Studying data science to improve educational outcomes
As a teacher at Toowoomba Grammar School, I teach mathematics and business studies, and manage the GPS Chess team. Prior to teaching, I worked as a financial analyst. Recently I have completed a master's degree in science at the University of Southern Queensland. My study was focused exclusively on data science, and I have become an expert in the management of big data with a specialisation in modelling and forecasting using machine learning techniques.
The motivation for this study was because of the identified opportunities to utilise data to assist in the educational outcomes of students. The observed diversity in student needs, coupled with the complex nature of education data sets, prompted me to seek the skill development from the international experts at USQ.
The culmination of my study has been in the successful publication of research paper in the international journal “Health Information Science and Systems” titled “A novel empirical wavelet SODP and spectral entropy-based index for assessing the depth of anaesthesia”. It focussed on the development of machine learning algorithms for determining the depth of anaesthesia in patients during surgery based on real time electroencephalography signal (potential difference due to brain activity). Assessment of the depth of anaesthesia (DoA) is an important and ongoing field of research to ensure patient stability during and post-surgery. This research addresses the limitations of current DoA indexes by developing a new index based on electroencephalography (EEG) signal analysis.
This model employed a variety of novel signal processing algorithms and has demonstrated successful DoA measurement with improved time responsiveness compared to current market leading DoA algorithms in a range of circumstances. This responsiveness is especially evident in cases of high signal interference.
It is a great privilege to have worked with such renowned medical researchers and to have had my own research recognised internationally in this field. I hope that in time this work can be used to influence professionals and assist in the development of medical monitoring devices to ensure more safe operating procedure for patients.
There was some challenge in managing the dual roles of a teacher and student, but this experience has been instrumental in developing a sense of empathy with the students I work with. Regardless of the level, pushing personal boundaries and extending one’s learning is always a challenge and a privilege. On a more practical level, I hope to eventually be able to apply elements of these research methods to student tracking and monitoring algorithms employed at TGS.
You can find Thomas' published research at A novel empirical wavelet SODP and spectral entropy based index for assessing the depth of anaesthesia | SpringerLink
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