Another component of the IEP that IDEA requires is specifying how the child's progress will be measured. This statement flows naturally out of the annual goals written for the child, which must be measurable. IEP teams may find it easier to address this component of the IEP by framing the discussion around specific questions. For example, the IEP team might ask itself these three questions:
- How will the child's progress be measured?
- When will the child's progress be measured?
- How well will the child need to perform in order to achieve his or her stated IEP goals (and, for some children, benchmarks or objectives)?
Characteristics of Effective Tracking Systems
Effective tracking systems should be accurate and efficient. Four characteristics of tracking systems include:
- They monitor progress toward IFSP goals;
- They show if the child needs to advance to the next level of the program;
- They indicate if the child is not making progress; and
- They show the effectiveness (or ineffectiveness) of the instructional strategies or methods.
Current literature stresses the importance of data collection in programs that serve children with special needs. The presence of an ongoing systematic data collection system has been cited as one indicator of a high quality program and has been identified as a key component in the listing of recommended educational practices. It is often necessary to break learning tasks into small parts for teaching and to plan carefully for skills to be practiced in a variety of settings to assure that children generalize them. These skills that are broken down and taught must be tracked to assure that if a child is making good progress that they can move ahead and if they are not, that they do not waste valuable time being frustrated by something that is either too difficult or not presented in a way that they can understand. In addition, the child may advance in such small increments that unless we collect fairly meticulous data, we may not see the progress. Therefore, data is a way to fine tune the learning process for children with disabilities. We need to view data as a tool; a means to an end, not an end in itself.
Three types of data: trial-by-trial, probe and anecdotal data.
Trial-by trial data is recorded on every trial of the targeted skill. Each time the child is asked to perform the skill a data point is recorded indicating whether or not the child could do the skill. For example, if a child is working on a transition routine and the routine occurs seven times during the day there would be seven data points collected. The advantages of trial-by-trial systems are that it gives the most information on child performance and gives the teacher information on each response the child makes at each step of the program. The major disadvantages of trial-by-trial systems are that it is time consuming and not always practical, especially on programs with a large number of trials or in group settings. Trial-by-trial data requires a large number of staff to implement on a continual basis.
Probe data is when a sample of data is collected that represents child performance. For example, a child may be working on the skill "make's choice" all day but data may be collected in only three settings during the day. The advantages of probe data systems are that it is more feasible in group settings, is more practical on programs with a large number of trials, and is more practical with a larger class size or limited staff. It also allows flexibility in data collection. Data may be collected on certain children or skills on certain days, or in several targeted settings. The main disadvantages of probe data systems are that it provides less information on which to base program decisions and the sample data may not accurately represent actual child performance. It may give the staff a more positive or negative impression of child performance than is true.
Anecdotal data is a narrative report where staff write down what the child did. The main advantage of anecdotal data is that it provides a lot of information on what the child did. The disadvantages of anecdotal data are that it is time consuming and it is difficult to make any program decisions based on the narrative. There may also be a tendency for staff to include subjective opinions or observations instead of simply reporting what they see.
The type of data that you will collect in your setting will depend on what information you are looking for.
- Correct and Incorrect (X and O's). The simplest type of data to collect. If the child responds correctly at the targeted level, an "X" is recorded. If the child did not perform the skill at the targeted level, an "O" is recorded. This type of data is easiest to record and update since there is little judgment involved.
- Levels of Assistance. As the child performs the skill, the staff records the level of assistance needed by the child to perform the skill (i.e., independent, prompt, model, gesture, indirect cue, etc.). This format requires more judgement and is more difficult to make program decisions.
- Anecdotal. The staff writes down in narrative form what they see the child doing. This type of data serves best when observing behaviors. It is also difficult to make program decisions based on narrative information.
- Frequency. Staff records how often a skill or behavior occurs. For example, the child has ten tantrums in a day.
- Duration. Staff records how long a skill or behavior occurs. For example, a child's tantrums last an average of 30 seconds in length.
- Percentage. Specifies how often a skill or behavior occurs out of how often it could occur. For example, the child was asked to do something ten times and did it two times or 20% of the time.
- Time sample. How often or does a skill or behavior occur in a specified time sample. This method is particularly practical for high frequency behaviors. For example, the child used 25 bad words in a ten minute time sample.
Tips for Data Collection
Child data should ideally be collected by a variety of classroom staff. This assists in the generalization of the skill and enhances the opportunities to collect more data. Data can be collected in a variety of settings throughout the day, not just during certain times of the day, during certain activities or in the same setting. And finally, make sure that enough data is collected to be useful.