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11_04_2019 EDUCON eMadrid special session on "Game learning analytics for educators"

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Authors: Antonio Calvo Morata, Cristina Alonso Fernández, Manuel Freire Morán, Iván Martínez Ortiz y Baltasar Fernández Manjón / Universidad Complutense de Madrid (UCM)

Publicado en: Tecnología
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11_04_2019 EDUCON eMadrid special session on "Game learning analytics for educators"

  1. 1. Game Learning Analytics for Educators Antonio Calvo-Morata, Cristina Alonso-Fernández, Manuel Freire, Iván Martínez-Ortiz, Baltasar Fernández-Manjón EDUCON 2019, Dubai UAE https://www.slideshare.net/BaltasarFernandezManjon/
  2. 2. Serious Games Serious Games: main purpose not entertainment (e.g. learning, raising awareness, changing players’ attitudes) For their application in education, educators may face several issues: ➢ technology or platform requirements ➢ gameplay average duration ➢ adaptation for users with special needs or disabilities ➢ availability of enough number of devices ? ? ? ?
  3. 3. Analytic System collection, analysis, reports Game Learning Analytics Game Learning Analytics aims to collect and analyze data from serious games. Game Analytics + Learning Analytics ➢ evaluate and improve games ➢ provide information that helps educators ➢ evidence-based decisions for institutions ➢ more authentic learning experience for students play information & feedback GLA data
  4. 4. GLA System: H2020 RAGE & BEACONING
  5. 5. Teachers’ process applying games GLA data
  6. 6. Serious Games formal validation First step for serious games: formal validation. Most common method: pre-post experiments - pre-test measures characteristic (e.g. knowledge, awareness) before playing - post-test measures same characteristic after playing ➢ Requirement: accepted questionnaire that measure the specific characteristic - If no such questionnaire exists, complexity escalates as first, the validation questionnaire itself has to be developed and validated!
  7. 7. Serious Games application in classes
  8. 8. SGs application in classes: before Before games are in play, teachers/educators will: 1. Read the educators’ guide ○ downloading/installing instructions ○ game goals ○ information about the game content ○ additional information about context ○ instructions for students 2. Play the game ○ get the same experience their students will ○ understand design decisions and link them to educational content
  9. 9. SGs application in classes: during While games are in play, teachers/educators will: 1. Receive real-time information ○ follow students progress ○ get overview of errors ○ receive warnings/alerts for specific situations 2. Act accordingly ○ help students having issues to continue ○ provide additional tasks to advanced students
  10. 10. After games are in play, teachers/educators will: 1. Conduct post-game activities ○ discussion/debriefing to promote reflection ○ link game content with curricula ○ additional exercises to apply the content of the game ○ even assessment activities SGs application in classes: after ➢ These post-game activities may be suggested in the educators’ manual.
  11. 11. Students evaluation based on in-game interactions Final step to simplify educators’ tasks: formal and automatic evaluation of students based on their actions playing the game ➢ common assessment method: pre-post questionnaires ➢ drawbacks can be avoided using GLA data from in-game interactions to predict players’ knowledge after playing 1. Create prediction models at validation step 2. Train algorithms and evaluate performance with actual data 3. Select accurate-enough models as assessment method 4. New players: predict knowledge with models and GLA data
  12. 12. Conclusions ● Educators are key to promote the application of games in education ● Games need to be transparent and reliable as educators are not game experts 1. Formal validation with accepted method (e.g. pre-post) 2. Application in class obtaining real-time information 3. Assessing students based on in-game interactions ● Limitations: ○ Technical support still needed in many contexts ○ Still a complex and fragile infrastructure that requires an analytic server ○ Privacy and security needs to be ensured when collecting data (GDPR compliance)
  13. 13. Thank you! Baltasar Fernandez-Manjon @baltaFM balta@fdi.ucm.es Code: https://github.com/e-ucm https://www.slideshare.net/BaltasarFernandezManjon/ www.e-ucm.es

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