FAST: earlyReading English

Letter Sounds

Rating Summary

Classification Accuracyfull bubble
GeneralizabilityModerate Low
Reliabilityfull bubble
Validityhalf bubble
Disaggregated Reliability and Validity Datahalf bubble
Efficiency
AdministrationIndividual
Administration & Scoring Time1-2 Minutes
Scoring KeyComputer Scored
Benchmarks / NormsYes
Cost Technology, Human Resources, and Accommodations for Special Needs Service and Support Purpose and Other Implementation Information Usage and Reporting

The Formative Assessment System for Teachers™ (FAST) is online software that requires no hardware or special add-ons. FAST is supported by an extensive set of materials to support teachers and students, including self-directed training modules that allow teachers to become certified to administer each of the FAST assessments. The entire FAST assessment package (i.e., reading, math, behavior, and on-line training) is provided at an annual flat rate of $6 per student.

Testers will require 1-4 hours of training.

Paraprofessionals can administer the test.

Where to Obtain

Address:http://www.fastbridge.org/

FastBridge Learning
520 Nicollet Mall, Suite 910
Minneapolis, MN 55402-1057

Phone: 612-254-2534

Websitehttp://www.fastbridge.org/

Training materials are included in the cost of the tool.  Additional, optional on-site and webinar-based training services are available for a fee.

Ongoing technical support is available by calling 612-424-3710 or emailing fast1@umn.edu

The Formative Assessment System for Teachers (FAST) earlyReading measure is designed to assess both unified and component skills associated with kindergarten and first grade reading achievement. earlyReading is intended to enable screening and progress monitoring across four domains of reading (Concepts of Print, Phonemic Awareness, Phonics, and Decoding) and provide domain specific assessments of these specific component skills and a general estimate of overall reading achievement.

The objective of the Letter Sounds measure is to assess the student’s ability and automaticity with saying the sounds of uppercase and lowercase letters in isolation. All 26 letters in the English alphabet are used. The letters c, g, and all vowels are included in a separate section of the measure (not within the automaticity portion of the measure).               

The tool is intended for use in Kindergarten or with ages 5-6.

Administration is computerized and is 1-2 minutes per student. Scoring is done automatically within the software and does not require any additional time.

Available scores include: raw scores, percentile scores, developmental benchmarks and cut points, subscale/subtest scores, composite scores, and error analysis.

 

Classification Accuracy

Classification Accuracy in Predicting Proficiency on GRADE for Kindergarten

 

15th Percentile

n = 214

40th Percentile

n = 195

False Positive Rate

0.20

0.27

False Negative Rate

0.18

0.25

Sensitivity

0.82

0.75

Specificity

0.80

0.73

Positive Predictive Power

0.26

0.53

Negative Predictive Power

0.98

0.88

Overall Classification Rate

0.80

0.74

AUC (ROC)

0.85

0.82

Base Rate

0.08

0.29

Cut Points:

34

28

At XX% Sensitivity, Specificity equals

88% sensitivity, 0.74 specificity

88% sensitivity, 0.53 specificity

At XX% Sensitivity, Specificity equals

82% sensitivity, 0.80 specificity

79% sensitivity, 0.71 specificity

At XX% Sensitivity, Specificity equals

71% sensitivity, 0.82 specificity

70% sensitivity, 0.83 specificity

 

Generalizability

Description of study sample:

·         Number of States: 1 (Minnesota)

·         Regions: 1

·         Gender

o   47% Male

o   53% Female

·         Race/Ethnicity:

o   65% White, Non-Hispanic

o   0% American Indian/Alaska Native

o   23% Black, Non-Hispanic

o   0% Asian, Pacific Islander

o   6% Hispanic

o   3% Other

·         Disability status: approximately 11% SWDs

·         First language: approximately 90% English

·         Language proficiency status: 100% English proficient

Reliability

Type of Reliability

Age or Grade

n (range)

Coefficient

SEM

Information (including normative data)/Subjects

range

median

Alternate Form Correlation

K

34-36

0.85-0.94

0.89

5.56(4.89)

 

Test Retest

K

36

 

0.91*

 

Collected in Fall 2012, ~2-3 week delay

Delayed Test-Retest

K

1,241

 

0.51

 

Fall-Winter.

Delayed Test-Retest

K

1,282

 

0.61

 

 Winter-Spring.

Delayed Test-Retest

K

1,600

 

0.35

 

 Fall-Spring.

Coefficient alpha

K

683

 

0.93 for first 10 items

 

0.98 for first 30 items

 

0.98 for first 50 items

 

Coefficients was derived from a random sample of students from the FAST database from the 2012-2013 academic year. Approximately 52.1% of students were female, and 47.9% of students were male. Approximately 55.1% of the sample was White, 17.4% Hispanic, 14.6% Black, 5.1% Multiracial, 4.5% Asian, and 3.2% American Indian or Alaska Native.

Split-half

K

683

 

0.93 for first 10 items

 

0.98 for first 30 items

 

0.99 for first 50 items

 

Coefficients was derived from a random sample of students from the FAST database from the 2012-2013 academic year. Approximately 52.1% of students were female, and 47.9% of students were male. Approximately 55.1% of the sample was White, 17.4% Hispanic, 14.6% Black, 5.1% Multiracial, 4.5% Asian, and 3.2% American Indian or Alaska Native.

