measuring preservice teacher self-efficacy of technology integration
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Measuring preservice teacher self-efficacy of technology integration. Jeremy Browne Department of Instructional Psychology & Technology Brigham Young University United States [email protected]. IP&T 286 / 287. Technology Integration Not a computer course Required for all preservice teachers - PowerPoint PPT PresentationTRANSCRIPT
Measuring preservice teacher self-efficacy of technology
integrationJeremy Browne
Department of Instructional Psychology & TechnologyBrigham Young University
United [email protected]
IP&T 286 / 287
• Technology Integration
• Not a computer course
• Required for all preservice teachers– 286: Secondary education– 287: Elementary, Early Childhood, Special
Education
• Aligned with ISTE’s NETS-T
Fostering Technology Integration
Skills & Knowledge
National EducationalTechnology Standards
Dispositions
Confidence
Perceived Value
EffectiveIn-PracticeTechnologyIntegration
Can / Can’t
Will / Won’t
Why Self-Efficacy?
1. More clearly defined than “Confidence”
2. Well established measurement methodology
3. Significant predictor of many in-practice behaviors
1. Self-Efficacy Defined
• Self-efficacy is a personal belief about one’s own ability to perform a given action. (Bandura, 1997; Denzine et al., 2005)
• Not to be confused with “Teacher Efficacy” (Tschannen-Moran et al., 1998)
2. Self-Efficacy Measures
• Bandura (2006):
3. Predictive Power
• Job-search “self-efficacy was a significant predictor of interviews, offers, employment status, and PJ [Person-Job] fit perceptions” (Saks, 2006).
• Perceived math self-efficacy predicted interest in the subject (Özyürek, 2005).
• “Data analysis indicated that perceived self-efficacy was a significant predictor of [new in-practice teacher] performance” (Jablonski, 1995).
3. Predictive Power
• “Among the six subscales of empowerment, professional growth, status and self-efficacy were significant predictors of organizational and PC [professional commitment]” (Bogler & Somech, 2004).
• The perceived self-efficacy and context beliefs of teachers regarding the use of computer technology correlated significantly with reported hours of in-class use of technology (Whitehead, 2002).
Self-efficacy Mediated
• It does mediate distressing events.
• Chwalisz et al., 1992– High self-efficacy = Problem-focused coping – Low self-efficacy = Emotion-focused coping – “EFC, not PFC, was associated with higher
levels of burnout [of in-practice teachers].”
Literature Review
• Don’t reinvent the wheel.– (Find an existing measure.)
• Don’t reuse a flat tire.
• MUTEBI (Enoch et al., 1993)
• Findings: We needed to create our own measure.– The Technology Integration Confidence Scale
(TICS).
TICS Item Development
1. Begin with NETS-T
2. Write 4-7 tasks for each
3. Review by faculty & students• Pen & paper comments
4. Return to step 2
Important Deviations
TICS v1
• 28-item TICS
• Web-based
• 52 Spring-term preservice teachers
• Administered at end of term
• Described in proceedings
TICS v2
• 33 Items• Expanded coverage of specific NETS-T• Targeted item revision (e.g. Item 13)
• Larger sample (200+)Pre- and post-course administration
• “New General Self-efficacy Scale” (NGSE; Chen et al., 2001) administered concurrently
Results: Item Analysis (pretest)
• Improvement from TICS v1
• Lower means (10 items > 4.0)
• Higher variances (0 items < .5)
• Well represented NETS-T
Results: Reliability Analysis (Pretest)
Projected number of items required for
NETS-T N # of items Alpha α = .80 α = .90
I.A 233 6 .84 5 11
I.B 238 2 .80 2 5
II 235 7 .90 4 7
III 231 5 .88 3 7
IV 234 4 .82 4 9
V 234 5 .83 5 10
VI 234 4 .86 3 6
Results: Factor Analysis (pretest)
% of variance explained by
NETS-T # of items Factor 1 Factor 2
I.A 6 57.7 --
I.B 2 84.1 --
II 7 63.8 --
III 5 68.7 --
IV 4 65.6 --
V 5 61.0 --
VI 4 70.7 --
RSM (Functional)
Strongly
disagree
Strongly
agree
Disagree Agree
Neutral
RSM (Functional)
Strongly
disagree
Strongly
agree
Disagree Agree
Neutral
RSM (Functioning)
Strongly
disagree
Strongly
agree
Disagree Agree
Neutral
RSM (Malfunctioning)
Strongly
disagree
Strongly
agree
Disagree
Agree
Neutral
NGSE
NETS-T I.A (pre & post)
NETS-T I.B (pre & post)
NETS-T II (pre & post)
NETS-T III (pre & post)
NETS-T IV (pre & post)
NETS-T V (pre & post)
NETS-T VI (pre & post)
Evidence of Validity
TICS v1: Construct ValidityResults of Item-Domain Congruence Survey.
Number and percent of judges who classified each item on the intended subscale
NETS-T Item number Number Percent
II 11 2 40
II 15 2 40
II 25 3 60
II 26 0 0
II 28 1 20
III 9 1 20
III 10 2 40
V 13 2 40
V 16 1 20
TICS v1: Content ValidityItem Relevancy Sores (Aiken’s V index).
Number of judges that classified this item as…
SubscaleItem
number RelevantSomewhat
relevantSomewhat irrelevant Irrelevant
Aiken’s V index
II 28 3 0 2 0 .730
III 10 2 3 0 0 .800
IV 27 2 1 2 0 .670
VI 20 2 2 1 0 .730
Anachronistic View of Validity
• “The Holy Trinity” (Guion, 1980)– Content Validity– Construct Validity– Criterion Validity
• Convergent Validity• Discriminate Validity
• Others– Consequential Validities– Face Validity– Etc.
Modern View of Validity
• There is no validity but construct validity.
– Messick 1995; AERA, APA, NCME, 1999
• “Validities” reassigned as “sources of validity-supporting evidence.”
Validity…
• …is a property of your interpretation of the test data (not of the test or the data).– …is an evaluative judgment of the
“soundness of your interpretations and uses of students’ assessment results”(Nitko & Brookhart, 2006)
• … changes based on purpose.
Applying Modern Validity Theoryto the TICS
• Intended Purposes1. Establish a baseline preservice teacher
profile
2. Monitor the effects of curricular adjustments
3. Identify preservice teachers in most need of intervention
4. Predict in-practice technology integration
1. Establish a baseline preservice teacher profile
Assumes the TICS functions well psychometrically.
Internal structure analysis
• Expert reviewsLow of correlation with NGSE
( < .28 or 8% variance explained)
2. Monitor the effects of curricular adjustments
Assumes the TICS is sensitive to changes in self-efficacy.
• Pre-Post analysis
• Comparisons of scores between IP&T 286 and 287
3. Identify preservice teachers in most need of intervention
Assumes TICS can predict in-classperformance.
RSM information analysis• Regression analysis
– XPre-course TICS scores Relevant demographics
– YIn-class performance indicators
(assignment / assessment scores)
4. Predict in-practice technology integration
• 5-year longitudinal, mixed methods study
4. Predict in-practice technology integration
• Review of self-efficacy literature
Future Directions
• TICS v2 showing promise
• Expanded use
• Inform NETS-T “refreshing”
• Modern validity theory can be applied systematically.