Wise Before the Event Troubleshooting Guide to IA in IB Diploma

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Wise Before the Event
Troubleshooting Guide to IA
in IB Diploma Chemistry.
GENERAL PROBLEMS & CONCERNS
Simplicity of task
•
Some tasks are being set that are too simple for IB
diploma level. Affects all criteria and severely distorts
the moderation process.
•
One type of simplicity is when the investigation is not
pitched at a level that is appropriate for the application
of IB Diploma level concepts and techniques. Eg.
separating a mixture of sand and salt or calculating the
density of a penny. If students are coming in the
Diploma with no prior practical skills then maybe such
activities have a role to play early in the course but
should not be used for formal assessment purposes
and should not take up a significant proportion of the
total practical scheme of work.
Simplicity 2
Minimum of data
Well constructed data tables with uncertainties
that contain only two or three pieces of data.
Is this enough to merit the full marks awarded by
the teacher?! Wouldn’t that be unfair on students
set much more demanding tasks that they have
only been able to partially fulfill.
SIMPLICITY 3
If you set simple tasks as training
exercises or as an introduction to
addressing the criteria then there is no
problem as long as you do not enter
resultant marks on the final 4PSOW forms.
Assessment of Group Work
• For the five written-evidenced criteria you
have to be certain that you are assessing
a student’s individual contribution. Can
you be that certain when candidate’s are
working in a team?
• All plans must be individual although
subsequent action phase can be group.
• DC in group work can be problematic.
• DPP and CE follow up to group work is
usually OK but watch out for collusion.
Academic Honesty within I.A.
•
Conjecture - there is less of a problem regarding
academic dishonesty within Group 4 I.A. than in nearly
any other non-written examination assessment
component within the Diploma programme. Certainly I
have less grounds for concern than when supervising
Extended Essays or TOK essays.
•
Reason: Group 4 I.A. structure can take the form of
continuous assessment with students starting to log
marks from very early on in the course. Students given
multiple opportunities. No single piece of work is ‘life or
death’. For me this is a real strength of our subject
group’s assessment structure.
Plagiarism for Planning (b).
• Some procedures have become very familiar
indeed (the Chemistry in Context Laboratory
Manual is an excellent book but seems to be
overly inspirational to some students!).
• When setting a planning task try to avoid areas
where the students do not have the practical
skills to devise the procedure for themselves and
will therefore be tempted into copying.
• Brief yourself as to which procedures are readily
available to the students (quick library/internet
search).
• Referencing: Do we encourage students to cite
literature sources?
COLLUSION
• If you identify any form of malpractice
within your class then deal with it at
source. Do not give any form of credit
to the students through the 4PSOW.
• For assessment use investigations
where students have collected their
own data as far as possible.
DELIBERATE OVERMARKING
• Headmasters and Heads of Science
expecting teachers’ grades to get
moderated down. Shows teachers were
trying to maximise students grades.
• Tendency to mark rigorously considered
emotionally illiterate and unfair on
students.
The Bureaucracy!
Poorly prepared samples for moderation
cause moderator fatigue! Don’t just stick
everything in a packet and hope for the
best.
Delays when further evidence/instruction
sheets/etc are called for via IBCA.
A new cover sheet coming your way!
New cover sheet
• Group 4 Internal Assessment Sample
Cover Sheet 2006-04.doc
Planning (a)
• Students have been moderated down to ‘not at
all’ in first aspect for repeating teacher’s aim.
• Set the planning task in a more discursive
fashion.
• Distilled single sentence aims are hard to focus
further into an original research question.
• Do not identify the independent variable(s) for
the students.
• Problem: Students have been moderated down
in second aspect for including a pseudohypothesis.
• A hypothesis should be a prediction of a
relationship that will be revealed or a statement
of theory that they expect to be supported.
• Pseudo-hypotheses that simply predict that the
experiment is going to work or that it will be
interesting.
• These are not predictions that have any
scientific value and are not worthy of even the
often awarded ‘partial’ in the second aspect.
Pl(a) Does the hypothesis have to
have a correct explanation for ‘c’?
No, but it has to be reasonable and based
on a clear understanding of the aim and
the phenomenon/property under
observation.
Hypothesis Example
• Aim: To investigate whether and how amount of
impurity (naphthalene) will affect degree of
supercooling of SALOL.
• Hypothesis: “Expect degree of supercooling to
increase as more naphthalene added because it
is known that impurities will lower the melting
point of a solid”.
Partial: Explanation demonstrates confusion
between minimum temperature during
supercooling and the melting temperature.
PLANNING (b)
Should the students cite materials and
apparatus as a separate list?
It is probably advisable but not obligatory
as long as the materials and apparatus are
clearly identified in procedure.
