This study explored relationships between special education personnel absences and demographic, policy, and practice variables to identify potential actions that could increase access to qualified personnel and continuity of instruction. Findings from 51 inclusion-oriented schools indicated that special educators and special education paraprofessionals were absent 12 days per year on average. Special educator absences were correlated with variables amenable to action by school leaders including special educator school density (i.e., ratio of special educators in full-time equivalents to total school enrollment) and special services concentration (i.e., ratio of special educators to special education paraprofessionals in full-time equivalents). Special education paraprofessional absences were not correlated with these variables. Implications for practice and suggestions for future research are discussed.
BettiniE. A.CrockettJ. B.BrownellM. T.MerrillK. L. (2016). Relationships between working conditions and special educators’ instruction. The Journal of Special Education, 50, 178–190. doi:10.1177/0022466916644425
2.
BillingsleyB. S. (2004). Special education teacher retention and attrition: A critical analysis of the research literature. The Journal of Special Education, 38, 39–55. doi:10.1177/00224669040380010401
3.
BillingsleyB. S. (2011). Factors influencing special education teacher quality and effectiveness. In KauffmanJ. M.HallahanD. P. (Eds.), Handbook of special education (pp. 391–405). New York, NY: Routledge.
BradleyS.GreenC.LeevesG. (2007). Worker absence and shirking: Evidence from matched teacher-school data. Labour Economics, 14, 319–334. doi:10.1016/j.labeco.2006.05.002
6.
BrightK. R.BooneS. A.GerbaC. P. (2010). Occurrence of bacteria and viruses on elementary classroom surfaces and the potential role of classroom hygiene in the spread of infectious diseases. The Journal of School Nursing, 26, 33–41. doi:10.1177/1059840509354383
7.
BrunstingN. C.SreckovicM. A.LaneK. L. (2014). Special education teacher burnout: A synthesis of research from 1979 to 2013. Education & Treatment of Children, 37, 681–711. doi:10.1353/etc.2014.0032
8.
BurrelloL. C.SailorW.Kleinhammer-TramillJ. (2013). Unifying educational systems: Leadership and policy perspectives. New York, NY: Routledge.
9.
ChristensonS. L.ReschlyA. L.WylieC. (2012). Handbook of research on student engagement. New York, NY: Springer.
10.
ClotfelterC. T.LaddH. F.VigdorJ. L. (2009). Are teacher absences worth worrying about in the United States?Education Finance and Policy, 4, 115–149. doi:10.1162/edfp.2009.4.2.115
11.
CohenJ. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
12.
DufloE.HannaR.RyanS. P. (2012). Incentives work: Getting teachers to come to school. The American Economic Review, 102, 1241–1278. doi:10.1257/aer.102.4.1241
13.
EhrenbergR. G.EhrenbergR. A.ReesD. I.EhrenbergE. L. (1991). School district leave policies, teacher absenteeism, and student achievement. The Journal of Human Resources, 26, 72–105. doi:10.2307/145717
14.
FaulF.ErdfelderE.BuchnerA.LangA. G. (2009). Statistical power analyses using G*Power 3.1. Behavior Research Methods, 41, 1149–1160. doi:10.3758/BRM.41.4.1149
15.
GarwoodJ. D.WertsM. G.VargheseC.GoseyL. (2017). Mixed-methods analysis of rural special educators’ role stressors, behavior management, and burnout. Rural Special Education Quarterly, 37, 30–43. doi:10.1177/8756870517745270
16.
GiangrecoM. F.BroerS. M.SuterJ. C. (2011). Guidelines for selecting alternatives to overreliance on paraprofessionals: Field-testing in inclusion-oriented schools. Remedial and Special Education, 32, 22–38. doi:10.1177/0741932509355951
17.
GiangrecoM. F.DoyleM. B.SuterJ. C. (2012). Constructively responding to requests for paraprofessionals: We keep asking the wrong questions. Remedial and Special Education, 33, 362–373. doi:10.1177/0741932511413472
18.
