1. Overview of USSKAR-30-2 (Dis?)Orientation
Practice & Communication of Science
Overview of USSKAR-30-2
(Dis?)Orientation

2. What is PaCoS/KAR About?
It’s about what science is and how it works
What is science?
Science is just “accounting for variation”
A belief system, but grounded in the physical world
How does it work?
by application of the scientific method
explanations based on observation/ experimentation rather than revealed truth
by recognising there is no absolute certainty
by being falsifiable
by using statistical analysis as arbiter
by embracing change through the literature

3. How is KAR Structured? 3 hours activity each week…
‘A’ Weeks – Practicals & Tutorials
Practicals – emphasis more on process than subject
eg mix of ‘abstract’, biochemistry, physiology
vehicle to investigate how meaning is derived from experiments & how that is communicated
Sem 1 : three x 2 week activities
Glassbeads – how measurement corrupts
Lactase – can change be picked up/used?
Spirometry – deriving quantitative models from complex systems
Sem 2 : one x 6 week activity (‘mini project’)
biochem/physio: hypothesis  communication

4. How is KAR Structured? 3 hours activity each week…
‘A’ Weeks – Practicals & Tutorials
Tutorials
immediately following 6 of the pracs
ones where data collection not critical
opportunity to practise statistics ‘core’
Lecture Notes & Tutorial Questions booklet
will also need calculator and book of Stats Tables
great practice for a lot of what will appear on the exam

5. How is KAR Structured? 3 hours activity each week…
‘B’ Weeks – Lectures, three overlapping ‘strands’
Fundamentals – key concepts in science
eg scientific method, probability, distributions
can be counter-intuitive
Nitty Gritty – ‘the devil is in the detail’
statistical methods, esp hypothesis-testing
absolutely core to scientific practice
Wider Context
differences between subjects
societal context (eg ethics, funding, pseudoscience)
communication

6. How is KAR Assessed? 50/50 coursework & exam Coursework : CW1 and CW2
CW1, 25% of mod – individual report
on either Lactase or Spirometry
week 28, 25% of module
CW2, 25% of mod – two group posters
assessed in practical class
Glassbeads – assessed week 11 (5% of mod)
Mini-project – assessed week 36 (20% of mod)
will seek some way to distribute week 11 marks

7. How is KAR Assessed? 50/50 coursework & exam
Exam, 50% of mod : three sections
Explanation (30% of exam)
written answers on understanding of concepts
Eg Qbank of ~20; 5 from 8 on exam (6% each)
Interpretation (40% of exam)
eg background to a study, Minitab output
type of test, what does it show?
Calculation (30% of exam)
eg some raw data – do a calculation/test
exam will have formula sheet
you need a calculator & book of stats tables

8. How is KAR Supported? web-based support…
Blackboard module ‘run’
lots of ‘background’ info to explore
week-by-week support material
‘before’, ‘for’, ‘after’
screencasts (talking though problems?)
question-bank
tutorials (6x 1h, per group)…
unusual for a year 2 module
espressomaths…

9. What are the Key Themes? measurement… variation… distributions…
measurement scales
the fundamental role of measurement in science
the limitations of measurement and its impact
variation…
where does variation come from?
the profound influence of variation
distributions…
the ways we describe/model data variation
completely fundamental to how science works!

10. What are the Key Themes? probability… statistics…
how chance works
putting chance to work in drawing conclusions
the Bayesian view
statistics…
the combined use of measurement, distributions, and probability to…
…summarise data
…test hypotheses; both central to…
the scientific method…
the formal basis of how science works
provisional/falsifiable nature of science

11. What are the Key Themes? ‘proof’… the scientific knowledge base…
what is ‘proof’ in science?
how does ‘proof’ differ amongst the disciplines?
the scientific knowledge base…
the scientific literature
writing scientifically
crossing scientific boundaries…
pseudoscience, fraud, bias
science and society…
funding science/ethics/communication/controversy

12. Why is there so much Maths? 
the ‘raw material’ of science is measurement
most measurement is numerical
data analysis is numerical
statistical inference is numerical
as our models of the world become more sophisticated/detailed, so we increasingly rely on mathematical models
mathematics is suspiciously good at describing the world
reality seems to ‘run’ on mathematical principles