Assessments in English that are constructed for native English speakers may not provide valid inferences about the achievement of English language learners (ELLs). The linguistic complexity of the test items that are not related to the content of the assessment may increase the measurement error, thus reducing the reliability of the assessment. Language factors that are not relevant to the content being assessed may also be a source of construct-irrelevant variance and negatively impact the validity of the assessment. More important, the results of these tests used as the criteria for identification and classification of ELL students, particularly those at the lower end of the English proficiency spectrum, may be misleading. Caution must be exercised when the results of these tests are used for special education eligibility, particularly in placing ELL students with lower English language proficiency in the learning/reading disability category. This article discusses psychometric issues in the assessment of English language learners and examines the validity of classifying ELL students, with a focus on the possibility of misclassifying ELL students as students with learning disabilities.
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References
1.
AbediJ. (1996). The interrater/test reliability system (ITRS). Multivariate Behavioral Research, 31, 409—417.
2.
AbediJ. (2004). The No Child Left Behind Act and English language learners: Assessment and accountability issues. Educational Researcher, 33, 4—14.
3.
AbediJ. (2005). Issues and consequences for English language learners. In HermanJ.L., and HaertelE.H. (Eds.), Uses and misuses of data in accountability testing (pp. 175—198). Maiden, MA: Blackwell.
4.
AbediJ., CourtneyM., and GoldbergJ. (2000). Language modification of reading, science and math test items. Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
5.
AbediJ., and LeonS. (1999). Impact of students’ language background on content-based performance: Analyses of extant data. Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
6.
AbediJ., LeonS., and MirochaJ. (2001). Examining ELL and non-ELL student performance differences and their relationship to background factors: Continued analyses of extant data. Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
7.
AbediJ., LeonS., and MirochaJ. (2003). Impact of student language background on content-based performance: Analyses of extant data (CSE Tech. Rep. No. 603). Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
8.
AbediJ., and LordC. (2001). The language factor in mathematics tests. Applied Measurement in Education, 14, 219—234.
9.
AbediJ., LordC., and HofstetterC. (1998). Impact of selected background variables on students’ NAEP math performance (CSE Tech. Rep. No. 478). Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
10.
AbediJ., LordC., HofstetterC., and BakerE. (2000). Impact of accommodation strategies on English language learners’ test performance. Educational Measurement: Issues and Practice, 19(3), 16—26.
11.
AbediJ., LordC., Kim-BoscardinC., and MiyoshiJ. (2000). The effects of accommodations on the assessment of LEP students in NAEP (CSE Tech. Rep. No. 537). Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
12.
AbediJ., LordC., and PlummerJ. (1997). Language background as a variable in NAEP mathematics performance (CSE Tech. Rep. No. 429). Los Angeles: University of California, National Center for Research on Evaluation, Standards, and Student Testing.
13.
AdamsM. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press.
14.
AllenM. J., and YenW. M. (1979). Introduction to measurement theory. Monterey, CA: Brooks/Cole.
15.
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.
16.
ArtilesA. J., and OrtizA. (Eds.). (2002). English language learners with special needs: Identification, placement, and instruction. Washington, DC: Center for Applied Linguistics.
17.
ArtilesA. J., RuedaR., SalazarJ., and HigaredaI. (2005). Within-group diversity in minority disproportionate representation: English language learners in urban school districts. Exceptional Children, 7(1), 283—300.
18.
BeattieS., GriseP., and AlgozzingB. (1983). Effects of test modifications on the minimum competency of learning disabled students. Learning Disabled Quarterly, 6, 75—77.
19.
BradleyR., DanielsonL., and HallahanD. P. (Eds.). (2002). Identification of learning disabilities: Research to practice. Hillsdale, NJ: Erlbaum.
20.
BotelM., and GranowskyA. (1974). A formula for measuring syntactic complexity: A directional effort. Elementary English, 1, 513—516.
21.
