Stephen Downes

Knowledge, Learning, Community

Half an Hour, Nov 07, 2019

November 07, 2019

 

Summary of a talk by Baltasar Fernandex Manjon at CELDA 2019

 

 

ie.ft.com/uber-game

Serious games

  • - Have been used successfully in many domains – medicine, military
  • - But low adoption in mainstream education
  • - So we say we’re working in ‘game-like simulation’

http://getbadnews.com

- Fake news, trolls, e-influencers

http://play.centerforgamescience.com

http://centerforgamescience.org

http://www.re-mission2.org

  • - Has been formally evaluated

Citizen science

  • - Uses games for crowdsourcing
  • Also:
    • - Educational versions of commercial games

Do serious games actually work?

  • - Very few sg have been formally evaluated
  • - Evaluation could be as expensive as producing the game  - difficult to get funding
  • - It is difficult to deploy the game in the classroom

Learning analytics

  • - Long and Siemens

Game Analytics

  • - Application of analytics to game dev and research
  • - Telemetry – info obtained at a distance
  • - Game metrics – interpretable measures of data related to games
  • - Mostly used for commercial purposes; proprietary

Business analytics

  • - From what happened, to why it happened, to what will happen, to how I can make it happen
  • - Ie., hindsight – insight – foresight
  • - Needs all the dat
  • - Now being used in MOOCs, because they have so much data

Game Learning Analytics (GLA)

  • - Learning analytics applied to serious games
  • - Collect, analyze and visualize

Uses of GLA

  • - Game testing – eg., how many finish, avg. time to completion
  • - Game deployment in class – tools for teachers, eg. ‘stealth’ student evaluation
  • - Formal game evaluation

RAGE – game analytics (using xAPI)

Beaconing – game deployment

GLA or Informagic?

  • - Informagic - false expectations of gaining full insight on the game educational experience based on shallow data
  • - Need to set realistic expectations – most of the games are black boxes


Minimum Requirements for GLA

  • - Need access to what’s going on during the game
  • - Need access to the game ‘guts’, or the game must communicate
  • - Need to understand the meaning of the data – access to developers
  • - Also must consider ethics of data collection
    • o Are user informed?
    • o Is data anonymized
    • o Note: GDPR – creates an overhead load

GLA structure

  • - Need to be based on learning objective
  • - Based on traces + analysis
  • - Different levels of design – LAM

Experience API

  • - New defacto standard, becoming an IEEE standard
  • - e-UCM group in collaboration with ADL for profile for serious games (xAPI-SG)
  • - xAPI-SG defines a set of verbs, activity types, and extensions

Game trackers / Analytics frameworks as open code

-  http://github.com/e-ucm

Systematization of Analytics Dashboards

  • - Provided analytics uses xAPI-SG, dashboards do not require additionalconfiguration
  • - You can also do real-time analytics and warnings – more complex to do
  • - We were surprised to find how hard it is to make a visualization understandable by the average teacher – eg. Teacher interprets difficulty as ‘you are in Facebook’

uAdventure

  • - uAdventure tool (on top of Unity)
  • - game development platform
  • - includes analytics

Overview of research – 87 papers

  • - GLA purposes – mostly assessment, n-game behavious; little on interventions\techniques: mostly classical linear analytics, clusters; neural nets not broadly applied
  • - Stakeholders – teachers came third; not widely deployed
  • - Focus – to teach, most domains math and science, small sample sizes
  • - Assessment – mostly pre-post assessments
  • - Method – 2 steps – game validation phases, game deployment phase

Research questions

  • - Can we predict student knowledge after playing the game
    • o With/without pretest
    • o Can we use for evaluation?
  • - Need to have greater student numbers for analysis to be useful
  • - Result – using naïve bayes – yes, we can predict student outcomes
  • - Not sure about use for evaluation

Case Study

  • - Game on Madrid Metro used with Down Syndrome students

Case

  • - Connectado – high school cyberbullying
  • - Some minigames you can never win
  • - Result – increase in cyberbullying perception

Simva

  • - Tool used for scientific validation of serious games
  • - Goal: to simplify the validation and deployment

 

Mentions

- Game Learning Analytcs for Evidence=Based Serious Games, Feb 13, 2020
, - CELDA 2020 – Cognition and Exploratory Learning in Digital Age, Feb 13, 2020
, - , Feb 13, 2020
, - Bad News, Feb 13, 2020
, - eUCM Development Community ยท GitHub, Feb 13, 2020


Stephen Downes Stephen Downes, Casselman, Canada
stephen@downes.ca

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Last Updated: Oct 28, 2020 02:55 a.m.