logging in or signing up SRSE Data Analysis Narrated practice8 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: 6 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 competence: 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.
SRSE Data Analysis Narrated practice8 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: 6 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 competence: 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