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PRESERVICE TEACHER GRADUATES’
TECHNOLOGY INTEGRATION
DISPOSITIONS: KNOWLEDGE,
ATTITUDES, AND CURRENT
BEHAVIORS
Joan E. Hughes, Ph.D.
Yu-Chi NikkiWen
University ofTexas atAustin
Conceptual Frame
 Teacher technology preparation moves from
“tech course” to “integrated”
 Teachers’ decision-making regarding
technology use for educative purposes is
mediated by their existing knowledge,
beliefs, and dispositions
 Emphasize understanding teachers’
knowledge, attitudes, and behaviors in
teacher research (Lawless & Pellegrino, 2007)
RESEARCH QUESTION:
WHAT ARE TEACHER GRADUATES’
KNOWLEDGE, ATTITUDES, AND
BEHAVIORS RELATED TO
TECHNOLOGY INTEGRATION?
Methods
 Participants: Fall 2008 (n=42), Spring 2009
(n=53), and Fall 2009 (n=20) from a southwestern
univ preservice program that requires laptops
 20-minute end-of-program survey
 Selected data
 attitudes (participant dispositions toward digital
technologies and learning technologies)
 behaviors (technology use)
 knowledge (projected technology use in future
classroom teaching)
 Mixed Methods (descriptive stats; qualitative)
Open-ended Questions
 Q1: “Describe the most valuable learning
technology (a technology you could not
imagine teaching without) that you or your
students will use in the future, if available”
 Q2: “Please explain why your chosen learning
technology (listed above) is so valuable, such
as its value to you and your students, how
you or your students will use it, and what
objectives it helps you reach?”
Qualitative Analysis
 Counted # of technologies mentioned in Q1
 Explanatory ideas in Q1 & Q2 coded for
knowledge explanation represented (TPACK)
 Coded for essence (not parts)
 Codes represent integrated ideas
 Coded # and type (student vs. tchr) of tech
uses in Q1 & Q2
RESULTS
Attitude: Tech Self-Efficacy
 Moderate/High DigitalTechnology Self-
Efficacy
 Fall 2008 cohort: mean score of 3.10 (n=40,
variance=.29, SD=.54)
 Spring 2009 graduates: mean score of 3.00 (n=51,
variance=.32, SD=.56).
 Fall 2009 cohort: mean score of 3.13 (n=20,
variance=.29, SD=.54)
*Teachers reported on a scale of 1-4 from Strongly disagree (1) to
Strongly agree (4)
Attitude:Learning Technology
 Strong positive dispositions towards the use of
learning technologies in classroom instruction
 Fall 2008 cohort: mean score 3.32 (n=40,
variance=.152, SD=.39)
 Spring 2009 cohort: mean score of 3.18 (n=50,
variance=.153, SD=.39)
 Fall 2009 cohort: mean score of 3.33 (n=19,
variance=.080, SD=.28)
Teachers reported on a scale of 1-4 from Strongly disagree (1) to
Strongly agree (4); A response of (1) reflects a negative
perspective of utilizing learning technologies in the classroom,
while a (4) represents a positive outlook on learning technologies.
Graduates’ Behaviors
Technology
Activity
% Reporting
Use
Frequency Purpose Skill
Communication 60% Daily /Weekly Mostly personal Very skilled
Web 46% Weekly Mostly personal Very skilled
Productivity 52% Monthly /
Weekly
Mostly
educational
Very skilled
Creation 38% Monthly or less Both personal &
educational
Very skilled
Knowledge: Most Valuable
Technologies Cited
 Most identified 1+
 F ‘08: 43 items (n=26)
 S ’09: 53 items (n=34)
 F ’09: 26 items (n=15)
 High prevalence of productivity software (PP,
Word), general hardware (computers,
projectors, doc cameras)
 Few content-specific: word & imovie for
publishing, math/rdg games, digital audio
creation
Knowledge: LT for teacher or
student?
