The goal of this research study was to explore the nature of the relationship between engagement in model-eliciting activities (MEAs) and pre-service secondary mathematics teachers' (PSMTs') mathematical knowledge for teaching (MKT) algebra. The data collection took place in an undergraduate mathematics education content course for secondary mathematics education majors. In this multiple case study, PSMTs were given a Learning Mathematics for Teaching (LMT) pre-assessment designed to measure their MKT algebra, and based on those results, three participants were selected with varying levels of knowledge. This was done to ensure varied cases were represented in order to be able to examine and describe multiple perspectives. The three examined cases were Oriana, a PSMT with high MKT, Bianca, a PSMT with medium MKT, and Helaine, a PSMT with low MKT. Over the course of five weeks, the three PSMTs were recorded exploring three MEAs, participated in two interviews, and submitted written reflections. The extensive amount of data collected in this study allowed the researcher to deeply explore the PSMTs' MKT algebra in relation to the given MEAs, with a focus on three specific constructs—bridging, trimming, and decompressing— based on the Knowledge of Algebra for Teaching (KAT) framework. The results of this study suggest that engaging in MEAs could elicit PSMTs' MKT algebra, and in some cases such tasks were beneficial to their trimming, bridging, and decompressing abilities. Exploring MEAs immersed the PSMTs in generating descriptions, explanations, and constructions, that helped reveal how they interpreted mathematical situations that they encountered. The tasks served as useful tools for PSMTs to have deep discussions and productive discourse on various algebra topics, and make many different mathematical connections in the process.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6982 |
| Date | 01 January 2018 |
| Creators | Abassian, Aline |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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