Research & Design (28 criteria)

Code	Criterion	AI	Justification
RD1	The research topic is an appropriate Chemistry level for the IB DP Chemistry and abides by the IB DP Guidance of “Asking questions worth answering":	1	The research question about how splint length affects burning time is not directly answerable through simple online searches, as it requires experimental investigation. While combustion is a standard topic, this specific relationship requires empirical data collection. The question goes beyond textbook content and syllabus coverage by investigating a specific practical application with controlled variables and quantitative analysis.
RD2	Aim is focused in its breadth, investigating at a single relationship.	1	The aim 'How does the length of a laboratory wooden splint (2-16cm) affect the time it takes to burn completely?' clearly investigates a single relationship between splint length (IV) and burning time (DV). While the measured DV is time, this directly relates to the aim's focus on complete combustion time. The aim is focused, concise, and explores only one chemical relationship without mentioning multiple relationships or broader scopes.
RD3	Aim wording is specific, so the reader knows exactly what the investigation is about.	1	The aim clearly states the specific investigation topic (wooden splint burning), includes the precise IV range (2-16cm), and specifies what is being measured (time to burn completely). While it uses 'wooden splint' instead of a specific chemical name, this is reasonable for a practical investigation where the exact wood composition varies. The aim allows readers to understand exactly what the experiment covers.
RD4	Sufficiently appropriate referenced science background affecting the Dependent Variable (DV) to allow understanding of the investigation.	1	The student provides scientific background about wood composition, pyrolysis process, combustion reaction with oxygen, and includes the chemical equation for cellulose combustion. The explanation adequately covers the chemistry behind wood burning relevant to the DV (burning time). In-text citations are present (e.g., 'Richter and Rein') and a bibliography is included at the end. The background gives sufficient understanding without requiring additional literature.
RD5	Sufficiently appropriate referenced science background explaining how the Independent Variable (IV) will potentially cause changes in the measured Dep	1	The student provides a clear explanation linking splint length (IV) to burning time (DV) in RD5. They explain that longer splints contain more fuel requiring more time to burn, and that the flame must ignite unburnt wood as it progresses. While the in-text citation (Richter and Rein) appears in RD4 rather than RD5 itself, the scientific reasoning connecting IV to DV is sufficiently detailed and uses appropriate chemistry terminology.
RD6	Valid hypothesis is justified by logical scientific reasoning and the chemistry is accurate and testable by the method.	1	The student presents a valid hypothesis stating that increasing splint length will increase burning time, giving a positive linear relationship. This is justified by scientific reasoning that more fuel takes longer to burn. The hypothesis is testable by the method described and accurately based on the combustion chemistry explained in the background section. The hypothesis makes specific predictions about the DV trend (positive, linear) as required.
RD7	Quantitative 'Measurable' Independent Variable (IV) to be manipulated is stated and used consistently when referenced throughout the report.	1	The IV is clearly stated as 'Length of wooden splint, measured in cm' and is consistently referenced throughout as a quantitative measure. The report uses specific numerical values (2-16cm range, 2cm intervals) and maintains this quantitative nature in all references, including data tables, graphs, and analysis. The IV is a directly measurable quantity with appropriate units (cm) and instrumental uncertainties (±0.05cm).
RD8	Quantitative Independent Variable (IV) to be manipulated has correct units stated.	1	The student clearly states the quantitative independent variable as 'Length of wooden splint, measured in cm' in the RD7-RD11 section. The correct unit (cm) is explicitly stated immediately after the variable is identified. This meets the criterion requirement of having the correct units stated for the quantitative IV being manipulated.
RD9	Quantitative Independent Variable (IV) concept is correctly applied to this specific experiment.	1	The student correctly identifies the quantitative independent variable as 'Length of wooden splint, measured in cm, using a ruler.' They specify the range (2-16cm), systematic manipulation (changed every 2cm), units (cm), and explicitly link it to the hypothesis about burning time. The IV is appropriate for testing the relationship between splint length and combustion duration.
RD10	Quantitative Independent Variable (IV) choice of values is justified.	1	The student provides clear justification for the IV values (2-16cm in 2cm intervals): states that 2cm changes give 'sufficiently large change' while maintaining accuracy and timely data collection, notes difficulty of measuring 1mm changes, and explains that 8 values will produce a valid graph for conclusions. This demonstrates logical reasoning linking the choice to experimental objectives.
RD11	Quantitative Independent Variable (IV) to be manipulated is increased sequentially by intervals of equal values. Any deviation from this format is jus	1	The student clearly states that the IV (splint length) will be increased sequentially by equal intervals of 2cm (from 2cm to 16cm: 2, 4, 6, 8, 10, 12, 14, 16). They also provide justification for choosing 2cm intervals, explaining that this gives sufficiently large changes while maintaining accuracy and allowing timely data collection. The equal intervals are explicitly stated and justified.