CattellB. R., and BurdsalA. C. (1975). The radial parcel double factoring design: A solution to the item-vs.-parcel controversy. Multivariate Behavioral Research, 10, 165—179.
22.
Celce-MurciaM., and Larsen-FreemanD. (1983). The grammar book: An ESL/EFL teacher's book. Rowley, MA: Newbury House.
23.
ChallJ. S., JacobsV. S., and BaldwinL. E. (1990). The reading crisis: Why poor children fall behind. Cambridge, MA: Harvard University Press.
24.
CockingR. R., and ChipmanS. (1988). Conceptual issues related to mathematics achievement of language minority children. In CockingR.R., and MestreJ.P. (Eds.), Linguistic and cultural influences on learning mathematics (pp. 17—46). Hillsdale, NJ: Erlbaum.
25.
CortinaJ. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78, 98—104.
26.
CronbachL. J., GleserG. C., NandaH., and RajaratnamN. (1972). The dependability of behavioral measurements: Theory of generalizability for scores and profiles. New York: Wiley.
27.
CumminsD. D., KintschW., ReusserK., and WeimerR. (1988). The role of understanding in solving word problems. Cognitive Psychology, 20, 405—438.
28.
DaleE., and ChallJ. S. (1948). A formula for predicting readability. Educational Research Bulletin, 27, 11—20 28, 37–54.
29.
De CorteE., VerschaffelL., and DeWinL. (1985). Influence of rewording verbal problems on children's problem representations and solutions. Journal of Educational Psychology, 77, 460—470.
30.
ForsterK. I., and OlbreiI. (1973). Semantic heuristics and syntactic trial. Cognition, 2, 319—347.
31.
GathercoleS. E., and BaddeleyA. D. (1993). Working memory and language. Hillsdale, NJ: Erlbaum.
32.
HaimanJ. (1985). Natural syntax: Iconicity and erosion. New York: Cambridge University Press.
33.
HallidayM. A. K., and MartinJ. R. (1993). Writing science: Literacy and discursive power. Pittsburgh, PA: University of Pittsburgh Press.
34.
HuntK. W. (1965). Grammatical structures written at three grade levels (Research Rep. No. 3). Urbana, IL: National Council of Teachers of English.
35.
HuntK. W. (1977). Early blooming and late blooming syntactic structures. In CooperC.R., and OdellL. (Eds.), Evaluating writing: Describing, measuring, judging (pp. 69—90). Urbana, IL: National Council of Teachers of English.
36.
JenkinsJ. R., and O'ConnorR. E. (2002). Chapter II: Early identification and intervention for young children with reading/learning disabilities. In BradleyR., DanielsonL., and HallahanD.P. (Eds.), Identification of learning disabilities: Research to practice (pp. 99—149). Hillsdale, NJ: Erlbaum.
37.
JustM. A., and CarpenterP. A. (1980). A theory of reading: From eye fixation to comprehension. Psychological Review, 87, 329—354.
38.
KingJ., and JustM. A. (1991). Individual differences in syntactic processing: The role of working memory. Journal of Memory and Language, 30, 580—602.
39.
KintschW., and GreenoJ. G. (1985). Understanding and solving word arithmetic problems. Psychological Review, 92, 109—129.
40.
KlareG. R. (1974). Assessing readability. Reading Research Quarterly, 10, 62—102.
41.
LemkeJ. L. (1986). Using language in classrooms. Victoria, Australia: Deakin University Press.
42.
LepikM. (1990). Algebraic word problems: Role of linguistic and structural variables. Educational Studies in Mathematics, 21, 83—90.
43.
LinnR. L. (1995). Assessment-based reform: Challenges to educational measurement. Princeton, NJ: Educational Testing Service.
44.
LinnR. L., and GronlundN. E. (1995). Measuring and assessment in teaching (7th ed.). Englewood Cliffs, NJ: Prentice Hall.
45.
MacDonaldM. C. (1993). The interaction of lexical and syntactic ambiguity. Journal of Memory and Language, 32, 692—715.
