Printer Friendly

A Comparison of Teacher and Student Functional Behavior Assessment Interview Information from Low-risk and High-risk Classrooms.


To understand and prevent problem behavior in schools, educators must increase the efficiency and accuracy of the information that they use to develop effective and relevant behavior intervention plans. The purpose of this study was to examine the usefulness of information secured from student and teacher interviews. Participants included eight middle school students who displayed substantially more problem behaviors in one general education classroom (high-risk classroom) than another general education classroom (low-risk classroom), and teachers from each of those classrooms. Teacher and student interview data were assessed for agreement on information obtained about behaviors, response classes, setting events, antecedents, and consequences. The results indicated that students were able to provide useful and reliable information in the functional assessment interview process. Moderate to high agreement was obtained between target students and teachers with direct knowledge of their problem behaviors in hig h-risk classrooms. Lower agreement was found between those same students and their teachers in low-risk classrooms. Implications for practitioners and researchers are discussed.

In the last decade, incidents of aggressive and antisocial behavior have risen steadily, and approximately 3-5% of the student population will display chronic problem behaviors at school (Sprague, Sugai, Horner, & Walker, 1999; Sugai & Horner, 1994, 1999). Although small, this group of students requires significant amounts of time and effort from school personnel (Sprague, et al., 1999; Sugai & Horner, 1994, 1999; Walker, Colvin, & Ramsey, 1995; Walker et al., 1996). Additionally, as the number of students with aggressive, acting-out, and/or antisocial behavior increases, more specialized educational resources and services are being required and greater involvement of general education is needed (Walker et al., 1995).

Given these increasing discipline, violence prevention, school safety, and behavior support-related needs, along with the emphasis on adopting a proactive response to those needs, several issues are of priority. First, schools must be able to access and use relevant, efficient, and effective strategies to address the increasing and intensifying discipline needs of their students, in particular those with severe and chronic challenging behaviors.

A second issue of major import for schools involves legal considerations with respect to the functional behavior assessment (FBA) process. With the passage of amendments to the Individuals with Disabilities Education Act of 1997 (IDEA 1997), behavior intervention plans for students with problem behaviors must be based on information determined by a functional behavior assessment (FBA). FBA is a process that entails examining the environmental context in which an individual's behaviors occur. Specifically, this process provides information regarding his or her observable behaviors as well as associated triggering antecedents, maintaining consequences, and potential setting events. An FBA results in the development of a behavior intervention plan (BIP) that is based on the environmental features that predict occurrences and nonoccurrences of problem behavior.

The third critical issue involves generalizing the FBA approach across a broader range of student ability levels, including general education students. Historically, FBA procedures were investigated with students with severe disabilities in order to eliminate a range of problem behaviors (e.g., Broussard & Northup, 1995; Cooper et al., 1992; Lalli, Browder, Mace, & Brown, 1993). The research base regarding the FBA process for students with mild disabilities or no documented disabilities who display behaviors that impede their learning or the learning of others, however, is relatively limited (Blakeslee, Sugai, & Gurba, 1994; Sugai, Horner, & Sprague, 1999). Fortunately, the conceptual logic and fundamental processes are clear (Homer, 1994; Iwata et al., 1994; Sugai, Lewis-Palmer, & Hagan, 1998) and a research base regarding the use of FBA with higher functioning students, including those with emotional and behavioral problems, is growing (Dunlap, White, Vera, Wilson, & Panacek, 1996; Kern, Dunlap, Clark, & Ch ilds, 1994; Lee, Sugai, & Homer, 1999; Lewis & Sugai, 1993, 1996a, 1996b; Lewis-Palmer, 1998; Todd, Homer, & Sugai, 1999; Umbreit, 1995). For example, Dunlap et al. (1996) used FBA strategies to examine variables affecting behavior and to guide the development of interventions to support students with emotional and behavioral disorders (EBD). Their research focused on modifying academic tasks and implementing these modifications within the student's public school general education classrooms. Certain aspects of the FBA and BIP processes, however, still remain to be validated (Fox, Conroy, & Heckaman, 1998).