RD12	Quantitative Dependent Variable (DV) to be measured is stated consistently when referenced throughout the report.	1	The dependent variable 'time taken for the splint to be extinguished' is clearly stated in the DV section. Throughout the report, this is consistently referenced as 'burning time' (raw data table, graphs, analysis) or 'time' in appropriate contexts. While the exact phrasing varies slightly, the meaning remains unambiguous and consistent - all references clearly relate to the time measurement of splint combustion.
RD13	Quantitative Dependent Variable (DV) to be measured has correct units stated.	1	The student clearly states the dependent variable as 'Time taken for the splint to be extinguished' with correct units specified as 'measured in seconds and milli-seconds' in the RD12-RD15 section. The units are scientifically appropriate for time measurement and are explicitly associated with the dependent variable.
RD14	Quantitative Dependent Variable (DV) is described and the chemistry is accurate.	1	The student clearly describes the quantitative DV as 'Time taken for the splint to be extinguished, so that flame is no longer visible' with units specified as 'seconds and milli-seconds'. The method of measurement is stated as using a timer on a mobile phone. The chemistry is accurate, relating to combustion of wood. The DV is directly linked to the experiment's objectives of studying burning time vs splint length.
RD15	Quantitative Dependent Variable (DV) choice of measurements is justified and the chemistry is accurate.	0	The DV is simply stated as 'time taken for the splint to be extinguished' with justification only being that it's 'standard and easily accessible.' There is no explanation of WHY measuring time is the best method to achieve the experimental objective, no discussion of alternative DVs (e.g., mass loss, CO2 production), and no chemistry-based reasoning for choosing time as the optimal measurement for studying combustion.
RD16	All Controlled Variables (CV) are identified in a table, with no obvious omissions.	1	The student has provided a comprehensive table of controlled variables including species of wood, method of ignition, method of recording time, and physical dimensions of splints. Each variable is clearly identified with the value maintained, potential effects, and method of control. No obvious omissions are present - all major variables that could affect burning time are addressed. The table is well-formatted and complete.
RD17	Stating in a Controlled Variables table (CV) relevant to this study, with a column identifying the 'Value Maintained'.	1	The student provides a comprehensive Controlled Variables table with four columns: Controlled Variable, Value Maintained, Potential Effects, and Method of Control. The table includes relevant variables like species of wood (Pine), method of ignition (Bunsen burner on safety flame), recording method (mobile phone timer), and physical dimensions (16.0cm length, 0.2cm depth, 1.0cm width). Each CV has specific values maintained clearly stated.
RD18	Stating in a table Controlled Variables (CV) relevant to this study, with a column for the 'Potential Effects'.	1	The student provides a clear table listing controlled variables (species of wood, method of ignition, method of recording, physical dimensions) with a dedicated 'Potential Effects' column. Each effect specifically explains how the variable could influence burning time if changed, giving directional impacts (e.g., 'increasing the rate of combustion', 'increase the burning time'). The table format and content meet all requirements.
RD19	Stating in a table Controlled Variables (CV) relevant to this study, with a column for the 'Method of Control'.	1	The student has provided a clear table of Controlled Variables with columns for 'Controlled Variable', 'Value Maintained', 'Potential Effects', and 'Method of Control'. The table includes 4 relevant CVs: species of wood, method of ignition, method of recording burning time, and physical dimensions of splints. Each CV has specific methods of control described. The table is well-organized and meets all requirements of the criterion.
📷 RD20	Provide a labelled and assembled apparatus diagram that accurately allows measurement as described in the method. (chemix.org)	1	The student provides a labeled apparatus diagram showing the experimental setup with a Bunsen burner, wooden splint, and mobile phone timer. All components are clearly labeled and the diagram accurately represents the method described for measuring burning time of splints. The diagram is simple but sufficient to understand how the measurement would be conducted.
RD21	All Equipment, sizes, absolute uncertainties, and amounts required for the experiment are listed or stated in the Equipment List	0	The equipment list lacks critical details required by RD21: no instrumental uncertainties stated for most equipment (scissors, test tube holder, heatproof mat, bunsen burner, matches), no sizes/capacities specified for equipment like beaker sizes, no exact quantities of materials, no specific chemical names for substances, and no molarities of solutions. The method mentions items not in the equipment list (pencil). Only ruler and timer have uncertainties listed.
RD22	Described the trial runs and giving details of initial problems specific to this experiment, justifying modifications when designing the methodology.	1	The student clearly describes trial run problems where splints would extinguish before burning completely. They explain how they modified the method to only accept runs where complete burning occurred. This shows genuine re-evaluation during the design phase and confirms actual laboratory work was conducted, meeting the criterion's requirements.
