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All charting of student performance is not precision teaching: a response to Koorland and Nelson.

All Charting of Student Performance is Not Precision Teaching: A Response to Koorland and Nelson

We think that Koorlant and Nelson protest too much! Marston (1988) did not suggest that educators "discard" the Standard Behavior Chart (SBC). It is unfortunate if Koorland and Nelson read this into the article. We believe there are many times and places where the SBC might well be used to display student growth and that the SBC is an important technological development in education.

Setting that issue aside, Koorland and Nelson raise several interesting issues that warrant comment. The primary issue they raise is the "importance of the predictive function," or whether the purpose of a slope line is to predict student performance. To Koorland and Nelson, "Marston's assertion that SBC proponents maintain that a significant characteristic of the chart if its better prediction of student performance is an overstatement"; and the authors go on to argue that the SBC was developed to meet several other needs. While we concede that the SBC can be used for a variety of purposes, we also think proponents of the SBC believe its predictive qualities are important for educational decision making. For example, in a chapter entitled "Projecting Celerations," Pennypacker, Koenig, and Lindsley (1972) state:

Because of the linearity of the celebration process displayed on the SBC, we can extend an observed celeration line to project future behavior frequencies. This enables us to: 1. Predict, within limits, when established behavioral goals will be reached, assuming relative constancy. 2. Evaluate changes in procedures against projections of outcomes had the procedures remained unchanged. (p. 78)

It is clear that active proponents of the SBC are interested in using it to predict student performance.

Though it is possible to make a variety of arguments about why any chart should be used to display student performance, we would argue that the essential value of charting repeated measurement data is to enable slope estimations--a metric unavailabe in traditional educational measurement. Slope estimations are then used to evaluate the future effects of current instruction and to decide whether to continue or change instruction on the basis of that prediction. We find it curious that Koorland and Nelson challenge Marston as overstating the importance of predicting from the trend line, yet report that the real reason for this line "is to provide a basis for timely program change decisions." What are "timely program changes" if they are not predictions that the child will be better at some point in the future if we make a change at this time?

Koorland and Nelson's second point is related to monitoring progress on individual educational plans (IEPs). They state, "Predicting a frequency weeks away, using many weeks of previously gathered data, in not a practice in which teachers typically engage." This statement reveals that Koorland and Nelson are evaluating Marston's paper from the perspective of precision teaching. Indeed, what they have to say about what teachers do is consistent with how teachers are trained to use data and charts in precision teaching. Ww understand that. For them to generalize that teachers do not gather data for several weeks, draw trend lines through the data, and make projections toward annual IEP goals is incorrect. In fact, many teachers in Minnesota and elsewhere currently do just that. The problem is not that we do not understand what precision teachers do, the problem is that Koorlant and Nelson do not understand that other approaches also involve repeated measurement and graphic data display to monitor pupil performance, predict future states, and make intervention decisions.

One alternative approach using repeated measurement and graphic data display emphasizes gathering data on long-range IEP goals. That approach is the formative evaluation model developed at the University of Minnesota Institute for Research on Learning Disabilities (Deno, 1987). That model uses frequent curriculum-based measurement (Deno, 1985) of student progress to create the time series data base for evaluating the effectiveness of program changes such as precision teaching. In fact, as part of our research and development activities in Minneapolis, teachers are taught how to use precision teaching as one alternative instructional approach for solving academic problems of students with mild disabilities (Deno, 1986). Perhaps a useful distinction might be that the data Koorland and Nelson are focusing on is descriptive of independent variables called "precision teaching," whereas we are more focused on measurement of the dependent variables that define the long-range outcomes toward which precision teaching is directed. Precision teaching proponents who wish to learn more about this formative evaluation model may consult Shinn (1989).

Finally, Koorland and Nelson raise the issue of the practical importance of the nine statistically significant differences out of 24 comparisons and state, "This hardly represents a clear empirical basis for discarding a measurement tool like the SBC." As we noted at the outset, Marston never stated, nor intended, that the SBC should be discarded. Clearly, however, the statistical analysis does not provide strong support for using the SBC rather than an equal-interval graph when long-range goal predictions are made from curriculum-based measurement data. Thus, the choice of what graph paper might be used can be made on other grounds. Because we find that communication with parents, teachers, social workers and other educators is facilitated with equal-interval charts without loss of precision, we prefer and recommend their use.

In closing, we do not consider the type of chart used in data analysis and display to be a major issue. Of more importance, in a world where single occasion, standardized norm-referenced testing is the modus operandi, is to show teachers how to repeatedly gather data on educationally relevant tasks and to evaluate the effectiveness of their intervention strategies. To this end, our energies are probably better spent training teachers on this alternative approach to measuring student performance rather than to invest undue time and energy into graph selection.

REFERENCES

Deno, S. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children, 52(3), 219-232.

Deno, S. L. (1986). Experimental teaching: An approach to improving student achievement, changing teacher beliefs, and identifying effective practices. Menneapolis: University of Minnesota.

Deno, S. L. (1987). Formative evaluation of individual student programs: A new role for school psychologists. School Psychology Review, 15(3), 348-374.

Marston, D. (1988). Measuring progress on IEPs: A comparison of graphic approaches. Exceptional Children, 55(1), 38-44.

Pennypacker, H. S., Koenig, C. H., & Lindsley, O. R. (1972). Handbook of the Standard Behavior Chart. Kansas City, KS: Precision Media.

Shinn, M. R. (Ed.). (1989). Curriculum-based measurement: Assessing special children. New York: The Guilford Press.

DOUGLAS MARSTON (CEC Chapter #298) is a School Psychologist in the Department of Special Education at Minneapolis Public Schools, Minneapolis, Minnesota; and STANLEY L. DENO (CEC Chapter #298) is a Professor in the Special Education Program at the University of Minnesota, Minneapolis.
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Title Annotation:Point/Counterpoint; reply to Koorland and Nelson's article in this issue
Author:Marston, Douglas; Deno, Stanley L.
Publication:Exceptional Children
Date:Sep 1, 1990
Words:1129
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