A variety of methods have been used to collect FBA information: archival review, checklists and routine analysis, interviews, and direct observation. Interviews are a common indirect method for obtaining FBA information about problem behaviors, typically with teachers, staff members, and/or parents. More recently, this method also has included the student (Clarke et al., 1995; Dunlap, Foster-Johnson, Clark, Kern & Childs, 1995; Dunlap et al., 1996; Ervin, DuPaul, Kern, & Friman, 1998; Kern et al., 1994; Nippe, Lewis-Palmer & Sprague, 1998; Lewis-Palmer, Sugai, & Horner, 1999; Reed, Thomas, Sprague, & Homer, 1997; Umbreit, 1995). Students can provide valuable information about preferences, academic difficulties, distractions, conflicts with peers, etc., which may not be readily apparent or available to teachers, parents, and staff members. Kern, et al. (1994) included students in the FBA process, and found that most elementary students were able to contribute valuable information to the development of hypothes is statements. However, they also stated that more research is needed to explore the impact of student's disability, age, verbal skills, etc. on their ability to participate successfully in the FBA process.

Although several studies have included the use of student interviews to develop interventions designed to reduce problem behavior, only a few have tested systematically the validity of student interviews for the FBA process. Reed et al. (1997) developed the Student-Guided Functional Assessment Interview and assessed agreement between students' and teachers' reports. They conducted interviews with ten public school students between the ages of 10-13 years and seven of their teachers. The results showed high agreement on reported antecedent and consequent events, and lower agreement on intervention plan recommendations and setting events.

In a study with three middle school students who displayed disruptive behaviors, Nippe et al. (1998) replicated and expanded research by Reed et al. (1997) by comparing interview information to direct observation data. Findings supported results reported by Reed et al. (1997) and provided preliminary support for agreement between student and teacher information and direct observations.

Most recently, Lewis-Palmer, Sugai, and Homer (1999) extended these studies to include interventions based on informant information and direct observation data. The study included 12 middle school students who displayed severe problem behaviors and their teachers. The results of their FBA data replicated previous findings (Nippe et al., 1998; Reed et al., 1997). Teachers and students agreed on response classes (84%), antecedents (88%), consequences (88%), and setting events (50%). Student information compared to direct observation data resulted in high agreement on response classes (100%), antecedents (100%) and consequences (81%). In addition, students and teachers were able to identify whose attention maintained the problem behavior, and students provided detailed information about behaviors that occurred outside the teachers' classroom (e.g., theft, smoking, skipping class). Overall, the results supported previous research and demonstrated that results from teacher and student FBA interviews are consistent with each other as well as direct observations.

The purpose of the current study was to extend the findings from research by Reed et al. (1997), Nippe et al. (1998), and Lewis-Palmer et al. (1999) by asking students to provide differentiated information across classroom environments and to investigate the validity of student-based FBA information. The following questions were addressed:

1. To what degree do teachers and students agree on FBA interview information (i.e., behaviors, response classes, setting events, antecedents, and consequences) within and between high-risk and low-risk classrooms?

2. Can students provide differential information across high-risk and low-risk classrooms?

3. Do teachers report similar information regarding response classes that occur across high-risk and low-risk classrooms?



Three Pacific Northwest suburban middle schools (6th - 8th grades) with student enrollments ranging from 459-575 participated in the study. General education classrooms were selected in which content area courses (e.g., science, math, language arts, reading, history) were offered.


As part of a larger study (Hagan, 1998), teachers and administrators in each school were asked to identify male students who were exhibiting high rates of severe problem behaviors (e.g., non-compliance, classroom disruptions, and/or aggression) in content-area classes (high-risk classrooms). Next, teachers were asked to identify a content-area class for each student where low rates of problem behavior typically occurred (low-risk classrooms). Direct observations were conducted in high-risk and low-risk content area classes to confirm the reported of differential rates of problem behavior. Student participants included one in 6th grade, five in 7th, and one in 8th grade. One student had a special education label (LD), but all observations occurred in general education classrooms. For more information regarding student participants' academic performance, see Hagan (1998).

Problem behavior rates were considered different between two classrooms if (a) the highest percent of intervals from one classroom never exceeded the lowest percentage m another, (b) the average percent of intervals of problem behaviors in one classroom was at least double the average percentage in another, and (c) adding twenty five percentage points to the average percent of problem behavior from one classroom did not equal or exceed the average percent of problem behavior in the other classroom. Observations were based on a 15-second momentary time sampling procedure by which student's behavior was coded as either (a) on-task, (b) off-task, or (c) off-task and engaging in additional problem behaviors

Observation sessions lasted 40-50 minutes, and observers alternated between observing teachers and students every two minutes. Therefore, observations of student behavior included 20-25 minutes of each session. Four observations were made in each high-risk and low-risk classroom for each student. In addition, observations in high-risk and low-risk classrooms occurred on the same days.

