Online learning processes - what users do and why it is important

cc by Karsten D. Wolf 2007

Karsten D. WolfDidactical Design of Interactive Learning Environments

interaktiivinen tekniikka koulutuksessa 2007Wednesday, 18.04.2007

Online Learning Processes –What Users Do and Why it is Important

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Karsten D. WolfFaculty educational science

Didactical design ofinteractive learning environments

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www.everlearn.eu

User Generated ContentDidactical PrototypingCollaborative Learning

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http://www.everlearn.eu

http://www.everlearn.eu

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© Karsten D. Wolf 2007

roadmap

1. Why educational research is hard

2. How can we produce evidence in educational research?

3. Multimethod approaches in educational research

4. Alternative methods: Intra-individual analysis of micro process timeseries

5. Educational technology as a research frontier in learning science

6. Some applied results

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soft sciences are hard

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btw: this is not a real sim.rocks do not decelerate before hitting the ground!

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what if rocks would behave?

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covariates hell

pic by Don Gato on Flickr11


3 strategies

control themlive with themr&d approach

Fischer/Waibel/Wecker (2006): Nutzenorientierte Grundlagenforschung im BildungsbereichArgumente einer internationalen Diskussion

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experimental researchdesign based research

engineering approaches

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75%15


Educational Researcher, Vol. 33, No. 2, 3–11

Educational Researcher, Vol. 32, No. 9, 3–14

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Problems with quasi-experiments

Steyer 2007 - www.causal-effects.de

Simpson

paradox

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Steyer 2007 - www.causal-effects.de18



Steyer 2007 - www.causal-effects.de19


Random Assignment & Propensity Score Matching

• Random Assignment

• is the population large enough?

• can the assignment truly random?

• doesn‘t it feel like a lottery?

• Propensity Score Matching

• need to collect covariates

• matching at an individual level between treatment and control

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• self-reports (behaviors, psychological contructs, forms of behaviors)

• informant assessment

• ecological momentary assessment

• web based / computer based methods

• ability tests

• implicit methods (performance measures)

• sequential observational methods

Multimethod approaches: assessment methods

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Multimethod approaches:assessment methods

• quantitative text analysis

• multilevel analysis: physiological & biochemical measures

• brain imaging

• experimental methods

• nonreactive methods

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Experiments vs. Assessments

Why is Explanandum?

If (A1 and A2) then Explanandum (general law, explanans)

A1 (antecedent condition 1)

A2 (antecedent condition 2)

Therefore: E (explanandum)

Experiments aim to develop and test general lawsAssessments aim to show that the antecedent conditions are met

Erdfelder & Musch 2006

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Level of nonreactivity

Low High

Type 0 Type 1 Type2 Type 3 Type 4 Type 5

Setting initially designed or selected for research yes yes yes yes yes no

Participants are aware of the research setting likely likely likely likely no no

Participants are aware of the research question likely likely likely no no no

Participants are aware of the research hypothesis likely likely no no no no

Participants are aware of the measures‘ manipulability likely no no no no no

Examples Participative expert interview

Bogus pipeline technique

Personality questionaire

Cover story experiments

Lost letter technique

Analysis of archival data

Fritsche and Linneweber 2006

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Methods for analyzing multimethod data

• Multitrait-Multimethod Matrix (Campbell and Fiske 1959)

• categorical variables analysis for asessing multimethod association

• multimethod item response theory

• multilevel analysis

• structural equation models

• longitudinal methods

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I feel taken seriously (EG1 TN1 SoLe III)

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1 2 3 4 5 6 7 8 9 10 11 12 13 14

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Taken seriously Cognitive Load Participation

I feel good I understand I am interested

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I am interested for19 students in EG1 SoLe III

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I feel taken seriously (EG1 TN1 SoLe III)Linear Trend

Trend

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I feel taken seriously (EG1 TN1 SoLe III)3rd Polynom

Trend

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I feel taken seriously (EG1 TN1 SoLe III)Spline λ=10.000

Trend

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I feel taken seriously (EG1 TN1 SoLe III)Spline λ=100.000

Trend

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Decomposition

Trend Microprocesses

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ARMA-Analysis

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AIC BIC R2 Φ

AR(1) 1201,8 1208,0 0,094 Φ1 = 0,307

AR(2) 1190,2 1200,9 0,139Φ1 = 0,238Φ2 = 0,223

AR(3) 1192,1 1206,5 0,139Φ1 = 0,237Φ2 = 0,222Φ3 = 0,007

AR(5) 1194,2 1215,8 0,145

Φ1 = 0,236Φ2 = 0,241Φ4 = -0,077Φ5 = -0,018Φ3 = 0,030

Model parameters

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AR(2)-Model

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Multivariate Analyis:Cross Correlations

FG

I

P

CL

t-3 t-2 t-1 t

I 0,1220,120

-0.143

0.146

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Multivariate Models: GMDH

FG

I

P

CL

t-2 t-1 t

0,097

-0.15

0.13

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“As the complexity of a system increases, our ability to make precise and significant statement about its behaviour diminishe until a threshold is reached … the closer one look at a real-world problem the fuzzier becomes its solution” (Kosko, 94)

Fuzzy Modelling (Zadeh)

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Fuzzification1

0,5

0Negative_X ZERO_X Positive_X

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IF

NOT_Participation (t-1) & TakenSeriously (t-2)

OR

NOT_Participation (t-1) & CognitiveLoad (t-2)

Fuzzy Rule InductionTakenSeriously (t-1) & NOT_Participation (t-2)

OR

NOT_Understand (t-1) & CognitiveLoad (t-2)

THEN FeelGood TN1 (prewhitened)

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Better communication?

Different interrelationships at different levels? (Thresholds)

non-linear models?

basis for building hypotheses?

Advantages?

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time consuming

lot of rules

no selection criteria

no „test of significance“

disadvantages

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Online learning as a research frontier?

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what is happening here?

how to measure this?

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???

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???Learning accompanying actions

BrowseSearchWrite…

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???creation

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???

construction

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???

communication

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???

cooperation

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???

collaboration

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© Prof. Dr. Karsten D. Wolf 2007

Some results from a prior online seminar

ZfE Cover

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Activity

# chat msg# forum entries

# created words

femalen=23

46.2(57.92)

7.0(7.44)

2301(363.5)

malen=13

24.7(23.43)

3.0(3.08)

1919(419.0)

1-tail significant test, n=36

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Activity and Post-Interest


# created words

Post-interest

.11(.258)

.19(.135)

.34*(.022)


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Pre-Interest and Activity


# created words

Pre-interest.30*

(.043).28

(.053).36*

(.019)


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Activity and Post-Interest


# created words

Post-interest

.11(.258)

.19(.135)

.34*(.022)


factors out by pre-interest!

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Activity and Social Relatedness


# created words

socialrelatedness

-.08(.319)

.30*(.036)

.31*(.035)


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Pre-Knowledge and Activity


# created words

pre-problemsolving

.34*(.021)

.47**(.002)

.54***(<.001)


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Activity and Knowledge


# created words

post-problemsolving

.03(.425)

.28*(.048)

.43**(.005)


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Which means: constructivism is right after all!

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© P

rof.

Dr. K

arst

en D

. Wol

f 200

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http://www.karsten-d-wolf.de/

[email protected]

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http://www.ifeb.uni-bremen.de/wolf/








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