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Teacher Biases in the Identification of Learning Disabilities: An Application of the LogisticMultilevel ModelAuthor(s): Georgios D. Sideridis, Faye Antoniou and Susana PadeliaduReviewed work(s):Source: Learning Disability Quarterly, Vol. 31, No. 4 (Fall, 2008), pp. 199-209Published by: Sage Publications, Inc.Stable URL: http://www.jstor.org/stable/25474652 .

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TEACHER BIASES IN THE IDENTIFICATIONOF LEARNING DISABILITIES: AN APPLICATIONOF THE LOGISTIC MULTILEVEL MODEL

Georgios D. Sideridis, Faye Antoniou, and Susana Padeliadu

Abstract. The purpose of the present studywas to investigatethe presence of teacher biases with regard to identification of students with learning disabilities (LD). Factors related to teachers'gender, age, and experience, along with children's gender, wereinvestigated. Results suggested that teacher gender is associatedwith biases with regard to identification of learning disabilities bya factor of 2:1. In other words, every child who is rated by femaleteachers as having an LD (who actually has LD) corresponds twochildren when rated by male teachers. Students' gender, on theother hand, did not differentially predict identification rates.Furthermore, teacher age and experience did not contribute significantly to student identification rates. The findings are discussedwith regard to policy mandates and classification schemes.

GEORGIOS D. SIDERIDIS, Ph.D., Department ofPsychology, University ofCrete.FAYE ANTONIOU, Ph.D., Department of Special Education, University ofThessaly.SUSANA PADELIADU, Ph.D., Department of Special Education, University ofThessaly.

Teachers' reports are often used to assess variousbehaviors in students with and without disabilities(Liljequist & Renk, 2007; Wingenfeld, Lackar, Gruber, &

Kline, 1998). Based on the premise that teachers arevery important adults in students' lives (Achenbach,1991), they are asked to contribute their unique perspective regarding various aspects of students' behaviorand achievement from preschool to college (Jensen,1980; Mashburn & Henry, 2004; Temp, 1971). Forexample, their ratings are used for identification purposes, classification, or just assessment. Regardless ofusage, these ratings carry information regarding teachers' predictions of how students will behave and achievein the future (Wood & Benton, 2005).Although there is evidence that general and special

education teachers often "miss" characteristics defining

a disability (Fox & Lent, 1996; Miller, Missiuna,Macnab, Malloy-Miller, & Polatajko, 2001), the importance of their ratings is not debated (Rosenthal &Jacobson, 1968; Rubovits & Maehr, 1973; Tenenbaum& Ruck, 2007), particularly because their estimationsare core predictors of students' placement (Podell &Soodak, 1993; Proctor & Prevatt, 2003).In the present study,we evaluated the role of teachersin identifying students with learning disabilities (LD)and examined the possible presence of bias on theirpart, including the moderating role of their personalcharacteristics. The term bias in this study refers to thesystematic difference in the ways by which teachersidentify learning disabilities and the factors related tothem. Those ways may affect teachers' assessment ofstudent performance.

Volume 31, Fall 2008 199

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Teachers as a Means of Identifying Students withDisabilitiesTeacher ratings are often used for identification of students suspected of having various disabilities. Teachers'involvement in the identification process of studentswith LD may now be greater than in the past, given theuse of the responsiveness-to-intervention (RTI)model ofidentification (Haager, Calhoon, & Linan-Thompson,2007; Kavale, Holdnack, & Mostert, 2006; Vaughn &Fuchs, 2003). As Kavale et al. (2006) pointed out, thedecision regarding identification is based on "vague'clinical' (i.e., teacher) judgements about the level ofresponse" (p. 120).