Based on these observation data and criteria, eight triads of students (n=8) and teachers (n=16) were selected to participate in the study. Each triad was comprised of a target student, his teacher from the high-risk classroom (high rates of problem behaviors), and his teacher from the low-risk classroom (relatively low rates of problem behaviors). For these eight triads, additional analysis was conducted involving the FBA information collected during the primary study.


Two teacher FBA interviews (high-risk and low-risk classrooms) and one student FBA interview were completed for each target student. Interviews were approximately 30-45 minutes in length, conducted in private locations (e.g.,conference room), and used to identify (a) problem behaviors, (b) response classes, (c) setting events, (d) antecedents, (e) maintaining consequences, and (f) hypothesis statement. Questions were open-ended and presented in a structured interview format. However, if interviewees were unsure or hesitant about their responses, they were given suggestions, for example, "Were academic tasks too hard, long, difficult, and/or boring?" If participants remained unsure after suggestions were given, their response was listed as none know/identified and considered a disagreement when compared to other sources of information. For maintaining consequences interviewees were provided with a forced choice format: (a) obtain social (peer or adult), (b) obtain tangible or activity, (c) escape social (peer or adult), (d) escape task/demand/activity, or (e) sensory stimulation.

Teacher interviews. Each teacher from high-risk and low-risk classrooms was interviewed individually about a student's classroom behaviors using a modified version of the Brief Functional Assessment Interview (adapted from O'Neill et al., 1997). Teachers were asked to (a) define problem behaviors, (b) describe the classroom contexts and antecedents and consequence events that were thought to be associated with those problem behaviors, and (c) generate a hypothesis statement about the functions that each student's problem behaviors served within their classroom context.

Student interviews. Students were interviewed independently using an adapted version of the Student-Guided Functional Assessment Interview (O'Neill et al., 1997). Students were asked about high-risk and low-risk classrooms separately but within same interview session, and provided information about (a) problem behaviors, (b) response classes, (c) antecedents and setting events, (d) consequences, (e) academic and social strengths, (f) level (rating) of problem behavior across school day, and (g) hypothesis statement.

Data Analysis

Interview results were compiled for all students and categorized by behaviors, setting events, antecedents, and maintaining consequences. Responses were taken verbatim from all interviews to control for research bias in interpretation. Responses to questions from student and teachers were compared by categories and independently rated by two individuals. For example, if a student identified "horsing around with friends" as a problem behavior, this wording was listed in the behavior category verbatim and used for agreement assessments. If a corresponding teacher identified that student's problem behavior as "disruptive," this also was listed verbatim. The raters then determined whether those descriptions were identifying the same problem behavior. Based on this information, hypothesis statements were generated for each student by the researchers. These hypothesis statements described conditions under which problem behaviors were most likely to occur and possible maintaining functions. Behaviors identified by teachers and students (using their original wording) during interviews are presented in Table 1.

Agreement was calculated for behaviors identified by students and teachers in high-risk and low-risk classrooms. Next, comparisons of identified behaviors were made between high-risk and low-risk teachers. Percentage of agreement was calculated by dividing the total number of agreements divided by the total number of agreements plus disagreements.

During the interview process, the interviewers organized the problem behaviors reported by students or teachers into response classes. First, the interviewee was asked to identify behaviors that were often part of an escalating chain or occurred under similar circumstances. Interviewees also were asked whether those behaviors were typically maintained by the same consequence. In other words, when similar maintaining functions for behaviors were identified by students and teachers, and those behaviors were reported as occurring together or as part of an escalating chain, the behaviors were combined to form response classes.

Agreement was assessed for all response classes identified by the students and teachers in high-risk and low-risk classrooms. Agreement was calculated by dividing the number of agreements by the total number of response classes identified by both participants. Agreement by setting events, antecedents, and consequences was calculated for response classes only where student and teacher agreement was found. When students and teachers disagreed on response classes, no further comparisons were made.

