Overview
We have ‘flipped’ the classroom for this module so we expect you to come to ‘lecture’ (except in Week 1!) having already watched the assigned videos and completed the assigned readings. From Week 3 you may be called upon to answer questions about the key points in, and relevance of, an assigned video or reading to the rest of the class.
This means that there is a mix of ‘asynchronous’ (work that you do in your own time) and ‘synchronous’ (work that we do during scheduled hours) interaction. Synchronous activities will normally be recorded for review afterwards, but you should bear in the mind the following: 1) we cannot be responsible for equipment failure; 2) we are unable to record practicals and other small-group activities; and 3) a 2-hour video of the in-person session will be rather less educational and informative than actually being there.
In short, recordings should not be used as a substitute for attendance save in exceptional circumstances.
Preparation
The nature and amount of preparation will vary from week to week, but may include:
- Readings from both academic and non-academic sources.
- Pre-recorded lectures from CASA staff.
- Pre-ecorded videos from non-CASA staff.
- Preparing contributions to set tasks (e.g. summaries, Q&A, etc.)
To get the most value from the module you must do the readings. We have raised the stakes for not doing so since, in previous years, students who did not do the readings often struggled with the final assessment and went on to have even more significant struggles with their dissertation.
If you don’t do the readings you are leaving a lot of easy marks on the table. More importantly, we believe that the single most important skill that you can acquire from FSDS is not the ability to code, it’s the ability to critically interrogate data and recognise the strengths and limitations that are relevant to the problem at-hand. You will learn the technical aspects of data analysis in the practicals. You will learn the critical dimension from doing the readings.
In-Person Session
Note that this is not your usual lecture, it’s going to be a very interactive in-person session involving responses to assigned questions, lecturer-led discussions, and some amount of ‘live coding’. We will assume you have completed the preparatory activities, which will include both ‘Preparatory Lectures’ (a series of short videos for which the slides are also available for note-taking) and ‘Other Preparation’ (primarily readings).
For the readings you will have a Template to complete. Download the raw QMD file and fill one in for each of the week’s assigned readings.
Practicals
In order to make use of these materials you will need to install the Spatial Data Science programming environment.
Practicals are run in groups to maximise your ability to ask questions and interact with other students. You will be notified of your group by the Professional Services team; there may be limited opportunities to switch, and the best way would be to swap with another student and then notify us of the arrangment. You may wish to download the week’s Jupyter notebook before the start of class in order to familiarise yourself with the material.
Improvements
We are always making improvements to FSDS and try to keep track of student-feedback here.