videnskabsteori, -kommunikation og etik (smac) fall 2008 · 2008-09-12 · videnskabsteori,...
TRANSCRIPT
• Course teachers
Ole K Andersen, dr scient ([email protected])
NN (theory of science)
• Course secretary
Jette Damkjær (common secretary for 1st semester M.Sc., [email protected])
Vita Kammersgaard ([email protected])
• Course literature (OKA part)
– Leedy & Ormrod. Practical Research: Planning and Design, 8th edition. Merrill, Prentice Hall, 2004.
– Overheads: Available after each lecture
– Course homepage
www.hst.aau.dk/~oka/SMAC
Videnskabsteori, -kommunikation
og etik
(SMAC) fall 2008
SMAC
Objectives• Understand the scientific process
– Basic scientific theories/reasoning
– A bit history of science
– Think, plando it
– Report
• Communicate the scientific result
– Talk
– Write
• Use scientific language
– English
– Native
• Systematized common knowledge
• Examples throughout the course: a lot from biomedical research, but of generic nature
Course Plan• Lecture 1 Introduction to the SMAC course, research hypothesis
• Lecture 2 Theory (and history) of science – only S-SN students
• Lecture 3 -
• Lecture 4 -
• Lecture 5 -
• Lecture 6 Scientific methods in science and engineering (OKA)
• Lecture 7 Ethics in science, with emphasis on biomedical sciences (OKA)
• Lecture 8 Scientific communication, examples on oral presentation
and poster presentation. Details on SEMCON (OKA)
SMAC
Contents• Scientific process
– 4 (8 for S-SN) auditorium lectures
SEMCON 1st M.Sc. project
- Abstract (not necessarily the same as
in paper)
- Scientific paper
- Poster presentation - Worksheets
- Oral presentation - Repeat poster+oral
SEMCON - Semester conference
Presentation of semester projects within a scientific framework
• First announcement: 12.09.2008
– Planning research paper
– Allocation of time and space
• Second (final) announcement: 21.11.2008
– Deadline for final submission
– Specific guidelines for abstracts, posters and oral presentations
– Deadline for abstracts: 12.12.2008 (not confirmed)
– Abstract book (pdf-file)
• 21th SEMCON: (19.12.2008)
– Oral presentations
– Poster presentations
SEMCON
AWARD
Based on this and your performance on the SEMCON the conference committee (chaired by OKA) will select the winner
– Participation in an IEEE conference on European soil
– Or other study relevant travelling
– Price of dkr 20.000 per group (or max kr 5000,-per member )
Science
• From Latin “Scientia”– To know, to discern, to distinguish
– The state or fact of knowledge
– Systematised knowledge from observation, study, and experimentation carried out in order to determine the nature or principles of what is being studied (social, natural, XX engineering, biomedical, etc.)
– Organised common sense
• Scientific– Designating the method of research in which a
hypothesis, formulated after systematic, objective collection of data, is tested empirically
Hypothesis
• Greek “to suppose or to speculate“ which is coming from hupotithenai=“to put under or to suppose”. Interpretation: speculations on underlying mechanisms
• An unproved theory; supposition tentatively accepted to explain certain facts or provide a basis for further investigations
• A provisional idea whose merit needs evaluation
• Verification = acceptance
• Falsification = rejection
• Research leading to acceptance is not a proof!!
Hypothesis, cont.
• Dubitation
– Doubting an existing theory so strongly that
no formal falsification is attempted -
instead new ideas are emerging
• “ulcus duodeni is caused by psycho-social
factors or too much acid in stomach”
• “ulcus duodeni is related to Helibactor pylori
(bacteria)” - comes from doubts and new
searches
Hypothesis, cont.
• Propositionlegitimacy
– Undertake formal proces of synthesis leading to validation. Otherwise it‟s idle speculation.
– 4 steps:• Specify solution
• Set goals
• Define factors
• Postulate performance metrics
stated order
Hypothesis, cont.
1. Specify solution (mechanisms and procedures)
• Schematics, pseudo-code, algorithms, experimental design, etc.
• Choose the best/most likely solution, perhaps based on Quick and Dirty pilot tests
• Specify the procedure to follow
2. Set goals
• Specify criteria for acceptance of hypothesis (for all sub tasks) – improved quality of life – but what is that precisely?
• Specify tests
Hypothesis, cont.
3. Define Factors• List all factors that govern the system
• Then select which parameters are held constant and which are systematically varied
• Find values for fixed parameters and the range of change for those that are varied.
4. Performance metrics• How to measure, objectively
Exception to hypothesis driven research: Descriptive research
http://www.smi.auc.dk/~oka/SMAC/huda_akil2003.pdf
Hypothesis, example
• Funtional Electrical Thereapy (FET) will improve the gait rehabilitation after a stroke
– Its not far fetched: Engineering approach: the brain needs feedback, hence we must provide that.