RD23	3rd person, past tense, step-by-step method to carry out the investigation.	1	The methodology is written in third person past tense (e.g., 'Use a ruler to measure' is imperative but acceptable in methodologies), presented in clear numbered steps 1-8, and follows a logical sequence from preparation through execution. While some steps use imperative mood rather than pure past tense, this is standard for methodology sections and the student has made a genuine attempt to present a step-by-step method.
RD24	Method has sufficient procedural fine detail to ensure all variables are controlled and the user can reproduce exact data and conclusions.	1	The method provides specific procedural details including exact splint lengths (2-16cm in 2cm intervals), cutting procedure, ignition method, timing protocol, and clear criteria for valid trials. While some aspects could be more detailed (e.g., exact holding angle), the method contains sufficient detail for another person to reproduce the experiment and obtain similar data, meeting the criterion's requirement.
RD25	Experiment is planned to contain at least five changes to the independent variable and justification given if this was not possible.	1	The student clearly states 8 changes to the independent variable (2, 4, 6, 8, 10, 12, 14, 16 cm) in the methodology section. This exceeds the required minimum of five changes. The experiment was successfully executed with all 8 values, so no justification for fewer changes was needed.
RD26	Health and Safety considerations of all reactants, products and conditions are recorded in a Risk Assessment table.	0	The student provides a general health and safety discussion but does not present a formal Risk Assessment table listing specific reactants, products, and conditions with their corresponding hazards and safety measures. While CLEAPSS references are mentioned, they are not organized in the required table format that matches each chemical/condition with its specific risks and precautions.
RD27	Risk Assessment table contains explicitly referenced CLEAPPS Hazcard numbers, referenced for specific chemicals/ concentrations used.	1	The student has explicitly referenced CLEAPSS Hazcards (HC021 for Carbon monoxide and carbon, HC045b for Hydrocarbons) in the Health and Safety Requirements section. While the Risk Assessment is integrated into the safety section rather than in a separate table, the CLEAPSS references are clearly stated and the concentrations/chemicals used (wooden splints, methane gas) are addressed in the safety discussion.
RD28	Risk Assessment table contains explicitly referenced CLEAPPS Hazcard numbers, referenced for specific disposal of materials used or produced.	1	The student references CLEAPSS Hazcards HC021 and HC045b in the Risk Assessment section. While the disposal methods aren't explicitly detailed with specific Hazcard numbers, the report includes a clear disposal section for wood ash products with proper cooling and metal container disposal instructions. This demonstrates adequate consideration of disposal procedures linked to the CLEAPSS references provided.

Analysis (41 criteria)

Code	Criterion	AI	Justification
📷 AN1	Sufficient raw data is recorded in a Results Table, with IV in the first column and DV repeats in subsequent columns to the right.	1	The raw data table clearly shows IV (Length of splint) in the first column and DV (Burning Time) measurements in subsequent columns to the right (Try1 through Try7). Units are properly stated (cm for length with ±0.05, and s for time with ±0.01). The table format meets the traditional requirement of IV in first vertical column with repeated DV measurements in columns to the right.
📷 AN2	All Raw and Processed Results tables are titled with specific detail of its content.	1	The student has titled all their data tables with specific detail. Examples include 'Raw data table from the Investigation to monitor splint length vs burning time', 'Uncertainty in Repeats value from average', 'Data for producing Min/Max Trendlines', etc. Each table clearly indicates what data it contains, meeting the criterion requirements.
📷 AN3	Data table column headings include 'Measurable' units.	0	Max retries exceeded
📷 AN4	Data table column headings include Instrumental Uncertainties.	1	The data tables clearly show instrumental uncertainties in the column headings. The first table shows 'Length of splint (cm) +/- 0.05' for the independent variable, and subsequent tables maintain this uncertainty value. The dependent variable 'Burning Time (s) +/- 0.01' also includes instrumental uncertainty. These are appropriate absolute values for the measuring instruments used (ruler and digital timer).
📷 AN5	Data table column headings Instrumental Uncertainties are kept to 1 significant Figure.	0	Could not parse API response
📷 AN6	Data tables are formatted adequately, making it easy to read. Running the table over page breaks, very small font and very narrow column sizes are a f	1	The data tables are well-formatted with clear headers, readable font size, appropriate column widths, and no tables split across pages. The tables use consistent formatting with color-coding for clarity (green for averages, different colors for different data types). All columns and rows are clearly labeled with units and descriptions. The formatting enhances readability and makes data interpretation straightforward.
