2015
DOI: 10.1016/j.jmathb.2015.08.003
|View full text |Cite
|
Sign up to set email alerts
|

Making sense of eigenvalue–eigenvector relationships: Math majors’ linear algebra – Geometry connections in a dynamic environment

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
5
0
1

Year Published

2017
2017
2022
2022

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 25 publications
(6 citation statements)
references
References 17 publications
0
5
0
1
Order By: Relevance
“…One of the most frequently applied methods to determine how much information is available in the examined data is to use the eigenvalue with its attributes as the indicator [ 30 ]. For this purpose, we have quantified the eigenvalues of the dimensions according to the correspondence analysis, as shown in Table 5 .…”
Section: Resultsmentioning
confidence: 99%
“…One of the most frequently applied methods to determine how much information is available in the examined data is to use the eigenvalue with its attributes as the indicator [ 30 ]. For this purpose, we have quantified the eigenvalues of the dimensions according to the correspondence analysis, as shown in Table 5 .…”
Section: Resultsmentioning
confidence: 99%
“…Although they did not use MRC in framing their work, both of these papers present findings consistent with the importance of representational fluency in students' mathematical development in linear algebra. We only found one study in linear algebra that explicitly attended to MRC; Çağlayan [27] had students explore eigenvalues and eigenvectors in a dynamic software program and argued that this provided opportunities for students to invent and develop, critique, and compare the adequacy of various representations, which are key aspects of MRC.…”
Section: B Literature On Student Understanding Of Symbols and Represmentioning
confidence: 99%
“…Several studies emphasized the use of DGE for the visualization, especially in Geometer's Sketchpad (Gol Tabaghi, 2014;Caglayan, 2015) and GeoGebra (Beltrán-Meneu, Murillo-Arcila, & Albarracin, 2016;Turgut, 2019). Cooley et al (2014) availed themselves of the affordances of GeoGebra to aid students' visualization of the ways in which points on polygons are transformed.…”
Section: Literature Reviewmentioning
confidence: 99%