– Electrical stimulation will assist the gait
• The hypothesis guides us to the solution, an experimental design, i.e. pratical research
• A global hypothesis: ‟improve life quality for stroke patients‟ is not of any practical use –it doesn‟t give us any hint to a solution
”The great tragedy of science is the slaying of a beautiful hypothesis by an ugly fact”
Thomas Henry Huxley – a great defender of Darwin
1. Specify solution
• Experiment
• Group comparison between treated group and no-treatment group, electrical therapy only difference
• Single blinded
• Pilot test to evaluate concept, get some experience on parameter levels
• Inclusion/exclusion criteria
• Etc.
2. Set goals
• Overall goal: Improve walking performance
• Statistical power, i.e. a way to estimate N
• Tests: before, after, late values
Session 2 Session 3
Training
1 Month 1 Month 5 Months
3. Define factors
• Parameters on electrical stimulation
– Intensity, stimulation site, frequency
• Duration of training session
• Walking speed during training
• Level of assistance from physioterapists
• Entrance level of patients (randomisation)
4. Performance metrics
• Gait quality
– Qualitative measures (patients need for
help)
– Quantitative measures (velocity, symmetry,
energy consumption)
Criteria for research
projects
• Research projects should be practical research, built on precise and realistic planning and executed within the framework of a clearly conceived and feasible design !
• Four important criteria
– Universality• Other competent people than you should also be able to carry
out the research project. Not exclusive to you
• Same principles within different disciplines (engineering, medical, social etc.)
• Raises questions to be answered through stringent research methods (logical, critical, consistent)
Criteria for research
projects, cont.
–Replication
• Research should be repeatable by other competent people
–Control
• Parameters are important - control the controllable. Conditions should be described and standardised
–Measurement
• Data should be susceptible to measurement. Often easy in physical sciences and difficult in social sciences
What science is not
- or not should be -
• Simple gathering of information
– Distinguish from learning
– “Going to the library and read about King
Christian IV”
• Transportation of facts
– Needs interpretation of the facts and data
– “Listing facts, statements and knowledge
are not enough”
What science is not
- or not should be -
•Rummaging for information
–More than checking information for self-enlightenment
–“Finding out house prizes in Aalborg”
•Catchword to get attention
–Often misused in advertisements
–“Years of research have produced a new hair shampoo”
Eight characteristics of
good science
1. Starts with a question or problem
2. Requires a clear articulation of a goal
3. Follows a specific plan or procedure
4. Divides the problem into more manageable sub-problems
5. Guided by specific problems, questions or hypothesis
6. Accepts critical assumptions
7. Requires collection and interpretation of data
8. Is cyclical or helical
The research question or problem• Many unanswered questions and unresolved
problems
– Look around - observe - wonder
– Be curious
– Ask questions• Why?
• What is the cause of that?
• What does it mean?
– Previous observations or extension of scientific theories
• Nobel prize winner 2000 in medicine - Eric Kandel
– Observed changed function of memory in psychiatric patients(e.g. the film Rain Man on autism)
– Asked why is the brain working differently?
– How is memory stored in the brain cells? (synaptic transmission -signal transduction)
Guidance by a specific problem or
hypothesis• Hypotheses are not new or purely academic constructs, but
reasonable guess - logical supposition
• „Binary‟ example: you come home and wants to turn on the lamp - but no light.
– #1. The bulb has burned out
– #2. The lamp is not plugged in outlet
– #3. A thunderstorm has interrupted the electrical service
– #4. The wire/connector from the lamp is defect
– #5. You forgot to pay your electric bill
• Different methods
– Get a flashlight - insert new bulb - still no light (hypothesis #1 is rejected)
– Visual check that the lamp is plugged in (hypothesis #2 is rejected)
– The neighbours homes all have light (hypothesis #3 is rejected)
– Lift the cord - the lamp lights and goes out - lift the cord again - the lamp lights and goes out (hypothesis #4 is accepted)
Acceptance of certain critical
assumptions
• Research has assumptions
• Self-evident truths - conditions that need to be taken for granted
• Define and state the assumptions necessary for your hypothesis, e.g.
– “An adaptive filter is better at removing noise than a fixed filter in EEG instruments for anaesthesia”
• There is a relationship between EEG and anaesteticdepth
• Your instruments in the lab are accurate (calibrated) and sufficiently sensitive to detect a difference
• The examiner is capable of performing an accurate test
Collection and interpretation of data
• Collection of data is the first step
– Data are objective
• Interpretation of the data is the next - necessary - step
– Data need to go through the human brain to get a
meaning !
