the item bias detection of the reading tests and the development of the item bank software

The Item Bias Detection of the Reading Tests and the Development of the Item Bank Software

Used for English Reading Courses at King Mongkut’s University of Technology North Bangkok

Supalak Nakhornsri, Ph.D.

Department of Languages, King Mongkut’s University of Technology North Bangkok,

Thailand

[email protected]

Outline of the Presentation

Background of the studyResearch QuestionsObjectives

Methodology

Results

Conclusion

Test DevelopmentItem Bias DetectionItem Bank Software

Definitions of Terms

Background of the Study

The results can be used to make changes to improve the potential usefulness of the test.

(Bachman, 2004)

Trying out a test

For classroom teachers, it is not advisable to try out a test with the same students who will take it.

(Bachman, 2004)

Background of the StudyItem Analysis

The essential part of analyzing the results of tests for improving their usefulness.

(Brown, 2004)Classical Item Analysis (IA): calculating

descriptive statistics for individual itemsItem Response Theory (IRT):

a more sophisticated procedure for estimating the statistical characteristics of item.

(Bachman, 2004)

Background of the StudyIA vs. IRTIASubpopulation

dependentImplicitly averaged

across all ability levels

(Bachman, 1990)

IRTIndependent of

group of examinees used

Independently estimated test taker ability

Known precision of ability estimates

Background of the StudyBias Vs. UnfairnessUnfairness: Concerning with test administration

Bias: A type of invalidity

(Shepard, 1982)

Background of the StudyDifferences among three methods

IA IRTDelta-plot Chi-square Three-parameter

modelTransforming item difficulty into Delta value and plot the value onto the Bivariate Graph

(Angoff, 1982)

Measuring the frequency of correct or incorrect responses in each ability groups

(Shepard, 1982)

The presence of some characteristic of an item that results in differential performance for individuals of the same ability but from different ethnic, sex, cultural, or religious groups. (Hambleton et.al, 1991.)


Delta-plotDot/Lines show Means

14.00 16.00 18.00

male

14.00

16.00

18.00

fem

ale


Chi-squareChi-Square Tests

1.988a 2 .370

2.198 2 .333

.509 1 .476

83

Pearson Chi-Square

Likelihood Ratio

Linear-by-LinearAssociation

N of Valid Cases

Value dfAsymp. Sig.

(2-sided)

4 cells (66.7%) have expected count less than 5. Theminimum expected count is .34.

a.

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 5.799(b)

1 .016

Continuity Correction(a)

4.602 1 .032

Likelihood Ratio 5.597 1 .018

Fisher's Exact Test

Linear-by-Linear Association

5.729 1 .017

N of Valid Cases 83


IRT: Three-parameter model


Sources of BiasGender

In some languages there are differences between the vocabulary items used by women and men.

Women tend to use more of the standard forms than men do.

(Homes, 2001)


Background KnowledgeSchema TheoryReaders can fully comprehend what they read when their schema or prior

knowledge, is activated by the words on the page.

(Chandavimol, 1998)


Sources of Bias Studied

Gender: male and femalePrior Knowledge: Faculties they are studying.


Problem of the Assessment of Reading Courses•Regarding Reading I course, it is an elective course for

second – fourth year undergraduate students, King Mongkut’s University of Technology North Bangkok.

•The same reading tests are used to all students to evaluate their achievement. Therefore, the important judgment on students’ grade is up to both midterm and final tests.

•The quality of test is necessary to be evaluated. Although both Classical IA and IRT can help analyze the quality of test items, the issue of test bias cannot be neglected.

•Since students who possesses different background knowledge or even different genders may perform differently in each test item.

Research Questions

1. Are there any biased items in the reading tests when comparisons are made for Faculties and genders?

2. What is the quality of the reading tests after being analyzed by the statistical procedures (classical item analysis and Item Response Theory)?

3. What is the efficiency of the item bank software reported by the English instructors (both native and non-native)?

Research Objectives

1. To detect item bias in the reading tests when comparisons are made for Faculties (Engineering, Applied Science, Technical Education and Industrial Technology and Management) and genders (males and females);

2. To analyze the test items in the reading tests used for the English Reading course;

3. To develop the item bank software for managing the test items.

Significance

Regarding the analysis of test quality by both classical IA and IRT, it can provide the following advantages.1. Diagnostic feedback to test takers on how students performed on individual test tasks can be illustrated.2. The findings can provide feedback to teachers and course developers relevant to the improvement of instruction.3. Test developers and test writer will obtain feedback to improve the usefulness of the test, enabling the test developer to:

3.1 Control the characteristics of the total score distribution, specifically the level of difficulty of the test and the dispersion of test scores;

3.2 Increase the internal consistency reliability of test; and3.3 Diagnose why items fail to function appropriately.

SignificanceSince IRT can offer the advantages over classical IA, the

results obtained from IRT analysis possess the following significances.1. Item parameter estimates are independent of the group of examinees used.2. Test takers ability estimates are independent of the particular set of test items used.3. Precision of ability estimates is known.