Judgments on the part of teachers are based on theirexpectations, perceptions, skills, and training. It isimperative for teachers to provide unbiased estimates oftheir students' ability, potential, and achievement.Several researchers have blamed teachers foroveridentification of learning disabilities (e.g., Wong, 1996).Others have suggested that the number of students withmental retardation has declined primarily because ofoveridentification of learning disabilities (MacMillan,Siperstein, & Gresham, 1996) (see also Keogh, 2005).Nevertheless, teacher ratings commonly assist inidentifying learning disabilities (e.g., The LearningDisability Diagnostic Inventory [LDDI]; Hammill, 1995)and attention deficit hyperactivity disorder (e.g.,Dupaul et al., 1998). A crucial question is how wellteachers accomplish their task, given the often discrepant findings between ratings and observational protocols (Lorenz, Melby, Conger, & Xu, 2007). Forexample, investigating the interrelationships betweenintelligence, academic achievement, and teacher estimations of that achievement, Svanum and Bringle(1982) found that teacher race or socioeconomic statusdid not affect the predictability of their ratings. Thisfindingwas replicated by Abidin and Robinson (2002).In contrast, Messe, Crano, Messe, and Rice (1979)reported that teacher ratings are biased by students'socioeconomic status. Social class and race seemedto be the main factors that influence these ratings(Knotek, 2003; McLeskey, Waldron, & Wornhoff, 1990;

Wehmeyer & Schwartz, 2001) aswell as placement (general vs. special education). That is, teachers in generaleducation settings appear to be less reliable when providing ratings related to LD than special educationteachers in special education settings (Vaughn & Fuchs,2003).

Chang and Demyan (2007) also studied the presenceofminority stereotypes in teacher ratings. The authorsnoted, "Contrary to expectation, therewas substantialcongruence in the degree of uniformity and favorableness of the stereotypic traits associated with blacks andwhites, with participants revealing both strong positive

and strong negative trait associations" (p. 91). Theauthors suggested the need for alternative methods ofassessment that may produce more valid ratings asstereotypical ratings can be catastrophic for students'educational experience. For example, teacher biaseshave been evident with minority groups (e.g., not calling on Asian-American students as often as they didCaucasian students; see Schneider & Lee, 1990).Rescorla et al. (2007) examined the consistency ofteacher-reported problems for students in 21 countries.Using a sample of 30,957 teachers, results indicated thatparticipating educators were fairly accurate in identifying students with behavioral and emotional problems.Internal consistency estimates averaged .90, and gendereffects (i.e., discrepancies or biases) ranged between 1%and 5%, which were pretty small and within the rangeof what constitutes reliable responding. Overall, theauthors concluded that teachers' reports were similarand consistent across countries, supporting a model ofteachers as valid raters of student behavior.

Another noteworthy finding is that parents' unwillingness to respond to questionnaires is associated withhigher bias on the part of teachers regarding the presence of social, emotional, attentional problems, and soforth, in their children (Stormark, Heiervang, Heimann,Lundervold, & Gillberg, 2008). In other words, thispattern of behavior from parents was linked to biasedestimates on the part of teachers.

Thus, research findings regarding the effectiveness ofteachers in rating students' attributes and behaviorshave been largely inconclusive, leaving unansweredsuch questions as: Which factors influence teachers'ratings? Are there specific teacher characteristics thatplay a prominent role in the validity of their ratings?Teachers' Characteristics as Predictors of TheirRatingsStudies have shown that teachers' characteristicsinfluence the validity of their ratings. For example,Rivard, Missiuna, Hanna, and Wishart (2007) investigated teachers' accuracy in identifying children withcoordination and behavioral problems. Using a sampleof 152 Canadian teachers and eight scenarios demonstrating different levels of motor and behavior problems, findings revealed differential effects due to teachergender. Specifically, female teachers were more likely tounderscore the severity of gross-motor problems; theopposite was true of male teachers.With regard to finemotor skills,males provided lower responses (were lessconcerned with) than female teachers, underscoring thesignificant interaction between teacher gender and typeofmotor problem with regard to degree of concern.An interaction between teacher gender and inappropriate student behavior was noted by Taylor, Gunter,