46.
MessickS. (1994). The interplay of evidence and consequences in the validation of performance assessments. Educational Researcher, 23(2), 13—23.
47.
MestreJ. P. (1988). The role of language comprehension in mathematics and problem solving. In CockingR.R., and MestreJ.P. (Eds.), Linguistic and cultural influences on learning mathematics (pp. 200—220). Hillsdale, NJ: Erlbaum.
48.
MunroJ. (1979). Language abilities and math performance. Reading Teacher, 32, 900—915.
49.
No Child Left Behind Act of 2001, Pub. L. No. 107–110, 115 Stat. 1425 (2002).
New York State Education Department. (1999). 1999 pocketbook of goals and results for individuals with disabilities. Retrieved July 11, 2002, from http://www.vesid.nysed.gov/pocketbook/1999/
53.
NoonanJ. (1990). Readability problems presented by mathematics text. Early Child Development and Care, 54, 57—81.
54.
OrrE. W. (1987). Twice as less: Black English and the performance of black students in mathematics and science. New York: W. W. Norton.
55.
OrtizA. A. (2002). Prevention of school failure and early intervention for English language learners. In ArtilesA.J., and OrtizA.A. (Eds.), English language learners with special education needs (pp. 40—58). Washington, DC: Center for Applied Linguistics.
56.
PauleyA., and SyderF. H. (1983). Natural selection in syntax: Notes on adaptive variation and change in vernacular and literary grammar. Journal of Pragmatics, 7, 551—579.
57.
RothmanR. W., and CohenJ. (1989). The language of math needs to be taught. Academic Therapy, 25, 133—142.
58.
RuedaA., ArtilesA. J., SalazarJ., and HigaredaI. (2002). An analysis of special education as a response to the diminished academic achievement of Chicano/Latino students: An update. In and and ValenicaR.R. (Ed.), Chicano school failure and success: Past, present, and future (2nd ed., pp. 310—332). London: Routledge/Falmer.
59.
SalviaJ., and YsseldykeJ. (1998). Assessment. Boston: Houghton Mifflin.
60.
SchachterP. (1983). On syntactic categories. Bloomington: Indiana University Linguistics Club.
61.
ShavelsonR., and WebbN. (1991). Generalizability theory: A primer. Newbury Park, CA: Sage.
62.
ShuardH., and RotheryA. (Eds.). (1984). Children reading mathematics. London: J. Murray.
63.
SlobinD. I. (1968). Recall of full and truncated passive sentences in connected discourse. Journal of Verbal Learning and Verbal Behavior, 7, 876—881.
64.
SpanosG., RhodesN. C., DaleT. C., and CrandallJ. (1988). Linguistic features of mathematical problem solving: Insights and applications. In CockingR.R., and MestreJ.P. (Eds.), Linguistic and cultural influences on learning mathematics (pp. 221—240). Hillsdale, NJ: Erlbaum.
65.
ThurlowM., and LiuK. (2001). State and district assessments as an avenue to equity and excellence for English language learners with disabilities (LEP Projects Report 2). Minneapolis: University of Minnesota, National Center on Educational Outcomes.
66.
TindalG., AndersonL., HelwigR., MillerS., and GlasgowA. (2000). Accommodating students with learning disabilities on math tests using language simplication. Eugene: University of Oregon, Research, Consultation, and Teaching Program.
67.
TrenholmeB., LarsenS. C., and ParkerR. M. (1978). The effects of syntactic complexity upon arithmetic performance. Learning Disabilities Quarterly, 1, 81—85.
68.
WangM. D. (1970). The role of syntactic complexity as a determiner of comprehensibility. Journal of Verbal Learning and Verbal Behavior, 9, 398—404.
69.
ZehlerA. M., HopstockP. J., FleischmanH. L., and GreniukC. (1994). An examination of assessment of limited English proficient students. Arlington, VA: Development Associates, Special Issues Analysis Center.
