Phase 3: What have I learned?
Student Question 9: What actions have I taken?
We are busy for writing up literature review and introuduction part for our final paper. But since like we also need to deal with different personalities in a group. Three of us has diffrent opinions, but i believe we should choose a person to our group leader so that we won't have too much arguement and conflicts. But because everyone is busy and we do not have much time to sit each other. I feel sad and frustrated. Most of time we communicate each other via email. I feel like one of my goals is to get our final paper done and everyone in the group is on the same page.
Student Question 10: What barriers have been removed?
Gretta and I focus on introduction and literature reivew. Both of us try to make a time and send our own part to each other. The purpose of doing that is to merge our senctions together. Try to listen her opinions and thoughts regarding the paper. At the same time, areen made lots of timelines for us. Obviously, we did not really follow the scheduel. She made lots of unrealistic timeline. But i have tried to discuss to her.
Student Question 11: What has changed about what I don’t know?
Gretta gave me some suggestions regarding my introduction. At the same time, Areen wants us to follow the outline on the paper.
Student Question 12: Do I know what I want to know?
Areen looks like want to focus on writing up chpater 3, methodology. Our study will be aimed at youth development data collected from a Web-based self-administered questionnaire. we will run the data by spss. we will have to compute and composite subscale of self-worth.
Traditional statistical methods normally utilize one statistical test to determine the significance of the analysis. However, Structural Equation Modeling (SEM), CFA specifically, relies on several statistical tests to determine the adequacy of model fit to the data. The chi-square test indicates the amount of difference between expected and observed covariance matrices. A chi-square value close to zero indicates little difference between the expected and observed covariance matrices. In addition, the probability level must be greater than 0.05 when chi-square is close to zero.
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