ELL Critical Data Matrix Overview
Purpose:
 Riverview School District will more appropriately identify students who speak a first language other than English
(ELLs) for special education services using the ELL Critical Data Collection and Analysis Process.
 This tool asks teams to gather information about and consider 16 factors when determining whether an ELL should
be referred to the MDT or should be given more interventions at the Guidance Team stage.
 The tool offers systematic evidence-based guidance for making decisions regarding ELLs.
Terminology:
ELL – a student who speaks a first language other than English
Qualifies for ELL services – an ELL who scores between Level 1 and Level 3 on the placement/annual WELPA
** RED FLAG FACTORS - These factors are critical, and are given more weight during decision making.
Factor 1: Student’s Primary Language (L1)
Data:
 How does the nature of the L1 compare to the English language (e.g., phonetics, phonology and its
predictability, grammatical structure, writing system)?
 How does the student’s progress in English (e.g., grammatical errors, pronunciation, writing) correspond to
differences in the two languages?
Examples of language characteristics:
 Spanish is phonetically predictable whereas English is fairly unpredictable.
 Languages without articles: Russian, Chinese, Japanese, Farsi, Urdu, Swahili
 Languages without progressive verb forms: French, German, Russian, Greek
 Languages where the verb precedes the subject: Hebrew, Russian, Spanish (optional), Tagalog, classical Arabic
 If the students’ English errors can be explained by the differences between L1 and English (i.e., language
transfer errors), data supports more intervention.
 If student errors are NOT consistent with language transfer errors, data supports referral.
Factor 2: Other languages spoken by the student
Data: Parent interview
 Is the student a proven language learner? Is s/he proficient in multiple languages?
 How does the student’s progress in English compare to his/her proficiency in L1?
 If the student is a proven language learner and they are struggling in English, what are the possible
issues/barriers?
 If the student is a proven first language learner, data supports more intervention.
 If the student did not show typical first language development, data supports referral.
Factor 3: Multiple languages spoken in the home
Data: Parent interview
 Are multiple languages spoken in the home? What is the pattern of language use—who is speaking what to
the student?
 What is the student’s level of exposure to English and what is the nature and competence of the models?
 If competent English exposure is minimal outside of school, data supports more intervention.
 If competent English exposure is widely available outside of school, data supports referral.
Based on the work of Steve Gill, school psychologist, Kent School District
2/25/14
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**Factor 4: Years of Education in L1
Data:
 How much schooling has the student received in L1? Has s/he had the expected years of education given
his/her age and national/cultural background?
 Has s/he learned how to “do school?”
 Has s/he learned the structure of L1 relative to academic learning? If s/he has had limited formal education in
L1, we are trying to teach them language and school expectations in addition to academic content.
 If a student has gaps in schooling in L1, data supports more intervention.
 If a student has not attended school in L1, data supports more intervention.
 If a student has received the expected years of schooling in L1 prior to attending school in the U.S., data
supports referral.
Factor 5: Parental education in L1
Data: Parent interview
 What is the level of parents’ education and literacy in L1?
 Parental education and literacy (English or not), impacts a student’s development of vocabulary and language
structures and, in turn, school preparedness and rate of learning. Accuracy of parents’ language use also has
an effect on a child’s language development.
 Illiteracy does NOT have a direct correlation with intelligence, especially in countries where education can be
difficult to access.
 If parents have limited education and/or limited literacy skills, data supports more intervention.
 If parents are educated and literate in their first language, data supports referral.
**Factor 6: Student literacy in L1
Data: Parent interview
 What is the student’s level of literacy in L1? How does their literacy in L1 relate to the level of instruction they
received in L1?
 If the student did not learn to read in their primary language, then we are trying to teach the process of
reading while teaching a new language – which slows the learning process.
 If a student was never taught to read in L1, data supports more intervention.
 If student successfully learned to read in L1, data supports more intervention.
 If a student had difficulty learning to read in L1 and is having difficulty learning to read in L2, data supports
referral.
**Factor 7: Years learning English
Data: OSPI LEP database, parent interview
 How many years has the student been learning English?
 Research shows that WITH appropriate ELL services ELLs may need 5-7+ years to become fluent and literate in
English and be able to learn at a comparable rate to native English learners.
 This does not mean that you cannot test a child for SPED services—however, it does mean that you need
more data to support a decision to evaluate for SPED eligibility, particularly young students.
 If a student has less than 7 years of English language learning, data supports more intervention.
 More than 7 years of English language learning, data supports referral.