 Identified 2 -3X more teacher uses of tech
than student uses
 F ‘08:Teacher LT=36; Student LT=12
 S ’09: Teacher LT=41; Student LT=16
 F ’09: Teacher LT=14; Student LT=7
 Skewness may dispose graduates to more
teacher-centric technologies as practitioners
Knowledge: Evidence in
Rationales
 Preservice graduates are relying mostly on
technological pedagogical knowledge (TPK) to
justify their identified valuable technologies
 Graduates possess depth of knowledge inTPK
 TPK is very broad category
Knowledge Types evidenced in ‘Most
Valuable LT’ Rationales, Fall 2008
96%
2%
0% 0% 0%
2%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TPK TK CK TCK PK PCK
FrequencyCited(%)
Knowledge Type
Knowledge Types evidenced in ‘Most
Valuable LT’ Rationales, Spring 2009
75%
6%
2%
5%
6% 6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TPK TK CK TCK PK PCK
FrequencyCited(%)
Knowledge Type
Knowledge Types evidenced in ‘Most
Valuable LT’ Rationales, Fall 2009
66%
19%
0%
3%
13%
0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TPK TK CK TCK PK PCK
FrequencyCited(%)
Knowledge Type
Knowledge: Depth of
Reasoning
 Mean number of explanatory ideas per
respondent
 F ‘08: 1.9 ideas
 S ’09: 1.8 ideas
 F ’09: 2.0 ideas
 Visualization represents each respondent’s #
of explanatory ideas & type of knowledge
associated with the ideas
 Only a handful are complex (show depth and
breadth)
Visualization of Depth of Rationalization
Fall 2008
0 1 2 3 4 5
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Knowledge References in Rationale
Respondent#
TPK
TK
CK
TCK
PK
PCK
Respondent #2, Fall 2008
LT: MicrosoftApplications:Word, Powerpoint, Excel
Rationale:Word can be used [to write lesson plans,] [help students publish
work], [communicate with students and parents.] Excel can be used [to
organize data and create graphs of student progress.] [Powerpoint can be
used to supplement lessons - the visuals it can help teachers create are great!]
(Respondent #2, Fall 2008)
LT: Microsoft Applications:Word, Powerpoint,
Excel
Rationale:Word can be used [to write lesson
plans,] [help students publish work], [communicate
with students and parents.] Excel can be used [to
organize data and create graphs of student
progress.] [Powerpoint can be used to supplement
lessons - the visuals it can help teachers create are
great!] (Respondent #2, Fall 2008)
TPK
TPK
TPK
TPK
TPK
Visualization of Depth of Rationalization
Spring 2009
0 1 2 3 4 5
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
Knowledge References in Rationale
Respondent#
TPK
TK
CK
TCK
PK
PCK
Respondent #25, Spring 2009
LT: [Video clips usually fromYoutube.]
Rationale: [In English students almost always read Shakespeare,] and [it is
hard to read something that is suppose to be performed and get students
actively engaged in the content] (Respondent #25, Spring 2009)
LT: [Video clips usually fromYoutube.]
Rationale: [In English students almost
always read Shakespeare,] and [it is hard
to read something that is suppose to be
performed and get students actively
engaged in the content] (Respondent #25,
Spring 2009)
TCK
CK
PCK
Visualization of Depth of Rationalization
Fall 2009
0 1 2 3 4 5
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Knowledge References in Rationale
Respondent#
TPK
TK
CK
TCK
PK
PCK
Respondent #11, Fall 2009
LT: I was a post-bach student who first graduated in
2000. I have to say that I became much more
comfortable with Powerpoint throughout my teacher
preparatory semesters. I also really enjoyed learning
how to make in imovie.
Rationale: [I have used numerous Powerpoint
presentations in my college classes as well as in my
placement.] Just recently [I was able to make a
Powerpoint slide show showing the first graders
pictures of kids in Ghana.] [We talked about the
similarities and differences between our school and
theirs.] I also was able to help a group of third graders
with their imovies on animals. [I felt confident enough
to answer their questions.] (Respondent #11, Fall 2009)
TK
TPK
PK
TK
Conclusion
 Graduates have high digital tech self-efficacy and
positive attitude toward LT
 50% graduates report technology use; Most use for
personal purposes
 Only 38% report using Creation activities (most
associated withWeb 2.0 affordances)
 Graduates have well-developedTPK
 Deep rationalization missing
 Having strong or moderate technology self-efficacy
and positive dispositions toward technology
integration are not enough to infer deep use of
TPACK
JOANH@MAIL.UTEXAS.EDU
Please email me for a copy of the paper – we will gladly send it to you!

