Exploratory Factor Analysis Participants, Procedures, & Measures

Slides:



Advertisements
Similar presentations
PORTFOLIO.
Advertisements

Champions Inside and Outside the Classroom: Analyzing extracurricular activities, academic self- efficacy, & academic achievement. Shults, L. S., Gibson,
Genre Shift: Instructor Presence and its Impact on Student Satisfaction in Online Learning.
Neag School of Education Using Social Cognitive Theory to Predict Students’ Use of Self-Regulated Learning Strategies in Online Courses Anthony R. Artino,
Motivating Language Learners’ Project University of Alberta, Edmonton, Canada Changes in Perceptions: Motivation, Teaching Styles, Engagement Maya Sugita.
Elizabeth C. Rodriguez Jessica Pettyjohn Chapter 11 Week 10.
1 MSP-Motivation Assessment Program (MSP-MAP) Tools for the Evaluation of Motivation-Related Outcomes of Math and Science Instruction Martin Maehr
Reliability and factorial structure of a Portuguese version of the Children’s Hope Scale José Tomás da Silva Maria Paula Paixão Catarina Carvalho dos Santos.
Implication of Gender and Perception of Self- Competence on Educational Aspiration among Graduates in Taiwan Wan-Chen Hsu and Chia- Hsun Chiang Presenter.
Presenter: Che-Yu Lin Advisor: Ming-Puu Chen Date: 06/15/2009
Asynchronous Discussions and Assessment in Online Learning Vonderwell, S., Liang, X., & Alderman, K. (2007). Asynchronous Discussions and Assessment in.
Understanding Satisfaction and Continuing Motivation in an Online Course: An Extension of Social Cognitive, Control-Value Theory Anthony R. Artino, Jr.
Tonya Filz & Regan A.R. Gurung University of Wisconsin – Green Bay Abstract As class sizes increase due to stagnating budgets, and as colleges and universities.
Parental involvement and student self-regulation: Testing a mediational model Joan M.T. Walker, James R. Dallaire, Christa L. Green, Howard M. Sandler.
1 CHAPTER 11 Motivating Students to Learn Exploring Motivation Motivation: The drive to satisfy a need and the reason why people behave the way.
THE RELATIONSHIP BETWEEN PRE-SERVICE TEACHERS’ PERCEPTIONS TOWARD ACTIVE LEARNING IN STATISTIC 2 COURSE AND THEIR ACADEMIC ACHIEVEMENT Vanny Septia Efendi.
1 Self-Regulation and Ability Predictors of Academic Success during College Anastasia Kitsantas, Faye Huie, and Adam Winsler George Mason University.
Jenefer Husman Arizona State University Jenefer Husman Arizona State University When learning seems (un)important: Future Time Perspective and post-secondary.
LEARNER CENTERED APPROACH
Online students’ perceived self-efficacy: Does it change? Presenter: Jenny Tseng Professor: Ming-Puu Chen Date: July 11, 2007 C. Y. Lee & E. L. Witta (2001).
The role of feedback and self-efficacy on web-based learning: The social cognitive perspective Presenter: Han, Yi-Ti Adviser: Chen, Ming-Puu Date: Jun.
Educational Technology and Science Teaching. Reading Assignment Chapter 13 in Teaching Science to Every Child: Using Culture as a Starting Point.
Methods Participants & Procedures Participants were draw from a larger study that included rd, 4 th, and 5 th grade students and sixty seven teachers.
An instructional design theory for interactions in web-based learning environments 指導教授 : 陳 明 溥 研 究 生 : 許 良 村 Lee, M.& Paulus, T. (2001). An instructional.
West Bowers Matt Ragas Jeff Neely University of Florida May 22, 2009.
Standard One: Engaging & Supporting All Students in Learning
C H A P T E R C H A P T E R 3 3 Motivation Motivation.
A short instrument to assess topic interest in multimedia research
Attachment style and condom use across and within dating relationships
Discussion & Conclusion
DEPARTMENT OF HUMAN AND SOCIAL CIENCES APPLIED LINGUISTICS IN ENGLISH CAREER    “THE INFLUENCE OF TEACHER’S ATTITUDES AND BELIEFS INTO TECHNOLOGY-RELATED.
Course Review Classes 1-6 & Creating Motivating Learning
First-Year Experience Seminars: A Benchmark Study of Targeted Courses for Developmental Education Students.
