Preservice Teachers' Dispositions Toward Technology Integration

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Research study that examined: What are teacher graduates' knowledge, attitudes, and behaviors related to technology integration as they set off to become novice teachers? Presentation at American Educational Research Association Annual Meeting: April, 2010.

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<ul><li> 1. PRESERVICE TEACHER GRADUATES TECHNOLOGY INTEGRATION DISPOSITIONS: KNOWLEDGE, ATTITUDES, AND CURRENT BEHAVIORS Joan E. Hughes, Ph.D. Yu-Chi NikkiWen University ofTexas atAustin </li></ul> <p> 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 &amp; 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 &amp; 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 &amp; Q2 7. RESULTS 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 &amp; 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 &amp; 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 respondents # of explanatory ideas &amp; 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! </p>