Percent agreement for setting events was calculated by dividing the number of agreements between students and teachers by the total number of student-identified setting events. Because students and teachers were asked about setting events by classroom and not by specific response classes, setting events calculations were not linked to prior response class agreement.

Student interviews were assessed to identify response classes reported in both classrooms. First, response classes with teacher and student agreement in high-risk classrooms were identified. Next, student interviews were used to determine which of those response classes were reported by students across classrooms. The resulting response classes were analyzed separately by classroom and provided the basis for comparison between teacher interviews across classrooms. Antecedent and consequence events that were identified during interviews are presented in Tables 2 and 3, respectively.

Inter-rater Agreement

A second rater independently determined whether teachers and students agreed on interview comparisons for behaviors and response classes. In other words, they compared the interview reports of (a) each student and his high-risk teacher, (b) each student and his low-risk teacher, and (c) information from corresponding high-risk and low-risk classroom teachers. Simple agreement was calculated by dividing the number of agreements by the number of agreements plus number of disagreements, and multiplying by 100. Inter-rater agreement for behaviors was 88% for student to high-risk teacher, 93% for student to low-risk teacher, and 88% for teacher to teacher comparisons.

The same process was used to assess inter-rater agreement regarding response classes. For response classes, inter-rater agreement was 93% for student to high-risk teacher, 92% for student to low-risk teacher. Additionally, inter-rater agreement was calculated for response classes identified by students as present in both high-risk and low-risk classrooms and was 100%.


High-Risk Classroom: Student to Teacher

Teachers from high-risk classrooms nominated 43 different behaviors that were combined to form 14 response classes. Students identified 34 behaviors in their high-risk classrooms that were combined into l2 response classes. Students identified 79% of behaviors identified by teachers, and teachers identified 74% of behaviors identified by students.

Students and teachers in high-risk classrooms agreed on 79% (11/14) of the teacher-based response classes. Two of the three non-agreements occurred when teachers identified additional response classes that were not


identified by students. Using agreed upon response classes as the unit of comparison, student and teacher agreement in high-risk classrooms was 100% on antecedents and 91% (13/14) on consequences. Agreement on setting events was 21% (6/29).

Low-Risk Classroom: Student to Teacher

Teachers in low-risk classrooms identified a total of 17 behaviors that combined to form 12 response classes. Students identified 44 behaviors in the low-risk classrooms that combined to form nine response classes, Students identified 41% of behaviors identified by teachers, while teachers identified 31% of behaviors identified by students.

When student and teacher response classes were combined, 13 response classes were identified. Of those 13, students and teachers agreed on 46% (6/13). Five of the non-agreements were additional response classes identified by teachers and not students One additional response class was identified by students and not by teachers. Using agreed upon response classes, students and teachers agreed 31% (4/13) on antecedents and 46% (6/13) on consequence. Additionally, students and teachers agreed 40% (10/25) on setting events.

Students identified 14 response classes from either high-risk or low-risk classrooms. Of the 14 response classes, 43% (6 of 14) were identified as occurring in both classrooms (i.e., across classrooms). For these six response classes, low-risk classroom teachers and students had 67% (4/6) agreement on antecedents 67% (4/6) and 83% (5/6) agreement on consequences, as compared to agreement on all low-risk classroom response classes (31% and 46%, respectively).

Across Classrooms: Teacher to Teacher

A comparison of response classes reported by students as present in both classrooms revealed similarities to information provided by teachers. Teachers in high-risk and low-risk classrooms identified 43% (6/14) of the same setting events, 83% (5/6) of the same antecedents, and 100% of the same consequences.


The purpose of this study was to examine the usefulness of student information, especially with respect to interview information from high-risk and low-risk classrooms. The results support previous finding that students are a reliable source of information (Lewis-Palmer et al. 1999; Nippe et al. 1998; Reed et. al. 1997), and extended the current literature by indicating that students and teachers from high-risk classrooms agree more than students and teachers from low-risk classrooms. In addition, an analysis of the data suggests that students were able to offer comprehensive FBA information regarding specific classrooms. In other words, they discriminated between classrooms environments where they experienced more and relatively less difficulty and identified antecedent and consequence information during FBA interviews.

