Investigating the Effect of Utilizing Learning Analytics on Stem Teachers’ Efficacy, Resiliency, and Data Analytics Knowledge
By: Cheng Yu Lin
Publisher: [publisher not identified]
Published: 2020
Place of publication: [New York, N.Y.?]
Language: eng
Description: High novice teacher turnover rate and shortage of skilled novice teachers continue to be an unsolved issue in the U.S. educational system. Novice teachers often suffer low teaching efficacy which may reduce their teacher resiliency and lead to teacher turnover. Past studies suggested that novice teachers’ low teaching efficacy results from their scant teaching experience and their inability to assess impacts of their teaching on students. The failure for novice teachers to utilize effective pedagogies and improve student learning often results in elevated professional anxiety, frustration, and motivation to quit teaching. Recent studies pointed out that learning analytics could help novice teachers to teach more effectively by tapping into student data and data analytics. But how to structure a professional development for novice teachers to learn to utilize learning analytics in teaching remains a question. To address these issues, a survey study and a case study are conducted in this research.

The survey study analyzed 72 teachers’ perceptions and experience of using learning analytics in teaching. The results indicated common barriers for teachers to use learning analytics such as lack of awareness of learning analytics, insufficient computer skills and math/statistics knowledge. Also, when teachers considered learning analytics useful their usage of learning analytics correlated positively with teaching efficacy and teacher resiliency. Built upon insights from the survey study, the case study recruited five novice teachers and investigated the effects of a learning analytics professional development. The results suggested that after the learning analytics professional development, all participants have generally improved their learning analytics knowledge, teaching efficacy, teacher resiliency, and developed higher confidence and intention to use learning analytics in future teaching. One implication of these results is that using teaching scenario could be an effective format to structure learning analytics professional development to improve novice teachers’ competence in assessing teaching practices and their teaching efficacy.

Another implication is that learning analytics professional development could be implemented as intervention in teacher education programs to reduce the likelihood of teacher turnover before novice teachers start teaching formally.
Notes: Department: Mathematics, Science, and Technology.

Thesis advisor: Sandra Okita.

Thesis (Ed.D.)--Teachers College, Columbia University, 2020.