2. What is the point of
GBL?
You will have heard a *lot* about motivation and
serious games.
Is that all SG / GBL have to offer?
If so, what is special about games?
3. Chen & Wang 2009
“Engaging learners in the learning process is the
pre-requisite for effective e-learning.”
“However, making learning more engaging relies
on considerate design of learning activities”
C&W argue for the value of interactivity in quality
learning
Thus - games - but what is “considerate” design?
4. Learning Theories
Two main schools:
Objectivism
Learning == transfer of knowledge
Constructivism
Learning == individual’s creating their own
version of knowledge
7. Procedural /
Declarative
We have evidence to support games for simple
declarative / procedural knowledge improvement.
Skill and Drill / Edutainment
factual & procedural knowledge depend on
strength of memory and ease of recall
so “all” you have to do is repeat until it’s muscle
memory. Memory, not thought.
8. Skill & Drill Pedagogy
Motivation of games is the main benefit.
Goal is repeated practice of a skill until automatic
Math Blaster, Brain Training, “training games”
Gamification type approaches to incentivise
9.
10.
11. Constructivism
Knowledge is created through contact between
thoughts and the world.
The model is IN YOUR HEAD and is modified by
how you interpret input you get.
Dewey / Piaget / Vygotski / Bruner / Gardiner /
Papert
12. Daniel Willingham
Motor learning is the change in capacity to
perform skilled movements that achieve
behavioural goals in the environment. A
fundamental and unresolved question in
neuroscience is whether there are specific neural
systems for representing sequential motor
responses. Defining such systems with brain
imaging and other methods requires a careful
delineation of what specifically is being learned for
a given sequencing task.
13. Daniel Willingham
A chiffon cake replaces butter— the traditional fat
in cakes— with oil. A fundamental and unresolved
question in baking is when to make a butter cake
and when to make a chiffon cake. Answering this
question with expert tasting panels and other
methods requires a careful description of what
characteristics are required for a cake.
14. Schema
We don’t easily store “facts”, we have networks of
related concepts.
When we encounter something new, we
understand it in context of what we already know.
So knowledge creating is a subtle modifying over
time of these networks of concepts.
15.
16. Games as
Microworlds
The Shaffer & Svarovski paper I spoke about last
week (SodaConstructing) introduces two
concepts:
Exploratoids (extension of Explanatoid)
Microworlds (robust simulation of some domain)
17.
18. Problem Based
Learning
Step 1: Topic Introduction - why it’s important
Step 2: problem statement
Step 3: generate hypotheses
Step 4: acquire data
Step 5: test hypothesis
23. Constructive
Alignment
Biggs 1996:
Learners construct meaning from what they do
Teacher makes deliberate alignment between
planned learning activities and desired learning
outcomes.
24.
25.
26.
27.
28. So here’s my idea
Cognitive Walkthrough for Learning Through
Game Mechanics
CWLTGM!
29. Cognitive
Walkthrough
One or more experts will “walk” through a set of
steps required to accomplish a task.
Before beginning, you detail as much as you can
about:
What the user knows
What steps are required to accomplish the task
Then you walk through each step questioning:
30. CW Questions
1: Will the user try to achieve the right effect?2:
Will the user notice that the correct action is
available?3: Will the user associate the correct
action with the effect to be achieved?4: If the
correct action is performed, will the user see that
progress is being made toward solution of the
task?
31. Success or failure
story
For each step you try to come up with a
(believable) success or failure story.
the user knows to click the print icon because
she recognises the shape of the printer as
representing the print function
the user fails to find the left-align icon because
she does not know to expand the “hidden
icons” area
33. CW for GBL
I did two things:
Contextualise
Extend
34. Contextualise: Inputs
Who are players and what do they know?
What are the desired learning outcomes of the
task?
How are game and domain entities represented?
What are the interactions required for player to
learn the content
35. Contextualise:
walkthrough
Step 1: will player attempt the desired task?
Step 2: Will player understand what game actions
would achieve the task?
Step 3: Will player associate their correct action as
making progress towards task completion?
Assuming player executes correct actions, is it
reasonable to expect learning to take place?
36. Step 4/1
List every logical connection that must be made by the player
in order to learn through playing this part of the game.
Must the player recognise domain-entity mappings?
Must player understand semantic meaning of an animation
or in-game action to subject domain?
How many game elements must the player consider at once
to understand the subject domain system?
Generally - you want to avoid making LEAPS of logic, you
want to detail each small logical link.
