your fellow students.
The above is not the packaging from a new playstation game but a project developed by Futurelab and the International Centre for Digital Content (ICDC) at John Moore's University, Liverpool, UK. Astroversity has the look and feel of commercial computer games but incorporates educational goals. It was designed to support students aged 13 to 15 to develop group skills (such as listening, turn taking, and providing justifications for suggestions), and scientific enquiry skills (such as data logging, hypothesis generation and testing, and analysis of data).
Astroversity is innovative due to:
- the use of multiple methods of representation: the students switch between a virtual online world and a paper-based representation they create as a consequence of exploring this world
- the requirement that team members do not simply work together by doing fulfilling different roles in the same task, but have to contribute information to a single activity with a collective outcome
- the explicit encouragement of meaningful self-assessment and reflection on the skills being developed within the task.
Section 2 below describes the Astroversity game. The paper then goes on in Section 3 to elaborate the theoretical approaches to collaboration and scientific enquiry that informed the games' design. Section 4 discusses the impact of this design on hypothesis generation and testing, and development of group skills based on the results of using the software with a total of 29 13 and 14 year-old students. The paper finishes with conclusions and recommendations for future work.
2. ASTROVERSITY DESIGN
2.1 The game
Astroversity is played by groups of three co-located students, using personal computers. The game is divided into two phases: individual training and group search and rescue. In the training session each student learns to control a probe, use a sensor, record data, and plot a route for the rescue vehicle. After they successfully complete the tasks an alien vessel hits the Astroversity. This releases three toxins: bloppo - which causes human brains to swell and finally explode, moob - which causes a human heart to speed up and explode, and gunk - which effectively drowns a human by forming a liquid in the lungs. Level 1 is polluted with bloppo, Level 2 by bloppo and moob, and Level 3 has all the toxins1. At this point the students are asked to form a group of three and rescue any casualties. The rescue activity has three stages - these are described below.
2.2 The search
The students must select a moob, bloppo or gunk sensor based on information given by the system about that level. They can choose any sensor - even if the level does not contain that toxin. They then select one of six tutors to advise on search and recording strategies. These selections can be done after discussion or independently. Then each group is given four minutes to explore. As they are in the same three-dimensional environment for the same time period students can interact with their teammates. They are distinguished by having different coloured probes that 'burn' different coloured gas. During this search stage the goal is to find the casualties and a safe route to the exit. They can also change the focus of each probe to provide detailed readings of a small area or average readings from a wider range.
Figure 1 shows the student with the red probe exploring Level 1. The map in the bottom right shows they are in square I:19 and their location within the entire environment. The sensor display on the left shows the atmosphere in this square is 30% bloppo. Students are encouraged to record their findings on their personal paper-based maps to help determine a route avoiding toxins - thus this stage requires developing search strategies and systematic recording and logging of data. Possible decisions include: should they divide the area into three and each explore one section? Should they do a quick reconnaissance with the sensor set to cover a large area to gain an overview and then focus on the most likely safe route? Or should they be systematic and record safe and dangerous areas?
Figure 1: Exploring screen shot; Figure 2: Wayplotting screen
1Using artificial toxins avoided complex modelling of real gases, permitted a clear representation of the impact of gases, allowed students to make hypotheses about gas interactions, and enabled the students to focus on developing collaborative and scientific enquiry skills rather than learning factual information.
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