Producing Colour Profiles With Correct Errors Using FDS Data and Improving inclusivity in astronomy education with the help of 3D physical models

Postema, Jasper (2022) Producing Colour Profiles With Correct Errors Using FDS Data and Improving inclusivity in astronomy education with the help of 3D physical models. Master's Thesis / Essay, Astronomy.

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Abstract

In this thesis the data generation process of the Fornax deep survey (FDS) is analyzed to create surface brightness and colour profiles for 10 dwarf galaxies inside the cluster. A method to determine the residual background values in the images together with sensible error is developed in this thesis. After subtracting the residual background from the corresponding images, surface brightness and colour profiles are created. A depth of 30 magnitudes/square arcsec was reached for the surface brightness profiles with the best signal to noise. The data produced in this thesis have errors that have been derived in a sensible way which is often not the case for similar data in other research. and Astronomy education is currently dominated by and catered to students with a visual learning style. The goal of this thesis is to improve the inclusion in astronomy education by making astronomy education more accessible to tactile learners. To improve this inclusion I designed 3 sets of 3D models for first year astronomy students that follow the observational astronomy course. The 3D models are made to explain the topics of galaxies, variable stars and point spread functions. I conclude that most of the models were intuitive to use, that most of the models improved the understanding of the students, that the models were more intuitive for tactile learners than visual learners and that the models helped the tactile learners understand the topics better than the visual learners.

Item Type:	Thesis (Master's Thesis / Essay)
Supervisor name:	Peletier, R.F. and Noel-Storr, J.
Degree programme:	Astronomy
Thesis type:	Master's Thesis / Essay
Language:	English
Date Deposited:	11 Jul 2022 10:09
Last Modified:	11 Jul 2022 10:09
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/27742

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