In terms of the development of the item bank software, the following results will be gained.1. Test developers can easily build tests to measure objectives of interest.2. Test developers, within the limits of an item bank, can produce tests with the desired number of test items per objective.3. If item banks consist of content – valid and technically sound items, test quality will usually be better than test developers could produce if they were to prepare the test items themselves.

SignificanceThe item bias detection can lead to the following advantages.

1. Having a test writer provide the item containing content that is not different or unfamiliar to all students.2. Having a student gets the item correct or incorrect by his or her true ability.3. Test writers can provide the content of the item reflecting information and/or skills within the educational background of all students.4. Test writers can provide clues included in the item that would not facilitate the performance of students from one faculty over another.5. Test writers can provide adequacies or clarity in the test instructions, item stem, keyed response, or distractors.

Definitions of Terms 1. Item bias detection: Item bias detection in this study refers to the detection of the presence of

some characteristic of an item that results in differential performance for individuals of the same ability when comparisons are made in the following conditions:

1.1 when comparisons are made for the four Faculties: Engineering, Applied Science, Technical Education and Industrial Technology and Management

1.2 when comparisons are made for gender: males and females 2. Item bias detection methods: This study will detect the item bias according to both Classical IA

and IRT. 2.1 Regarding Classical IA, Delta Plot method and chi square technique are employed. 2.2 In terms of IRT, three-parameter model is used. Accordingly, item parameters that vary

across groups indicate Differential Item Functioning (DIF) or Item Bias. 3. Item analysis: This study will analyze the tests by being based on two main test theories,

Classical Item Analysis (IA) and Item Response Theory (IRT). The indices obtained from the two theories are as follows:

3.1 The indices obtained from Classical IA are: Item difficulty and Item discrimination. 3.2 The indices obtained from IRT are: a-parameter (discrimination), b-parameter

(difficulty) and c-parameter (guessing). 4. Text readability: Readability index derived from Fry Readability formula and Flesch Reading

Ease formula. 5. The efficiency of the item bank software: The efficiency of the item bank software is from the

opinions of the English instructors who use the software. They are required to respond to the questionnaire. In order to triangulate the data, the retrospective method using the semi-structured interview will be conducted with them.

MethodologyScope of the study

1. Population1.1 In terms of analyzing the quality of the reading tests, the

population is second-fourth year undergraduate students at King Mongkut’s University of Technology North Bangkok in the first semester of the academic

year 2008. The students study in the Faculties of Engineering, Applied Science, Technical Education and Industrial Technology and Management.

Typically, most are male, aged between 18 – 22. 1.2 Regarding the efficiency of the item bank software, the

population in this study is all the English instructors (both native and non-native instructors) from the Department of Languages, Faculties of Applied

Arts, King Mongkut’s University of Technology North Bangkok.2. Reading tests

Reading tests used in this study are the tests written for evaluating students’ learning achievement for the Reading I course. The tests are the

ones used for both midterm and final tests in the first semester of the academic year 2008.

Methodology

Phase I: The development and validation of the research instruments. The instruments used in this study can be divided into three main sets: 1) Reading Tests and 2) Item bank software 3) the questionnaire and the Retrospective Method.

Phase II: The implementation of the study Phase III: Analysis of the data and report

writing

Methodology Test Development

Phase 1: The development and validation of the research instruments.Stage 1: Design

Stage 2: Operationalization

Stage 3: Test administration

Bloom’s Taxonomy

Bloom’s Taxonomy(a hierarchy of abilities)

Reading comprehension skills

Knowledge level Pronoun reference

Finding specific information

Comprehension level Understanding explicit and implied information

Interpret ideas

Analysis level Making inferences, identifying components

Synthesis level Finding main idea

Finding topic/title

Guessing word meaning

Course Objectives1.Preview: Previewing to get an idea of what you will find in the text2.Scanning: Looking for specific information3.Skimming: Getting the general sense of a passage4.Using vocabulary knowledge for effective reading: Guessing word meaning in context5.Making inferences: Guessing about the text or the writer’s idea when some ideas are not directly stated.6.Finding topics: Identifying topics