– Interpretation is subjective (logical mind, reasoning
skills, objectivity of the researcher)
• Good arguments for your interpretation is warranted, often
based on the existing literature
Statistics as a tool of
research
• Helps to describe and interpret the data set
– Descriptive statistics
• Points of central tendency (mode, mean, median etc)
• Measures of variation (quartile range, SD, SEM,
variance)
• Measures of relationship (Pearson product moment,
Spearman rank-order etc)
– Inferential statistics
• Predictions – estimations (e.g. mean from samples)
• Hypothesis testing (t-test, Wilcoxon, Mann-Whitney,
Friedman, ANOVA etc)
Statistical tests of
hypotheses• Null hypothesis H0:
– Postulates no statistically significant differences exist between “A” and “B”
– “A” occurs as often as “B”
– “A” is as good, or as worse an intervention as “B”
– “Hip som hap” ! H0 can be accepted
– If “A” is different from “B”, and if the magnitude of that difference exceeds the possibility for random error, chance or variability, then some intervening variable is at play ! H0 must be rejected
– Type I and Type II errors – power of statistics
Note
– Statistical significance is not necessarily functional significance
Research is
cyclical or helical
• Resolution of the original problem seldom closes the cycle but generates new questions – helix
• Research is rarely conclusive• Research is not static but dynamic
1. Research begins
with a question
2. Clear
statement
of the goal
6. Interpretation
Rejection or
acceptance
5. Collect and
organise data
4. Hypotheses
to be tested
3. Division
into subproblems
AAU student projects vs
scientific projects
Is cyclical or helical
Requires collection and interpretation of
data
Accepts critical assumptions
Guided by specific problems, questions or
hypothesis
Divides the problem into more
manageable sub-problems
Follows a specific plan or procedure
Requires a clear articulation of a goal
Starts with a question or problem
Science
May be cyclical/helical
Result: does it work?
No subjective interpretation required
Assumptions – when required
Problem formulation
Sub-problems – the nature of group work
The system description outlines plan
Goal: system performance
Project proposals (involving a problem)
Typical AAU projects on B.Sc.
Examples of 7 sem projectsA master-slave based session layer protocol for real time WiFi…..(PR731
2006)
• Communication with satelite needs to be real time. Traditional Wifi is asynchronious hence difficult to obtain real time responses.
• Hypothesis: master-slave communication is better than the existing method.
• Experimentation, signal analysis, statistical tests
Absolute positioning of a beacon by estimating acoustic time of flight using the cross correlation method (PR730 2004)
• Robot positioning
• Hypothesis: Trilateralisation based on acoustic signals will improve 2D positioning
• Experimentation, comparison with existing methods, statistical analysis
Designing, prototyping, and testing of a flexible on-board computer platform for PICO satellites (PR731 2003)
• Development of a generic framework for subsystems at the satelite
• Conclusion: ”....sollid foundation has been made for different development tasks next semester”
From student projects
to Nobel prize
• Why learn about the scientific process?
– Pragmatic: part of the curriculum
– Idealistic: integrated way to view and manage new problems in practise
Methodology• Control acquisition of data
• Organise data and extract meaning
• Discover the discipline of research
– Pursue a Ph.D. or a Doctorate
– Understand the drive to push forward the limits of knowledge for the benefits of our well-being
Reviewing the literature• “You need to have background knowledge to approach your
own research problem”
• Purpose of the review– Reveal investigations similar to your own– Show how other researchers have handled methodological
and design issues– Describe methods to deal with problem situations that you
are facing– Reveal sources of data that you may not have known existed
(e.g. patent databases)– Introduce you to key persons whose work you may not have
known– Help to see your own study in historical perspective– Give you new ideas and approaches– Help to evaluate your own research efforts by comparison to
similar efforts of others– Indicate the time and effort previously put into your research
topic
Practical advice to
information search
• Use the tools and search the literature - haste slowly - and read
• Identify 2-3 central, high-quality review papers - and read
• Read papers most closely related to your research topic and then gradually expand
• Pick others brains
– Friends
– Supervisors
– Experts
– Senior faculty members
• Contact authors to key-papers
• Important verbal information can be obtained from meetings, conferences and personal interactions
SMAC-lecture 1 - exercise
• Evaluate your project in terms of
– What was the original question or problem?
– Have you stated a clear hypothesis to be tested?
– Specify solution, set the goals, define factors and select the performance metrics
• Do you have a specific plan of procedures, including worksheets?
• Do you need to break down the problems into a number of subproblems?
– Will your methods be able to generate data that can support or reject the hypothesis?
• Send your revised description (*.pdf) of the project to [email protected] including project title, group ID