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Preservice Teachers' Dispositions Toward Technology Integration

  • 1. PRESERVICE TEACHER GRADUATES’ TECHNOLOGY INTEGRATION DISPOSITIONS: KNOWLEDGE, ATTITUDES, AND CURRENT BEHAVIORS Joan E. Hughes, Ph.D. Yu-Chi NikkiWen University ofTexas atAustin
  • 2. Conceptual Frame  Teacher technology preparation moves from “tech course” to “integrated”  Teachers’ decision-making regarding technology use for educative purposes is mediated by their existing knowledge, beliefs, and dispositions  Emphasize understanding teachers’ knowledge, attitudes, and behaviors in teacher research (Lawless & Pellegrino, 2007)
  • 3. RESEARCH QUESTION: WHAT ARE TEACHER GRADUATES’ KNOWLEDGE, ATTITUDES, AND BEHAVIORS RELATED TO TECHNOLOGY INTEGRATION?
  • 4. Methods  Participants: Fall 2008 (n=42), Spring 2009 (n=53), and Fall 2009 (n=20) from a southwestern univ preservice program that requires laptops  20-minute end-of-program survey  Selected data  attitudes (participant dispositions toward digital technologies and learning technologies)  behaviors (technology use)  knowledge (projected technology use in future classroom teaching)  Mixed Methods (descriptive stats; qualitative)
  • 5. Open-ended Questions  Q1: “Describe the most valuable learning technology (a technology you could not imagine teaching without) that you or your students will use in the future, if available”  Q2: “Please explain why your chosen learning technology (listed above) is so valuable, such as its value to you and your students, how you or your students will use it, and what objectives it helps you reach?”
  • 6. Qualitative Analysis  Counted # of technologies mentioned in Q1  Explanatory ideas in Q1 & Q2 coded for knowledge explanation represented (TPACK)  Coded for essence (not parts)  Codes represent integrated ideas  Coded # and type (student vs. tchr) of tech uses in Q1 & Q2
  • 8. Attitude: Tech Self-Efficacy  Moderate/High DigitalTechnology Self- Efficacy  Fall 2008 cohort: mean score of 3.10 (n=40, variance=.29, SD=.54)  Spring 2009 graduates: mean score of 3.00 (n=51, variance=.32, SD=.56).  Fall 2009 cohort: mean score of 3.13 (n=20, variance=.29, SD=.54) *Teachers reported on a scale of 1-4 from Strongly disagree (1) to Strongly agree (4)
  • 9. Attitude:Learning Technology  Strong positive dispositions towards the use of learning technologies in classroom instruction  Fall 2008 cohort: mean score 3.32 (n=40, variance=.152, SD=.39)  Spring 2009 cohort: mean score of 3.18 (n=50, variance=.153, SD=.39)  Fall 2009 cohort: mean score of 3.33 (n=19, variance=.080, SD=.28) Teachers reported on a scale of 1-4 from Strongly disagree (1) to Strongly agree (4); A response of (1) reflects a negative perspective of utilizing learning technologies in the classroom, while a (4) represents a positive outlook on learning technologies.
  • 10. Graduates’ Behaviors Technology Activity % Reporting Use Frequency Purpose Skill Communication 60% Daily /Weekly Mostly personal Very skilled Web 46% Weekly Mostly personal Very skilled Productivity 52% Monthly / Weekly Mostly educational Very skilled Creation 38% Monthly or less Both personal & educational Very skilled
  • 11. Knowledge: Most Valuable Technologies Cited  Most identified 1+  F ‘08: 43 items (n=26)  S ’09: 53 items (n=34)  F ’09: 26 items (n=15)  High prevalence of productivity software (PP, Word), general hardware (computers, projectors, doc cameras)  Few content-specific: word & imovie for publishing, math/rdg games, digital audio creation
  • 12. Knowledge: LT for teacher or student?  Identified 2 -3X more teacher uses of tech than student uses  F ‘08:Teacher LT=36; Student LT=12  S ’09: Teacher LT=41; Student LT=16  F ’09: Teacher LT=14; Student LT=7  Skewness may dispose graduates to more teacher-centric technologies as practitioners
  • 13. Knowledge: Evidence in Rationales  Preservice graduates are relying mostly on technological pedagogical knowledge (TPK) to justify their identified valuable technologies  Graduates possess depth of knowledge inTPK  TPK is very broad category
  • 14. Knowledge Types evidenced in ‘Most Valuable LT’ Rationales, Fall 2008 96% 2% 0% 0% 0% 2% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% TPK TK CK TCK PK PCK FrequencyCited(%) Knowledge Type
  • 15. Knowledge Types evidenced in ‘Most Valuable LT’ Rationales, Spring 2009 75% 6% 2% 5% 6% 6% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% TPK TK CK TCK PK PCK FrequencyCited(%) Knowledge Type
  • 16. Knowledge Types evidenced in ‘Most Valuable LT’ Rationales, Fall 2009 66% 19% 0% 3% 13% 0% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% TPK TK CK TCK PK PCK FrequencyCited(%) Knowledge Type