Reactant concentrations, masses,
volumes, etc, to be included.
Pl (b) Control of Variables
• By control of variables we mean the
manipulation of the independent variable and
the attempt to maintain the controlled variables
at a constant value.
• In a good Pl (b) task the student should have
actively had to consider the control of variables.
• eg, Control of temperature in rate of reaction experiments.
(does a titration really give opportunity of active consideration of
variables)
Pl (b)
Sufficient data
• The planned investigation should anticipate the
collection of sufficient data so that the aim or research
question can be suitably addressed and an evaluation of
the reliability of the data can be made.
• Very few candidates considered the assessment of
reproducibility through replication or the assessment of
uncertainty through calibration of experimental set-up
with a known standard.
• Candidates fail to plan for a suitable number of trials in
order to properly investigate, ideally through graphical
means, the effect of changes in the independent variable
upon the dependent variable.
Example considerations when assessing sufficiency of data could be:
• The plan allows for the gathering of at least 5 data points to show a
trend by graphical means eg. at least five values of independent
variable in a rate of reaction investigation.
• A plan investigating comparative properties within a homologous
series, or similar, should allow for use of at least four homologues to
identify a trend. It is acknowledged that any follow-up practical work
may be modified if not all resources are available.
• The plan allows for repeats measurements to calculate a mean eg
repeat calorimetric determinations when investigation on enthalpy of
reaction.
• The plan shows appreciation of need for trial run and repeats until
congruency in titrimetric determinations.
SETTING A SUCCESSFUL
ASSESSED PLANNING TASK
Train them in skills either pre-Diploma
programme or early in Diploma course
Take your time with early planning activities.
Better to not assess first planning activities
and to really guide students as to
expectations of Pl(a) and Pl(b)
SETTING A SUCCESSFUL ASSESSED PLANNING TASK 2
• Select a task in which the students already have
some background knowledge and practical skills
• Give them a pre-session in which to familiarise
themselves with the system and the
materials/equipment before they write their plan.
• Students should be trained to at first select
possible independent/control variables.
GENERAL RULE
• The more possible independent/control variables
the better.
Leads to
• Greater variety of individualised plans.
• More meaningful opportunity to design for
control of variables.
Planning (b)
• Do not do a practical prior to the planning
task that requires an identical procedure if
Pl(b) is to be assessed.
• Eg. DCPIP titration for Vitamin C analysis
of orange juice that is simply extended to
consideration of juice samples. Not
assessable for Pl(b).
SETTING A SUCCESSFUL ASSESSED PLANNING TASK 3
EXAMPLE
FACTORS EFFECTING SUPERCOOLING IN SALOL
Many of you have carried out melting point determinations on SALOL (phenyl
salicylate, CAS number 118-55-8) and have been impressed to see the that it
remains in the liquid state until well below the literature melting temperature range
of 41-43°C. This phenomenon is called supercooling.
HO
O
O
Phenyl salicylate
Your task is to plan a series of experiments that will investigate at least one
chemical or physical factor that you believe may influence the degree of
supercooling in materials such as phenyl salicylate.
SETTING A SUCCESSFUL ASSESSED PLANNING TASK 4
SALOL Timeline
• Session 1 (80-90 mins): Task is set to the students. Students
will draft initial ideas re. independent variables and
experimental procedure. They may use rest of double period
for preliminary trials.
• The plans will be written as homework and submitted prior to
Session 2 for assessment.
• The plans are marked and returned to students. These are
the final Pl(a) and Pl(b) marks entered on 4PSOW.
• Session 2 (160 mins!): Students carry out action phase
following their plans. Since the plans have now been
assessed for Pl(a) and Pl(b) the teacher is free to suggest
modifications to any student whose plan was unworkable
(possibly owing to unavailable materials) or overly simplistic in
order to help them generate data to satisfy other criteria.
SETTING A SUCCESSFUL ASSESSED PLANNING TASK 5
SELECTING THE VARIABLES
Possible Variables
• Example selection
Cooling Rate
Degree of stirring/agitation
Initial Temperature
Mass of compound
Surface area of sample compound
Identity of vessel
Chemical Structure of Compound
Composition of binary mixture
(possible independent)
•
•
•
•
•
•
•
•
Control (measure/active)
Independent
Control (active)
Control (active)
Control (passive)
Control (passive)
Control (passive)
Control (active)
How Much Guidance?
Do not give too much task specific guidance but
there is no limit to the general reminders:
• “Don’t forget to explain your hypothesis”
• “Have you identified the variables?”
etc, etc
..\Bonds\IB Chemistry\ib lab grades\IB
Chemistry Report Writing Checklist.doc
An Individual Research
To improve the individuality of students plans and
subsequent reports you could set aside time for
an individual project.
