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IB Biology – Internal Assessments

This comprehensive guide offers strategies for improving IB Biology internal assessments. It covers essential topics such as formulating specific research questions, developing clear hypotheses, and systematically organizing data. Key areas of focus include enhancing controls, thoughtful citations, and incorporating quantitative data. The guide emphasizes the importance of clarity in methods and results, recommending clear labeling of graphs and data tables. Additionally, it provides insights into self-evaluation techniques and methods for determining reliability and validity, ensuring a well-rounded assessment process.

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IB Biology – Internal Assessments

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  1. IB Biology – Internal Assessments IMPROVEMENTS and SUGGESTIONS and REQUIREDs

  2. GENERAL • HOW TO Self Evaluate • Link between Self Evaluation / Rubric / Aspect 1-2 3 • Scores • N - Not at ALL 0 pt • P - Partial 1pt • C - COMPLETE 2 pt.

  3. GENERAL • MORE RESEARCH • and UNDERSTANDING … • BEFORE THE LAB BEGINS…. • Stomata/vaseline/transpiration/surface area estimation

  4. TITLE - AIM- RQ- • RESEARCH ------MORE • Be MORE SPECIFIC • Include SPECIFIC IV and Specific DV

  5. HYPOTHESIS • WHAT YOU THINK WILL HAPPEN • BASED ON RESEARCH !!!!!!!!!!!!! • More RESEARCH before • More Citation • More Quantitative (numbers or description) • SPECIFICS of what will happen to each IV • SYSTEMATIC !!

  6. IV table • SPECIFICS !!! • Column 2 – EXACTLY what is it is • Column 3 – HOW you plan to manipulate change the IV

  7. DV Table • SPEDIFICS !!!!! • Exactly what the DV is (second column) g/cm2 or gcm-1 • Using average grams lost in the leaves over the average surface area of the leaves in each treatment • HOW it is calculated or measured and error (3rd column) • Using analytical scale • Avg mass difference of the three leaves after 24 hrs in grams ±0.0005 or ± 0.001 • Avg surface area of leaves in each trial ….count the # of full squares and add the number of ½ squares to estimate the surface area of each leaf.

  8. CONTROLS table • Commonly POORLY DONE ….too few or not specific enough • Column 1 – the NAME Column 2 – HOW it will be controlled Colum 3 WHY it should be controlled/WHAT impact would it have on the data (science of that control) • MAKE SURE it is on ONE page don’t run it over two pages or start a NEW(cont’d) TABLE with Headings on the next page • LINE UP the items properly

  9. Materials – Methods Procedures • CITE source of Method even if it is given to you like the leaft lab was !!!! Put it in bibliography/appendices/ and cite nest to Section – Method-Procedure • VERY DETAILED • Show Uncertainty of each tool !!!

  10. Materials – Methods Procedures • Photos/Diagrams ?? Refer to them in the Method • EXPLAIN how Surface Area is CALCULATED (processed) • END with SPECIFIC DETAILS of how you plan to PROCESS the data and PRESENT the data

  11. RAW DATA • UNITs and Error/Uncertainty……. CLEAR AT TOP • SAME NUMBER OF digits in Uncertainty AND the Data !!!! • QUALITATIVE DATA Required (use in conclusion as well!!!)

  12. PROCESSED DATA • UNITS CLEAR AT TOP • EVERY TABLE should only be ONE STEP in the processing • Sample Calculations and Formula are REQUIRED ….

  13. PROCESSED DATA • EVERY TABLE should have the WRITTEN FORMULA and a SAMPLE CALCULATION for the data in the table • INDICATE which SAMPLE/TEST you are show for the sample calculation

  14. GRAPH(s) • USUALLY just of your final processed data (see method) • GRAPH make sure you plan to explain/cite it in your conclusion. • Indicate WHICH data Table is being graphed • EXPLAIN and/or LABEL what the error bars are for if present

  15. GRAPH(s) • ALL AXISes CLEARLY LABELED • Sometimes graphs of raw data or steps in processed data might be useful to explain/support your hypothesis/evaluation (leaf size) (g lost) • PUT DATA in order that makes sense ….

  16. CONCLUSION • RESEARCH MORE • EXPLAIN PATTERNS seen in Data and Graph • CITE how RESEARCH supports or does not support • DESCRI

  17. CONCLUSION • RESEARCH MORE • DESCRIBE and EXPLAIN PATTERNS seen-Data and Graphs • CITE how RESEARCH supports or does not support

  18. EVALUATION – IMPROVEMENTS • Use the TABLE !!! On the template • Reliability of data (SD important here • Science Evaluation (SD should help) • NO SD ….explain why • AVOID overly ‘human error’

  19. EVALUATION – IMPROVEMENTS • IMPROVEMENTS based on Evaluation ….so in SAME TABLE is okey • SCIENTIFIC !!!! • More Repetitions always • Improved equipment • Controls improved ..specifics • Etc

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