  • 17. Knowledge: Depth of Reasoning  Mean number of explanatory ideas per respondent  F ‘08: 1.9 ideas  S ’09: 1.8 ideas  F ’09: 2.0 ideas  Visualization represents each respondent’s # of explanatory ideas & type of knowledge associated with the ideas  Only a handful are complex (show depth and breadth)
  • 18. Visualization of Depth of Rationalization Fall 2008 0 1 2 3 4 5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Knowledge References in Rationale Respondent# TPK TK CK TCK PK PCK
  • 19. Respondent #2, Fall 2008 LT: MicrosoftApplications:Word, Powerpoint, Excel Rationale:Word can be used [to write lesson plans,] [help students publish work], [communicate with students and parents.] Excel can be used [to organize data and create graphs of student progress.] [Powerpoint can be used to supplement lessons - the visuals it can help teachers create are great!] (Respondent #2, Fall 2008) LT: Microsoft Applications:Word, Powerpoint, Excel Rationale:Word can be used [to write lesson plans,] [help students publish work], [communicate with students and parents.] Excel can be used [to organize data and create graphs of student progress.] [Powerpoint can be used to supplement lessons - the visuals it can help teachers create are great!] (Respondent #2, Fall 2008) TPK TPK TPK TPK TPK
  • 20. Visualization of Depth of Rationalization Spring 2009 0 1 2 3 4 5 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 Knowledge References in Rationale Respondent# TPK TK CK TCK PK PCK
  • 21. Respondent #25, Spring 2009 LT: [Video clips usually fromYoutube.] Rationale: [In English students almost always read Shakespeare,] and [it is hard to read something that is suppose to be performed and get students actively engaged in the content] (Respondent #25, Spring 2009) LT: [Video clips usually fromYoutube.] Rationale: [In English students almost always read Shakespeare,] and [it is hard to read something that is suppose to be performed and get students actively engaged in the content] (Respondent #25, Spring 2009) TCK CK PCK
  • 22. Visualization of Depth of Rationalization Fall 2009 0 1 2 3 4 5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Knowledge References in Rationale Respondent# TPK TK CK TCK PK PCK
  • 23. Respondent #11, Fall 2009 LT: I was a post-bach student who first graduated in 2000. I have to say that I became much more comfortable with Powerpoint throughout my teacher preparatory semesters. I also really enjoyed learning how to make in imovie. Rationale: [I have used numerous Powerpoint presentations in my college classes as well as in my placement.] Just recently [I was able to make a Powerpoint slide show showing the first graders pictures of kids in Ghana.] [We talked about the similarities and differences between our school and theirs.] I also was able to help a group of third graders with their imovies on animals. [I felt confident enough to answer their questions.] (Respondent #11, Fall 2009) TK TPK PK TK
  • 24. Conclusion  Graduates have high digital tech self-efficacy and positive attitude toward LT  50% graduates report technology use; Most use for personal purposes  Only 38% report using Creation activities (most associated withWeb 2.0 affordances)  Graduates have well-developedTPK  Deep rationalization missing  Having strong or moderate technology self-efficacy and positive dispositions toward technology integration are not enough to infer deep use of TPACK
  • 25. JOANH@MAIL.UTEXAS.EDU Please email me for a copy of the paper – we will gladly send it to you!

Hinweis der Redaktion

  1. Movement from technology skills to infusion/integration within preservice programField has more recently begun to consider teachers’ knowledge – and many explorations of TPACK. In sum, when preservice teachers learn about technology embedded within disciplinary content, they may be more likely to develop TPACK that in turn, supports technology supported teaching and learning
  2. Situated within a teacher education program that privileges ubiquitous computing …
  3. TPK captures ideas relating to instruction, assessment, classroom management, NETS, and lesson plannig. Most cited TPK evidence was: (#6 general pedagogical tasks) - displaying information in more visible way, supporting research, accessing more information. Also #1 – motivating students; and #14 support lesson planning.
  4. Conceptually – we argue that a rationale that contains a range of knowledge types represents thinking and decision-making that is more complex and reflects more depth.