Jingwei Viola Liu
Systemic Improvement Indicator B
Indicator B: Collaborate to establish metrics, collect and analyze data, interpret results, and share findings to improve staff performance and student learning.
Artifact:
Artifact & Course Description:
Course Title
GREV 611 Statistics III
Course Description
This educational statistics course covers multivariate normal distribution. Topics include matrix algebra, pre-analysis screening of data, multiple regression, multivariate analysis of variance and covariance, factor analysis, discriminant function analysis, logistic regression, and multilevel linear models.
Project Description
This assignment was to provide practice in analyzing data and writing up results. The dataset was fabricated to provide an example of a hypothesis-driven analysis. The example hypothesis explored whether a cloud education model was equivalent to the teaching and learning model with respect to efficacy in a college algebra class in Chinese universities. A methods section was described, along with a data analysis plan. The fabricated dataset was analyzed, and the results presented, along with an interpretation, conclusion, and references.
Reflection
This assignment was very helpful because it provided the opportunity to demonstrate many of the skills associated with study design, research, and statistics. A background with references was necessary to build an argument for the research, and a hypothesis needed to be developed. Methods needed to be imagined and described, and an appropriate dataset to answer the question needed to be created. Finally, the data analysis took place, providing an opportunity to practice linear regression. The report includes an interpretation as well.
Even though this was an academic exercise, it was very helpful in stimulating thought about future study designs. Throughout the career of an educator, it is necessary at different times to collaborate to establish metrics about a particular situation, as well as collect and analyze data. This needs to take place both within academic research as well as in the day-to-day processes of educational administration. Interpreting these results and sharing these findings are necessary for improving staff performance and student learning, so applying these skills is imperative to improving the quality of teaching and learning in education.
References
Turner, Y., & Acker, A. (2002). Education in the new China: Shaping ideas at work. Burlington, VT: Ashgate.
Sultan, N. (2010). Cloud computing for education: A new dawn? International Journal of Information, 30(2), 109-116.