Table of Test Specification for Reading I Midterm Test

Parts Texts Reading comprehension skills Item types Number of Items

1: Unit 1 (Preview) +Unit 2 (Scanning)

3-4 very short paragraphs(assessing both previewing and scanning at the same time)

- Previewing to get an idea of what you will find in the text- Looking for specific information

Short answer 77

Total 14

2: Unit 3 (Skimming) + Unit 6 (Finding topics)

4-5 very short paragraphs

- Getting the general sense of a passage- Identifying topics

Short answerMultiple choice (MC)

66

Total 12

3: Unit 5 (Making inferences)+ Unit 6 (Finding topics) +Unit 4 (Using vocabulary knowledge for effective reading)

A passage (350 – 400 words)

- Guessing about the text or the writer’s idea when some ideas are not directly stated.- Identifying topics- Guessing word meaning in context

MCMatching

MC

645

Total 15

4: Unit 5 (Making inferences)+ Unit 4 (Using vocabulary knowledge for effective reading)

A passage (350 – 400 words)

- Guessing about the text or the writer’s idea when some ideas are not directly stated.- Guessing word meaning in context

True/FalseMC

45

Total 9

Total 50

Proportion of the Test Items (based on Boom’s Taxonomy)

Units Bloom’s Taxonomy(a hierarchy of abilities)

Reading comprehension skills(According to Bloom’s Taxonomy)

1: Preview: Previewing to get an idea of what you will find in the text

Knowledge level 7 items Pronoun reference

2: Scanning: Looking for specific information

7 items Finding specific information

3. Skimming: Getting the general sense of a passage

Comprehension level

6 items Understanding explicit and implied information

- - Interpret ideas

5: Making inferences: Guessing about the text or the writer’s idea when some ideas are not directly stated.

Analysis level 10 items Making inferences, identifying components

- Synthesis level - Finding main idea

6: Finding topics: Identifying topics 10 items Finding topic/title

4: Using vocabulary knowledge for effective reading: Guessing word meaning in context

10 items Guessing word meaning

50 items

Phase II: The implementation of the study1. Research design 1.1 This study is conducted as a Research and Development

(R&D) project. Hence, the findings, which will be obtained from the systemic and objective analyzing method, can lead to the development of the quality of the language assessing instruments including an advance technology like item bank software.

1.2 The population of this study consists of two main groups: 1.2.1 The population used for trying out the tests in order to

analyze the test quality is second-fourth year undergraduate students from the Faculties of Engineering, Applied Science, Technical Education and Industrial Technology and Management. .

1.2.2 The population asked to evaluate the efficiency of the item bank software is all the English instructors (both native and non-native instructors) from the Department of Languages, Faculties of Applied Arts.

6 instructors will be randomly selected. Each instructor will be recorded about 10–15 minutes. All the reports will be transcribed. The data will be coded and decoded by the researchers.

2. Research procedures2.1 All the students who enroll in the Reading course will be

assigned to have the reading tests written for midterm and final tests.2.2 The students’ answer sheets will be collected to analyze the test

quality. The values obtained from the analysis are: the text readability, test reliability, item difficulty and item discrimination (from Classical IA), a-parameter, b-parameter and c-parameter (from IRT), item bias values obtained from Delta Plot method, Chi Square technique and 3-parameter model IRT. 2.3 The values obtained from 2.2 will be used to create the item bank software.

2.4 The English instructors will be asked to use the item bank software. Then the questionnaire will be given to evaluate its efficiency. A week after trying out the software, the retrospective method will be conducted in order to collect information about the efficiency of the software.

Phase III: Data Analysis In order to answer the research questions, the data will be analyzed

according to the following techniques.Research questions: 1. Are there any biased items in the reading

tests when comparisons are made for Faculties and genders?1. Mathcad will be used to detect the item bias by means of Delta Plot

method and IRT.2. SPSS will be implemented to analyze the item bias by means of Chi

Square technique.Research questions: 2. What is the quality of the reading tests after

being analyzed by the statistical procedures (classical item analysis and Item Response Theory)?

1. Regarding Classical IA, SPSS will be used to analyze the tests. Accordingly, test reliability (KR-20), item difficulty and item discrimination will be obtained.

2. In terms of IRT, XCALIBRE will be used. The indices obtained are a-, b- and c- parameters.

Research questions: 3. What is the efficiency of the item bank software reported by the English instructors (both native and non-native)?