37. Step 4/2
For each of the logical links identify - reconsider it
and ask if it is actually two or more steps of logic -
if so, split it
by just FORMALLY going over each item, you
find mistakes
Rinse and repeat
38. Step 4/3
When you are satisfied that each link is explicit, consider each
logical link and ask whether it is reasonable to expect the player
to make this connection / logical inference.
Will the imagined player understand the visual metaphors?
Will the player read and understand required text?
Will the player’s attention be drawn to the elements mentioned
in the logical link?
Will the players understand the relationship between the in-
game entities, but fail to recognise how that applies to the
subject domain?
39. At the end of step 4
This is where you write your “success” or “failure”
story for each item of your logical chain.
I categorise into low, medium, or high risk.
40. What’s the point?
Firstly, we can understand WHY things worked or
did not work in a given design.
But more powerfully (in theory) by applying the
technique to designs PRIOR to implementation,
we can identify flaws that would not be spotted.
41. What next
I have handouts:
The e-Bug evaluation paper (has the table
explaining results)
An overview of Cog Walk
My (in progress) Cog Walk paper
I want you to read these before the lab if you can.
42. Labs
Between now and the labs, I’m going to move to
the next turn of CareerQuest.
So we’ll do that in the labs for 5 mins.
The rest of the lab will be you applying CWLTGM
to evaluate the “white blood cell” bit of the game.
I want to see if you end up with the same answers
as me!
43.
44. References
Chen, M., & Wang, L. (2009). The Effects of Type of Interactivity in Experiential Game-Based Learning, 273–
282.
Svarovsky, G., & Shaffer, D. (2006). Sodaconstructing an Understanding of Physics: Technology-Based
Engineering Activities for Middle School Students. Proceedings. Frontiers in Education. 36th Annual
Conference, 17–23. doi:10.1109/FIE.2006.322594
Farrell, David (City University, L., Kostkova, P (City University, L., Lecky, D. (Health P. A., & McNulty, C.
(Health P. A. (2009). Teaching Children Hygiene Using Problem Based Learning: The Story Telling
Approach to Games Based Learning. International Conference on Web-based Learning (ICWL), Second
Workshop on Story-Telling and Educational Games (Vol. 37).
Willingham, D. T. (2009). Why don’t students like school: A cognitive scientist answers questions about
how the mind works and what it means for the classroom. Jossey-Bass.
Queens University, Problem Based Learning. http://meds.queensu.ca/pbl/pbl_in_practice/pbl_process
Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher education. Retrieved from
http://www.springerlink.com/index/l2q3820h2436l607.pdf
Wharton, C., & Rieman, J. (1994). The cognitive walkthrough method: A practitioner’s guide. In J. Nielsen &
R. Mack (Eds.), Usability Inspection Methods. New York: John Wiley & Sons. Retrieved from http://psych-
www.colorado.edu/ics/techpubs/pdf/93-07.pdf
Hinweis der Redaktion
The first paragraph is understandable if you take your time. 1: definition 2: problem 3: a descritpion of the thing under study is necessary before the problem can be addressed. The 2nd paragraph is written with same structure - but which will you remember tomorrow? You already know a lot about cakes. A cake is buttery, not oily so the use of oil unusual. Also the sentence “what characteristics are required” - you already kind of know for cakes.
But as Squire says, you can’t use Civ in classrooms because it doesn’t align with curricula!
Note the use of reflection. This could be a key element of the design that I missed. Let’s spend some time thinking about this model. Can you design using this?
Remember Civ? How it’s not aligned with curricula. There lies a KEY angle for designers.
This is why I designed e-bug the way I did.
This is why I used a MDA style approach.
You can see (hopefully) how I was trying to design these activities. But there is a gap. The models aren’t enough. The game doesn’t REALLY work.
Why do YOU think the game wasn’t more successful? And why the inconsistency? Same designer / programmer / artists / scientists / teachers. I didn’t know! Had some vague ideas. But that’s a crazy way to design. You can’t rely on “vague ideas”.
They key is to ask those questions while SIMULATING THE USER IN YOUR BRAIN
I realised that there is NOTHING UI specific about CW. It’s actually about UX not UI. You just need to ask different questions - the general process is universal.
At this point, it’s not really ALL THAT different from existing practice. But Step 4 is the magic - and that is the extension. I divide step 4 into sub steps.
Links can be categorised as low risk if it is likely that the player will make the connection; moderate risk if the player should make the connection, but there is enough doubt to warrant further attention; high risk if it is unlikely that the player will make the connection.