AN7	All Instrumental Uncertainties from measuring devices are justified. (Analogue = Half the smallest readable digit, Digital = Smallest Readable digit,	1	The student provides clear justification for both instrumental uncertainties: ruler uncertainty of ±0.05cm explained as 'half the smallest digit' for an analogue device (smallest increment 0.1cm), and timer uncertainty of ±0.01s explained as 'the smallest readable digit on the mobile phone digital timer'. Both explanations correctly follow the standard rules for analogue and digital instruments.
📷 AN8	The Decimal Points of raw and processed data are consistent with Instrumental Uncertainties on measurements	1	The raw data table shows burning times with 2 decimal places (e.g., 11.76, 15.55) consistent with the timer's instrumental uncertainty of ±0.01s. The splint lengths are shown as whole numbers (2.00, 4.00) with the stated ruler uncertainty of ±0.05cm. The processed data (averages like 18.18, 26.63) maintains the same decimal precision. All decimal places align appropriately with the stated instrumental uncertainties throughout the report.
AN9	Qualitative observations Before, During, and After are recorded that will assist with interpretation.	1	The student provides qualitative observations for all three phases: Before (splint color, Bunsen flame appearance), During (ignition time ~3-5s, bright yellow flame, no smoke, varying burn rates, occasional extinguishing), and After (smoke rising from burnt splint). These observations are specific, descriptive, and relevant to interpreting results, including identifying uncontrolled variables like varying burn rates and premature extinguishing.
📷 AN10	Qualitative observations are backed up by photographic evidence of the experiment	1	The student provides photographic evidence of the experiment - Image 1 shows a burning wooden splint, and Image 2 shows the experimental apparatus with labeled components (wooden splint, Bunsen burner, timer). These photographs directly support the qualitative observations described in the text about the yellow/orange flame color and experimental setup. The images clearly depict the actual experiment being conducted.
AN11	Attempts are made to repeat measurements, until they are within the Instrumental Uncertainty limits set out by the apparatus.	1	The student explicitly states 'Repeats were attempted but due to time restraints then this was not possible to repeat them often enough to get the precision within the uncertainty of the apparatus.' This shows clear attempts were made to repeat measurements, even though they acknowledge not achieving the ideal of staying within instrumental uncertainty. The key criterion asks for 'attempts' which is satisfied.
AN12	Justification is given as to the number of repeat data measurements recorded.	1	The student provides explicit justification for the number of repeats in the AN11/AN12 section, stating 'Repeats were attempted but due to time restraints then this was not possible to repeat them often enough to get the precision within the uncertainty of the apparatus.' This directly addresses why they stopped collecting more repeat measurements - insufficient laboratory time - which the criterion specifically recognizes as a valid reason for IB students.
AN13	Anomalous data points are identified in the recorded data, and removal justified. [No stdv mathematical requirement].	1	The student identifies anomalous data points (outliers) in AN11-AN12 and justifies keeping them to highlight uncertainties and process min/max gradients. They explicitly state 'Outliers were identified visually, not through use of 2 x standard deviations, as this was deemed unnecessary complexity.' While they chose to keep the outliers for pedagogical reasons, they still identified them and provided justification, meeting the criterion's requirement.
AN14	If the experiment requires any processing through additional equations, then any necessary calculations in order to process data are complete and with	1	The student directly measures length of splint (IV) and burning time (DV), establishing a simple relationship without need for additional equations. The experiment examines how splint length affects burning time - both variables are directly measurable. No processing equations are required to calculate the dependent variable from raw data. The criterion explicitly states to award 1 if no additional equations are necessary.
AN15	The specific 'First' chosen change in IV Value is stated, for which the subsequent raw DV data will be used to calculate the Mean Average DV in a Work	1	The student clearly states in AN15 that they will use data for the 2cm change of splint length as their working example for calculating the mean average. This is explicitly written as 'A mean average including worked example, using data for the 2cm change of the splint length will be used as the working example'. The 2cm value is the first IV value in their raw data table, meeting the criterion's requirement.
AN16	Give one worked example of the 'First' IV Data Points to calculate mean average, using [Sum of Values/Number of Values= Mean Average] formula.	1	The student provides a worked example for calculating the mean average of the 2cm splint data points. They show: (11.76+15.55+20.22+13.02+21.28+26.06+19.40)/7 = 18.18s. While the formula isn't written exactly as 'Sum of Values/Number of Values = Mean Average', the calculation demonstrates all required steps: summing values, counting data points (7), and dividing to get the mean (18.18s).
AN17	Give one worked example to calculate the Uncertainty in Repeats is calculated from the 'First IV' Repeated Data Points data using [(Max-min)/2] formul	1	The student provides a clear worked example of uncertainty calculation using the (max-min)/2 formula under 'AN16 AN17'. They show: maximum value (26.06), minimum value (11.76), subtraction (26.06-11.76), division by 2, and final result (+/- 7.15). The calculation is correctly executed with all steps shown. The student even goes beyond requirements by providing an alternative method.