Previous research has identified a need to validate FBA strategies (Mace, 1994; Taylor & Romancszyk, 1994) and to determine which strategies are most efficient and effective in building intervention plans (Nelson, Roberts, Mathur, & Rutherford, 1999). Specifically, recommendations have included (a) determining the types of students who should be involved as information sources (e.g., communication skills, cognitive abilities, etc.) (Kern et al., 1995), (b) examining the impact of linking interview questions to classroom conditions (Reed et al., 1997), and (c) corroborating interview outcomes with data from direct observations (Lewis-Palmer, Sugai, & Homer, 1999; Nippe et al. 1998).

Results from the current study contributed to the growing support for the usefulness and accuracy of student-based FBA information. Specifically, students and teachers in high-risk classrooms agreed on reported response classes (79%), behaviors (78%), antecedents (100%), and consequences (91%). Similar to results from other studies (Lewis-Palmer et al., 1999; Nippe et al. 1998; Reed et al. 1997), agreement on setting events was low (21%).

Lewis-Palmer et al. (1999) recommended that further research be conducted to determine which teachers should participate in the FBA process. Specifically, how much knowledge or experience the teacher must have to provide accurate and useful information. The results from this study indicate that the selection of participants who are interviewed is important and must be done carefully. For example, students and teachers in low-risk classrooms had poor agreement across all FBA areas, suggesting that teachers who are observing problem behavior at higher rates have more information about environmental influences. Five non-agreements were response classes identified by the teacher and not the student, and could be due to several factors. First, the interview format for the teacher included a checklist of possible problem behaviors, which could bias teachers toward specific problem behaviors. Teachers often expressed that they had few problems with the target student, but still provided information about past or mi nor behaviors. Future research should focus on re-formatting interview items and questions to emphasize the development of operational definitions of behavior(s) and to improve the validity of the information. Second, the frequency and intensity of behaviors may have been so low that interactions between the teacher and the student were minimized. Consequently, the student would not view his or her behavior as a problem. Direct observation data should be used in the future to determine actual behavioral frequencies and intensities of in high-risk and low-risk classrooms.

When students were asked about low-risk and high-risk classrooms separately, they were able to discriminate between these classrooms and to provide detailed information regarding the behaviors and antecedent and consequence events. Students identified six response classes that occurred in both classrooms and that also were identified by their teachers. The remaining response classes were unique to one or the other classroom. Future research should examine the context and nature of problem behaviors that occur and are reported across classrooms. In particular, assessments should investigate whether commonly reported response classes have similar triggering antecedents or are affected similarly or differently by setting events. In addition, an examination should be conducted of the competing stimulus control features (e.g., curriculum demands, teacher requests, instructional design) that increase or decrease the likelihood of a behavioral occurrence within and across classrooms.

Several limitations should be noted when considering and applying findings from this study. First, caution should be exercised in extending the results of the study to students and teachers with characteristics that are different from those of the participants of this study. For example, the schools were all suburban and located in the Pacific Northwest, and teacher and students were in middle schools. Future research should focus on the inclusion of students from diverse populations, grade levels, and classrooms. Previous research has recommended investigating exactly what student characteristics are needed to improve the accuracy of information that is provided by students and teachers (Kern et al., 1995; Reed et al., 1997).

Second, the results must be viewed with caution because no direct observation data were collected to verify information provided by the informants. Future investigations should include direct observations and/or environmental manipulations (i.e., functional analyses) to validate hypothesis or summary statements. Finally, if information derived from student and teacher interviews is reliable, future research also should examine the kinds of behavior intervention plans that result, and whether these plans are more or less effective or efficient than other methods of deriving and developing interventions for students with severe problem behavior.

Future research also needs to examine sources of low agreement scores obtained from students and teachers regarding setting events. One possible solution is to modify and/or expand the interview questions to (a) provide a clear definition of setting events, (b) obtain more complete setting event information, (c) increase specificity by discussing setting event information in relation to response classes, or (d) provide follow-up questions that narrow the respondent's answers. Another solution might involve the identification and validation of other information sources for accessing setting event information (e.g., daily event logs, rating scales).

Recently, Nelson et al., (1999) expressed concern about including FBA procedures in educational policy without a foundation of research to support its effectiveness. These authors recommended that future research focus on types of information that might be most useful in developing behavior intervention plans that are manageable for educators. In addition, present special education requirements indicate that schools must conduct FAs on all students' with an Individualized Education Plan and who are pending a disciplinary action. This policy implies that educators need to be trained to conduct functional behavioral assessments and develop intervention plans. Research should focus on the identification and development of the most efficient and accurate sources of assessment practices for school staff.

