1a introduction to rasch measurement model msm

Introduction to Rasch Measurement Model

Intangible Measurement

231804-P

Mohd Saidfudin MasodiMeasurement and Psychometry

Integrated Advance Planning Sdn. [email protected]

+60 1240 2821

2

The Speaker: An introduction…

MOHD SAIDFUDIN MASODI, B. Arch. (Aust.); IRCA (Lon.)ISO QMS Lead Assessor, Measurement / Psychometry Consultant

Trained by Nigel Bauer Ltd., UK and Rheinisch-Westfalischer Technischer Uberwachungsverein A.G. International (RWTUV, Germany) and AOTS Japan with wide experience in conducting assessment in local and multi-national corporate organisations specifically the institutions of higher learning.

Expertise: Rasch measurement and probabilistic statistical methods, Quality Audit.

Research Area: Measurement, evaluation and Statistical Analysis in (MESA) Learning Outcomes (LO) and learning culture in institution of higher learning using Bloom’s & SOLO Taxonomy.

Publications: Co-published 3 book chapters, eight monographs, and over 30 international conference proceedings and articles in prime international refereed journals i.e.IEEExplore, WSEAS Transactions, NAUN etc.

Special Appointments: Member in the Board of Study for the programs International Labour Organisation, Executive Management Program, Master in Protective Security Management, IIUM; GiatMARA and Human Resource Dept, State of Sabah .

Other credentials: Best Paper Award in ICEED 2009 (Eng’g Education)Best Visiting Lecturer UTM_SPACE 2007, 2008. Invited as plenary speaker in several international conferences and many faculty talks. Conduct training and short courses regularly; in area of Strategic Planning using Blue Ocean Strategy and Balanced Score Card, Testing & Evaluation and KPIQMS Internal Audit and QA/QC in the manufacturing industry.

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M O D U L E - 2

I N T R O D U C T I O N TO RASCH UNIDIMENSIONAL

MEASUREMENT MODEL


+60 1240 2821

03:37 PM 4

• A concept of Probalilistic Model • Construct of the Logit Ruler• Rasch Theorems• Cognisance of Responses Pattern• Q & A Session

PRESENTATION STRUCTURE


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Research MotivationIn developing quality education, we need to improve our teaching and learning outcomes (LO) hence measurement. In any measurement, there must be an instrument.

•What is the instrument to measure LO?

•What is the unit for this measurement?

•Is the Instrument Construct valid?

Mohd Saidfudin MasodiMohd Saidfudin Masodi+60122402821+60122402821

[email protected]@gmail.com

03:37 PM 6

Problem Statement

• Social scientists have great need for the development of valid measures, e.g., of the quantity and quality of services and of the outcomes of those services.

• Many researchers are frustrated when existing instruments are not well tailored to the task, since they then cannot expect sensitive, accurate, or valid findings. Limitations of traditional statistics abound.



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Introduction to Rasch Measurement

• This presents a theorem of "modern" measurement as practiced using item response theory with a focus on Rasch Unidimensional Measurement Model (RUMM) .

• Rasch analysis provides the social sciences with the kind of measurement that characterises measurement in the natural sciences; the field of metrology.



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Introduction to Rasch Measurement• Since item response theory focuses on the items

and the persons rather than the test score, the synthesis of quantitative analysis with qualitative issues is experienced in a way that is rare in social science.

• Ultimately, RUMM can facilitate more efficient, reliable, and valid assessment while improving privacy and convenience to users.

• This workshop is useful for anyone who wants to understand the role of modern measurement in research.



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Introduction to Rasch Measurement

• Evaluation using raw score in Traditional Test Method is rather superficial and intractable. Marks are orderly data on a continuum scale; deemed non-parametric.

• Rasch Measurement is a probabilistic model uses ‘logit’ as the measurement unit, transforms these ordinal data and raw scores into ratio data hence a linear correlation.

• It offers new dimension of qualitative data analysis quantitatively.



