FAST: earlyReading English

Sight Words (50)

Rating Summary

Classification Accuracyfull bubble
GeneralizabilityModerate Low
Reliabilityfull bubble
Validityhalf bubble
Disaggregated Reliability and Validity Datafull 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: http://www.fastbridge.org/

Address:

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 Sight Words 50 measure is to assess whether students are able to recognize common high-frequency words. This is distinct from a decodable word measure in that, though some sight words may be decodable, students recognize them with automaticity rather than utilizing cognitive resources to decode them.

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 = 214

False Positive Rate

0.28

0.35

False Negative Rate

0.22

0.29

Sensitivity

0.78

0.71

Specificity

0.72

0.65

Positive Predictive Power

0.20

0.43

Negative Predictive Power

0.97

0.85

Overall Classification Rate

0.72

0.66

AUC (ROC)

0.82

0.74

Base Rate

0.08

0.28

Cut Points:

25

39

At XX% Sensitivity, Specificity equals

89% sensitivity, 0.62 specificity

83% sensitivity, 0.50 specificity

At XX% Sensitivity, Specificity equals

83% sensitivity, 0.70 specificity

78% sensitivity, 0.63 specificity

At XX% Sensitivity, Specificity equals

67% sensitivity, 0.80 specificity

69% sensitivity, 0.68 specificity

Classification Accuracy in Predicting Proficiency on aReading (Adaptive Reading) 

 

Kindergarten

(Winter predicting Spring; 15th Percentile)

n = 22

Kindergarten

(Spring predicting Spring; 15th Percentile)

n = 115

Kindergarten

(Spring predicting Spring; 40th Percentile)

n = 115

False Positive Rate

0

0.20

0.23

False Negative Rate

0.71

0.31

0.25

Sensitivity

0.29

0.69

0.75

Specificity

1.00

0.80

0.77

Positive Predictive Power

1.00

0.50

0.77

Negative Predictive Power

0.29

0.90

0.74

Overall Classification Rate

0.45

0.77

0.76

AUC (ROC)

0.87

0.88

0.88

Base Rate

0.77

0.23

0.51

Cut Points:

1.00

10

21.5

At XX% Sensitivity, Specificity equals

80% sensitivity, 0.82 specificity

73% sensitivity, 0.79 specificity

70% sensitivity, 0.84 specificity

At XX% Sensitivity, Specificity equals

 

80% sensitivity, 0.75 specificity

80% sensitivity, 0.75 specificity

At XX% Sensitivity, Specificity equals

 

92% sensitivity, 0.67 specificity

90% sensitivity, 0.60 specificity

AUC and overall classification rates may not be consistent due to the proportion of the true values of the data set. While specificity is very high, sensitivity is low. While AUC considers all possible thresholds, overall classification accuracy only considers one specific threshold. In other words, the AUC may not reflect the expected classification accuracy at a single selected threshold. The overall classification accuracy represents the extent to which, overall, the classifier is correct. FAST used the classification worksheet provided by NCRtI to calculate all relevant statistics. 

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

Kindergarten

24-28

0.94-0.99

0.97

4.40 (4.13)

 

Test-retest

Kindergarten 

34

0.94-0.99

0.97

2.82

Collected in Fall 2012

Test-Retest (Winter to Spring)

Kindergarten

169

 

0.73

 

Participants included 85 Kindergarten and 71 first grade students from two elementary schools in a metropolitan area in the Midwest. Kindergarten students who participated in the study were enrolled in all day kindergarten at two different elementary schools within the same school district. 

Coefficient alpha

 

505

 

0.90 for first 11 items

 

0.97 for first 29 items

 

0.99 for first 47 items

 

Coefficients were derived from a random sample of students from the FAST database from the 2012-2013 academic year. Approximately 47.7% of the sample was female, and 52.3% was male. Approximately 56.2% were White, 21.2% Black, 14.1% Hispanic, 4.2% Asian, 3.2% Multiracial, and 1.2% American Indian or Alaska Native.

Split-half

 

505

 

0.91 for first 11 items

 

0.98 for first 29 items

 

0.99 for first 47 items

 

Coefficients were derived from a random sample of students from the FAST database from the 2012-2013 academic year. Approximately 47.7% of the sample was female, and 52.3% was male. Approximately 56.2% were White, 21.2% Black, 14.1% Hispanic, 4.2% Asian, 3.2% Multiracial, and 1.2% American Indian or Alaska Native.

 

Validity

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient

Information (including normative data)/Subjects

Concurrent

K

GRADE

213

0.19

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%).

Discriminant validity (End)

K

Sight Word 50

177

Difference stats: t = 27.33

d = 2.64

 

Predictive Validity

K

aReading

22

0.70

The sample consisted of approximately 118 Kindergarten students (42.9% female). The majority of students (76.7%) were not eligible to receive special education services.  Winter to Spring prediction.

