logging in or signing up Megan s Data Analysis Presentation meklei2 Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 43 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: March 26, 2010 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Predicting Growth Trajectories in High School Students' Self-Efficacy for Self-Regulated Learning : Predicting Growth Trajectories in High School Students' Self-Efficacy for Self-Regulated Learning Megan Thomas EDP 778 Background Information : Background Information Self-Efficacy: Beliefs individuals hold about their capabilities in specific domains Self-Efficacy for Self-Regulated Learning Belief in one’s self-regulatory capabilities Content area: Science Self-efficacy in science has received growing attention from educational researchers Purpose: Investigate changes in high school student self-efficacy for self-regulated learning over time using growth curve modeling (one aspect of hierarchical linear modeling) Research Questions : Research Questions What is the initial status of high school students' self-regulatory self-efficacy? What was the rate of change of students' self-regulatory self-efficacy over time? How do gender, ethnicity, grade level, and teacher ratings of student competence in science affect the rate of change of student self-regulatory self-efficacy? Participants : Participants Participants in the study were 183 students from an urban high school in the southeastern U.S. Teacher rating of student science achievement: M = 7.49; SD = 1.78 Procedure : Procedure Students completed a survey of science attitudes in three waves: Early February 2007 Early April 2007 Early May 2007 Measures : Measures Self-Efficacy for Self-Regulated Learning: Children’s Self-Efficacy Scale, Bandura (2006) Assesses students’ confidence in their self-regulatory capability in completing science work 11 items rated on a Likert-type scale (1 = Not very well; 6 = Very well) “How well can you finish your science homework on time?” Student background variables: Gender Ethnicity Grade level Teacher ratings of their students' competence in science Data Analysis : Data Analysis Two-level, three-time-point hierarchical linear growth model Level 1: Yit = π0i + π1i(wave)it + Rit Level 2: π0i = β00 + β10(gender)i + β20(ethnicity)i + β30(teacher rating of student science competence)i + β40(10th grade)i + β50(11th grade)i + β60(12th grade)i + u0i π1i = β01 + β11(gender)i + β21(ethnicity)i + β31(teacher rating of student science competence)i + β41(10th grade)i + β51(11th grade)i + β61(12th grade)i + u1i Results : Results Sample Size, Means, and Standard Deviations of Self-Regulated Self-Efficacy Across Waves Results: Unconditional Growth Model : Results: Unconditional Growth Model Results: Final Model : Results: Final Model Results: Final Model cont. : Results: Final Model cont. Conclusions : Conclusions Major findings: Decrease in students’ self-efficacy for self-regulated learning over time Females had significantly higher initial self-efficacy for self-regulated learning Initial self-efficacy for self-regulated learning was significantly higher for students in Grade 9 No significant influences on rate of change Ethnicity and teacher rating of student science competence did not predict students’ initial status or rate of change in self-efficacy for self-regulated learning Covariates only explain 7% of the variation in initial status Conclusions : Conclusions Limitations Small sample size Data collected over short period of time Implications Self-efficacy for self-regulated learning is decreasing over time Inform intervention Future research Investigate these contextual variables with other outcome measures Investigate the influence of other contextual variables on self-efficacy for self-regulated learning Collect data over a longer period of time You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
Megan s Data Analysis Presentation meklei2 Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 43 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: March 26, 2010 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Predicting Growth Trajectories in High School Students' Self-Efficacy for Self-Regulated Learning : Predicting Growth Trajectories in High School Students' Self-Efficacy for Self-Regulated Learning Megan Thomas EDP 778 Background Information : Background Information Self-Efficacy: Beliefs individuals hold about their capabilities in specific domains Self-Efficacy for Self-Regulated Learning Belief in one’s self-regulatory capabilities Content area: Science Self-efficacy in science has received growing attention from educational researchers Purpose: Investigate changes in high school student self-efficacy for self-regulated learning over time using growth curve modeling (one aspect of hierarchical linear modeling) Research Questions : Research Questions What is the initial status of high school students' self-regulatory self-efficacy? What was the rate of change of students' self-regulatory self-efficacy over time? How do gender, ethnicity, grade level, and teacher ratings of student competence in science affect the rate of change of student self-regulatory self-efficacy? Participants : Participants Participants in the study were 183 students from an urban high school in the southeastern U.S. Teacher rating of student science achievement: M = 7.49; SD = 1.78 Procedure : Procedure Students completed a survey of science attitudes in three waves: Early February 2007 Early April 2007 Early May 2007 Measures : Measures Self-Efficacy for Self-Regulated Learning: Children’s Self-Efficacy Scale, Bandura (2006) Assesses students’ confidence in their self-regulatory capability in completing science work 11 items rated on a Likert-type scale (1 = Not very well; 6 = Very well) “How well can you finish your science homework on time?” Student background variables: Gender Ethnicity Grade level Teacher ratings of their students' competence in science Data Analysis : Data Analysis Two-level, three-time-point hierarchical linear growth model Level 1: Yit = π0i + π1i(wave)it + Rit Level 2: π0i = β00 + β10(gender)i + β20(ethnicity)i + β30(teacher rating of student science competence)i + β40(10th grade)i + β50(11th grade)i + β60(12th grade)i + u0i π1i = β01 + β11(gender)i + β21(ethnicity)i + β31(teacher rating of student science competence)i + β41(10th grade)i + β51(11th grade)i + β61(12th grade)i + u1i Results : Results Sample Size, Means, and Standard Deviations of Self-Regulated Self-Efficacy Across Waves Results: Unconditional Growth Model : Results: Unconditional Growth Model Results: Final Model : Results: Final Model Results: Final Model cont. : Results: Final Model cont. Conclusions : Conclusions Major findings: Decrease in students’ self-efficacy for self-regulated learning over time Females had significantly higher initial self-efficacy for self-regulated learning Initial self-efficacy for self-regulated learning was significantly higher for students in Grade 9 No significant influences on rate of change Ethnicity and teacher rating of student science competence did not predict students’ initial status or rate of change in self-efficacy for self-regulated learning Covariates only explain 7% of the variation in initial status Conclusions : Conclusions Limitations Small sample size Data collected over short period of time Implications Self-efficacy for self-regulated learning is decreasing over time Inform intervention Future research Investigate these contextual variables with other outcome measures Investigate the influence of other contextual variables on self-efficacy for self-regulated learning Collect data over a longer period of time