In summary, the results of this study build on the present literature base by supporting previous research on the reliability of teacher-based and student-based FBA information. The results extend the previous findings by indicating that middle school students can discriminate verbally between classrooms contexts in which they are more and less behaviorally successful. Further, middle school students and their teachers can agree on the presence of problem behaviors as well as features of the problem context (i.e., antecedents and maintaining consequences), especially, in their high-risk classrooms.


Blakeslee, T., Sugai, G., & Gruba, J. (1994). A review of functional assessment use in data-based intervention studies. Journal of Behavioral Education, 4, 397-413.

Broussard C. D., & Northup, J. (1995). An approach to functional assessment and analysis of descriptive behavior in regular education classrooms. School Psychology Quarterly, 10,151-164.

Clarke, S., Dunlap, G., Foster-Johnson, L., Childs, K. E., Wilson, D., White, R., & Vera, A. (1995). Improving the conduct of students with behavioral disorders by incorporating student interests into curricular activities. Behavioral Disorders, 20, 221-237.

Cooper, L. J., Wacker, D. P., Thursby, D., Plagmann, L. A., Harding, J., Millard, T., & Derby, M. (1992). Analysis of the effects of task preference, task demands, and adult attention on child behavior in outpatient and classroom settings. Journal of Applied Behavior Analysis, 25,823-840.

Dunlap, G., Foster-Johnson, L., Clarke, S., Kern, L., & Childs, K. E. (1995). Modifying activities to produce functional outcomes: Effects on the disruptive behaviors of students with disabilities. Journal of the Association for Persons with Severe Handicaps, 20,248-258.

Dunlap G., White, R., Vera A., Wilson, D., & Panacek, L. (1996). The effects of multi-component, assessment-based curricular modifications on the classroom behavior of children with emotional and behavioral disorders. Journal of Behavioral Education, 6,481-500.

Ervin, R. A., DuPaul, G. J., Kern, L, & Friman, P. C. (1998). Classroom-based functional and adjunctive assessments: proactive approaches to intervention selection for adolescents with attention deficit hyperactivity disorder. Journal of Applied Behavior Analysis, 31,65-78.

Fox, J., Conroy, M., & Heckaman, K. (1998). Research issues in functional assessment of the challenging behaviors of students with emotional and behavioral disorders. Behavioral Disorders, 24, 26-33.

Hagan, S. L. (1998). An examination of classroom management procedures that support middle school students with severe and chronic problem behaviors. Unpublished doctoral dissertation, University of Oregon, Eugene.

Horner, R. H. (1994). Functional assessment: contributions and future directions. Journal of Applied Behavior Analysis, 27, 401-404.

Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., & Richman, G. S. (1994). Toward a functional analysis of self-injury. Journal of Applied Behavior Analysis, 27, 197-209.

Kern, L., Dunlap, G., Clarke, S., & Childs, K. E., (1994). Student-assisted functional assessment interview. Diagnostique, 19, 29-39.

Lalli, J. S., Browder, D. M., Mace, F. C., & Brown, D.K. (1993). Teacher use of descriptive data to implement interventions to decrease students' problem behaviors. Journal of Applied Behavior Analysis, 26, 227-233.

Lee, Y., Sugai, G., & Horner, R. (1999). Effect of component skill instruction on math performance and on-task, problem, and off-task behavior of students with emotional and behavioral disorders. Journal of Positive Behavioral Interventions, 1, 195-204.

Lewis, T., & Sugai, G. (1996a). Descriptive and experimental analysis of teacher and peer attention and the use of assessment-based intervention to improve the pro-social behavior of a student in a general education setting. Journal of Behavioral Education, 6,7-24.

Lewis, T. J., & Sugai, G. (1996b). Functional assessment of problem behavior: A pilot investigation of the comparative and interactive effects of teacher and peer social attention on students in general education settings. School Psychology Quarterly, 11, 1-19.

Lewis, T. J., & Sugai, G. (1993). Teaching communicative alternatives to socially withdrawn behavior: An investigation in maintaining treatment effects. Journal of Behavioral Education, 3, 61-75.

Lewis-Palmer, T. (1998). Using functional assessment strategies in regular classroom settings with students at-risk for school failure. Unpublished doctoral dissertation, University of Oregon, Eugene.