1. In terms of the questionnaire used for evaluating the efficiency of the item bank software, mean and standard deviation are calculated.

2. Regarding the retrospective interview, the mode is used as a descriptive technique to examine the English instructors’ opinions. The highest frequency of the opinions will be reported.

Research questions: 1. Are there any biased items in the reading tests when comparisons are made for Faculties and genders?

1. Mathcad will be used to detect the item bias by means of Delta Plot method and IRT.

Delta-plot

• Major Axis: Y = bx+a

• slope b=



Delta-plot

• constant a =



Three-Parameter Model

Analyze the test items in order to get the three parameters:



Three-Parameter Model

Calculate the area of Item Characteristic Curve of each item.



Three-Parameter ModelCompare the area of Item Characteristic Curve of the same item obtained

from different groups.

Research questions: 1. Are there any biased items in the reading tests when comparisons are made for Faculties and genders?2. SPSS will be implemented to analyze the item bias by means of Chi Square technique.

Research questions: 1. Are there any biased items in the reading tests when comparisons are made for Faculties and genders?2. SPSS will be implemented to analyze the item bias by means of Chi Square technique.

Crosstab

1 29 18 48

100.0% 55.8% 78.3% 63.2%

0 23 5 28

.0% 44.2% 21.7% 36.8%

1 52 23 76

100.0% 100.0% 100.0% 100.0%

Count

% withinStudents' gender

Count


Count


0

1

Part 1- item 2:previewing and scanning

Total

0 male female

Students' gender

Total

Chi-Square Tests

4.058a 2 .131

4.554 2 .103

2.319 1 .128

76

Pearson Chi-Square

Likelihood Ratio

Linear-by-LinearAssociation

N of Valid Cases

Value dfAsymp. Sig.

(2-sided)

2 cells (33.3%) have expected count less than 5. Theminimum expected count is .37.

a.

ResultsTest Quality: IA Vs. IRT

IATest Reliability 8893= .

IRTTest Reliability ..8 84

IA Item Selecting CriteriaDifficulty Level = 0.2 -0.8Discrimination Index = .20 up

Number of good items36 of 50 itemsDifficulty Level ranged from .26 - .80.Discrimination Index was between .21 - .54

IRT Item Selecting Criteriaa-parameter(Discrimination) = a> 0.50b-parameter(Difficulty) = b + 3.0c-parameter(Guessing) = c<0.30

Number of good items49 of 50 itemsa-parameter(Discrimination) = .56 – 1.37b-parameter(Difficulty) = -2.41 – 3.00c-parameter(Guessing) = .17 - .26

Results Comparison was made for faculty

No. Delta Plot Chi Square IRT

1

2 2

3 3

4 4 4

5 5 5

6

7

8 8

Results

Biased Items Content Measured

Ability Measured Reading Topic Text Type

4 1. Knowledge Level: Scanning - Looking for specific information

The Bicycle Messenger and the Mysterious

Synopsis



Synopsis

10 1. Knowledge Level: Preview - Previewing to get an idea of what you will find in the text

Fish Stories General Science Article



22 4. Synthesis Level: Finding topics - Identifying topics

civilians Short News


wildlife Tourism Advertisement

37 3. Analysis Level: Making inferences - Guessing about the text or the writer’s idea when some ideas are not directly stated.

The internet addiction Social Science Article

Comparison was made for faculty


Biased Item Characteristics (faculty)

Ability Measured Reading Topic Text Type No. of Item No. of Biased Item

%

Level 1 Knowledge Level: Preview - Previewing to get an idea of what you will find in the text


Synopsis 2 0 0

Christmas Job Opportunities

Job Advertisement 1 0 0


2 1 50

Total 5 1 20



Level 1: Knowledge Level: Scanning - Looking for specific information


Synopsis 3 2 66.67

Christmas Job Opportunities Job Advertisement 3 0 0


3 1 33.34

Total 9 3 33.34



Level2: Comprehension Level: Skimming: - Getting the general sense of a passage

Suicide Blast Killed People

Short News 1 0 0

CEO’s plan to develop the company

Short News 1 0 0

Environmental problem caused by some chemical

Short News 1 0 0

Visiting a place in America with a European

Architecture Style

Tourism Advertisement

1 0 0

A New Type of Solar Energy Collector

Science and Technology

Article

1 0 0

A New Natural Wonders Named

Tourism Article 1 0 0

Total 6 0 0



Level 3: Analysis Level: Making inferences - Guessing about the text or the writer’s idea when some ideas are not directly stated.