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and Slate (2001) using videotaped scenarios showingstudents acting out. They engaged 186 teachers to viewthe scenarios and to complete a rating scale on inappropriate behaviors. Teacher gender was once again themost influential factor on perceptions. Specifically,female teachers more often referred students with learning and behavioral problems; thiswas especially true forboys (Hopf & Hatzichristou, 1999). However, Hopf andHatzichristou found that female educators were moresensitive than theirmale counterparts. This effect couldbe attributed to the fact that female teachers may bemore expressive when interactingwith students (Meece,1987), although they pay more attention tomale thanto female students (Bellamy, 1994). Duffy,Warren, andWalsh (2001) reported that, regardless of the subjectmatter taught, female teachers interacted heavily withmale students compared to female students. Regardingbehavioral assessment, Ritter (1989) documented thatmale teachers were less accurate in identifying students'behavioral problems than female teachers, who showedmore sensitivity in distinguishing problem behaviors.In terms of teaching experience, Stevens, Quittner,and Abikoff (1998) reported that special educationteachers rated behavioral problems as less of a burdenthan did general education teachers. Further, accordingtoMashburn and Henry (2004), the higher the level ofthe teachers' education, themore accurate their ratings.In their study, preschool and kindergarten teachersrated children's skills to evaluate their readiness toattend school. Teachers with low levels of educationand training produced systematically inflated estimations and invalid ratings, and preschool teachers'ratings were less valid than kindergarten teachers' estimates. Previous studies also noted that more experienced elementary and secondary teachers aremore ableto handle students' challenging behaviors (Borg &Falzon, 1998; Kokkinos, Panayiotou, & Davazoglou,2005).The most common characteristic that teachers relyupon in making their judgments seems to be theirexperience (Brennan O'Neil & Liljequist, 2002). Thus,teacher experience, as reflected by years of teaching ingeneral education classrooms and age, comprised variables thatwere examined as predictors of classificationrate. Neither knowledge of the disorders nor professional experience and educational background seems toplay an important role in teachers' accuracy of attentionto deficit symptoms or oppositional defiant disorder(Stevens et al., 1998).There is also compelling evidence to suggest thatteachers' ethnicity does not influence their judgments(Abidin & Robinson, 2002). Judging the correctness ofthe referral estimations of almost 200 teachers withdiverse ethnic backgrounds, Tobias and his colleagues

(Tobias, Cole, Zibrin, & Bodlakova, 1982) found thatneither teachers' nor students' races were significantpredictors of biased estimations of student ability. Thiswas not the case, however, in another study by the sameresearchers (Tobias, Zibrin, & Menell, 1983) in whichthey concluded that teachers of a specific race estimatedstudents of their own race as less likely to have specialeducational needs than students of a different race. Inanother investigation, Tobias et al. (1983) found thatthis could be a result of teachers' experience in specialeducation settings.Attitudes towards the placement of students withlearning disabilities may affect not only teachers' estimations but also the quality of their interactions withthe students (Bender, Vail, & Scott, 1995). The quality ofthis interaction isnot predictive by teacher characteristics, such as perceptions of self-efficacy, knowledge ofspecial education (Bender, Vail, & Scott, 1995; Stevens,Quittner, & Abikoff, 1998), but mostly by students'gender (Anderson, 1997).Teachers Biases with Regard to Student GenderThere is also evidence suggesting thatmore boys thangirls are identified as having a disability (Anderson,1997; Shaywitz, Shaywitz, Fletcher, & Escobar, 1990).Regardless of whether the identification refers to neurological (e.g. autism, attention-deficit/hyperactivity,speech and language disorders) or learning and readingdisabilities, boys are more often referred for special education services than girls (Lieberman, Kantrowitz, &Flannery, 2005). The disproportionate placement interms of student gender has been so salient that teacherbiases have been suspected (Gillberg, 2003). For example, Rivard et al. (2007) observed differential effectswithregard to student gender. Specifically, teachers weremore concerned about gross-motor problems in boysthan in girls. Conversely, they were more concernedwith fine-motor problems in girls than in boys.Overidentification of boys has been replicated bothin younger groups of children and in diverse specialeducation fields. For example, Mashburn and Henry(2004) reported that preschool and kindergarten boyswere systematically rated lower by their teachers in academic and communication skills than same-age girls.Along the same lines, Berry, Shaywitz, and Shaywitz(1985) observed biases in the evaluation of studentswith attention deficit/hyperactivity disorder, favoringboys over girls.Nevertheless, teacher biases must bemore that an artifact of the methodology used (Flannery, Liederman,Daly, & Schultz, 2000). In an attempt to find outwhether the evaluation method plays a significant rolein that difference, Flynn and Rahbar (1994) reportedthat methods requiring subjective estimations lead to




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higher proportions of special education referrals forboys than forgirls, and that objective methods are moreaccurate thanmore subjective ones.Biases in teacher ratings favoring girls over boys havebeen reported previously (Helwig, Anderson, & Tindal,2001; Peterson & Baindbridge, 1999; Vogel, 1990;Wehmeyer & Schwartz, 2001). However, due toincreased awareness, this effectmay no longer be asprominent (Abidin & Robinson, 2002; Gillberg, 2003).For example, Goodman and Webb (2006) found noteacher gender bias in student referrals. Similarly,Helwig et al. noted that student gender was not a significant parameter in teachers' evaluations of their students' mathematics achievement. However, such bias inmathematics assessment does appear in later ages (e.g.,secondary education) (Wimer, Ridenour, Thomas, &Place, 2001).

