An iterative approach to designing scalable and adaptive

computer-based science instruction

Mari Strand Cary, David Klahr,

Stephanie Siler, Cressida Magaro,

Kevin Willows, Junlei LiCarnegie Mellon University & University of Pittsburgh

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Goal of this EdBag?

• Discuss this iterative research process and its role/prominence in curriculum design, HCI, etc.– Usefulness to researchers and designers

(and, more importantly, end-users)– How different is it from “design research”– Difficulties we’ve encountered– Other?

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Overview of the TED projectCurriculum: Experimental design, evaluation,

and interpretationAge: 5th-8th grade studentsSchools: 6 inner city

– 4 low SES & challenging classroom environments– 2 mid-high SES

End goal: Computer-based adaptive tutor– 1 student : 1 computer in classroom environment

– Provides individualized, adaptive instruction– Supplements (does not replace!) teacher

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“Experimental design” = CVS (Control of Variables Strategy)

1. Simple procedure for designing unconfounded experiments

(Vary one thing at a time)

2. Conceptual basis for making valid inferences from data

(Isolating the causal path)

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Does SURFACE affect how

far balls roll?

A

B

Variable Ramp 1 Ramp 2

Surface Smooth Rough

Track length Short Long

Height High Low

Ball Golf Rubber

Ramp 1 Ramp 2

Smooth Rough

Short Short

High High

Golf Golf

Confounded Unconfounded

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What’s the best way to teach CVS?

• As a society (educators, researchers, and legislators), we don’t know

• Our research team knows of one effective way…

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Our basic CVS instruction (used in various forms in past studies)

• Students design experiments

• Students answer questions

• Instructor provides explicit instruction about CVS

• One domain

• Short instructional period

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But…

Our brief, focused CVS instruction is differentially efficient and effective for different student populations, settings, and transfer tasks.

We want to reach ALL students!

To improve our instruction for the entire student population, we must engage in modification & individualization

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A computer tutor could facilitate differentiated instruction

• Instruction that suited for full-class setting could be provided by teacher

• Remaining instruction could be provided by computer tutor– Individualized & self-paced– Provides instruction, practice, and

feedback– Teacher freed to provide coaching as

needed

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How are we building our tutor?

4 development phases

&

Iterative design process

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4 development phases:1. Information gathering: What are the

novice models students hold and how can we address those?

2. Refining the basic instruction and “going virtual”

3. Building a computer tutor with a few “paths”

4. Building an adaptive computer tutor with a “web” of paths

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Improve current version &

Inform next version

Compare against previous version

Our iterative design process:

Version n

Pilot testing

Delayed post assessment

One-on-one human tutoring

Classroom validation study(+ pre, post, and formative

assessments)

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An evolving CVS computer tutor

Version 1 Version 2 Version 3 Version 4

Instructional mode

Class (teacher) 2a) Class (teacher) Class (teacher)

Individual (computer)

Class (teacher)

Individual (computer)

InflexibleFlexibility Limited flexibility(differentiation points)

Flexible (multiple paths)

Adaptive (“web” of paths)

Stimuli Simulations

Computer interface

Physical apparatus

Overhead transparencies

Simulations

Computer interface

Simulations

Computer interface

Instructional components

(domain)

Procedural & Conceptual (Ramps)

Prereq. skills (Auto sales)

Procedural (Study habits)

Conceptual (Ramps)

TBD TBD

DiscussionFeedback Discussion, paper exchange, researchers

Discussion, Computer, researchers TBD

2b) Small groups (us!)

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What are we learning from each version that will help us design the final, adaptive tutor?

