What do they know? Investigating students’ ability to analyse experimental data in secondary physics education

Figures & data

Figure 1. The PACKS model (Millar et al., 1994) relates the various phases in inquiry and the types of knowledge affecting the decisions made in these phases.

Table 1. Data analysis and interpretation skills for 15-year-olds in selected international curricula assessed in interview (I1–3) and practical (P1–3) probes.

Competence			Probe number						# of docs
Code	Description		I1	I2	I3	P1	P2	P3
C1	Visualise data graphically and use/interpret these					v	v	v	56
C2	Establish the correct trend line.			v	v	v	v	v	109
C3	Qualitatively describe and identify the main features of a dataset or trend		v		v		v		71
C4	Describe qualitative similarities and differences between datasets						v	v	32
C5	Draw a conclusion which is supported by the dataset			v	v	v		v	79
C6	Justify the conclusions and indicate restrictions concerning the data analysis and conclusions				v	v		v	29
C7	Estimate the value of a variable using interpolation or extrapolation			v		v	v		66

Figure 2. Graphs presented to interviewees in probes I1–3, respectively.

Figure 3. Practical probes P1–3 on analysis of data and drawing conclusions

Table 2. Level attainment criteria (where level ‘Novice’ is allocated if neither ‘Master’ nor ‘Intermediate’ apply).

Code	Competence	Master	Intermediate
C1	Visualise data graphically and use/interpret these	In the graph drawn independent variable is assigned to x-axis, dependent to y-axis axes are labelled data points are plotted (4) scale is drawn, sensible range chosen.	One aspect missing
C2	Establish the correct trend line.	In the trendline established is considered whether the origin is part of the dataset, is accounted for whether the data pattern is straight or curved (3) the drawn line passes as closely as possible to the data points	(1) or (2) ignored
C3	Qualitatively describe and identify the main features of a dataset or trend	Description includes I1: labels, starting point, 3 features of shape I3: labels, 3 regions P2: graph’s shape, technical specification (‘gradient’, ‘slope’), essential features clear enough to reproduce the graph	No more than two missing
C4	Describe qualitative similarities and differences between datasets	A correct qualitative comparison of shapes and gradients of graphs of different data sets is given	One comparison missing or incorrect
C5	Draw a conclusion which is supported by the dataset	All of the following are satisfied: the conclusion answers the research question, the conclusions is backed by the data, (3) the most extensive conclusion is drawn that fits the data.	Only (1) and (2) are satisfied
C6	Justify the conclusions and indicate restrictions concerning the data analysis and conclusions	Conclusions are actively supported though explicit backings, qualifiers, rebuttals and warrants. One at most is missing of: provides the reasoning through which the data support the claim; accounts for level of data accuracy; discusses limitations of data, analysis, claims (4) accounts for assumptions underlying conclusions	(1) and (2) or (3) are present.
C7	Estimate the value of a variable using interpolation or extrapolation	Predicted values accord with theoretical or teacher’s values. (2) Justification is given of the method.	Suitable method is found but not well applied.

Figure 4. Attainment levels per student pair in each competence (N = 51).

Figure 5. A representative graph from P2 (P2–3) with travelled distance displayed on the x-axis and the measured time on the y-axis. Scientific conventions (C1) are satisfied, the trend line is smooth, partly connecting the data points (C2).

Figure 6. A straight line is drawn in I2, disregarding the identified anomaly at t = 9 s. As the graph displays the motion of a ball, starting from rest, in a travelled distance versus time graph, the origin should be used as well.

Figure 7. In probe P1, students investigate how the swing time (y-axis) is affected by the length of the swing (x-axis). Some students combine a curved and a straight line to connect the last datum of initial dataset with the additional datum at l = 5,0 m, both indicated with arrows.

Millar, R., Lubben, F., Gott, R., & Duggan, S. (1994). Investigating in the school science laboratory: Conceptual and procedural knowledge and their influence on performance. Research Papers in Education, 9(2), 207–248. https://doi.org/10.1080/0267152940090205

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