This report is the final deliverable for the master track ‘Design for Interaction’ of the faculty of Industrial Design Engineering at the Technical University of Delft. It describes the process and results of the graduation project ‘Assuring the occurrence of intended learning si
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This report is the final deliverable for the master track ‘Design for Interaction’ of the faculty of Industrial Design Engineering at the Technical University of Delft. It describes the process and results of the graduation project ‘Assuring the occurrence of intended learning situations in a nautical simulator’ that is executed in cooperation with VSTEP, a Dutch company that develops simulators and visual training software. VSTEP learned from its customers that Nautis is suffering from usability issues. It is initially not described where these issues are located. The project therefore starts with desk research, analysing Nautis’ current system. Additional expert interviews are conducted and literature research is executed. Observations and semi-structured interviews were conducted with instructors, the endusers, at five organisations that use Nautis. This has demonstrated that instructors are have a relatively small fraction of time available to develop scenarios. A scenario implies a virtual environment in which target vessels are following pre-specified routes, in order to mimic nautical traffic and thereupon form learning situations for the trainee. A significant amount of the little available time goes into testing and subsequently modifying. Testing usually occurs by the instructor entering one of the bridges connected to the simulator and sailing through his created scenario. Testing suggests verifying the behaviour of target vessels along their respective routes in order to prevent collisions with others, while at the same time checking if learning situations are encountered by a trainee vessel as intended. Modifications are made to the scenario when it does not come out as desired, and extra learning situations are added to accommodate different trainee performances, i.e., their pace through the scenario. This would allow for a better comparison of trainee performances. After modifying a scenario, it is again tested. Nautis offers an inefficient way of developing scenarios, which leaves instructors doubting if a trainee will reach the training goals properly. Therefore it is decided to focus on creating a solution for instructors which them to efficiently design learning situations in scenarios that allow for comparing trainee performance in order to assure that learning goals are reached. A design is proposal consisting of three components; an event creator, a trigger system, and a route generating algorithm. Each component supports the user in efficiently creating learning situations as intended. The first two components have been designed through an iterative process, suggesting sketching, prototyping, and user testing. Seven prototypes were made to validate concepts and test interactions with 13 unique participants. Some participants have tested multiple prototypes. Three instructors have taken part in the user tests. The algorithm is evaluated on its feasibility with an AI expert and desirability with an instructor. The route creator enables the user to efficiently draw out learning situations. A timeline is used to give the instructor quick access to any given timeframe in his scenario. When drawing a route for a target vessel, the currently displayed timeframe moves forward concordantly to the time it takes the particular vessel to travel the distance between the previous and the new waypoint. All target vessels in the scenario are displayed at their respective locations associated to the current timeframe. This offers the instructors direct insight whether a collision occurs, and can as such be immediately avoided. The trigger system allows the instructor to connect specific locations for target vessels in a learning situation to a manually drawn trigger area. The system assures that the target vessels sail their routes following the specified locations when the trainee enters the area with his vessel. This way the learning situation happens as intended by the instructor, independent of the trainee’s performance up until the trigger area. The route generating algorithm is used to save time on scenario development. Instructors are enabled to focus on drawing relevant parts of routes for target vessels that form learning situations. Parts that are deemed irrelevant, i.e., prior to or after a learning situation, are generated to lead the target vessels out of the trainees view. It is calculated that through the design proposal instructors can save more than 80% of their time on the development of a single scenario, ergo more time can be spend on the quality and the variety of the scenarios. Furthermore provides the assurance of the occurrence of learning situations them more guidance during the actual training sessions, and offers better comparison of trainee performances. To conclude, it can thus be stated that the design proposal would support an improvement in educational use of Nautis.