VERSION 1 (Completed)

• Initial list of student biases, misconceptions, errors & areas of difficulty

• Inventory of successful tutoring approaches

• familiar domains

• instruction in prerequisite skills

• step-by-step approach

• Student-friendly terminology, definitions, and phrasing

• Requiring explicit articulation by student

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A sampling of what students do wrong:

Common errors:• Vary everything• Hold target variable

constant and vary other variables

• Partially confounded• Nothing varied (identical)

Common justifications:• “I don’t know”• You told me to test x!• Describe their set-up• Want to see if x happens• Want to see if this setup

is better than that setup

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Why?• By accident

– misread question– working carelessly

• Are led astray– by saliency of physical apparatus (e.g., ramps) – don’t understand written representations (e.g.,

tables)

• On purpose – different goals (e.g., “engineering”)– misconception of experimental logic– think other variable(s) don’t matter

• Just guessing

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VERSION 2a (Complete) & 2b (Fall 2007)

Information regarding:

• Addressing most common problems in full-class instruction using successful tutoring approaches

• Instructional effectiveness of switching domains

• effect of emphasizing domain-generality

• interface usability

• worksheet usability

• 2b: Implementation of successful tutoring approaches with small groups (groups will differ in the “paths” they take)

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VERSION 3 (being developed)

Information regarding:

• division of instruction between teacher and tutor

• individual tutor usability and pitfalls

• comparative efficacy of set learning paths

• efficacy of immediate computer feedback

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The adaptive tutor will include:

• Pre-testing and ongoing monitoring of student knowledge

• Self-paced instruction

• Diverse topics matching student’s interests

• An interactive and engaging interface

• Teacher-controlled and/or computer-controlled levels of difficulty

• Level of scaffolding, feedback, and help aligned with student’s needs

• Computerized assessments

• Logging capability (“level” of output TBD)

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Discuss!

• Discuss this iterative research process and its role/prominence in curriculum design, HCI, etc.– Usefulness to researchers and designers (and,

more importantly, end-users)– How different is it from “design research” (and

would it have gotten funded if we had labeled it that?)

– Difficulties we’ve encountered– Other?

Questions? Comments?

MariStrandCary@cmu.edu

Klahr@cmu.edu

Funding provided by:Institute of Education Sciences (IES _____)

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V1 learning examples:

VERSION 1

• Database of student biases, misconceptions & areas of difficulty

• Inventory of successful tutoring approaches

• familiar domains

• instruction in prerequisite skills

• step-by-step approach

• Student-friendly terminology, definitions, and phrasing

• Requiring explicit articulation of understanding and reasoning

Ignore the data or Biased by expectations

Create “best” outcome or Most dramatic difference

Learn about all variables at once

Pets, Sports drinks, Cars, Study habits, Running races

Variable vs. Value

Experiment

Result vs. ConclusionRead carefully, Identify question, Identify variables…

Good vs. Fair vs. Informative vs. True

“Variable” = something that can change

Table format

Remembering the target variable

Drawing conclusions based on the experiment

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Stand-alone, detailed lesson plan with

visual aids

Examples of exp. designs

(good and bad)

Assessments (formative and

summative)

Students designing experiments

Asks students to explain, justify,

and infer

Feedback

Every version

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Increasing complexity and adaptiveness

Physical apparatus Virtual simulations

Full class Full class & individual computer use

Inflexible Individually-adaptive & self-paced

One domain Multiple domains

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What if later versions are less effective than earlier versions?• “Stop the presses!”

• Look for obvious reasons

• Examine lesson components individually

• Consider what is missing

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“Procedures”

Test one variable at a time

1. Make the values for the variable you’re testing be DIFFERENT across groups.

2. Make the values for the variables you’re not testing be the SAME across groups.

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“Concepts”

• You need to use different values for the variable you’re testing in order to know what effect those different values have.

• You need to use the same value for all the other variables (hold all the other variables constant; “control” the other variables) so that they can’t cause difference in the outcome.

• If you use CVS, you can know that only the variable you’re testing is causing the outcome/result/effect.

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Beyond our classroom instruction…

• Where on the contextual / abstract continuum should this type of instruction be focused? When?

• Single vs. multiple domains?

• Static pictures vs. simulations vs. tabular representations

• Best mix of explicit instruction, exploration, help, feedback, etc.