Variables Predicting Physical Attacks on Public School Teachers

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Variables Predicting Physical Attacks on Public School Teachers in the United States with Data from the Schools and Staffing Survey: A Brief Report

 

 

ABSTRACT

 

In this brief report, data from the 2011-2012 Schools and Staffing Survey Teacher Questionnaire was analyzed through multiple regression to determine variables that were statistically significantly associated with physical attacks on public school teachers in the United States.  It was found that special education teachers were statistically significantly more likely to be physically attacked than general education teachers.  In addition, the number of students with Individualized Education Programs, the number of students with limited English proficiency, and the number of threats received were statistically significant predictors of the number of physical attacks on teachers.  The four variables accounted for 46 percent of the variance for teachers who reported being physically attacked in the preceding 12 months.

 

Key Words: Schools and Staffing Survey, School and Staffing Survey Teacher Questionnaire, student-on-teacher attacks, special education, school violence

 

 

INTRODUCTION

This brief report presents results of a preliminary investigation regarding physical attacks on public school teachers in the United States. It is not the intent of this paper to provide an in-depth review of the literature on student-on-teacher violence and a detailed analysis of the literature concerning attacks on school teachers is not presented in this paper. A thorough analyses of the literature concerning school violence can be found in Espelage, Anderman, Brown, Jones, Lane, McMahon, Reddy, & Reynolds (2013), McMahon, Martinez, Espelage, Rose, Reddy, Lane, Anderman, Reynolds, & Brown (2014), and Robers, Zhang, Morgan, and Musu-Gillette  (2015).

The purpose of this study was to examine variables related to student-on-teacher violence using data from a nationally representative sample of teachers in the United States. As Espelage et al., (2013) stated, contextual information about student-on-teacher assaults in the United States is lacking. The Indicators of School Crime and Safety Report showed that public school teachers were more likely to report being threatened and physically attacked that their private school peers (Robers et al., 2015). McMahon et al. (2014) found that a majority of teachers surveyed in the United States reported at least one type of harassment or victimization experience in the past year while others have suggested these experiences are under-reported (Levin et al., 2006).

Williams, Billingsley, and Banks (2018) found that special education teachers were statistically significantly more likely to be physically attacked than 11 other categories of public school teachers listed on the 2011-2012 Schools and Staffing Survey Teacher Questionnaire (SASS TQ). Williams and Ernst (2016) presented a descriptive analysis of demographic characteristics from the SASS TQ that were associated with higher levels of reported physical attacks on public school teachers. However, there have been no statistical analysis utilizing SASS TQ variables that predict student-on-teacher violence.  This investigation was launched to determine if there were statistically significant variables that may predict physical attacks on public school teachers in the United States based on data from the SASS TQ. 

 

RESEACH QUESTION

This study examined measures of physical attacks on public school teachers sin the United States using the following research question to guide the analysis:

  1. Which SASS TQ variables are statistically significant predictors of public school teachers who reported being physically attacked by students?

METHODOLOGY

Instrumentation

The Schools and Staffing Survey was conducted by the National Center for Education Statistics and administered by the Institute for Education Sciences (IES) on behalf of the U.S. Department of Education to collect extensive data on American elementary and secondary schools. This study analyzed data from the SASS TQ. The purpose of the SASS TQ was to obtain information about teachers, such as education and training, teaching assignment, certification, workload, and perceptions and attitudes about teaching to present a comprehensive picture of elementary and secondary education in the United States. The SASS TQ was designed to produce national, regional, and state estimates and is an excellent resource for analysis and reporting on elementary and secondary educational issues. (Tourkin, Thomas, Swaim, Cox, Parmer, Jackson, Cole, & Zhang, 2010, p. 1).

Participants

This study examined data from full and part-time public school teachers who completed the SASS TQ and responded affirmatively to the question asking whether they were physically attacked in the past 12 months.  This resulted in an unweighted sample size of 1,550 teachers and 197,360 teachers when weighted. 

Variables Analyzed

Table 1 includes the question or the variable name from the SASS TQ and coding for each variable incorporated in the study. The dependent variable in this study was physical attacks. The independent variables were threats, main teaching assignment, gender, race, students with individualized education plans (IEP) caseload, students with limited English proficiency (LEP), education level, years teaching experience,  certification route, certification status, school type and poverty level. 

Table 1. Variables used in the analysis.

Variable

SASS TQ Question*

Variable Type and Coding

Dependent Variable

Physical Attacks

In the past 12 months, how many times has a student FROM THIS SCHOOL physically attacked you? (SASS TQ, p. 38 )

Continuous

Independent Variables

Threats

In the past 12 months, how many times has a student FROM THIS SCHOOL threatened to injure you? (SASS TQ, p. 38)

Continuous

Main Teaching Assignment

The IES created ASSIGN03 to categorized teachers into their main teaching assignments.  ASSIGN03 consisted of 12 categories: 1) Early Childhood or General Elementary; 2) Special Education; 3) Arts or Music; 4) English and Language Arts; 5) ESL or Bilingual Education; 6) Foreign Language; 7) Health or Physical Education; 8) Mathematics; 9) Natural Science; 10) Social Science; 11) Vocational Career, or Technical Education, and 12) All Others.