6 1 16,67

The Best Foods You Aren’t Eating

Health Article from a Magazine

4 0 0

Total 10 1 10



Level 4: Synthesis Level: Finding topics - Identifying topics

a major restructuring of the company

Short News 1 0 0

civilians Short News 1 1 100

Spanish-colonial architecture Tourism Advertisement 1 0 0

wildlife Tourism Advertisement 1 1 100

sport activities Short News 1 0 0

Eight new natural wonders Tourism Article 1 0 0


4 0 0

Total 10 2 20

Level 4: Synthesis Level: Using vocabulary knowledge for effective reading - Guessing word meaning in context


5 0 0



5 0 0

Total 10 0 0


Reading Ability Levels (faculty)

Ability Measured No. of Items

No. of Biased Items

%

Level 1: Knowledge Level: Preview - Previewing to get an idea of what you will find in the text

5 1 20

Level 1: Knowledge Level: Scanning - Looking for specific information 9 3 33.34


6 0 0


10 1 10

Level 4: Synthesis Level: Finding topics - Identifying topics 10 2 20


10 0 0

Total 50 7 14

Results Comparison was made for faculty Biased Reading Topics (faculty)

Reading TopicNo. of Items

No. of Biased Items

%

1. The Bicycle Messenger and the Mysterious 5 2 40

2. Christmas Job Opportunities 4 0 0

3. Fish Stories 5 2 40

4. Suicide Blast Killed People 1 0 0

5. CEO’s plan to develop the company 1 0 0

6. Environmental problem caused by some chemical 1 0 0

7. Visiting a place in America with a European Architecture Style 1 0 0

8. A New Type of Solar Energy Collector 1 0 0

9. A New Natural Wonders Named 1 0 0

10. a major restructuring of the company 1 0 0

11. civilians 1 1 100

12. Spanish-colonial architecture 1 0 0

13. wildlife 1 1 100

14. sport activities 1 0 0

15. Eight new natural wonders 1 0 0

16. The internet addiction 15 1 100

17. The Best Foods You Aren’t Eating 9 0 0

Total 50 7 14


Biased Text Types (Faculty)

Reading Topic No. of Items

No. of

Biased

Items

%

1. Synopsis 5 2 40

2. Job Advertisement 4 0 0

3. General Science Article 5 2 40

4. Science and Technology Article 1 0 0

5. Short News 6 1 16.67

6. Tourism Advertisement 3 1 33.34

7. Tourism Article 2 0 0

8. Social Science Article 15 1 6.67

9. Health Article from a Magazine 9 0 0

Total 50 7 14

Results Comparison was made for gender

Compare Gender

Delta Plot Chi Square IRT

1

2

3

4 4

5

8

9

10

Results Comparison was made for genderGender Bias Content Measured

Ability Measured Reading Topic Text Type



Synopsis

16 2. Comprehension Level: Skimming: - Getting the general sense of a passage

CEO’s plan to develop the company Short News


civilians Short News

32 4. Synthesis Level: Using vocabulary knowledge for effective reading - Guessing word meaning in context







The Best Foods You Aren’t Eating Health Article from a Magazine






Biased Item Characteristics (Gender)

Ability MeasuredReading Topic Text Type No. of Item No. of

Biased Item

%

Level 1 Knowledge Level: Preview - Previewing to get an idea of what you will find in the text


Synopsis 2 0 0



2 0 0

Total 5 0 0



Synopsis 3 1 33.34



3 0 0

Total 9 1 11.12



Suicide Blast Killed People Short News 1 0 0

CEO’s plan to develop the company

Short News 1 1 100

Environmental problem caused by some chemical

Short News 1 0 0

Visiting a place in America with a European Architecture

Style

Tourism Advertisement 1 0 0

A New Type of Solar Energy Collector

Science and Technology Article

1 0 0

A New Natural Wonders Named

Tourism Article 1 0 0

Total 6 1 16.67



6 2 33.34



4 1 25

Total 10 3 30



a major restructuring of the company

Short News 1 0 0

civilians Short News 1 1 100

Spanish-colonial architecture


1 0 0

wildlife Tourism Advertisement

1 0 0

sport activities Short News 1 0 0

Eight new natural wonders Tourism Article 1 0 0


4 0 0

Total 10 1 10



5 1 20



5 2 40

Total 10 3 30


Reading Ability Levels (Gender)