Factor 8: Attendance history
Data:
 What has been the student’s attendance pattern and history?
 Poor attendance and inconsistent schooling decreases achievement.
 Every mid-year school transition may cost a student 4 months’ worth of achievement.
 If a student has >3 unexcused/yr or total of 15 absences per yr (excused or not), data supports more
intervention.
 If a student has been enrolled in multiple schools/school districts, data supports more intervention.
 If there is a history of good attendance and consistent schooling, data supports referral.
Based on the work of Steve Gill, school psychologist, Kent School District
2/25/14
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Factor 9: Approach taken with Tier I ELL support
Data:
 Has the student had access to research-based, well-implemented Tier I ELL support? (Dual Language, SIOP,
GLAD)
 These programs increase children’s access to learning—opportunities and access to learning are critical prior
to making a SPED referral.
 If the student has not had access to research-based Tier I ELL support, data supports more intervention.
 If the student has had access to research-based Tier I ELL support that has been implemented with integrity,
data supports referral.
**Factor 10: Rate of growth on WLPT II/WELPA
Data: OSPI Peer Analysis Tool
 Is the student’s rate of English language acquisition similar to peers at the same proficiency level in the
school/district with equal duration of ELL services?
 Use OSPI Peer Analysis Tool (via ELL facilitators)
 If rate of growth similar to like-proficiency level peers, data supports more intervention.
 If rate of growth is significantly different than like-proficiency level peers, data supports referral.
Factor 11: Intervention description
Data: School intervention information, ELL RTI form
 What is the student’s response to evidence-based, well-implemented Tier II intervention?
 Tier II support refers to targeted interventions that supplement Tier I support. Progress monitoring needs to
be frequent and include the student’s individual progress as well as comparison to other students receiving
the intervention.
 2-3 rounds of intervention and refinement (based on progress monitoring data) should be conducted for ELL
students.
 If the interventions included baseline, progress-monitoring, and post-intervention data that reflect the
objectives/goals of the intervention, data supports referral.
 If the interventions had appropriate language and academic goals, data supports referral.
 If support was consistent and implemented with integrity during the intervention, data supports referral.
 If no to any of the above, data supports more intervention.
Factor 12: Expectations in the general education classroom
Data: Classroom teacher
 What have been the classroom expectations and work requirements for this student?
 All students should be expected to complete assignments, no matter the level of their language development.
 It is impossible to determine the presence of a learning disability if the student has not produced any work.
 If lack of clear expectations, lack of consistent requirements or work production, data supports more
intervention.
 If student has had clear expectations, consistent requirements, and work production, data supports referral.
Factor 13: Classroom observation
Data: Observation
 During classroom observations, what is the student’s engagement, attention, participation, and quality of
output?
 Given appropriate Tier I support, if a student with a history of cognitive engagement is not showing growth at
the rate of like-proficiency level peers, data supports referral.
 Lack of engagement does not provide any specific data, so will appear neutral on the matrix.
Based on the work of Steve Gill, school psychologist, Kent School District
2/25/14
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Factor 14: Comparison student data
Data: OSPI Peer Analysis Tool – MSP comparison (grades 4-9), school data
 How does the student’s progress in terms of language learning and academic achievement compare to likeproficiency level peers with similar backgrounds?
 Use the MSP comparison data from OSPI Peer Analysis Tool – Grades 4-9
 If growth curve is similar to/better than comparison students, data supports more intervention.
 If growth curve indicates notably slower growth or lack of response to interventions, data supports referral.
**Factor 15: Parent interview
Data: Parent interview
 What has the student experienced in his/her family, educational, and social history? How does it support or
hinder language or academic growth?
 Use the parent interview to find out:
o Environmental history (trauma, loss of a parent, displacement, poverty)
o Educational history (retentions, previous school performance concerns in L1/L2)
 If the family interview shows that the student has been a capable learner historically, data supports more
intervention.
 If the family interview shows that there has been an “adverse childhood experience,” data supports more
intervention.
 If the family interview shows that there have been learning issues in the past, data supports referral.
Factor 16: Developmental history
Data: Parent interview
 What is the nature of the student’s birth and developmental history? Are there red flags that may signal
developmental lags or insults to healthy growth/development?
 The developmental history is critical to knowing whether or not there is another explanation for academic
difficulties.
 Consider:
o Siblings and their development and learning
o Health history (e.g., illness, injury)
o Milestones
 If there is a history of developmental delays, data supports referral.
 If there is no history of developmental delays, data supports more intervention.
Based on the work of Steve Gill, school psychologist, Kent School District
2/25/14
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