Dichotomous

Special Education/General Education

Gender

Are you male or female? (SASS TQ, p. 42)

Dichotomous

Male/Female

Race

What is your race? The SASS TQ provided five choices for race: White, Black or African-American, Asian, Native Hawaiian or Other Pacific Islander, or American Indian or Alaska Native. (SASS TQ, p. 43 )

Dichotomous

White/Teachers of Color

IEP Caseload

Of all the students you teach at this school, how many have an Individualized Education Program (IEP) because they have disabilities or are special education students? (SASS TQ, p. 10 )

Continuous

LEP Caseload

Of all the students you teach at this school, how many are of limited-English proficiency or are English-language learners (ELLs)? (Students of limited-English proficiency [LEP] or English-language learners [ELLs] are those whose native or dominant language is other than English and who have sufficient difficulty speaking, reading, writing, or understanding the English language as to deny them the opportunity to learn successfully in an English-speaking-only classroom.) (SASS TQ, p. 10 )

Continuous

School Poverty

The IES created variable NSLAPP_S asked of schools that participated in the National School Lunch Program (NSLP), the percentage of their K–12 enrollment that was approved for free or reduced-price lunches.

Dichotomous

High/All other levels

75%  or greater free or reduced lunch was deemed high poverty

Certification Type

Which of the following describes the teaching certificate you currently hold that certifies you to teach in THIS state? (SASS TQ, p. 22 )

Dichotomous

Fully Certified/Not Fully Certified

Certification Route

Did you enter teaching through an alternative certification program?  (SASS TQ, p. 27 )

Dichotomous

Alternative/Traditional

Education Level

The IES created variable HIDEGR was used to determine the highest degree obtained.

Dichotomous

Master’s Degree or greater/Bachelor’s degree or less

Teacher Age

The IES created variable AGE_T was used to determine teacher age.

Continuous

Teaching Experience

The IES created variable TOTYREXP was used to determine years of teaching experience

Continuous

School Level

The IES created variable TLEV2_03 grouped teachers’ responses into either elementary or secondary as the instructional level.

Dichotomous

Elementary/Secondary

Note: * A detailed explanation of the variables in the SASS TQ can be found in Cox, Parmer, Strizek & Thomas (2016).

 

Procedure

This study consisted of a secondary analysis of the 2011-2012 SASS TQ restricted-use dataset. Specific NCES reporting protocols were followed and all findings were submitted to the IES for approval and authorization for release. The findings met reporting protocols for release to the general public.

Data were analyzed using STATA 13. Data were weighted using the Teacher Final Sampling Weight (TFNLWGT) variable and the SASS TQ supplied 88 replicate weight variables (TREPWT1-TREPWT88). The analysis utilized a balanced repeated replication procedure as required by IES. Multiple regression was used to examine the relationship between physical attacks and the selected teacher, school, and student demographic variables. Table 2 shows the values for the variables employed. Probability levels of .05 or less were deemed to statistically significant. The IES required that all degrees of freedom be rounded to the nearest 10. The results presented are based on weighted data.

 

Table 2. Descriptive statistics for regression variables.

Variable

Mean

SD

Minimum

Maximum

Physical Attacks

6.12

14.01

1

99

IEP Students

14.43

17.28

0

140

LEP Students

4.95

15.61

0

200

High Poverty

0.27

0.44

0

1

Certification Route

0.15

0.35

0

1

Certification Status

0.87

0.33

0

1

Special or General Education

0.46

0.49

0

1

School Level

0.56

0.49

0

1

Race

0.90

0.28

0

1

Gender

0.22

0.42

0

1

Threats

11.01

20.75

1

99

Age

40.09

11.78

21

71

Teaching Experience

11.46

9.33

1

47

RESULTS

The number of students with IEPs, the number of students with LEP, and number of threats received, and being a special education teacher were statistically significant predictors of the number of physical attacks on teachers in public schools in the United States. These variables explained a statistically significant proportion of variance in physical attacks, R2 = .465, F(10, 80) = 9.090, p < .001. Table 3 shows the coefficients for each variable in the model, t values, and p values.

Table 3. Regression coefficients, standard errors, t-values, and p-values

 Variable

Coefficient

BBR SE

t-value

p-value

IEP Students

-0.609

0.021

-2.85

0.005

LEP Students

0.024

0.010

2.30

0.024

High Poverty

-1.051

0.664

-1.58

0.117

Certification Route

-0.122

1.030

-0.12

0.906

Certification Status

-3.496

1.865

-1.87

0.064

Special or General Education

3.290

0.765

4.30

0.000

School Level

1.238

0.724

1.71

0.091

Race

0.526

0.789

0.67

0.507

Gender

0.582

0.899

0.65

0.519

Threats

0.388

0.057

6.80

0.000

Age

-0.037

0.031

-1.18

0.240

Teaching Experience

0.085

0.622

1.38

0.172

Note. BBR is balanced repeated replication. SE is standard error.

