aimswebPlus Reading

Area: Letter Naming Fluency

Cost

Technology, Human Resources, and Accommodations for Special Needs

Service and Support

Purpose and Other Implementation Information

Usage and Reporting

aimswebPlus™ is a subscription-based tool. There are three subscription types available for customers:

aimswebPlus Complete is $8.50 per student and includes all measures.

aimswebPlus Reading is $6.50 per student and includes early literacy and reading measures.

aimswebPlus Math is $6.50 per student and includes early numeracy and math measures.

Test accommodations that are documented in a student’s Individual Education Plan (IEP) are permitted with aimswebPlus. However, not all measures allow for accommodations.  Letter Naming Fluency is a test that employs a strict time limit to generate rate-based scores. As such, valid interpretation of national norms, which are an essential aspect of decision-making during benchmark testing, depend on strict adherence to the standard administration procedures.

These accommodations are allowed for Letter Naming Fluency: enlarging test forms and modifying the environment (e.g., special lighting, adaptive furniture)

NCS Pearson, Inc.
Phone: (866) 313-6194

www.aimsweb.com

www.aimswebplus.com

Training manuals are included and should provide all implementation information.

Pearson provides phone- and email-based ongoing technical support, as well as a user group forum that facilitates the asking and answering of questions.

aimswebPlus is a brief and valid assessment system for monitoring reading and math skills. Normative data were collected in 2013-14 on a combination of fluency measures that are sensitive to growth as well as new standards-based assessments of classroom skills. The resulting scores and reports include Letter Naming Fluency, and they inform instruction and help improve student performance in Kindergarten.

The student is presented with a page of 100 letters in a student-friendly font. Twenty unique progress monitoring (PM) forms are available; PM testing is conducted at teacher-determined intervals. 

While the Kindergarten and Grade 1 measures are administered individually, most of the Grades 2 through 8 measures can be taken online by entire classes. Once testing is complete, summary or detailed reports for students, classrooms, and districts can be immediately generated, and the math and reading composite scores can be used to estimate the risk to students or classes for meeting end-of-year goals. aimswebPlus reports also offer score interpretation information based on foundational skills for college and career readiness, learning standards, and other guidelines, Lexile® and Quantile® information, and recommendations for appropriate teaching resources.

Raw score and percentiles scores (based on grade norms) are provided. Local norms are also available.

The raw score is calculated by tallying the letters named correctly in 60 seconds. Letters not reached within 60 seconds are not considered “incorrect”; they are ignored for the purpose of reporting the number of letters named correctly.

 

Reliability of the Performance Level Score: Convincing Evidence

Reliability Coefficients for Letter Naming Fluency, Kindergarten

Type of Reliability

Grade

n (range)

Coefficient Range

Coefficient Median

SEM

Alternate form

Kindergarten

674

0.82

0.82

6.9

Retest

Kindergarten

1,463

0.81

0.81

 

Interscorer Agreement

Kindergarten

50

0.94

 

 

 

Reliability of the Slope: Convincing Evidence

Validity of the Performance Level Score: Unconvincing Evidence

aimswebPlus Math LNF Score Concurrent Validity Coefficient, by Grade and Criterion Measure

     

Concurrent

Gender

Race

ELL

% Free/Reduced Lunch

Criterion

Grade

N

Unadj

Adj1

F

M

B

H

O

W

Yes

68 - 100

34 - 67

0 - 33

WRF

k (w)

975

0.57

0.57

50

50

14

25

10

51

9

32

33

36

1 correlation adjusted for range restriction

aimswebPlus Math LNF Score Predictive Validity Coefficient, by Grade and Criterion Measure

     

Predictive

Gender

Race

ELL

% Free/Reduced Lunch

Criterion

Grade

N

Unadj

Adj1

F

M

B

H

O

W

Yes

68 - 100

34 - 67

0 - 33

WRF

k (w)

975

0.58

0.58

50

50

14

25

10

51

9

32

33

36

1 correlation adjusted for range restriction

aimswebPlus Word Reading Fluency

Overview: The student reads read words aloud for 1 minute.

Test Format:  individually-administered, timed

Test Content: The student is presented with two pages of word lists totaling 99 words.