*Outliers that were +/- 2 standard deviations from the mean were removed from the test-retest reliability sample. In this case 2 cases, making up 3% of the sample, were removed.

Validity

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient (if applicable)

Information (including normative data)/Subjects

range

Median

 

Concurrent

 

K

GRADE Level P

85

 

0.53

The majority of students within the school district were White (78%), with the remaining students identified as either African American (19%), or other (3%). In school District 2, the majority of students within the school district are White (53%), with the remaining students identified as African American (26%), Hispanic (11%), Asian (8%), or other (2%).

Predictive

K

GRADE Level K

230

 

0.44

See above

Predictive

K

GRADE Level K

210

 

0.63

See above

Concurrent

K

GRADE Level K

214

 

0.19

See above

Discriminant Validity (beginning)

K

Letter Sounds

187

 

Difference Stats:

t = 25.33

d = 2.41

 

Discriminant Validity (middle)

K

Letter Sounds

173

 

t = 27.66

d = 2.69

 

Discriminant Validity (end)

K

Letter Sounds

212

 

t = 25.59

d = 2.38

 

 

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient

Information (including normative data)/Subjects

Predictive Validity

1st

aReading

78

0.69

Winter to Spring prediction

Predictive Validity

K

aReading

482

0.62

Winter to Spring prediction

Predictive Validity

1st

aReading

17

0.71

Winter to End of School Year prediction

Concurrent validity

1st

aReading

18

0.71

Spring data collection

Concurrent validity

1st

CBMreading

27

0.72

Spring data collection

Concurrent validity

K

aReading

461

0.70

Winter data collection

Concurrent validity

K

aReading

1,301

0.62

Fall data collection

Predictive validity

K

aReading

453

0.62

Fall to Winter

Concurrent

K

AIMSweb

Letter Names

141

0.86

See below.

Concurrent

K

AIMSweb

Letter Sounds

141

0.96

See below.

Concurrent

K

AIMSweb

Nonsense Words

141

0.86

See below.

Concurrent

1

AIMSweb

Letter Sounds

140

0.81

See below.

*Correlations disattenuated based on reported reliabilities.

AIMSweb Letter Names requires students to read letter names aloud for one minute. The score is the correct number of letter names a student can read per minute.

AIMSweb phoneme segmentation requires students to listen to a word and respond with all of the sounds, or phonemes, in the word. The score is the correct number of sounds identified per minute.

AIMSweb Letter Sounds requires students to read letter sounds aloud for one minute. The score is the correct number of letter sounds a student can read per minute.

AIMSweb Nonsense Word Fluency requires students to read short CVC or VC non-words.  The two scores are the correct number of sounds per minute and the correct number of words per minute.

DIBELS Next First Sound Fluency requires students to listen to words and provide the initial sound in the word. The score is the number of correct sounds per minute.

The earlyReading validity evidence study coefficients were derived from a sample of approximately 140 students each in Kindergarten and First Grade. Approximately 47% of students were female. Reported races of students were White (59%), Hispanic (9%), Black (12%), American Indian (1%), and Asian/Pacific Islander (18%). Approximately 21% of students were English Language Learners, 32% were eligible for free or reduced lunch, and 9% received special education services.

Disaggregated Reliability, Validity, and Classification Data for Diverse Populations

Disaggregated Classification Accuracy

Classification Accuracy in Kindergarten (15th Percentile – Fall earlyReading Letter Sounds to Fall aReading)

 

White Students

False Positive Rate

0.12

False Negative Rate

0.78

Sensitivity

0.22

Specificity

0.88

Positive Predictive Power

0.63

Negative Predictive Power

0.56

Overall Classification Rate

0.57

AUC (ROC)

0.80

Base Rate

0.47

Cut Points:

22.5

At 71% Sensitivity, Specificity equals

73%

At 81% Sensitivity, Specificity equals

60%

 

Disaggregated Reliability

Type of Reliability

Age or Grade

n (range)

Coefficient

Information (including normative data)/Subjects

Delayed test-retest Reliability

1st

50

0.70

Fall to Winter; Non-white students

Delayed test-retest Reliability

1st

17

0.71

Fall to Winter; White students

 

 

 

Ethnicity

 

Test-Retest Coefficient (N)

F to W

Test-Retest Coefficient (N)

F to S

Letter Sounds

Black

K

0.53 (409)

0.45 (408)

Letter Sounds

Hispanic

K

0.46 (270)

0.29 (292)

Letter Sounds

White

K

0.50 (1,410)

0.31 (1,687)

 

Disaggregated Validity

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient

Information (including normative data)/Subjects

Concurrent Validity

K

aReading

98

0.70

Asian students; Winter data collection

Predictive validity

K

aReading

141

0.70

Asian students; Winter to Spring

Concurrent validity

K

aReading

53

0.71

African American students; Winter data collection

Concurrent validity

K

aReading

39

0.76

Hispanic students; Winter data collection

Predictive validity

K

aReading

123

0.73

Asian students; Fall to Spring prediction

Concurrent validity

K

aReading

70

0.78

Asian students; Fall data collection