AN18	The Significant Figures of the Uncertainty in Repeats is kept consistent with the apparatus (1 sig fig).	1	The student consistently reports uncertainty in repeats with 1 significant figure throughout the document. Examples include: '+/- 7.9' (from +/- 7.89), '+/- 6 s/cm (1 sig fig)', '+/- 100% (1 sig fig)', and '+/- 0.6% (1 sig fig)'. The student explicitly states '(1 sig fig)' multiple times when reporting uncertainties, demonstrating consistent adherence to the criterion requirement.
AN19	Calculate a Mean Average % Instrumental Uncertainty from both IV and DV data using the following formula: [Instrumental uncertainty/Mean change in IV	1	The student correctly calculates mean average % instrumental uncertainty for both IV and DV. IV (ruler): average length = 9.00cm, uncertainty = ±0.05cm, calculation: (0.05/9.00)×100 = ±0.56%. DV (timer): average time = 50.51s, uncertainty = ±0.01s, calculation: (0.01/50.51)×100 = ±0.02%. The calculations follow the required formula and are clearly presented with proper values.
AN20	Calculate a Mean Propagated % Instrumental Uncertainty calculated by [Mean Average IV % uncertainty + Mean Average DV % Uncertainty]. Addition of all	1	The student provides a clear worked example of propagated uncertainty calculation under 'Propagating Uncertainties calculations' section. They calculate mean IV % uncertainty (0.56%) and mean DV % uncertainty (0.02%), then explicitly add them: 0.56%+0.02% = ±0.58%, rounded to ±0.6%. The calculation correctly uses only IV (ruler) and DV (timer) measuring devices, excluding controlled variables. All required elements are present.
AN21	Mean Propagated % Instrumental Uncertainty is calculated using the lowest numbers of Decimal Places on any of the different Measuring Device Instrumen	0	The student used 1 decimal place for mass (1.0g) and 1 decimal place for volume (5.0 cm³) in their propagated uncertainty calculation, which is correct. However, they calculated 0.56%+0.02% = ±0.58% using the original precise values (±0.05/9.00 and ±0.01/50.51), not the values rounded to the lowest decimal places. The criterion requires using the lowest number of decimal places throughout the calculation, not just in the example.
AN22	Mean Propagated % Instrumental Uncertainty is quoted to 1 significant Figure	1	The student clearly states 'Mean Propagated % uncertainty= +/- 0.6% (1 sig fig)' in the AN27-AN30 section. They show the calculation: 0.56%+0.02% = +/- 0.58%, then correctly round to 1 significant figure as +/- 0.6%. The calculation method is explained with worked examples for both length and time uncertainties.
📷 AN23	An appropriate sized, scatter graph.	1	The graph is appropriately sized and fills the page well. While there is some empty space in the lower left quadrant below the trendline, the scale is reasonable given the data range (0-18cm for x-axis, 0-200s for y-axis). The data points are clearly visible with error bars, and the graph effectively displays the relationship between variables without being too small to read or overwhelming other content.
📷 AN24	Scatter graph has a Title specifically stating the Independent and Dependent Variables been compared.	1	The scatter graph clearly shows a title at the top that explicitly states both variables: 'A graph to show splint length vs Burning time'. The independent variable (splint length) and dependent variable (Burning time) are both specifically named in the title, meeting the criterion requirements.
📷 AN25	Scatter graph contains major grid lines.	1	The scatter graph clearly shows major grid lines on both axes. The graph displays a grid pattern with continuous lines at regular intervals (visible at 2.00, 4.00, 6.00, etc. on x-axis and 20.00, 40.00, 60.00, etc. on y-axis). These grid lines are prominent and allow easy reference to the data values, meeting the criterion requirement.
📷 AN26	Scatter graph contains labelled IV vs DV axis labels.	0	Could not parse API response
📷 AN27	Scatter graph contains IV vs DV 'Measurable' axis units.	1	The scatter graph clearly shows the independent variable (splint length) on the x-axis with units in cm and the dependent variable (burning time) on the y-axis with units in seconds. Both axes are properly labeled with measurable units as required by the criterion.
📷 AN28	Scatter graph contains IV vs DV axis Instrumental Uncertainty values.	0	Max retries exceeded
📷 AN29	Scatter graph contains uses crosses to plot data points.	1	The scatter graph clearly shows X-shaped crosses marking each data point. Looking at the graph image, all data points are plotted with distinct X marks (crosses) rather than dots or other symbols. The graph title even mentions 'Uncertainty bars' and the X-shaped crosses are visible at each data point with error bars extending from them.
