Winning and Learning: Making the link between domain content and

game success explicit

H. Chad LaneInstitute for Creative

TechnologiesFriday August 25, 2006

Cannon-Bowers vs. Prensky

do I care if my pilot had fun when he learned to fly a plane?

learning doesn’t have to be fun to be successful (but we should try)

also need interesting, engaging, useful, challenging, fulfilling, motivating…

pedagogy is not a “noose”. doubts game designers will

make right decisions all the time – why risk it?

“instructional designers suck the fun out”

12 activities learners need to do (trying, deciding, observing, creating, etc.)

“negative training” is an instructional designers way of instilling fear

need “good” instructional strategies (that leave the fun).

build, eval, repair… don’t try it all at once from the beginning.

Staying focused on learning

learning objectives should be the centerpiece of a serious game• story/narrative content• game/learning activities• tutoring interventions• modeling the student & evaluation of learning

“having fun” and “entertainment” are tools to achieving learning objectives

Motivation

I made a perfect simulation about growing a company.

The only problem is that it takes twenty-five years to play.

– Steven Wright

Motivation: AARs involving simulated entities

US Army Training Circular 25-20 identifies three questions to address in an After-action Review:

1. What happened?– specify facts, actions, & outcomes

2. Why did it happen?– causes of salient actions & outcomes

3. How can units improve/sustain their performance?– alternate courses of action– areas for future practice

reflective tutoring

(discovery)

Reflective tutoring

DO EXERCISE REVIEW & REFLECTPREPARE

defined as a 1-1 tutorial dialogue with a student that happens after an exercise. To perform, one must:• judge exercise performance• decide what to talk about and how to do it• react to student’s answers and possibly adapt plans

improves students’ self-assessment and self-correction skills, and future performance

(Katz, Allbritton, & Connelly 03; Foss 87; White & Frederiksen 98; White, Shimoda, Frederiksen 99)

What human tutors do during reflective tutoring

(Katz, Allbritton, & Connelly 03)

review solution steps

clarify underlying concepts

elicit alternate solutions

“reify” problem solving strategiesidentify reasoning

behind steps

give “distributed” explanations

identify more efficient solutions

WHAT HAPPENED?

WHY DID IT HAPPEN?

HOW TO IMPROVE?

Army Needs

Support the ‘strategic corporal’• Leadership as the ultimate battlefield force multiplier (Ulmer, 1998)

• Leadership tasks have migrated downward (Brown, 2003; Wong, 2004)

Accelerate the development of adaptable leaders• Learning orientation (Kolditz, 2004)

• Complexity of roles, warfare, change (Wong, 2004)

Enhance cultural awareness• Decisions in a cultural context

• Social interaction

• Second and third order effects

Rapidly transfer lessons learned from COE• Stories and experiences

• New tactics

Two projects

SASO-ST / Virtual Humans• conduct AARs for sessions with Dr. Perez• separate prototype system & not yet general• XAI-heavy (rich cognitive models)

ELECT• online coaching & reflective tutoring• integrated system that runs on 3 characters• authorability a top priority• XAI-light (shallow cognitive models)

SASO-ST Reflective Tutoring System

exercise log annotate

executortutorial planner“critic”

expert taskknowledge

commonmistakes

A B G…

tutoringtactics

plan out AAR

utterances &expected answers

conduct AAR

AGENDA

Sample Dialogue with Doctor

1. CAPTAIN: Hello Doctor Perez.

2. DOCTOR: Hello.

3. CAPTAIN: I have orders to move this clinic to another location.

4. DOCTOR: You want to move the clinic.

5. CAPTAIN: Yes.

6. DOCTOR: Do you see that girl? She lost her mother today.

7. CAPTAIN: It is not safe here. We cannot protect you.

8. DOCTOR: Protect me? Protect me from what?

9. DOCTOR: You are going to attack?

10. CAPTAIN: Yes.

11. DOCTOR: I would have to refuse this decision.

12. DOCTOR: My patients need my attention now.

Got

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ELECT

also focuses on interpersonal skills, cultural awareness, & negotiation

coaching & reflective tutoring authorability top priority

• learning objectives• game content• tutoring utterances, timing, and form• inherently limits the richness of the underlying

models

preparing & executing an AAR

load game log from DB prepare agenda

• process coach’s assessments• collect into groups (called agenda items)• skip less critical events• build scoreboard from agenda

conduct AAR• work through all agenda items• execute tutoring tactics to address each • replay when it is important to establish context• for now, AARs are chronological and tutor controlled.

Linking actions to LOs

LEARNING OBJECTIVESLO#1

LO#2

LO#N

…

GAME ACTIONS

CHALLENGE NETWORKS

GIVE Candy

GIVE Decorative sword

ASK About family

DO Menace Tariq

…

IF (flatter > 3)

Challenge

a) ------

b) ------

c) -------

IF (weapons & helmet)

Challenge

a) ------

b) ------

…

++

-+

+-

…

+

Reflective tutoring plans

Agenda

Agenda-Item A

Annotation Group 1

Annotation a1

Learning Objective +/-

Agenda-Item B Agenda-Item C ...

Annotation Group 2

...

... Annotation Group 3

...

Annotation a2Tutoring Cognitive Model consists of: Agenda traversal rules:

• Iterates over nodes of the agenda, in simulation-chronological order, depth first

Tutoring Tactics rules:• Rules that generate text and

interactions at various levels of the Agenda-Learning Objective Hierarchy

Types of Tutoring Tactic Actions

Give direct feedback (e.g., “Good job starting the meeting.”)

Do over• Video replay to re-establish context (similar to Peters et. al. @Stanford)

• Prompts the user to choose a new action at the same time-point of the simulation that the current action took place at.

Generate ideal action• Same as above, but identifies the best action at the same time-point of the current

action.

Tutor/Student interaction• Generates a menu of tutor questions and allows for a limited number of incorrect

responses and retries.

XAI interaction (aka, “investigation”)• Hands over control to XAI

• Student asks questions of the game character(s).

• Gives hints for non-progress on the investigation plan, and positive feedback on progress.