V Jornadas eMadrid sobre “Educación Digital”. Ángel Serrano, Universidad Complutense de Madrid: Applied games, learning analytics and standards. 2015-06-30
Bill Aulet GEC2016 keynote speech March 16 2016 Medellin Colombia
Similar to V Jornadas eMadrid sobre “Educación Digital”. Ángel Serrano, Universidad Complutense de Madrid: Applied games, learning analytics and standards
Playability & Player Experience ResearchLennart Nacke
Similar to V Jornadas eMadrid sobre “Educación Digital”. Ángel Serrano, Universidad Complutense de Madrid: Applied games, learning analytics and standards (20)
3. Well, it depends...
Who?
First year law student
Teacher of “Applied Maths”
Vice Dean of the School of Medicine
Minister of Education
Where?
Khan Academy
Udacity
Complutense University
UNED
Why?
Suggest educational pathways after completing a law degree
Assess students performance in “Applied Maths”
Identify teachers whose students perform best in the School
of Medicine
Evaluate child's reading level in Spain
4.
5.
6. Some ideas
Rich reporting is awesome for research and data
analysts...
… but not necessarily for most final users.
Largest amount of information in the most concise
representation.
Interventions and actions required by users of the
system's users in the center.
8. Goals
1) Reliable framewok to assess students
performance through educational videogames.
2) All data and information collected by the
framework could be shared with others.
9. Main challenges
1) The great variability in videogames
Mechanics, genre, aesthetics...
2) Lack of public research in Game Analytics.
Far less in Game Learning Analytics
Public research mostly focused in monetization.
13. Game model
●
Quests: the current goal of the player, the next
thing he needs to accomplish to advance in the
game
●
Zones, areas, levels...: a virtual area in which the
player can enter or exit
●
Variables: a variable with a meaningful weight
inside the game
●
Choices: a set of options offered to the player,
usually with different consequences
15. Player action Event Target Value
Gameplay started start Empty Empty
Gameplay ended end Empty Empty
Entered in a zone. Implicitily,
exits any previous zone
zone Empty Zone identifier
Variable value updated var Variable name New variable value
Quest started quest_started Quest id Empty
Quest finished quest_finished Quest id Quest result
Selected an option in a
choice
choice Choice id Option id
Traces
21. Gameplay State
{
"zone": "menu"
"vars": {
"score": 100,
},
"quests_finished": ["quest1", "quest2"],
"quests_started": ["quest3", "quest4"],
"choices": {
"players": {
"player1": 1
}
},
"..."
}
Built in real time... (with Apache Storm)
Server holds gameplay state for each indivdual player
22. Assessment Model
●
Score
– Overall performance of the player
●
Progress
– General progress in the game. How long until the player is done
with the simulation
●
Alerts
– Gameplay state in an undesired condition
– Might need instructor intervention
Gameplays are the base for assessment. In our
assessment model:
33. Conclusions
● General Game Model to define games in a
common vocabulary
● Analysis over game states represented as an
aggregation of traces
● Simple visualizations, focused on actions
● xAPI as communication standard