La evaluación del Aprendizaje Basado en Juegos en contextos informales mediante ciencia de datos

• Xavier Rubio Campillo ^[1] ; Kevin Marín-Rubio ^[1] ; Celia Corral Vázquez ^[2]
  1. [1] Universitat de Barcelona

     Universitat de Barcelona

     Barcelona, España

     
  2. [2] IMIM: Institut Hospital del Mar d'Investigacions Mèdiques
• Localización: RELATEC: Revista Latinoamericana de Tecnología Educativa, ISSN-e 1695-288X, Vol. 23, Nº. 2, 2024, págs. 9-26
• Idioma: español
• DOI: 10.17398/1695-288X.23.2.9
• Títulos paralelos:
  • Using Data Science to evaluate Game-Based Learning in informal contexts
• Enlaces
  • Texto completo
• Resumen
  • español

    El auge del aprendizaje basado en juegos (ABJ) digitales ha generado un interéspor explorar su eficacia, ya que su compleja combinación de narrativa e interactividad hacedifícil evaluar hasta qué punto un videojuego consigue alcanzar los objetivos de aprendizajeplanteados. Este reto se incrementa de manera exponencial cuando la sesión de juego seproduce de manera espontánea en entornos informales, sin la supervisión de educadores nila posibilidad de evaluar los conocimientos y las capacidades previas del jugador. Estetrabajo presenta una metodología de análisis de experiencias de ABJ a partir del uso deciencia de datos y las funcionalidades de recogida de información ofrecidas por lasplataformas actuales de creación de videojuegos. La estrategia se aplica aquí al análisis deun simulador de redes sociales creado para promover la alfabetización informacional,enmarcado dentro del juego Julia: A Science Journey. El sistema registró datos sobre 436partidas realizadas por 112 jugadores distintos durante seis meses y recopiló informaciónsobre la repetición de partidas, la identificación de fake news o la velocidad de reacción. Losresultados sugieren que los jugadores aprenden a identificar fake news de manera másefectiva y rápida a medida que encadenan partidas. El éxito en la identificación de ladesinformación también está relacionado con la temática, ya que los bulos vinculados acontenido científico son más fácilmente reconocidos que los relacionados con controversiaspolíticas

  • English

    The emergence of digital Game-Based Learning (GBL) has sparked interest inassessing its efficacy. This assessment needs to consider the complex mix of narrative andinteractivity typical of video games, which makes it difficult to evaluate to what extent avideo game achieves its stated learning objectives. This challenge is exponentially increasedwhen gaming sessions happen spontaneously in informal contexts, without any supervisionby educators or the option to assess the players’ prior knowledge and skills. This workpresents a methodology for analyzing GBL experiences based on data science and the datacollection functionalities offered by current game development platforms. This strategy isapplied to the analysis of a social media simulator designed to promote information literacywithin the video game Julia: A Science Journey. The system collected data on 436 sessionsfrom 112 unique players over six months. The records included information on replayability,identification of fake news, and reaction times. The results suggest that players becomemore adept and swifter at identifying fake news through repeated games. Success inidentifying misinformation is also related to the topic, with hoaxes related to scientificcontent being more easily recognized than those associated with political controversies

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