Thus, the findings from this line of research suggestthat theremay be biases when teachers rate boys compared to girls based on false expectations or other reasons. Shaywitz (1996) supported the finding thatmalevulnerability to reading disabilities is a result of referraland identification biases and has no genetic basis. Suchbiases may be due to the fact that boys tend to havemore behavioral problems and attentional disordersthan girls,which lead teachers to overrefer boys and clinicians to overdiagnose them with learning disabilities(Mamlin & Harris, 1998; Naiden, 1976; Share & Silva,2003; Shaywitz et al., 1990; Ysseldyke et al., 1983).Apart from students' gender and behavior, whichseem to be themain factors that influence teacher eval

uations, Anderson (1997) concluded that students'placement also plays a significant role through themediating role of disruptive and inattentive behavior inthe general classroom (Leinhardt, Seewald, & Zigmond1982; Smart, Sanson, & Prior, 1996).The present study investigated the presence of teacherbiases with regard to identification of students with LD.More specifically, the studywas designed to answer thefollowing research questions in an attempt to furtherresolve current contradictory research findings:1.Does teachers' gender differentially affect their rat

ingswith regard to identification of LD?2. Are teachers' age and experience, in addition totheir gender, significant predictors of their studentratings?3. Does children's gender bias teacher ratings?

METHODParticipantsThe sample consisted of 246 Greek public schoolstudents, 33 with a diagnosis of LD and 213 typical students (125 boys, 121 girls). The students with LD wereidentified by a state multidisciplinary team of experts

and referred for special education services. The definition of the disorder inGreece is identical to that ofU.S.Department of Education currently used in the UnitedStates, identifying students as having LD when theydemonstrate a significant discrepancy between potential and achievement. Nineteen of the students with LDwere educated in inclusive general education classrooms. They were receiving special education services inaddition to their education intypical (general education) settings.The participating students were in grades 3 to 9 asfollows: grade 3 = 33 (16 girls, 17 boys), grade 4 = 39(17 girls, 22 boys), grade 5 = 39 (22 girls, 17 boys), grade6 = 36 (18 girls, 18 boys), grade 7 = 29 (13 girls, 16 boys),grade 8 = 30 (15 girls, 15 boys), and grade 9 = 40 (20girls, 20 boys). Two hundred and seventeen studentsspoke Greek as their native language; 29 were bilingual.Participating schools were selected by stratified sampling techniques in order to reflect the representativedemographic areas of Greece. One boy and one girlwereselected randomly from each class by excluding students who had a spoken language other than Greek astheirnative language or had not been attending a Greekschool since firstgrade.Student ratingswere completed by 98 teachers duringout-of-school hours, including 33 teachers of languagearts, 63 elementary school teachers, and 2 from inclusive classrooms. With regard to gender distribution,there were 61 females and 31 males (data on genderwere missing for 6 teachers). Teachers were distributedacross grades as follows: grade 3 = 15, grade 4 = 19,grade 5 = 21, grade 6 = 18, grade 7 = 14, grade 8 = 17,and grade 9 = 19 (the total is larger than 100% becausesome teachers taught more than one grade). No significant effects were observed across distributions compared to the null model that all /swere equal (chi-square[6] = 3.496, p = .745). Teacher age ranged between 24and 58 years, with amean of 43.13 years. On average,teachers had 18.24 years of teaching experience. Sixtywere teaching in elementary school units and 28 in secondary (data on setting were missing for 10 teachers).All teachers had fulfilled the requirements to teach inGreek public elementary or secondary schools.ProceduresTeachers who were well acquainted with students'work and achievement were asked to complete theLearning Disabilities Screening Scale for Teachers(Padeliadu & Sideridis, 2008). This scale is identical (inprinciple and concept) to the Learning DisabilitiesDiagnostic Inventory (LDDI) developed by Hammill(1995; see also Hammill & Bryant, 1998).