Ability Measured No. of

Items

No. of

Biased

Items

%

Level 1: Knowledge Level: Preview - Previewing to get an idea of what you will find in the text

5 0 0


9 1 11.12


6 1 16.67


10 3 30

Level 4: Synthesis Level: Finding topics - Identifying topics 10 1 10


10 3 10

Total 50 9 18

Results Comparison was made for gender Biased Reading Topics (Gender)

Reading TopicNo. of Items

No. of Biased Items

%

1. The Bicycle Messenger and the Mysterious 5 1 20

2. Christmas Job Opportunities 4 0 0

3. Fish Stories 5 0 0

4. Suicide Blast Killed People 1 0 0

5. CEO’s plan to develop the company 1 1 100

6. Environmental problem caused by some chemical 1 0 0

7. Visiting a place in America with a European Architecture Style 1 0 0

8. A New Type of Solar Energy Collector 1 0 0

9. A New Natural Wonders Named 1 0 0

10. a major restructuring of the company 1 0 0

11. civilians 1 1 100

12. Spanish-colonial architecture 1 0 0

13. wildlife 1 0 0

14. sport activities 1 0 0

15. Eight new natural wonders 1 0 0

16. The internet addiction 15 3 20

17. The Best Foods You Aren’t Eating 9 3 33.34

Total 50 9 18


Biased Text Types (Gender)

Reading Topic No. of Items

No. of Biased Items

%

1. Synopsis 5 1 20

2. Job Advertisement 4 0 0

3. General Science Article 5 0 0

4. Science and Technology Article 1 0 0

5. Short News 6 2 33.34

6. Tourism Advertisement 3 0 0

7. Tourism Article 2 0 0

8. Social Science Article 15 3 20

9. Health Article from a Magazine 9 3 33.34

Total 50 9 18

Conclusion Prior Knowledge

(Faculty) BiasLevel 1 Knowledge Level: Preview - Previewing to get an idea of what you will find in the text

Text Type: General Science Article

Fish Stories


SynopsisLevel 1: Knowledge Level: Scanning - Looking for specific information


Civilians

Short News

Wild life


Conclusion

Gender BiasLevel 3: Analysis Level: Making inferences - Guessing about the text or the writer’s idea when some ideas are not directly stated.

Social Science Articles

Internet Addiction



Health Article from Magazine

Ex.1 Internet Addicts

The US could be rife with "internet addicts" who are as clinically ill as alcoholics, according to psychiatrists involved in a nationwide study. The study, carried out by researchers at Stanford University School of Medicine in California, US, indicates that more than one in eight US residents show signs of "problematic internet use". The Stanford researchers interviewed 2,513 adults in a nationwide survey. According to the study's lead author Elias Aboujaoude, the most disturbing result is the discovery that some people hide their internet surfing, or go online to cure foul moods – behavior that mirrors the way alcoholics behave. " And, obviously, something is wrong when people go out of their way to hide their internet activity," Aboujaoude says. ……………………….

Ex.2 The Best Foods You aren’t Eating

The Best Foods You Aren't EatingBy JONNY BOWDEN, Ph.D.

Although some guys aren't opposed to smoking some weed, most wouldn't think of eating one. It's a shame, really, since a succulent weed named purslane is not only delicious but also among the world's healthiest foods.

Guava; beets and cinnamon are among the super-healthful foods that you should probably be getting more of in your diet

Of course, there are many super foods that never see the inside of a shopping cart. Some you've never heard of, and others you've simply forgotten about. That's why we've rounded up the best of the bunch. Make a place for them on your table and you'll instantly upgrade your health -- without a prescription. …………………….

(item code assignments)(item instoration)(test generation)(test utilization)

Item Bank SoftwareSoftware Structure

MethodologyItem Bank Software

Toolbar

•Menu File


Toolbar

•Menu File

•Create Exam


Toolbar

•Menu File

•Create Exam

•Manage Form


Toolbar

•Menu File

•Create Exam

•Manage Form

•Help


•Create Exam


•Create Exam

•View Report


•Create Exam

•View Report

•Exit

Conclusion

Efficiency of the Item Bank Software (1st Trial)

Interface design

Easy to read

Unpleasant screen design Application

Very convenient to retrieve the test items

The storing process is complicated.

END OF THE PRESENTATION

SINCEREST THANKS

the item bias detection of the reading tests and the development of the item bank software

Documents

reading tests

issue of test bias

test administrationbias

quality of test items

different background

results of tests

students grade

classical item analysis