Murat KEZER1 Barış SEVİ1, Zeynep CEMALCILAR1, & Lemi BARUH2
Social and Cognitive Presence in Online Learning: An Investigation of the Cohort Model in an Information School Setting A Research Study Conducted by Susan.
Reliability and validity of the BREQ-2 for measuring high school students’ motivation for physical education Stuart Forsyth¹, David Rowe¹, and Nanette.
Oleh: Beni Setiawan, Wahyu Budi Sabtiawan
Improving Student Engagement Through Audience Response Systems
Predictors of Parenting Self-Efficacy in Parents Attending College
Introduction Method Results Conclusions
Background and Overarching Aims
Iowa Teaching Standards & Criteria
STEM Communal Affordances
Assist. Prof.Dr. Seden Eraldemir Tuyan
Friendship Quality as a Moderator
Participants and Procedures
Technology to Promote Presence Interactive Strategies
Participants and Procedures
Justin D. Hackett, Benjamin J. Marcus, and Allen M. Omoto
The impact of being research-engaged; how do teachers involved in research believe it has impacted upon their professional development, practice and sense.
THE JOURNEY TO BECOMING
Aidyn L. Iachini a, Allie Riley b, and Dawn Anderson-Butcher b
Derek Herrmann & Ryan Smith University Assessment Services
NJCU College of Education
Assessment of Exceptional Students
Rachel Fundator Clarence Maybee Michael Flierl Purdue University
Kozan, K. , & Richardson, J. C. (2014)
CMC Meina Zhu, Susan C. Herring, and Curtis J. Bonk
Learning online: Motivated to Self-Regulate?
Trends in math motivation and math self-concept: gender differences
THE RELATIONSHIP BETWEEN PRE-SERVICE TEACHERS’ PERCEPTIONS TOWARD ACTIVE LEARNING IN STATISTIC 2 COURSE AND THEIR ACADEMIC ACHIEVEMENT Vanny Septia Efendi.
The Heart of Student Success
Understanding a Skills-Based Approach
Dept. of Science & Technology Education
General Social Competence (18)
English Language Writing Apprehension of University English Major Students – A survey carried out in Kunming University of Science and Technology. 昆明理工大学.
Presenter: Zong-Lin Tsai Advisor: Ming-Puu Chen
Supervisor: Ms M Visser Co-Supervisor: Prof DJ Malan
The impact of being research-engaged; how do teachers involved in research believe it has impacted upon their professional development, practice and sense.
指導教授:Chen, Ming-Puu 報 告 者:Chen, Wan-Yi 報告日期:
Presentation transcript:

Exploratory Factor Analysis Participants, Procedures, & Measures Predicting Utility Value Beliefs and Cognitive Engagement From Instructor Involvement and Provision of Relevance Antonio P. Gutierrrez, Gwen C. Marchand & Nicholas M. Nardi Department of Educational Psychology and Higher Education, University of Nevada, Las Vegas Introduction Results Results Multiple theories of motivation view instructional support as interacting with individual motivational orientations or perceptions to support or undermine student engagement and learning in the classroom. When students experience supportive relationships with an instructor and the instructor is successful in communicating the usefulness of research methods topics to students, students may be more likely to develop positive beliefs about the value of difficult or initially uninteresting topics, such as research methods, to their lives outside of school and to their career goals (Eccles, 2006). We identified no studies specifically investigating the relationships among instructional support, motivation, and engagement for graduate-level learners. We sought to investigate how changes in instructional support influenced changes in student beliefs about the value of research methods and cognitive engagement. The overarching research questions guiding the study are: Does instructional support predict changes in beliefs about utility value during the course of a semester? Does instructional support and beliefs about course utility value uniquely predict changes in cognitive engagement over the course of a semester? Does change in utility value beliefs mediate the relationship between perceived initial instructional support and end-of-semester cognitive engagement? Table 1.   Descriptive Statistics of Instructional Support, Motivation, and Cognitive Engagement Exploratory Factor Analysis Results of the three EFAs indicated that the factor structure of the four constructs under consideration was stable across time and that the manifest variables were in fact adequate measures of the latent constructs. Relevance Model Results of the relevance model indicated that relevance, utility value, and cognitive engagement remained somewhat stable across the semester in this sample of graduate students, but some variability was present in student perceptions of these constructs across the semester. As expected, initial relevance predicted mid-semester utility value and cognitive engagement, and mid-semester utility value predicted end-of-semester cognitive engagement, while controlling for previous waves of the model. Mid-semester utility