Offer them a list of those TSM 1 Pl(a) & Pl(b)
suggestions for which you have the materials
and/or
Allow students to come up with original ideas
Data Collection
Inclusion of quantitative preferred. New curriculum
compatible.
Uncertainties to be included.
Annotate work for moderator if you felt no relevant
qualitative data was generated.
Moderation observation: Teachers prone to over-reward
their students in purely qualitative DC tasks with full
reward being given for poorly phrased observations that
either lacked detail or were not primary observational
statements.
Data Processing and Presentation
• Processing of raw data may include:
• subjecting raw data to numerical calculations
• using graphical means to derive a quantity or
relationship.
• The simple transformation of raw data into
graphical form is not sufficient to fulfill
completely the criterion unless there is some
expectation that further quantitative or qualitative
information will be extracted from the graph.
DPP
• For example the plotting of volume of gas
produced against time in a rate of reaction
experiment would not completely fulfill this
aspect but if the student has compared
qualitatively or quantitatively gradients for rate
curves obtained under different conditions then
the aspect can be assessed fully.
• Similarly a titration curve where raw pH and
volume of acid/base measurements are plotted
is sufficient only so long as the graph is used to
obtain further data, such as a pKa value of a
weak acid or the titre.
Data Processing and Presentation
• Increased minority of school encouraged
meaningful treatment of errors or uncertainties in
DPP.
• There is an ambiguity in the expectation for SL.
Safest to treat as HL or to assess through
graphical analysis
• The TSM 1 should be referred to for guidance in
this area. TSM 1\errors & uncertainties.htm
DPP (examiner’s report comments)
• Relatively small number of graphs presented for
moderation and their poor quality overall.
• Poor use of Excel. Contemporary versions of
Excel can be used to great effect in DPP but the
normal expectations of graphing , i.e. labeled
axes with units, best-fit lines and curves, etc,
must still be observed, as well as the candidate’s
individual contribution being evident.
• A graphing program that does not permit user
control over the processing or output is not
suitable for assessment of this criterion.
DPP (examiner’s report comments)
• Very few candidates undertook further
processing of the data such as finding a gradient
or intercept through extrapolation.
• Second aspect’s requirement to take into
account uncertainties can be fulfilled through a
suitable best-fit line should make data
processing through graphing an increasingly
important component of most school’s
programmes and hopefully the quality of graphs
presented will as a result improve.
DPP
• Although the data collection phase may be
carried out in groups the actual recording
and treatment of data should be
independently undertaken if DPP is to be
assessed.
• Online data collection exercises may be
suitable for then assessing DPP.
Conclusion and Evaluation
• Low scoring
• Many candidates fail to compare their results to
literature values where appropriate.
• Often no valid conclusion with an explanation
that is based on the correct interpretation of the
results.
• Little evidence that candidates make any
attempt at background reading or research in
order to interpret their findings.
CE (con’t)
• Most candidates attempt to evaluate the
procedure and list possible sources of error.
• Often this evaluation was superficial
• Candidates should attempt to identify
reasonable systematic errors.
• If a total % uncertainty for DPP is determined
then use to assess if the final result was
explainable by random error or required the
consideration of systematic errors.
• Many candidates were able to make appropriate
suggestions to improve the investigation
following the identification of weaknesses.
MS, PS(a), PS(b)
Evidence need not be included
Warning!
Marks get moderated down by your moderation
factor.
Recommend to use TSM checklists for
assessment. TSM 1\MS & PS a & b.htm
Examples of Marking Guidance to
Moderators
• Planning (a): Teacher gives the problem or
research question but still awards: c, c, c =
3. Maximum moderator can give is n c c =
2.
• Planning (b): Teacher gives c, c, c but it is
clear that the students have been told
what apparatus and materials they require.
Maximum moderator can award is
n, c, c = 2.
• Data Collection: Teacher gives c, c = 3 but
the students have used a photocopied
data table with headings and units.
Maximum moderator can give is p, n = 0.
Or the teacher gives 3 (c, c), but the
student has only recorded quantitative
data (e.g., in titration) and qualitative data
such as colors of solutions, indicator, color
change etc. are missing. Moderator gives
p, c = 2. However, do not be overzealous
and penalize DC every time a student
does not find qualitative data to record.
• Data Processing & Presentation: Teacher
gives c, c = 3 but the students have been
told, on the method sheet, to draw a graph
from their raw data and which variables to
plot. Moderator gives c, n = 1.
• Conclusion & Evaluation: Teacher gives c,
c, c = 3 but the student has only indicated
as a criticism that they ran out of time.
Maximum moderator can give is c, n, p =
1.
From OCC Resources
• DOs&DONTs.pdf
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