1. Dr Maurice Hendrix Researcher Link workshop, Brazil, 21 Mar 2017
Personalisation in educational games and virtual environments: Difficulty balancing, procedural content generation and VR
Dr Maurice Hendrix
Researcher Link workshop, Brazil, 21 Mar 2017

2. Outline
Educational games
Personalisation VR
Open questions

3. 42% of Americans play regularly Average 13 years experience
Computer Games
Electronic game involving interaction with a computer
Large proportion of population plays
Large industry for entertainment games
26%
27%
44%
56%
17%
30%
AGE
of Game Players
26% under 18 years
30% years
17% years
27% 50+ years
GENDER
of Game Players
56% male
44% female
42% of Americans play regularly
Average gamer is 35 years old
Average 13 years experience

4. Types of Serious Games

5. Educational Games Games often used as they are seen as engaging
Issues:
Competing with commercial games
Different players (styles, knowledge, gaming abilities)
Depending on game design: representation on a screen has limitations for immersion
Often scenario based and very limited replayability

6. VR Adaptation

7. Personalisation What to adapt in a game? Depends on game design
Content
Choose from alternative
Procedural generation

8. Personalisation What to adapt to? Learning styles? Controversial 
Background knowledge / skills? Many games stand-alone or poorly integrated (don’t know background)
Csikszentmihalyi's Flow? Difficulty balancing is a ‘low hanging fruit’

9. Case study: obesity prevention (pegaso eu project)

10. 6 steps for difficulty balancing
Identify what in the game indicates difficulty by examining the gameplay and victory conditions.
Identify what of these elements we can influence?
If an implementation exists, locate variables in code.
Consider whether the game features multiple mechanics and if so, if they are dependant or independent.
Decide how variables will be used to calculate difficulty.
Decide upon sensible starting values.

11. 6 steps for difficulty balancing
Indicators of difficulty
zombie mechanic: number killed, score, nights survived
Food matching: amount of food, XP, nights survived
We can influence:
Amount, and speed of zombie enemies faced.
Amount of possible matches on boards and size of boards
Variables located in code (scripts in Unity 3D engine)
Multiple mechanics.
Semi-independant
Decide how variables will be used to calculate difficulty.
Weighted average
Decide upon sensible starting values.
Empirical with a few volunteers

12. Evaluation? Also conducted with small platform game
Case studies show how steps can
be used by developers
Participants like adapted versions better
But small scale and brief so no meaningful data on learning (yet)

13. Case study: Kayaking VR rehab
Kayak vr rehab learnig

14. Kayaking VR rehab
Need to influence the environment (as with platformer)
Conducted using procedural generation
Motion sickness can be a problem

15. Open questions & further directions
Game engine plugin (Unity 3D)
Is engine independent framework possible?
In VR – how does generation of content effect cyber sickness? Can we adapt to a persons susceptibility?
Practical way to get background knowledge / skills or dos it need VLE integration?