In accordance with aim 7—that is, to “develop and apply the students’ information and communication technology skills in the study of science”—the use of information and communication technology (ICT) is encouraged in practical work throughout the course, whether the investigations are assessed using the IA criteria or otherwise.

Section A: use of ICT in assessment

Data-logging software may be used in experiments/investigations assessed using the IA criteria provided that the following principle is applied.

The student’s contribution to the experiment must be evident so that this alone can be assessed by the teacher. This student’s contribution can be in the selection of settings used by the data-logging and graphing equipment, or can be demonstrated in subsequent stages of the experiment.

(When data logging is used, raw data is defined as any data produced by software and extracted by the student from tables or graphs to be subsequently processed by the student.)

The following categories of experiments exemplify the application of this principle.

1. Data logging within a narrowly focused task

Data-logging software may be used to perform a traditional experiment in a new way.

Use of data-logging software is appropriate with respect to assessment if the student decides and inputs most of the relevant software settings. For example, an investigation could be set up to monitor a person’s breathing capacities while on an exercise bike using a spirometer sensor linked to a calculator-based data logger in which the student controls the level of exercise (speed or workload). Data-logging software that automatically determines the various settings and generates the data tables and graphs would be inappropriate with regard to assessment because the remaining student input required to investigate the breathing capacities would be minimal.

If the experiment is suitable for assessment the following guidelines must be followed for the DCP criterion.

Data collection and processing: aspect 1

Students may present raw data collected using data logging as long as they are responsible for the majority of software settings. The numerical raw data may be presented as a table, or, where a large amount of data has been generated, by graphical means. For example, the student should set the duration and rate of the sampling, and the generated data in the form of lists of measurements from the calculator or computer could be downloaded by the student into a computer spreadsheet. Students must organize the data correctly, for example, by means of table or graph titles, columns or graph axes labelled with units, indications of uncertainties, associated qualitative observations, and so on.

The number of decimal places used in recorded data should not exceed that expressed by the sensitivity of the instrument used. In the case of electronic probes used in data logging, students will be expected to record the sensitivity of the instrument.

Data collection and processing: aspects 2 and 3

Use of software for graph drawing is appropriate as long as the student is responsible for most of the decisions, such as:

• what to graph

• selection of quantities for axes

• appropriate units

• graph title

• appropriate scale

• how to graph, for example, linear graph line and not scatter.

In the example of the investigation to monitor breathing capacities, the student could process data by drawing a graph in the spreadsheet and measuring the breathing frequency from the data. By inspecting the graph or spreadsheet data, the maximal and minimal lung volume values could be identified and used to calculate the mean tidal volume at rest. The mean volume of air breathed per minute and recovery rate after exercise could also be calculated.

Statistical analysis carried out using calculators or calculations using spreadsheets are acceptable provided that the student selects the data to be processed and chooses the method of processing. In both cases, the student must show one example in the written text. For example, the student must quote the formula used by or entered into a calculator and define the terms used, or the student must write the formula used in a spreadsheet if it is not a standard part of the program’s menu of functions (for example, mean, standard deviation).

2. Data logging in an open-ended investigation

Data-logging software can enhance data collection and transform the sort of investigations possible. In this case fully automated data-logging software is appropriate with regard to assessment if it is used to enable a broader, complex investigation to be undertaken where students can develop a range of responses involving independent decision-making.

For example, a task could be set to investigate a factor that affects the rate of photosynthesis. If an oxygen sensor with automatic pre-programmed software to monitor the amount of oxygen released by an aquatic plant is used, the student could use the program to develop a broader, complex investigation, for example, comparing rate of photosynthesis in different species of aquatic plants at different light intensities.

Design: aspect 1

The student must state a focused problem/research question, for example: “What is the difference in the rate of photosynthesis at different light intensities, as measured by oxygen release, between Elodea canadensis and Myriophyllum spicatum?”

Relevant variables must also be identified, for example:

• independent variable—species of aquatic plants

• dependent variable—rate of oxygen production

• controlled variables—temperature, mass of plant, leaf surface area, time, light quality (wavelength).

Design: aspect 2

The student must design a method to monitor and control the variables (for example, a water bath for control of temperature), use an electronic balance to determine the mass of the plants, and use the same light source to control light quality.

Design: aspect 3

The student must design the method for the appropriate collection of sufficient raw data. The student would select the species of aquatic plants to use, and measure the amount of dissolved oxygen in the water using the oxygen sensor program. The student would also decide on the range and number of different light intensities and the number of experimental replicates.

Data collection and processing: aspect 1

Appropriate raw data would consist of the rates of photosynthesis derived from the graphs of the experimental runs generated by the program using the oxygen sensor. These rates of photosynthesis may be calculated by the student using a function on the program that analyses the graphs. This must be done without prompting by the teacher. The derived data for rates of photosynthesis could be annotated on a series of graphs or presented in a table with an appropriate title, column headings and units. Calculation of uncertainties would not be expected in this experiment. In addition, other important data should be recorded, for example, water temperature.

Data collection and processing: aspect 2

The graphs showing changes in oxygen concentration would not be assessed, as these would have been generated automatically by the pre-programmed software on the data logger, without input from the student. However, the rates of photosynthesis derived from these graphs could be plotted against light intensity for each species using graph-plotting software where student input is possible, for example, choice of type of graph, x and y axes, range and scale.

Data collection and processing: aspect 3

The student would generate graphs of light intensity versus rates of photosynthesis for each species, which should have clear titles, correctly labelled axes, a legend for the data of the different species of plants, and trend lines to reveal the degree of uncertainty.

Section B: use of ICT in non-assessed practical work

It is not necessary to use ICT in assessed investigations but, in order to carry out aim 7 in practice, students will be required to use each of the following software applications at least once during the course.

• Data logging in an experiment

• Software for graph plotting

• A spreadsheet for data processing

• A database

• Computer modelling/simulation

There are many examples of the above in the ICT resources for biology, chemistry and physics on the OCC.

Apart from sensors for data logging, all the other components involve software that is free and readily available on the Internet. As students only need to use data-logging software and sensors once in the course, class sets are not required.

The use of each of the above five ICT applications by students would be authenticated by means of entries in the students’ practical scheme of work, form 4/PSOW. For example, if a student used a spreadsheet in an investigation, this should be recorded on form 4/PSOW. Any other applications of ICT can also be recorded on form 4/PSOW.