value beliefs partially mediated the effect of initial perceived relevance on end-of semester cognitive engagement. Moreover, mid-semester relevance significantly predicted end-of-semester utility value. Table 2. Exploratory Factor Analysis Results Across Three Waves for Instructional Support, Utility Value, and Cognitive Engagement Involvement Model Results of the involvement model indicated that utility value remained stable across the semester whereas involvement demonstrated greater variability from beginning to end of the semester. Evidently, students’ perceptions of instructor involvement increased significantly from the beginning and middle to the end of the semester while perceptions of utility value remained high. Initial involvement significantly predicted mid-semester utility value, and mid-semester involvement predicted end-of-semester utility value, although the structural path coefficients were relatively modest. Mid-semester utility value did not mediate the relationship between initial perceived instructor involvement and end-of-semester cognitive engagement. Note. Loadings greater than .40 are reported. Explained Variances: T1 = 62%; T2 = 60%; T3 = 57%. N = 217 a Label indicates the suggested factor (i.e., extracted factor) name. . Discussion Methods Evidence from this study suggests that learning contexts that foster the substantive connection of to-be-learned material with events outside the classroom (e.g., students’ professional practice) and include instructors who are engaging, empathic, and receptive to student needs are associated with an increase in students’ cognitive engagement as manifested in deeper processing and the use of more meaningful learning strategies. Further, changes in instructional support influences changes in perceived task value. Instructional support that is perceived as highlighting the relevance of a task may influence student engagement by supporting perceptions of task value. Our research supports the line of inquiry of Assor and associates (Assor et al., 2002; Katz & Assor, 2007), who contend that taking into account characteristics of the learning environment is essential for success in learning, as learning environments that are more supportive will encourage students to strive for success and engage more meaningfully with the topic. Participants, Procedures, & Measures A convenience sample of 219 graduate students enrolled in a research methods course from a large, urban, southwestern university. Data were collected via online self-report questionnaires during the 2nd , 7th and 13th week of the semester. Cognitive engagement. Greene, Miller, Crowson, Duke, and Akey’s (2004) measure of meaningful strategy use was used to assess students’ learning strategy use with the course material. A subset of items was selected for use in this study. Utility Value. The extrinsic utility value scale was adapted from the work of Eccles and Wigfield (1995) and measured perceived value of the task. Instructional Support. Items were loosely adapted from existing measures (Assor et al., 2002; Nix et al., 2005; Belmont et al., 1992) and some new items were created for the purpose of this study. A subset of items was selected for use in this study that focused on perceived provision of relevance and instructor involvement. References Assor, A., Kaplan, H., & Roth, G. (2002). Choice is good, but relevance is excellent: Autonomy-enhancing and suppressing teacher behaviors predicting students’ engagement in schoolwork. British Journal of Educational Psychology, 72, 261-278.   Belmont, M., Skinner, E. A., Wellborn, J., & Connell, J. P. (1992). Teacher as social context (TASC): Two measures of teacher provision of involvement, structure, and autonomy support: Student report measure. Technical Report, University of Rochester, Rochester, NY. Eccles, J. S. (2006). A motivational perspective on school achievement: Taking responsibility for learning, teaching, and supporting. In R. F. Subotnik & R. J. Sternberg (Eds.), Optimizing student success in school with the other three Rs: Reasoning, resilience, and responsibility (pp. 199-224). Information Age Publishing. Eccles, J. S., & Wigfield, A. (1995). In the mind of the actor: The structure of adolescents’ achievement task values and expectancy-related beliefs. Personality and Social Psychology Bulletin, 3, 215-225. Greene, B. A., Miller, R. B., Crowson, H. M., Duke, B. L., & Akey, K. L. (2004). Predicting high school students cognitive engagement and achievement: Contributions of classroom perceptions and motivation. Contemporary Educational Psychology, 29, 462-482. Katz, I., & Assor, A. (2007). When choice motivates and when it does not. Educational Psychology Review, 19, 429-442. Nix, R. K., Fraser, B. J., & Ledbetter, C. E. (2005). Evaluating an integrated science learning environment using the Constructivist Environment Survey. Learning Environments Research, 8, 109-133.