 

DISCUSSION

Violence and aggression toward public school teachers in the United States is a problematic issue.  Our findings indicated that special education teachers reported a statistically significantly higher number of physical attacks by students than their general education counterparts in the United States. These findings were consistent with prior research studies (Duhart, 2001; Wei et al., 2013; Williams, Billingsley, & Banks; 2018). It was interesting to note that the lower the number of students with IEPs, the more likely the teacher was to be assaulted. One possible explanation could be that these teachers work with students who are in a more restrictive environment such as self-contained classrooms where student to teacher to student ratios are typically low and the students typically have more severe behavioral issues. A higher number of students’ with LEPs was a statistically significant indicator of being physically attacked as was the number of times that a teacher was threatened. None of the other variables examined in this study produced statistically significant findings.

It is important to acknowledge the limitations of these findings. The results of this study are exploratory in nature and represented a set of variables that Williams and Ernst (2016) found to be associated with physical attacks in their descriptive analysis of teachers who reported being physically attacked within the preceding 12 months on the SASS TQ.  As the dependent variable was based on teacher self-reports, it is subject to errors of recall and bias. To reduce errors of recall, we only selected participants who indicated the frequency of physical attacks experienced from students in the previous 12 months. The variables examined in this analysis were not exhaustive in nature and other variables not included in this analysis might be statistically significant as well.  In addition, no interaction effects were examined in this study. Therefore, results should be interpreted with caution.

The results are also limited inasmuch as the SASS TQ data set does not provide information on the severity of students’ threats or attacks or the nature of the attacks.  As stated in Williams, Billingsley and Banks (2018) the SASS TQ offers no information about whether physical attacks were perpetrated by a single student or whether multiple students are involved. Since the SASS TQ is self-reported data, teacher perceptions of what constitutes a physical attack would likely vary across teachers and environments. We believe that these findings, despite the limitations, provide a sound basis for the continued investigation into student on teacher physical attacks using nationally representative data sets such as the SASS TQ to gain broader insight into issues related to school violence.

REFERENCES

  • Cox, S., Parmer, R., Strizek, G., and Thomas, T. (2016). Documentation for the 2011–12 Schools and Staffing Survey (NCES 2016-817). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved December 1, 2018 from http://nces.ed.gov/pubsearch.
  • Duhart, D. T. (2001). Violence in the Workplace, Bureau of Justice Statistics, 1993-99.
  • Espelage, D., Anderman, E. M., Brown, V. E., Jones, A., Lane, K. L., McMahon, S. D., . . . Reynolds, C. R. (2013). Understanding and preventing violence directed against teachers: Recommendations for a national research, practice, and policy agenda. American Psychologist, 68(2), 75-87. doi:10.1037/a0031307Levin, P.F., Martinez, M. Q., Walcott-McQuigg, J., Chen, S. P., Amman, M., & Guenette, C. (2006). Injuries associated with teacher assaults, AAOHN Journal, 54(5), 210-216.
  • McMahon, S. D., Martinez, A., Espelage, D. L., Rose, C., Reddy, L. A., Lane, K., … Brown, V. (2014). Violence directed against teachers: Results from a national survey. Psychology in the Schools51(7), 753-766. https://doi.org/10.1002/pits.21777
  • Robers, S., Zhang, A., Morgan, R.E., & Musu-Gillette, L. (2015). Indicators of School Crime and Safety: 2014 (NCES 2015-072/NCJ 248036). National Center for Education Statistics, U.S. Department of Education, and Bureau of Justice Statistics, Office of Justice Programs, U.S. Department of Justice. Washington, DC. 
  • Tourkin, S., Thomas, T., Swaim, N., Cox, S., Parmer, R., Jackson, B., Cole, C., & Zhang, B. (2010). Documentation for the 2007–08 Schools and Staffing Survey (NCES 2010-332). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved December 17, 2015 from http://nces.ed.gov/pubsearch
  • Wei, C., Gerberich, S. G., Alexander, B. H., Ryan, A. D., Nachreiner, N. M., & Mongin, S. J. (2013). Work-related violence against educators in Minnesota: Rates and risks based on hours exposed. Journal of Safety Research, 44(1), 73–85. http://doi.org/10.1016/j.jsr.2012.12.005
  • Williams, T. O.,Billingsley, B.B., & Banks, A. (2018). Student on teacher threats and assaults: A comparison of general and special education teachers. Journal of Special Education Leadership (31)1.
  • Williams Jr, T., & Ernst, J. (2016). Physical Attacks: An Analysis Of Teacher Characteristics Using The Schools and Staffing Survey. Contemporary Issues In Education Research (CIER), 9(3), 129-136. doi:10.19030/cier.v9i3.9708

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