Lewis-Palmer, T., Sugai, G., & Horner, R. H. (1999). Using functional assessment strategies in regular classroom settings with students at-risk for school failure. Unpublished manuscript, University of Oregon.

Mace, F. C. (1994). The significance and future of functional analysis methodologies. Journal of Applied Behavior Analysis, 27, 385-392.

Nelson, J. R., Roberts, M. L., Mathur, S. R., & Rutherford, R. B. (1999). Has public policy exceed our knowledge base? A review of the functional behavior assessment literature. Behavioral Disorders, 24, 169-179.

Nippe, G. E., Lewis-Palmer, T., & Sprague, J. (1998). The student-directed functional assessment II: An analysis of congruence between student self-report, teacher report and direct observation. Unpublished manuscript, University of Oregon.

O'Neill, R. E., Horner, R. H., Albin, R. W., Sprague, J. R., Storey, K., & Newton, J. S. (1997). Functional assessment and program development for problem behavior: A practical handbook. Pacific Grove, CA: Brooks/Cole.

Reed, H., Thomas, E., Sprague, J. R., & Horner, R. H. (1997). The student guided functional assessment interview: An analysis of student and teacher agreement. Journal of Behavioral Education, 7, 33-49.

Sprague, J. R., Sugai, G., Horner, R., & Walker, H. M. (1999). Using office discipline referral data to evaluate school-wide discipline and violence prevention interventions. Oregon School Study Council Bulletin, 42(2), 1-18. College of Education, University of Oregon, Eugene.

Sugai, G., & Horner, R. H. (1999). Discipline and behavioral support: Preferred processes and practices. Effective School Practices, 17(4), 10-22.

Sugai, G., & Horner, R. (1994). Including students with severe behavior problems in general education settings: Assumptions, challenges, and solutions. In J. Marr, G. Sugai, & G.

Tindal (Eds.). The Oregon conference monograph (Vol. 6) (p. 102-120). Eugene, OR: University of Oregon.

Sugai, G., Horner, R. H., & Sprague, J. (1999). Functional assessment-based behavior support planning Research-to-practice-to-research. Behavioral Disorders, 24,223-227.

Sugai, G., Lewis-Palmer, T., & Hagan S. (1998). Using functional assessments to develop behavior support plans. Preventing School Failure, 43(1), 6-13.

Talyor, J. C., & Romanczyk, R. G. (1994). Generating hypotheses about the function of student problem behavior by observing teacher behavior. Journal of Applied Behavior Analysis, 27,251-265.

Todd, A. W., Horner, R. H., & Sugai, C. (1999). Self-monitoring and self-recruited praise: Effects on problem behavior, academic engagement, and work completion in a typical classroom. Journal of Positive Behavior Interventions, 1(2), 66-76, 122.

Umbreit, J. (1995). Functional assessment and intervention in a regular classroom setting for disruptive behavior of a student with attention deficit hyperactivity disorder. Behavioral Disorders, 20, 267-278.

Walker, H. M., Calvin, G., & Ramsey, E. (1995). Antisocial behavior in school: Strategies and best practices. Pacific Grove, CA: Brooks/Cole.

Walker, H. M., Homer, R. H., Sugai, G., Bullis, M., Sprague, J. R., Bricker, D., & Kaufman, M. J. (1996). Integrated approaches to preventing antisocial behavior patterns among school-age children and youth. Journal of Emotional and Behavioral Disorders, 4, 193-256.
Table 1

Problem Behaviors Identified During Student and Teacher Functional
Assessment Interviews

Student Teacher Student Student
 High-Risk High-Risk Low-Risk
 Classroom Classroom Classroom