20 unique progress monitoring forms; PM testing conducted at teacher-determined intervals

Score: number of words read correctly in 1 minute

Time limit: 1 minute

Predictive Validity of the Slope of Improvement: Data Unavailable

The predictive validity of the Letter Naming Fluency (LNF) slope was assessed using the correlation of the annual LNF ROI (LNFROI) with a spring Word Reading Fluency (WRFSpring) test scores, after controlling for fall LNF (LNFFall) performance. The model used is shown here:

〖WRF〗_spring= Intercept+ (β_1 )×〖LNF〗_Fall+ (β_2 )×〖LNF〗_ROI+ ε

A positive and statistically significant β_2 indicates that for a given fall LNF score, students with higher LNF ROIs had higher spring Criterion scores. 

aimswebPlus Word Reading Fluency (WRF) is described above in GOM 3.

Predictive validity of the fall to spring rate of improvement, Letter Naming Fluency

Measure

n

b2

SE

T

p

LNF

925

4.0

0.44

9.0

<0.01

 

Disaggregated Reliability and Validity Data: Data Unavailable

Alternate Forms: Partially Convincing Evidence

Sensitive to Student Improvement: Convincing Evidence

Describe evidence that the monitoring system produces data that are sensitive to student improvement (i.e., when student learning actually occurs, student performance on the monitoring tool increases on average).

Sensitivity to improvement was assessed by demonstrating that annual performance gains were statistically significant and moderate in size as expressed in fall standard deviation units. A gain expressed in SD units that exceeds 0.3 can be considered moderate (see Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences (Second Edition). Lawrence Erlbaum Associates.)

LNF fall and spring benchmark means, SDs, paired-sample t, and annual gain represented as fall standard deviation units

 

Mean

SD

N

Paired t

p

Gain/SD

Measure

Fall

Spring

Fall

Spring

LNF

46.9

55.4

18.14

19.05

2000

25.5

<0.01

0.47

 

End-of-Year Benchmarks: Convincing Evidence

Are benchmarks for minimum acceptable end-of-year performance specified in your manual or published materials?

Yes

Specify the end-of-year performance standards:

aimswebPlus allows users to select from a range of end-of-year targets the one that is most appropriate for their instructional needs. The targets are based on spring reading or math composite national percentiles by grade level. Twelve national percentile targets ranging from the 15th through the 70th percentile are provided, in increments of 5.
 
For Grades 3 through 8, it is recommended that users select the spring percentile that most closely aligns to the overall percentage of students below proficient on state reading/math tests. This is the percentage considered at risk. For example, if the percentage of students below proficient on the state test is 20%, the recommended end-of-year benchmark is the 20th percentile. Likewise, if the percentage of students below proficient on the state test is 60%, the recommended end-of-year benchmark is the 60th percentile.
 
Because passing rates on state assessments are fairly consistent across grades, the percentage of students at risk in Kindergarten through Grade 2 is likely to be very similar to the percentage at risk in Grade 3. As such, aimswebPlus recommends using the percentage of students below proficient on the Grade 3 state reading/math tests as the end-of-year benchmark for students in Kindergarten through Grade 2. For example, if the percentage of students below proficient on the state test in Grade 3 is 30%, the recommended end-of-year benchmark for students in Kindergarten through Grade 2 is the 30th percentile.
 
If these percentages are not available, aimswebPlus recommends using the 25th percentile as the end-of-year benchmark.
 
Fall and winter benchmark cut scores are derived automatically by the aimswebPlus system. The cut scores are based on empirical research of the relationship between fall/winter scores and spring benchmarks. Two cut-scores are provided: one corresponding to a 50% probability of exceeding the spring benchmark, and the other corresponding to an 80% probability of exceeding the spring benchmark. Fall or winter scores above the 80% probability cut score are deemed low risk; fall or winter scores between the 50% and 80% cut scores are deemed moderate risk; and fall or winter scores below the 50% probability cut score are deemed high risk. These three levels correspond to the RTI tiers reported in the aimswebPlus system.

What is the basis for specifying minimum acceptable end-of-year performance?

Norm-referenced

Specify the benchmarks:

Percentage of students below proficient level on state test.

What is the basis for specifying these benchmarks?

Norm-referenced

If norm-referenced, describe the normative profile:

Demographic Characteristics of the aimswebPlus Reading Norm Sample, Grade 1

   

Sex

Race

SES (F/R lunch)

Subject

Grade

F

M

B

H

O

W

Low

Mod

High

Reading

1

0.50

0.50

0.13

0.25

0.10

0.51

0.32

0.32

0.36

Representation: National

Date: 2013–2014

Number of States: 10

Regions: 4

Gender: 50% male, 50% female

SES: Low, middle, high, free and reduced lunch

ELL: 10%

Rates of Improvement Specified: Convincing Evidence

Is minimum acceptable growth (slope of improvement or average weekly increase in score by grade level) specified in your manual or published materials?