Ratings were collected during the last two months ofthe academic year to ensure that teachers were knowl




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edgeable of students' behaviors and achievement levels.The latterwas a prerequisite for teacher participation;that is, teachers had to feel confident that they couldproperly rate students' performance and achievement.Teachers were not introduced to the concept of LD;instead theywere asked to rate each item in terms of thefrequency of that behavior (1 = always to 9 = never).Each subscale contained 17 to 20 items; the total number of items was 116. Ifa teacher was not able to complete a subscale (e.g., mathematic achievement insecondary schools), the teacher who best knew a givenstudent's achievement in the corresponding field wasasked to complete the ratings.The screening inventory refers to grades 3 through 9and is composed of six subscales: listening, speaking,reading, writing, reasoning, and mathematics. Thesesubscales correspond to specific areas of deficiency inthe definition of learning disabilities from theNationalJoint Committee on Learning Disabilities (see Hammill,1990). Specific behaviors involve, for example, theinability to discriminate between phonemes, comprehend text, and so on. Teachers supplied their owndemographic information on a section of a givenstudent's rating scale.Data AnalysisMultilevel random coefficient modeling (MRCM) wasemployed to evaluate whether a student's diagnosiscould be predicted by teacher gender and other characteristics (Kreft& de Leeuw, 1998; Roberts, 2003; Shin,Espin, Deno, & McConnell, 2004) or student characteristics. For that purpose, we fit the logistic multilevelmodel with a binary dependent variable (Boomsma,1986). Further, in order for the resultant logistic coefficient to be translated into percentage points, weemployed the following formula (Bryk& Raudenbush,1992; Raudenbush & Bryk, 2002):

Probability of an Outcome = --(Equation1) 1+ exPHij}with r)ij being the logistic regression coefficient. Thespecifics are discussed separately for each model in thefollowing.

RESULTSUnconditionalModel ofLD IdentificationThe following unconditional model was applied tothe data to assess themean ratings of LD prevalenceusing a population-based model (Choi, 2001;Raudenbush & Bryk, 2002; Singer & Willet, 2003), asfollows:Level-1 Model

ProbabilityDiagnosis ^Logfoy/O


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Figure 1. Distribution of simulated frequency distributions based on the parametric bootstrap andusing 1,000 replications. The distribution shows the negligible bias in the probability of a studenthaving a diagnosis of learning disabilities.

20-j

IHHHHm

-1-1-1-?l-1-10.04 0.06 0.08 0.10 0.12 0.14Value

male teachers identifying children as having LD weresignificantly different from zero. When transformingthese logits into percentages using Equation 1, the probability of classifying students as having LD was 12.13%for female teachers and 25.7% formale teachers. Giventhat population estimates were slightly below 10% (i.e.,9.3%), itwas concluded that male teachers producedinflated judgments regarding identification of studentshaving LD compared to female teachers. The bias introduced by teacher gender was substantial, and for thatreason a series of alternative hypotheses were investigated to ensure that this finding is real and not an artifact of other teacher characteristics (i.e., teachingexperience or age).Bias Due to Student GenderA number of studies have shown that student genderinfluences teacher judgments (Rivard et al., 2007). In

order to evaluate the potential differential effects ofstudents' gender, the following model was fit to thedata:Level-1 Model

ProbabilityDiagnosis p0j+ Pij (Gender of Child) + ryLevel-2 Model

Poj= Yoo+ u0jp^ = y10+Y11 (Gender ofTeacher)

The coefficients of interest here are pXj and yn- Theterm Px, evaluates whether students' gender affects theprobability of identification. In other words, whethermore girls than boys are identified as having LD. Theterm yii evaluates whether teacher gender affects therelationship between students' gender and diagnosis. Inother words, the model testswhether teachers' gendermoderates the relationship between students' gender




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and probability of diagnosis (Aiken & West, 1991; Tate,2000).Results indicated that both coefficients were nonsignificant. Specifically, p^ = -0.019, p = 0.367, suggesting that the probability of having LD was independentof a child's gender. Also, the term yn = 0.016, p = 0.448was nonsignificant, suggesting that the relationshipbetween a child's gender and the probability of an LDdiagnosis was not affected by teacher gender (i.e., by theteacher who provided the ratings).Contribution of Teacher Age and ExperienceIn order to testwhether teacher characteristics such ofage and years of experience working with students withspecial needs affected their judgments, the followingmultilevel logisticmodel was fit to the data:

Level-1 ModelProbabilityDiagnosis ^Logfoy/O 4>ij) Poj

Level-2 ModelPoj= Poo+ P01 (Teacher's Age) + p02 (Teacher's Experience) u0jwith all |3Srepresenting partial regression coefficientsassociated with teachers' age and experience, controlling for all other variables in the model. Age and teaching experience were entered as a grand mean centered,so the results are reflected as ifvariables had undergonea z-score transformation. Results, as shown in Table 1,indicated that neither of these demographic variables

was a significant predictor of prevalence rates.

DISCUSSIONThis study investigated the presence of teacher biaseswith regard to identification of students with learningdisabilities. Factors related to teachers' gender, age, andexperience, along with students' gender, were investigated. Results indicated that teachers' gender significantly biases their identification of learning disabilities,with females being more lenient than males. The biaswas in themagnitude of 2:1, with male teachers identifying two students as having LD for every one studentidentified by female teachers.This finding may be interpreted tomean that femaleteachers initiate more interactions with their studentsand especially pay more attention to boys (Einarsson &Granstroem, 2002). With regard to themore "positive"evaluations by female teachers, Noddings (1984) andGilligan (1982) noted that woman teachers are morecaring (Einarsson & Granstroem), supportive, andexpressive (Hopf & Hatzichristou, 1999) than men.Additionally, Einarsson and Granstroem found thatmale teachers pay less attention to male students asthey grow older, a fact that may offer a logical explanation of the results of this study. Thus, overrepresentation of LD may partly be due to the gender of theteacher (ifwe consider that the ratings ofmale teacherswere enhanced compared to the baseline model).This finding agrees with previous ratings showingsubstantial biases based on teacher characteristics suchas psychopathology (Lovejoy, 1996) but not other char

Table 1Multilevel Random Coefficient Model Predicting Prevalence of Identification Rates Due toTeacher Age and Years of Experience

Variablesoefficient S.E. t-ratiop fIntercept (30Intercept yoo -2.118 2.466 -0.859 0.3948

Level-2 ModelTeacher's Age y02 -0.016.067 -0.240 0.811 68Teacher's Experience Y03 0.030.040 0.740 0.862 68

Note. Coefficients reflect fixed effectsof themodel. S.E. = Standard errorofmeasurement.




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acteristics such as teaching specialty (general vs. specialeducation) (Liljequist & Renk, 2007). However, thepresent findings disagree with those of Rescorla et al.(2007) with a different population (i.e., students withemotional problems) in that students referred for emotional problems did not lead to substantially differentteacher ratings.A second important finding was that teachers' ageand experience were not significant predictors of theiridentification ratings. This finding is troublesome andcontradicts the literature,which points to these factorsbeing important teacher resources (Liljequist & Renk,2007).A third important finding relates to the fact that students' gender was not associated with differentialteacher ratings. In addition, these ratings were notrelated to teacher gender. This agrees with past researchin that the gender of the child was not a significantdeterminant of teachers' ratings of a disability (Riveraet al., 2007). This finding is extremely important givenprior research confirming that teacher biases createmindsets and can be devastating for the development ofprejudice in specific groups or populations (Rosenthal &Jacobson, 1968).Limitations

Despite important findings, the present study is limited by a number of factors. First, although all studentshad a diagnosis of LD by an approved authority, it iswell known that teams employ variable criteria (e.g.,use different standardized assessments or place moreemphasis on Factor A than Factor B). For example,teams with experts on speech and language pathologymay relymore heavily on such measures than teamsthat apply a discrepancy (Stanovich, 2005) or an RTImodel (Fuchs & Deshler, 2007; Haager, 2007; Vaughn &Fuchs 2003). Thus, although all students had a diagnosis of LD, we cannot verify the validity of these ratingsbeyond the fact that students demonstrated significantsub-average achievement.A second limitation pertains to the fact that onlyteachers' age, gender, and experience were tested. Thus,it is likely that other demographic variables may havebeen responsible for the observed gender effect.Inclusion of such variables may aid our understandingof the existence of biases by teachers. For example,Pugach and Johnson (1995) and Tournaki and Podell(2005) reported that low numbers of referralsby teacherswere predicted by their efficacy ratings; nevertheless,the opposite findingwas reported by Soodak and Podell(1993, 1996).Furthermore, as two thoughtful reviewers of this article suggested, the ratings by teachers may reflect notjust their observations but other sources of influence as