 1 Talks out Talk outs Not working
 Teases peers Talk to peers
 Disrupts class Teasing
 Inattentive Disrupt Class
 2 Talking to peers Talk-outs Disruptive
 Disrupts class Disruptive Talking to peers
 Insubordination: Talking to peers
 Teases/ horseplay Walking around
 3 Notworking
 Insubordination Talking back Talking back
 inattentive Talking to peers Talking to peers
 Disrupts class Goofing off Goofing off
 Teases peers Not working Not working
 Not prepared
 Doesn't listen
 Runs around class
 Not working
 4 Inattentive Talking to peers Talking out
 Verbal Talking-out Disruptive
 harassment Not working Disrespectful
 Disrupts class
 Can't stay
 Not working
 5 Tardy Talking to peers Talking to peers
 Inattentive Disruptive Disruptive
 Disruptive Not following
 Noisy directions
 Fidgety Talking out
 Talk out Tardy
 6 Off- Tardy Nothing
 task/inattentive Talk-outs
 Disrupts class Disrespectful
 Talks constantly Disrupts Class
 Not working Profanity
 Tardy Not following
 Talk outs directions
 7 Off task Talldng to friends No Problems
 Engaged with Hyper
 peers Disrupts class
 Not working
 Easily distracted
 8 Disrupting class Insubordination Insubordination
 Horseplay Talking out Talking Out
 Inattentive Disrespectful Disrespectful
 Can be aggressive Disruptive Disruptive

Student Teacher

 1 Inattentive
 Teases peers

 2 Not working

 Not working

 4 Inattentive
 Disrupt class
 Cannot focus

 5 No problems

 6 Tardy

 7 Off task
 Easily distracted

 8 Not working
Table 2

Antecedent Agreement Between Students and Teachers in High-risk and
Low-Risk Classrooms and Comparisons Between Teachers for Generalized
Response Classes

Student Teacher Low Risk Student Teacher High-Risk
 Classroom Classroom

 2 Peer Encouragement Peer Encouragement Peer Encouragement
 Class Demands Class Demands Class Demands
 3 Class Demands Class Demands Class Demands
 Peer Teasing
 Teacher Reprimands
 4 Peer Encouragement Peer Encouragement Peer Encouragement
 Class Demands Teacher Reprimands Teacher Reprimands
 5a Peer Encouragement Peer Encouragement Peer Encouragement
 Class Demands Class Demands Class Demands
 Teacher Reprimands
 5b Class Demands Class Demands Class Demands
 8 None Identified Class Demands Class Demands
Table 3

Consequences [Agreement.sup.*] Between Students and Teachers in
High-Risk and Low-Risk Classrooms and Comparisons Between Teachers
for Generalized Response Classes

Student Teacher Low Risk Student Teacher High Risk
 Classroom Classroom

 2 Peer Attention Peer Attention Peer Attention
 Teacher Attention Teacher Attention
 3 Escapes Work Escapes Work Escapes Work
 Escapes Peer Teasing
 4 Peer Attention Peer Attention Peer Attention
 Teacher Attention Teacher Attention Teacher Attention
 5a Peer Attention Peer Attention Peer Attention
 Teacher Attention Teacher Attention Teacher Attention
 5b Escapes Work Escapes Work Escapes Work
 8 Escapes Work Escapes Work Escapes Work
COPYRIGHT 2001 West Virginia University Press, University of West Virginia
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2001 Gale, Cengage Learning. All rights reserved.

 Reader Opinion




Article Details
Printer friendly Cite/link Email Feedback
Author:Kinch, Carol; Lewis-Palmer, Teri; Hagan-Burke, Shanna; Sugai, George
Publication:Education & Treatment of Children
Geographic Code:1USA
Date:Nov 1, 2001
Previous Article:Evaluation of a Comprehensive Behavior Management Program to Improve School-Wide Positive Behavior Support.
Next Article:Translating Research into Effective Practice: The Effects of a Universal Staff and Student Intervention on Indicators of Discipline and School Safety.

Related Articles
High-Probability Requests and a Preferred Item as a Distractor: Increasing Successful Transitions in Children with Behavior Problems.
Translating Research into Effective Practice: The Effects of a Universal Staff and Student Intervention on Indicators of Discipline and School Safety.
The efficacy of function-based interventions for students with learning disabilities who exhibit escape-maintained problem behaviors: preliminary...
A truncated functional behavioral assessment procedure for children with disruptive classroom behaviors.
Training a general education teacher to apply functional assessment.
The effects of a peer-mediated positive behavior support program on socially appropriate classroom behavior.
A function-based intervention to decrease disruptive behavior and increase academic engagement.
From FBA to implementation: a look at what is actually being delivered.
Outcomes of functional assessment-based interventions for students with and at risk for emotional and behavioral disorders in a job-share setting.

Terms of use | Copyright © 2015 Farlex, Inc. | Feedback | For webmasters