Yes

Specify the growth standards:

aimswebPlus provides student growth percentiles (SGP) by grade and initial (fall and winter) performance level for establishing growth standards. An SGP indicates the percentage of students in the national sample whose seasonal (or annual) rate of improvement (ROI) fell at or below a specified ROI. Separate SGP distributions are computed for each of five levels of initial (fall or winter) performance to control for differences in growth rate by initital performance level. 

When setting a performance goal for a student, the system automatically generates feedback as to the appropriateness of the goal. An SGP < 50 is considered Insufficient; an SGP between 50 and 85 is considered Closes the Gap; an SGP between 85 and 97 is considered Ambitious; and an SGP > 97 is considered Overly Ambitious. aimswebPlus recommends setting performance goals that represents rates of growth between the 85th and 97th SGP. However, the user ultimately determines what growth rate is required on an individual basis.

What is the basis for specifying minimum acceptable growth?

Norm-referenced

If norm-referenced, describe the normative profile.

Demographic Characteristics of the aimswebPlus Reading Norm Sample, Grade 1

   

Sex

Race

SES (F/R lunch)

Subject

Grade

F

M

B

H

O

W

Low

Mod

High

Reading

1

0.50

0.50

0.13

0.25

0.10

0.51

0.32

0.32

0.36

Representation: National

Date: 2013–2014

Number of States: 10

Regions: 4

Gender: 50% male, 50% female

SES: Low, middle, high, free and reduced lunch

ELL: 10%

Please describe other procedures for specifying adequate growth:

To get the most value from progress monitoring, aimswebPlus recommends the following: (1) establish a time frame, (2) determine the level of performance expected, and (3) determine the criterion for success. Typical time frames include the duration of the intervention or the end of the school year. An annual time frame is typically used when IEP goals are written for students who are receiving special education. For example, aimswebPlus goals can be written as follows: In 34 weeks, the student will compare numbers and answer computational problems to earn of score of 30 points on Grade 4 Number Sense Fluency forms.
 
The criterion for success may be set according to standards, local norms, national norms, or a normative rate of improvement (ROI). For example, the team may want to compare a student’s performance to district/local norms, which compares the student’s score to his or her peers in the context of daily learning.
 
For normative ROIs, aimswebPlus uses student growth percentiles to describe these normative rates of improvement. Within the aimswebPlus software, the user enters the goal date and moves a digital slider to the desired ROI.  As the slider moves, it provides feedback about the strength of the ROI: Insufficient, Closes the Gap, Ambitious, or Overly Ambitious. Users are encouraged to use the Ambitious (85th – 97th SGP) for students in need of intensive intervention.

Decision Rules for Changing Instruction: Convincing Evidence

Does your manual or published materials specify validated decision rules for when changes to instruction need to be made?

Yes

Specify the decision rules:

aimswebPlus applies a statistical procedure to the student’s progress monitoring scores in order to provide empirically-based guidance about whether the student is likely to meet, fall short of, or exceed his/her goal. The calculation procedure (presented below) is fully described in the aimsweb Progress Monitoring Guide (Pearson, 2012). aimswebPlus users will not have to do any calculations—the online system does this automatically. The decision rule is based on a 75% confidence interval for the student’s predicted score at the goal date. This confidence interval is student-specific and takes into account the number and variability of progress monitoring scores and the duration of monitoring. Starting at the sixth week of monitoring (when there are at least four monitoring scores), the aimswebPlus report following each progress monitoring administration includes one of the following statements:

A. “The student is projected to not reach the goal.” This statement appears if the confidence interval is completely below the goal score.

B. “The student is projected to exceed the goal.” This statement appears if the confidence interval is completely above the goal score.

C. “The student is projected to be near the goal. The projected score at the goal date is between X and Y” (where X and Y are the bottom and top of the confidence interval). This statement appears if the confidence interval includes the goal score.

If Statement A appears, the user has a sound basis for deciding that the current intervention is not sufficient and a change to instruction should be made. If Statement B appears, there is an empirical basis for deciding that the goal is not sufficiently challenging and should be increased. If Statement C appears, the student’s progress is not clearly different from the aimline, so there is not a compelling reason to change the intervention or the goal; however, the presentation of the confidence-interval range enables the user to see whether the goal is near the upper limit or lower limit of the range, which would signal that the student’s progress is trending below or above the goal.