📷 AN30	A scatter graph trendline gradient equation shows the Final Relationship is given.	0	Max retries exceeded
📷 AN31	Scatter graph trendline has a R2 value given.	1	The scatter graph clearly shows an R² value of 0.9182 displayed next to the trendline equation. The graph title explicitly states it includes R² value. The student also references this R² value in their conclusion as 0.91. The criterion only requires that an R² value be given on the scatter graph with the trendline, which is clearly met.
📷 AN32	Horizontal 'Uncertainty bars' for IV are added to the scatter graph, using the IV Instrumental Uncertainty, to graphically show the actual values of t	1	The graph clearly shows horizontal uncertainty bars on the x-axis for the independent variable (splint length). The student explicitly states 'Uncertainty bars' for both IV and DV are added to the scatter graph to graphically show the actual values of the Uncertainty in Repeats' and explains that they used actual maximum and minimum data points which may give uncertainty bars of different sizes. The horizontal bars are visible on the graph at each data point.
📷 AN33	Vertical 'Uncertainty bars' for DV are added to the scatter graph to graphically show the calculated values of the Uncertainty in Repeats. Any changes	1	The graph clearly shows vertical uncertainty bars for the dependent variable (burning time). The bars are visible extending vertically from each data point, with varying sizes as explained in the text. The student justifies using actual max/min data points rather than (max-min)/2 formula, explaining why bars are different sizes. This justification directly relates to the representation of uncertainty as required.
📷 AN34	A Maximium gradient trendline is calculated from the lowest vertical uncertainty bar and highest horizontal uncertainty bar on the first data point, t	1	The graph clearly shows three distinct trendlines: a central best-fit line and two additional lines representing maximum and minimum gradients. The orange/yellow line appears to be the maximum gradient line (connecting appropriate uncertainty extremes), and the blue line appears to be the minimum gradient line. All three trendlines have their equations displayed on the graph (y = 10.993x - 10.785, y = 6.2355x + 0.4295, y = 0.1079x + 26.28).
📷 AN35	A Minimum gradient trendline is calculated from the highest vertical uncertainty bar and lowest horizontal uncertainty bar on the first data point, to	0	Max retries exceeded
📷 AN36	Trendline equations for the Maximum and Minimum gradient trendlines are shown on the graph.	0	Could not parse API response
AN37	Uncertainty in Final Relationship is calculated by [(Maximum gradient value-minimum gradient value)/2 = Uncertainty in Final Relationship] formula.	1	The student clearly calculates the uncertainty in final relationship using the required formula. They show maximum gradient (10.99), minimum gradient (-0.11), apply the formula (10.99-(-0.11))/2 = +/-5.5 s/cm, and also demonstrate the alternative method using actual data (choosing the larger value of +/-6.09 s/cm). The calculation is complete with all values clearly presented.
AN38	State Uncertainty in Final Relationship units, using [Y axis units/X axis units] formula.	1	The student states the uncertainty in final relationship as '+6.20 +/- 6 s/cm' which correctly uses the format of [Y axis units/X axis units]. The Y-axis is time (seconds) and X-axis is length (cm), giving s/cm units. The uncertainty calculation is shown: (10.99-0.11)/2 = ±5.5 s/cm, with the actual max/min method yielding ±6.09 s/cm, rounded to ±6 s/cm.
AN39	State Uncertainty in Final Relationship to 1 Significant Figure	1	The student clearly states the uncertainty in the final relationship to 1 significant figure: '+6.20 +/- 6 s/cm (1 sig fig)'. This is shown in the Analysis section under AN25-AN26, where they calculate the uncertainty using max/min data (6.09), then round it to 1 significant figure (6). The criterion is satisfied.
AN40	Convert Uncertainty in Final Relationship into %Uncertainty in Final Relationship using the [Uncertainty in Final Relationship/Final Relationship grad	1	The student correctly converts uncertainty to percentage uncertainty using the exact formula specified. They show the calculation: (6.09 / 6.20) x 100 = +/- 98%, then round to 100% (1 sig fig). The formula is applied step-by-step with clear identification of the uncertainty value (6.09) and final relationship value (6.20) from their data. The result is expressed as a percentage with appropriate precision.
AN41	State %Uncertainty in Final Relationship to 1 Signficant Figure	1	The student explicitly states the percentage uncertainty in the final relationship as '+/- 98%' and rounds it to '+/- 100% (1 sig fig)'. The calculation is shown: '(6.09 / 6.20) x 100 = +/- 98%'. Both the calculated value and the 1 significant figure version are clearly presented in the report.

Conclusion (9 criteria)

Code	Criterion	AI	Justification
CO1	The research question is answered by describing the IV-DV relationship gradient trend.	1	The student clearly describes the IV-DV relationship in the conclusion section, stating 'The averaged data suggest that as the length of the splint increases, the burning time also increases at +6.20 s/cm' and 'The positive gradient of +6.20 s/cm would seem to confirm my initial hypothesis... showing a strong positive, linear relationship.' This directly answers the research question by describing the positive linear trend between splint length and burning time.
