I was extremely apprehensive about taking the SEM and Meta-Analysis course. After my experience in regression, which was a preparation course for SEM and Meta-Analysis, I was very nervous and not self-efficacious about doing well. However, I realized that fear was not a good enough reason to not take a course that would be beneficial to my future career and research. Therefore, I enrolled in it and surprisingly, this course was not as intense as I had expected. I am sure that this was due to my experience in the previous SEM course that I had taken. I learned a new analysis program called Lisrel and although it is not as user-friendly as the program that I used in my previous SEM course (Mplus), this design of this program required you to truly understand SEM in order to have it run properly. Specifically, if the model is miss-specified in any way, it will not run properly and yield statistics that do not make sense. It would then be up to the researcher to figure out where the problem is and develop a theoretically and statistically sound solution.

In terms of the meta-analysis section, I was excited but overwhelmed with the amount of work required to conduct a meta-analysis. In fact, I feel that the concepts in meta-analysis were not as difficult to understand as compared to the amount of work required to actually conduct a meta-analysis. I decided to develop my meta-analysis with Dr. Michelle Buehl on how culture can moderate the relationship between epistemological beliefs and achievement. At first, the idea seemed doable, however, as I delved deeper into the literature, I am no longer sure if this can be done due to the lack of articles with an actual numerical achievement outcome variable. However, I am optimistic that another idea will come to me as I continue to code the articles.