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W H A T I SM E A S U R E M E N T ?• INSTRUMENT• CONSTRUCT• UNIT QUANTITY• LINEAR OF EQUAL INTERVAL• REPLICABLE• PREDICTIVE



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A valid measurement must meet five (5) criteria:

Measurement of Psychological Construct

1. Linear Scale: AMOUNT

2. Reasonable numerical values: ACCURACY

3. Empirical Coherence: Response, Item and Construct VALIDITY

4. Incorporate parameter separation: REPLICABLE

5. Overcome missing data: PREDICTIVE(Wright & Mok, 2004)



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D E F I N I T I O N OF M E A S U R E M E N T

ONLY RASCH MEASUREMENT MODEL

MEET ALL THESE REQUIREMENTS



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Georg Rasch (1901-1980)

Concept: Liken Person’s Ability and Height of High Jump Bar

Person’s Ability Varying height The higher, the more difficult

Developing a Measurement Construct

B-DIFFICULTA-EASY

In any measurement endeavour, the aim is to put enough stepping stones along the path to represent all the stepping points useful for the measurement purposes; from little to much development.

(Bond & Fox, 2001)



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Rasch Model: Provide Ruler Measuring a Construct (e.g. Jumper and Bar)

More able; stronger jumper

Less able; weaker jumper

Higher bar

Lower bar

When we have:1. Valid items2. Valid responses3. Items that can separate

persons along a continuum of ability4. Sufficient number of items; and5. Items that behave according to theoretical expectationThen, we can be sure thatthe measurement isvalid & reliable (Bond & Fox, 2001)

Rasch Theorem: In order to assess persons ability, the measure must be of equal interval on a linear scale.



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e.g. On a graduation day, what is the likelihood of a lady liking a piece of rose as your giving ? Perhaps 30:70Compare if you send a bouquet instead. It increases to 60:40; and so forth if you put a Fererro Roche.. the chances gets better.

1090

In Rasch Model, a turn of event is seen as a chance; a likelihood of happenings hence a ratio.

Rasch Unidimensional Ruler

10-2

-2

3070

6040

5050

991

199

100 102

0 2-1 1

indices

logit

Now, we already have an instrument with a unit termed ‘logit’.



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Q1 Q15 Q16 Q30 Q31 Q50

10111011111111111 11111111111111111 111111111111001 = 48

1010010001111111 11111111111111111 111111111011111 = 43

10111111111111111 1110111111100100 01101010001101 = 33

10111111111011111 1111111111010100 10110100000011 = 33

10110111111111111 1011111101001110 00010000100001 = 33

10111111111111111 111101100100010 01000000000001 = 27

10111111111111101 110101000100010 00000000001001 = 24

Student.1

1. But, atypical test result tabulation only rank the students from the highest score in descending order

2. Need to assess beyond raw score. Rasch sorts further according to response pattern in descending order; called ‘Guttman scale’.

Rasch Model Measurement Theorem



Student.7

S-03

S-05

EASY ITEMS Q3 q6 Q1 Q7 Q5

DIFFICULT ITEMS Q4 Q2

11111011111111111 11111111111111111 11111111111100 = 48

11000011111111111 11111111111111111 11111111111100 = 43

111111111111111 1 1111111111110011 11100010000000 = 33

111110111111111111 0111111111101001 00110100000000 = 33

11111010011101101 1011111111111101 00110100101010 = 33

11111111111111110 0111011101000100 010000 0000000 = 27

11111111111111101 1101110100100100 00000000000100 = 24

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SMART

POOR

T1. Persons who are more able / more developed have a greater likelihood of correctly answer all the items / able to complete a given task.

T2. Easier items / task are more likely to be answered correctly by all persons.

7 6 4 3 0

Rasch Model Measurement Theorem



TOTAL RESPONSE

S-01

S-07

S-05

S-03

5

S-02

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Rasch Measurement Model Theorem

Two (2) propositions appears:1. Persons who are more able / more developed have a greater likelihood of correctly answer all the items / able to complete a given task.

2. Easier items / task are more likely to be answered correctly by all persons.

Person AbilityPr (Success )Difficulty of a given task= -

In summary; the additive correlation is:



1a introduction to rasch measurement model msm

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