Wise Before the Event Troubleshooting Guide to IA in IB Diploma Chemistry.

1. Wise Before the EventTroubleshooting Guide to IAin IB Diploma Chemistry.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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?

8. 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.

9. 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.

10. 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!

11. New cover sheet • Group 4 Internal Assessment Sample Cover Sheet 2006-04.doc

12. 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.

13. Problem: Students have been moderated down in second aspect for including a pseudo-hypothesis. • 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.

14. 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.

15. 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.

16. 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.

17. 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)

18. 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.

19. 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.

20. 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)

21. 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.

22. 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.

23. 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).

24. SETTING A SUCCESSFUL ASSESSED PLANNING TASK 3EXAMPLE FACTORS EFFECTING SUPERCOOLING IN SALOL

25. 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.

26. Possible Variables 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) Example selection Control (measure/active) Independent Control (active) Control (active) Control (passive) Control (passive) Control (passive) Control (active) SETTING A SUCCESSFUL ASSESSED PLANNING TASK 5 SELECTING THE VARIABLES

27. 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

28. 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

29. 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.

30. 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.

31. 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.

32. 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

33. 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.

34. 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.

35. 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.

36. 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.

37. 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.

38. 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

39. 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.

40. 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.

41. 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.

42. From OCC Resources • DOs&DONTs.pdf