Abstract

Serious Games (SGs) are used to support knowledge acquisition and skill development. For this, there is a need to measure the results achieved (both during and after students play) to ensure the game effectiveness. In this context, the aim is to develop and evaluate the AvaliaJS, a conceptual model to structure, guide and support the planning of the design and execution of the student's performance assessment in SGs. AvaliaJS has two artifacts: a canvas model, for high-level planning, and an assessment project document, for more detailed specifications of the canvas. To analyze and exemplify the use of the model, the artifacts were applied to three ready-made games as a proof of concept. In addition, the quality of AvaliaJS was evaluated by experts in SGs development and assessment using a questionnaire. The results of experts' answers confirm a good internal consistency (Cronbach's alpha α = 0.87) which indicates that AvaliaJS is correct, authentic, consistent, clear, unambiguous and flexible. However, the model will need to be validated during the process of creating a new game to ensure its usability and efficiency. In general, AvaliaJS can be used to support the team in the planning, documentation and development of artifacts and data collection in SGs, as well as in the execution of the assessment, learning measurement and constant and personalized feedback for students.

Highlights

  • There are two main points in Serious Games (SGs): (1) combination of games with one or more functions, such as broadcasting a message, providing training or promoting data exchange; and (2) application in a specific domain, such as defense, training, education, healthcare, and not just in the entertainment area (Zyda, 2005; Alvarez; Djaouti, 2012)

  • The objective of the application and exemplification of the AvaliaJS is (according to Goal/Question/Metric (GQM) method, proposed by Basili et al (1994)) : Analyze the games GLPSobControle (G1), Guerra em Alto Mar (G2) and Expedição Antártica (G3) for the purpose of evaluating and exemplify the use of the conceptual model as proof of concept with respect to coverage of contents to fill in the model from the viewpoint of researchers in the context of development and assessment/evaluation in serious games

  • Filling out the canvas model and the project document was prepared by the researchers (who participated in the productions of these games (G1: author 2, G2: author 1, G3: authors 1, 2 and 3)), after defining the games analyzed

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Summary

Introduction

There are two main points in Serious Games (SGs): (1) combination of games with one or more functions, such as broadcasting a message, providing training or promoting data exchange; and (2) application in a specific domain, such as defense, training, education, healthcare, and not just in the entertainment area (Zyda, 2005; Alvarez; Djaouti, 2012). SGs can be digital (computer use) or analog games (boards and physical objects), and grouped into genres, such as adventure, action, puzzle, strategies (Abt, 1987; Shell, 2008; Petri, 2018) In this context, Djaouti et al (2011) have developed a model for serious game classification, consisting of three aspects: (1) gameplay: intended to provide information about the game structure of the SG, can be gamebased (well-defined rules, such as Mario World) ou playbased (does not feature stated goals, such as Sim City); (2) purpose: indicates the overall goal of the game, which is divided into three types: (a) message-broadcasting (educative, informative, persuasive and subjective); (b) training (to improve cognitive performance or motor skills); (c) data exchange (collecting player information); and (3) escope: indicates the kind of market (health, military, education, religious) and the audience (general public, professionals and students). The assessment is defined as the process of collecting, reviewing and using data, to improve the student's current performance (help to learning and skills development), to provide them feedback on their errors and hits (Bellotti et al, 2013; Daoudi et al, 2017)

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