GiangrecoM. F.HurleyS. M.SuterJ. C. (2009). Personnel utilization and general class placement of students with disabilities: Ranges and ratios. Intellectual and Developmental Disabilities, 47, 53–56. doi:10.1352/2009.47:53-56 (Erratum published 2010, Intellectual and Developmental Disabilities, 48(1), ii. doi:10.1352/1934-9556-48.1.ii)
19.
GiangrecoM. F.SuterJ. C. (2015). Precarious or purposeful? Proactively building inclusive special education service delivery on solid ground. Inclusion, 3, 112–131. doi:10.1352/2326-6988-3.3.112
20.
GiangrecoM. F.SuterJ. C.HurleyS. M. (2013). Revisiting personnel utilization in inclusion-oriented schools. The Journal of Special Education, 47, 121–132. doi:10.1177/0022466911419015
21.
GottfriedM. A. (2010). Evaluating the relationship between student attendance and achievement in urban elementary and middle schools: An instrumental variables approach. American Educational Research Journal, 47, 434–465. doi:10.3102/0002831209350494
22.
HattieJ. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. New York, NY: Routledge.
23.
HerrmannM. A.RockoffJ. E. (2012). Worker absence and productivity: Evidence from teaching. Journal of Labor Economics, 30, 749–782. doi:10.1086/666537
MaslachC.LeiterM. P. (2005). Stress and burnout: The critical research. In CooperC. L. (Ed.), Handbook of stress medicine and health (pp. 155–168). Lancaster, UK: CRC Press.
MillerR. T. (2012). Teacher absence as a leading indicator of student achievement: New national data offer opportunity to examine cost of teacher absence relative to learning loss. Washington, DC: Center for American Progress. Retrieved from https://www.americanprogress.org/wp-content/uploads/2012/11/TeacherAbsence-6.pdf
29.
MillerR. T.MurnaneR. J.WillettJ. B. (2008). Do teacher absences impact student achievement? Longitudinal evidence from one urban school district. Educational Evaluation and Policy Analysis, 30, 181–200. doi:10.3102/0162373708318019
30.
MontoA. S.MaloshR. E.PetrieJ. G.ThompsonM. G.OhmitS. E. (2014). Frequency of acute respiratory illnesses and circulation of respiratory viruses in households with children over 3 surveillance seasons. The Journal of Infectious Disease, 210, 1792–1799.
31.
RobyD. (2013). Teacher attendance effects on student achievement: Research study of Ohio schools. Education, 134, 201–206.
32.
RussS.ChiangB.RylanceB. J.BongersJ. (2001). Caseload in special education: An integration of research findings. Exceptional Children, 67, 161–172. doi:10.1177/001440290106700202
33.
SimonN. S.JohnsonS. M. (2015). Teacher turnover in high-poverty schools: What we know and can do. Teachers College Record, 117(3), 1–36.
34.
SuterJ. C.GiangrecoM. F. (2009). Numbers that count: Exploring special education and paraprofessional service delivery in inclusion-oriented schools. The Journal of Special Education, 43, 81–93. doi:10.1177/0022466907313353
35.
TabachnickB. G.FidellL. S. (2013). Using multivariate statistics (6th ed.). Boston, MA: Pearson.
U.S. Department of Education. (2018a). Number and percent of students ages 6 through 21 served under IDEA, Part B, by educational environment and state: 2017-18 [Data file]. Washington, DC: Author. Retrieved from https://www2.ed.gov/programs/osepidea/618-data/static-tables/index.html
39.
U.S. Department of Education. (2018b). Public elementary/secondary school universe survey, 2010-11, 2011-12, 2012-13 [Data file]. Washington, DC: Author. Retrieved from https://nces.ed.gov/ccd/pubschuniv.asp
40.
VanVoorhisC. W.MorganB. L. (2007). Understanding power and rules of thumb for determining sample sizes. Tutorials in Quantitative Methods for Psychology, 3, 43–50. doi:10.20982/tqmp.03.2.p043
