The Experiment
Following on the development of a New methodology for detecting soft skills with commercial video games, the project began testing the with volunteers. To connect what happens in our mind while we play video games, it is necessary to carry out an experiment that tests our hypotheses. In this experiment we have formulated about thirty hypotheses and sub-hypotheses, however the main one remains the same: “Do video games have a positive influence on the development of soft skills compared to the control group?” Taking into account that the control group will take the tests but will not play the proposed video games.
To give a summarised example of this link between the tests and their rubrics, we can say that one of the tests selected to measure the Problem Solving skill of an individual goes through “CPS2. Learn from previous problems and improve your performance and efficiency when solving new problems.” Subsequently, a matrix is created listing the video games that contain mechanics in which the player, in one way or another, is evaluated based on their ability to improve their performance and efficiency as they solve increasingly complex situations but with relationships to their previous challenges. We parameterise these parallel rubrics in video games thanks to the use of Steam achievements.
After comparing a list ofpotentially compatible video games, those with a greater compatibility rate between their mechanics and the rubrics of the standard tests were selected,resulting in the following list:
*Special thanks to the FLAZM team for providing us with the necessary licenses to carry out this experiment.
Smart assessment and digital certification
One of the novelties thatwe include in our research trajectory in the relationships between soft skillsand video games comes from the hand of the project leader. TECNALIA willincorporate its Artificial Intelligence team with the aim of establishing relationshipsbetween gamers’ behaviors within the game and the results of the tests throughthe identification of specific patterns. The advantage of using advancedartificial intelligence algorithms is that an immense amount of information canbe processed from interactions with games and test data. It will also bepossible to generate comparisons between participating users so that we canfind patterns not only of improvement but also of projection and potential, aswell as improve the detection model and even, in the future, be able toautomate the cataloging procedure of games based on their training capabilitiesfor these skills.
The tasks of this part ofthe project involve training the AI to be able to identify the rubric system ofthe tests that we use and find their equivalences in the game mechanics,detecting whether the relationships between them are significant enough to corroboratethat soft skills learning really happens and how can be measured.
The most technologicalpart of the project culminates with a digital and standard accreditation systemfor the skills acquired through the MEGASKILLS platform. Our purpose is forthese certifications to be protocolized with the European Europass curriculumvitae system standards.
A platform adapted to a pedagogical implementation model
In the MEGASKILLS projectwe clearly differentiate what is the development of a technological innovationin the educational sector from its implementation in a pedagogical context. Thecreation of a technology does not mean that it will be naturally and intuitivelyaccepted in a classroom and in a job training context. That is why it isnecessary to propose a methodology to solve potential challenges in the use ofthe platform for measuring soft skills with video games, among which are:teachers and/or students with deficiencies in digital skills and gamer culture,deficient knowledge in soft skills (importance and definition), learningprocess perceived as a memorable and enjoyable experience, flexibility inadapting content and experience to the receiving sectors, among others.
Once the pedagogicaldesign is completed, several pilot-tests will be executed in collaboration withour partner CEGOSto evaluate the performance of the platform and the satisfaction of theexperience. Our intention is to collect enough information and suggestions torefine the model and turn it into the reference pedagogical system for thetraining and measurement of soft skills. Also generate the necessary materialsfor both students and teachers and thus be able to eliminate the gaps mentionedabove.
References
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This text is part of an article was first published in GECON's website on the 14/02/2024.
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Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.