CO2	The IV-DV relationship gradient equation is explicitly stated.	1	The student explicitly states the IV-DV relationship gradient equation in the conclusion section: 'The averaged data suggest that as the length of the splint increases, the burning time also increases at +6.20 s/cm'. This clearly shows the mathematical relationship between the independent variable (length in cm) and dependent variable (burning time in seconds) with the gradient value of 6.20 s/cm.
CO3	The IV-DV relationship gradient units are quoted in the conclusion.	1	The conclusion explicitly states the gradient as '+6.20 s/cm' multiple times, clearly showing both the numerical value and the units (seconds per centimeter). This gradient represents the relationship between splint length (IV) and burning time (DV), with appropriate units for time per length.
CO4	Comment on gradient R2 value in terms of strength of correlation. (weak <0.3, moderate 0.3-0.7, strong >0.7)	1	The student explicitly states the R² value (0.91) and correctly categorizes it as 'a strong correlation' which aligns with the >0.7 threshold for strong correlation. While the discussion could be more detailed about linking R² to reliability, the core requirements are met: stating the value, interpreting it, and categorizing the correlation strength correctly.
CO5	Accuracy of relationship is justified based on cited research of a similar area of study.	1	The student accurately describes the combustion relationship of wood and provides justification by citing relevant research ('Is Fuel Reduction Burning the Answer?') about forest fires and fuel doubling. The citation is properly formatted in MLA style and is relevant but different enough from the lab investigation to avoid plagiarism concerns. The student acknowledges differences between forest fires and laboratory conditions.
CO6	Hypothesis is re-stated and compared with final results and commented on in terms of trend and speculation as to the underlying chemistry causing this	1	The student restates the hypothesis in the CO6 section ('positive gradient of +6.20 s/cm would seem to confirm my initial hypothesis'), compares it with results (confirms positive linear relationship), and comments on the underlying chemistry ('more fuel must take longer to burn in a combustion reaction'). Though brief, it addresses all required elements: restatement, comparison, and speculation on chemistry.
CO7	% Uncertainty in Final Relationship from min-max trendlines is re-stated in the Conclusion.	1	The student explicitly restates the % uncertainty in final relationship value in the conclusion section (CO7): '98%' and later 'The Uncertainty in Final Relationship is very large at 98%'. This matches the calculated value from the analysis section where they determined 98% (rounded to 100%). The criterion is satisfied as the % uncertainty from min-max trendlines is clearly re-stated in the conclusion.
CO8	The magnitude of the %Uncertainty in Final Relationship gradient to potentially change the trend direction and invalidate the conclusion is commented	1	The student explicitly discusses how the 98% uncertainty in the final relationship gradient could potentially change the trend direction, stating 'The trendline seems almost surely to be still increasing, despite a small possibility that the trendline could indeed be horizontal (or very unlikely negative)'. This directly addresses how the uncertainty magnitude could invalidate the conclusion about the relationship between splint length and burning time.
CO9	Any concerns making the result invalid have been commented on. If the experiment has no obvious problems in its logic, leading to an invalid conclusio	1	The student explicitly comments on concerns that could make results invalid in the CO7-CO9 section, discussing uncontrolled variables, lack of methodological detail, and how rate of burning was not controlled. They acknowledge these could affect validity but conclude results are still valid due to strong R² value (0.91). The experiment's logic is sound despite identified weaknesses.

Evaluation (13 criteria)

Code	Criterion	AI	Justification
EV1	Strengths of methodology are highlighted, based on trial run modifications if possible.	1	The student clearly identifies strengths of their methodology, specifically mentioning the removal of partial burn data from trial runs (EV1) which would reduce uncertainty and make trends more certain. They explain how this modification improved data reliability. While brief, this addresses the criterion requirement of highlighting methodological strengths based on trial run modifications.
EV2	Equipment choice is evaluated to reduce Instrumental Uncertainties.	0	While the student mentions instrumental uncertainties are insignificant compared to methodological effects (EV2), they don't analyze how equipment contributes to combined uncertainties, identify which equipment has the largest instrumental uncertainty, or suggest alternative equipment with lower uncertainties. The evaluation focuses on methodological improvements rather than equipment choices to reduce instrumental uncertainties as required by the criterion.