A 75% confidence interval was chosen for this application because it balances the costs of the two types of decision errors. Incorrectly deciding that the goal will not be reached (when in truth it will be reached) has a moderate cost: an intervention that is working will be replaced by a different intervention. Incorrectly deciding that the goal may be reached (when in truth it will not be reached) also has a moderate cost: an ineffective intervention will be continued rather than being replaced. Because both kinds of decision errors have costs, it is appropriate to use a modest confidence level.

Calculation of the 75% confidence interval for the score at the goal date:

Calculate the trend line. This is the ordinary least-squares regression line through the student’s monitoring scores.

Calculate the projected score at the goal date. This is the value of the trend line at the goal date.

Calculate the standard error of estimate (SEE) of the projected score at the goal date, using the following formula:

〖SEE〗_(predicted score)= √((∑_i^k▒(y_i-y ́_i )^2 )/(k-2))×√(1+1/k+(GW-(∑_1^k▒w_i )/k)^2/(∑_i^k▒(w_i-(∑_1^k▒w_i )/k)^2 ))

where k = number of completed monitoring administrations, w = week number of a completed administration, GW = week number of the goal date, y = monitoring score, y’ = predicted monitoring score at that week (from the student’s trendline).The means and sums are calculated across all of the completed monitoring administrations up to that date. Add and subtract 1.25 times the SEE to the projected score, and round to the nearest whole numbers.

What is the evidentiary basis for these decision rules?

The decision rules are statistically rather than empirically based. The guidance statements that result from applying the 75% confidence interval to the projected score are correct probabilistic statements, under certain assumptions: The student’s progress can be described by a linear trend line. If the pattern of the student’s monitoring scores is obviously curvilinear, then the projected score based on a linear trend will likely be misleading. We provide training in the aimsweb Progress Monitoring Guide about the need for users to take non-linearity into account when interpreting progress-monitoring data. The student will continue to progress at the same rate as they have been progressing to that time. This is an unavoidable assumption for a decision system based on extrapolating from past growth.

Even though the rules are not derived from data, it is useful to observe how they work in a sample of real data. For this purpose, we selected random samples of students in the aimsweb 2010–2011 database who were progress-monitored on either Reading Curriculum-Based Measurement (R-CBM) or Math Computation (M-COMP). All students selected scored below the 25th percentile in the fall screening administration of R-CBM or M-COMP. The R-CBM sample consisted of 1,000 students (200 each at of Grades 2 through 6) who had at least 30 monitoring scores, and the M-COMP sample included 500 students (100 per Grades 2 through 6) with a minimum of 28 monitoring scores. This analysis was only a rough approximation, because we did not know each student’s actual goal or whether the intervention or goal was changed during the year.

To perform the analyses, we first set an estimated goal for each student by using the ROI at the 85th percentile of aimsweb national ROI norms to project their score at their 30th monitoring administration. Next, we defined “meeting the goal” as having a mean score on the last three administrations (e.g., the 28th through 30th administrations of R-CBM) that was at or above the goal score. At each monitoring administration for each student, we computed the projected score at the goal date and the 75% confidence interval for that score, and recorded which of the three decision statements was generated (projected not to meet goal, projected to exceed goal, or on-track/no-change).

In this analysis, accuracy of guidance to change (that is, accuracy of projections that the student will not reach the goal or will exceed the goal) reached a high level (80%) by about the 13th to 15th monitoring administration, on average. The percentage of students receiving guidance to not change (i.e., their trendline was not far from the aimline) would naturally tend to decrease over administrations as the size of the confidence interval decreased. At the same time, however, there was a tendency for the trendline to become closer to the aimline over time as it became more accurately estimated, and this worked to increase the percentage of students receiving the “no change” guidance.

Decision Rules for Increasing Goals: Convincing Evidence

Does your manual or published materials specify validated decision rules for when changes to increase goals?

Yes

Specify the decision rules:

The same statistical approach described under Decision Rules for Changing Instruction (GOM 9 above) applies to the decisions about increasing a goal. aimswebPlus provides the following guidance for deciding whether to increase a performance goal:

 If the student is projected to exceed the goal and there are at least 12 weeks remaining in the schedule, consider raising the goal.

What is the evidentiary basis for these decision rules? 

See GOM 9 evidentiary basis information above.

Improved Student Achievement: Data Unavailable

Improved Teacher Planning Data Unavailable