Concurrent Validity

K

aReading

110

0.70

The sample consisted of approximately 118 Kindergarten students (42.9% female). The majority of students (76.7%) were not eligible to receive special education services.  Spring data collection.

 

Concurrent validity

1st grade

aReading

456

0.75

Winter data collection

Concurrent validity

1st grade

aReading

30

0.76

Spring data collection

Concurrent

K

AIMSweb

Nonsense Words

141

0.73

See below.

Concurrent

K

Fuchs SW

140

0.93

See below.

*Correlations disattenuated based on reported reliabilities.

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.

The Fuchs Sight Words task requires students to read non-decodable words aloud.  The score is the number of words read correctly in one 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 in Predicting Proficiency on aReading (Adaptive Reading) 

 

Kindergarten

(Spring predicting Spring; 15th Percentile; Non-White)

n = 36

Kindergarten

(Spring predicting Spring; 15th Percentile; White)

n = 79

Kindergarten

(Spring predicting Spring; 40th Percentile; Non-White)

n = 36

Kindergarten

(Spring predicting Spring; 40th Percentile; White)

n = 79

False Positive Rate

0.27

0.17

0.46

0.16

False Negative Rate

0.20

0.38

0.17

0.31

Sensitivity

0.80

0.63

0.83

0.69

Specificity

0.73

0.83

0.53

0.84

Positive Predictive Power

0.53

0.48

0.76

0.78

Negative Predictive Power

0.90

0.90

0.64

0.77

Overall Classification Rate

0.75

0.78

0.72

0.77

AUC (ROC)

0.90

0.87

0.85

0.89

Base Rate

0.28

0.20

0.64

0.46

Cut Points:

5.5

13.5

10

22.5

At XX% Sensitivity, Specificity equals

90% sensitivity, 0.71 specificity

94% sensitivity, 0.50 specificity

91% sensitivity, 0.54 specificity

89% sensitivity, 0.60 specificity

At XX% Sensitivity, Specificity equals

80% sensitivity, 0.80 specificity

81% sensitivity, 0.78 specificity

83% sensitivity, 0.70 specificity

81% sensitivity, 0.81 specificity

At XX% Sensitivity, Specificity equals

60% sensitivity, 0.92 specificity

63% sensitivity, 0.91 specificity

65% sensitivity, 0.85 specificity

64% sensitivity, 0.91 specificity

 

Disaggregated Reliability

Type of Reliability

Age or Grade

n (range)

Coefficient Range

Coefficient Median

SEM

Information (including normative data)/Subjects

Delayed test-retest

Kindergarten

76

 

0.81

 

Black; Winter to Spring

Delayed test-retest

Kindergarten

39

 

0.86

 

Hispanic; Winter to Spring

Delayed test-retest

Kindergarten

449

 

0.79

 

White; Winter to Spring

 

Disaggregated Validity

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient Range

Coefficient Median

Information (including normative data)/Subjects

Concurrent validity

1st grade

aReading

76

 

0.72

Hispanic students; Spring data collection

Concurrent validity

1st grade

aReading

235

 

0.71

White students; Spring data collection

Concurrent validity

K

aReading

24

 

0.72

Asian students; Spring data collection

Concurrent validity

1st grade

aReading

33

 

0.81

Native American students; Spring data collection

Concurrent validity

1st grade

aReading

34

 

0.75

Multiracial students; Spring data collection

Concurrent validity

K

aReading

95

 

0.76

African American students; Spring data collection

Predictive validity

1st grade

aReading

28

 

0.77

Native American students; Winter to Spring data collection

Concurrent validity

1st grade

aReading

105

 

0.77

Asian students; Winter data collection

Concurrent validity

1st grade

aReading

40

 

0.77

African American students; Winter data collection

Concurrent validity

1st grade

aReading

39

 

0.77

Multiracial students; Winter data collection

Predictive validity

1st grade

aReading

34

 

0.85

Multiracial students; Winter to Spring prediction

Concurrent validity

1st grade

aReading

230

 

0.76

White students; Winter data collection

Concurrent validity

1st grade

aReading

28

 

0.73

Native American students; Fall data collection

Predictive validity

1st grade

aReading

17

 

0.73

Native American students; Fall to Spring

Concurrent validity

1st grade

aReading

152

 

0.71

Multiracial students; Fall data collection

Predictive validity

1st grade

aReading

39

 

0.78

Multiracial students; Fall to Winter prediction

Predictive validity

1st grade

aReading

34

 

0.85

Multiracial students; Fall to Spring

Predictive validity

1st grade

aReading

593

 

0.72

White students; Fall to Spring