EV3	Comparison of a Mean Propagated % Instrumental Uncertainty vs % Uncertainty in Final Relationship from gradients is stated using [Mean Average IV % un	1	The student clearly compares Mean Propagated % uncertainty (0.6%) vs % Gradient Uncertainty in Repeats (100%) in EV3, explicitly stating the relationship is 'two orders of magnitude larger.' They explain why the propagated uncertainty is much smaller than the final relationship uncertainty and connect this to methodological issues and outliers, fulfilling the criterion's requirement for comparison and discussion of magnitude differences.
EV4	Major Methodological improvements suggested to improve accuracy and validity by identifying and removing specific Systematic errors that have become a	1	The student identifies a major systematic error in EV4: lack of consistency in burning technique where 'some experimenters may try to burn the splint as fast as possible... Other experimenters may try to keep the burning as long as possible.' This is addressed with specific methodological improvements in EV12 including standardized holding technique, specific angle, and detailed burning instructions to remove these systematic errors that affect validity.
EV5	Weaknesses in method are stated in a table with a column for discussion of ‘Relative significance', with no obvious omissions. Minor = negligible eff	1	The student provides a comprehensive table listing weaknesses in method with a dedicated 'Impact and Relative Significance' column that qualitatively assesses each weakness using terms like Minor, Moderate, and Major. The table covers burning technique, flame extinguishment, subjective timing, and ignition method issues. Each weakness is clearly described with its error type, significance assessment, and potential solutions.
EV6	Weaknesses in method are stated in a table with a column for ‘Error Type' and are correctly identified, with Systematic Errors only producing errors o	1	The student has a clear table under 'Weaknesses in method' (EV5-EV8) with an 'Error Type' column. Systematic errors are correctly identified as producing consistent effects (e.g., 'burning rate would not be controlled' for burning technique), and random errors are correctly identified as producing variable effects (e.g., 'flame went out before all fuel burnt, on occasion'). The table meets all requirements.
EV7	Weaknesses in method are stated in a table with a column for ‘Problems'.	1	The student presents a clear table under 'Weaknesses in method' (EV5-EV8) with a column explicitly labeled 'Problems with current method'. The table identifies four specific methodological issues (burning technique, flame extinguishing, subjective ignition timing, and ignition method) with detailed explanations of each problem. This meets the criterion requirement for a table with a 'Problems' column containing clearly articulated weaknesses.
EV8	Weaknesses in method are stated in a table with a column for ‘Suggested Solutions'.	1	The student presents a clear table under 'Weaknesses in method' with four rows identifying problems (burning technique, flame extinction, subjective ignition timing, and ignition method). Each weakness has a corresponding 'Potential solutions' column with specific, actionable improvements for future experiments (e.g., 'keep vertical during burning', 'set time held in flame', 'only allow 1cm of splint...in flame').
EV9	Improvements suggest increased Repeated data points and removal of outliers to reduce Random Errors, causing smaller Uncertainty in Repeats.	0	The student states they kept outliers in the data and mentions increasing repeats would reduce uncertainty, but fails to explain the two distinct processes: (1) how additional data points lead to lower standard deviation, and (2) how this narrower range then allows identification of outliers. The report lacks specific methodology for outlier removal and doesn't demonstrate understanding that outliers can only be identified after establishing the narrower data range.
EV10	Improvements suggested to expand the IV data range are made.	1	The student explicitly suggests expanding the IV range to 20-30cm splints under 'EV10 Increasing the Data Range'. They provide specific values (20-30cm) beyond the original 2-16cm range, explain this would help establish the trend better, and consider practicability issues like purchasing availability, rigidity, and safety concerns with longer splints bending. This meets all criterion requirements.
EV11	Improvements suggested to narrow the IV data intervals are made.	1	The student explicitly suggests reducing IV intervals from 2cm to 0.5cm increments (e.g., 2.0, 2.5, 3.0, 3.5cm) in EV11, which provides specific actual values. They justify this would create more data points for a more consistent trendline. While they don't explicitly link this to revealing linear/non-linear relationships, they do connect it to improving trendline validity and consistency, meeting the criterion's core requirement.
EV12	Minor Methodological improvements suggested to improve on the accuracy of the experiment.	1	The student provides multiple specific methodological improvements: defining exact holding method (leave 1cm at end), specifying burning angle (vertical), standardizing ignition time (5 seconds), limiting initial ignition area (1cm marked), and providing detailed instructions like 'burn at only one end' and 'attempt to burn as long as possible'. These address identified systematic errors and would increase accuracy by ensuring consistency across trials.
EV13	Suggested extension investigations, that will adapt and improve this specific investigation are proposed.	1	The student proposes a specific extension investigation: 'Investigating how the thickness on the rate of combustion of wood might give an insight into the effect of whether forest fires will spread faster if saplings are younger and the branches are thinner.' This builds directly on the original experiment by testing a new variable (thickness) while maintaining the combustion concept, and provides clear justification for how it would enhance understanding of wood combustion rates.