well. Unfortunately, this is always the case with ratingsthat may contain both a subjective and an objectivepart. Thus, ratings likely reflect a knowledge base that isdue to various sources, including observations. If othersources of influence bias teachers' ratings, they shouldbe systematically examined in a methodological study(beyond the scope of the present study). Nevertheless,teacher ratings represent a reality in our current use ofevaluative criteria in learning disabilities. If othersources influence these ratings (besides those examinedin the present study), we hope that they are randomlydistributed across teachers, thus adding to the unsystematic source of error (i.e., random error).Implications for PracticeThe fact that the present study found biases in teachers is troublesome; especially, given themandate by theNo Child Left BehindAct (2001) forhighlyqualifiedteachers (King-Sears, 2005). Teachers are increasinglyrelied on to rate students' achievement and behavior.As a result, if their ratings are lacking in validity, itcan have serious implications for students' placement(Fierros & Bloomberg, 2005) and subsequent wellbeing. Although the present findings using Greekteachers and students cannot be directly generalized toU.S. teachers, it is plausible that such an effectmay bepresent given the resemblance in the two educationalsystems and teachers' education (the Greek system hasborrowed themain components of theU.S. educationalsystem). Nevertheless, U.S. studies are needed to ensurethat such an effect is present.Teacher awareness and training may be avenues forimproving the accuracy of their ratings (Moore, 2008;Rivard et al., 2007). Teacher efficacy has proven to beone of the most important factors contributing tothe validity of teacher judgments (Einarsson &Granstroem, 2002; Shinn, Tindal, & Spira, 1987). Thatis, teachers with low personal efficacy aremore likely to

mistakenly refer students for special education services(Einarsson & Granstroem). Training and practical guidance may enhance teachers' personal efficacy and, inturn, influence the validity of their estimates. The U.S.Department of Education's emphasis on enhancingteachers' content knowledge is important in this connection (Boe, Shin, & Cook, 2007). Other suggestionsfor improving the validity of teacher ratings involvethe use of brief, rather than lengthy, assessments(Henderson & Sugden, 1992) and instruments withdocumented positive psychometric properties (Junaid,Harris, Fulmer, & Carswell, 2000).As Rivera et al. (2007) pointed out, 'Teachers have acritical role to play in the identification and management of children" (p. 645) with and without disabilities. Future studies could enrich our understanding of

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the factors that contribute to valid teacher ratings orenhance the efficacy of teachers to be successful intheir multidisciplinary role (Dembo & Gibson, 1985;Gibson & Dembo, 1984; Merrett, & Wheldall, 1993).REFERENCESAbidin, R. R, & Robinson, L. L. (2002). Stress, biases, or professionalism: What drives teachers' referral judgments of studentswith challenging behaviors? Journal of Emotional and Behavioral

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Psychiatry.Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing andinterpreting interactions. Newbury Park, CA: Sage.Anderson, K. G. (1997). Gender bias and special education referrals. Annals ofDyslexia, 47, 151-162.

Bellamy, N. (1994). Bias in the classroom: Are we guilty? ScienceScope, 17, 60-63.

Bender, W. N., Vail, C O., & Scott, K. (1995). Teachers' attitudestoward increased mainstreaming: Implementing effectiveinstruction for students with learning disabilities. Journal ofLearning Disabilities, 28, 87-94.

Berry, C A., Shaywitz, S. E., & Shaywitz, B. A. (1985). Girls withattention deficit disorder: A silent minority? A report on behavioral and cognitive characteristics. Pediatrics, 76, 801-809.Boe, E. E., Shin, S., & Cook, L. H. (2007). Does teacher preparationmatter for beginning teachers in either special or general education? Journal of Special Education, 41, 158-170.Boomsma, A. (1986). On the use of bootstrap and jackknife incovariance structure analysis models. Compstat, 7, 205-210.Borg, M. G, & Falzon, J.M. (1998). Secondary school teachers'

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Please address correspondence regarding this article to: GeorgiosD. Sideridis, University of Crete, Department of Psychology,Rethimno, 74100 Crete, Greece; e-mail: [email protected]


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