Non-Technical Skill Level of Electrical Engineering Undergraduates Using the Rasch Measurement Model

2020 ◽  
Vol 24 (5) ◽  
pp. 5388-5403
Author(s):  
Aini Najwa Azmi
Keyword(s):  
Electrical Engineering ◽  
Measurement Model ◽  
Rasch Measurement ◽  
Technical Skill ◽  
Skill Level ◽  
Rasch Measurement Model ◽  
Engineering Undergraduates

scholarly journals DEVELOPMENT AND VALIDATION OF A VOCATIONAL LEARNING STYLES INSTRUMENT USING THE RASCH MEASUREMENT MODEL

2019 ◽  
Vol 5 (1) ◽  
pp. 81-85
Author(s):  
Mazlili Suhaini
Keyword(s):  
Learning Styles ◽  
Measurement Model ◽  
Rasch Measurement ◽  
Technical Training ◽  
Validity And Reliability ◽  
The Past ◽  
Technology Students ◽  
Rasch Measurement Model ◽  
Vocational Learning ◽  
Development And Validation

Malaysia is considered one of the developing countries undergoing rapid economic development over the past five decades. As a developing country with a rapidly growing population, providing the citizens with comprehensive and updated knowledge is crucial for the country, particularly in vocational training. A number of vocational and technical training have been developed. However, the success of vocational education relies on the capability of instructors or teacher’s approach to achieve the goals. It is important to create appropriate method that take into consideration their students’ learning styles to get better outcome. Therefore, the purpose of this paper is to develop vocational learning styles instrument. Empirical evidence on the validity and reliability of modified items has been done. A survey of 57 Electrical Technology students were distributed. The Rasch measurement model was used to examine the functional items and detect the item and respondent reliability and index separation, the polarity of item, measuring the fit of item in measuring the construct and standardised residual correlation values.

scholarly journals Comparing item parameter estimates and fit statistics of the Rasch model from three different traditions

2020 ◽  
Vol 24 (1) ◽  
Author(s):  
Bahrul Hayat ◽  
Muhammad Dwirifqi Kharisma Putra ◽  
Bambang Suryadi
Keyword(s):  
Factor Analysis ◽  
Rasch Model ◽  
Measurement Model ◽  
Rasch Measurement ◽  
Item Parameter ◽  
Rasch Models ◽  
Rasch Measurement Model ◽  
Item Factor Analysis ◽  
The Rasch Model ◽  
Special Case

Rasch model is a method that has a long history in its application in the fields of social and behavioral sciences including educational measurement. Under certain circumstances, Rasch models are known as a special case of Item response theory (IRT), while IRT is equivalent to the Item Factor Analysis (IFA) models as a special case of Structural Equation Models (SEM), although there are other ‘tradition’ that consider Rasch measurement models not part of both. In this study, a simulation study was conducted to using simulated data to explain how the interrelationships between the Rasch model as a constraint version of 2-parameter logistic (2-PL) IRT, Rasch model as an item factor analysis were compared with the Rasch measurement model using Mplus, IRTPRO and WINSTEPS program, each of which came from its own 'tradition'. The results of this study indicate that Rasch models and IFA as a special case of SEM are mathematically equal, as well as the Rasch measurement model, but due to different philosophical perspectives people might vary in their understanding about this concept. Given the findings of this study, it is expected that confusion and misunderstanding between the three can be overcome.

scholarly journals Student Perspective on Technology Enabled/Enhanced Active Learning in Educational: Rasch Measurement Model

2020 ◽  
Vol 16 (06) ◽  
pp. 34
Author(s):  
Nur Farha Hassan ◽  
Saifullizam Puteh ◽  
Amanina Muhamad Sanusi ◽  
Nor Hartini Che Mohamad Zahid
Keyword(s):  
Pilot Study ◽  
Active Learning ◽  
Engineering Students ◽  
Industrial Revolution ◽  
Measurement Model ◽  
Rasch Measurement ◽  
Technology In Education ◽  
Validity And Reliability ◽  
Survey Question ◽  
Rasch Measurement Model

Nowadays, the industrial revolution 4.0 had given a great impact on education. An active environment which applied technology in education can developed multiple skills in students. Technology Enabled/Enhanced Active Learning (TEAL) is one of the active environments that used technology in education. TEAL is the combination of several active learning domains which enhances students' understanding of learning and built job-related skills. However, students have lack of knowledge in their field which led to increase in unemployment of students. Hence, TEAL can help students in perform their practical works to develop knowledge and skills in students. This pilot study was distributed survey question about create an active and effective environment using TEAL application among the engineering students. The survey is consisted of 141 items and was distributed to 40 respondents. This pilot study used Rasch Measurement Model for measuring the validity and reliability of survey questions. Winsteps software is used to check the functionality of the item in terms of (i) Reliability and separation of respondents - items; (ii) detect the polarity items of PTMEA CORR Value; (iii) the item fit based on MNSQ Value; and (iv) Determine the dependent items based on the standardized residual value measurement correlation. The final result 109 items is suitable to use for measurement of the real study in future work.

Measuring Self-Service Technology Latent Difficulties: Insurance Decisions on Utilitarian and Hedonic Influences

2015 ◽  
Vol 9 (1) ◽  
pp. 1-33 ◽  
Author(s):  
Ann Shawing Yang
Keyword(s):  
Measurement Model ◽  
Rasch Measurement ◽  
High Income ◽  
Middle Aged ◽  
Rasch Measurement Model ◽  
Expectation Disconfirmation ◽  
Self Service ◽  
Self Service Technology ◽  
Insurance Decisions

AbstractThis study investigates the difficulties encountered by consumers in forming insurance decisions when using self-service technology (SST) channels, such as electronic insurance. Rasch measurement model is applied. This model employs the expectation disconfirmation theory to categorize and rank the order of importance of latent utilitarian and hedonic insurance purchase motives. Consumers find that electronic insurance has high risks and high premiums with respect to utilitarian motives but lacks information and performs unsatisfactorily in terms of hedonic motives. Nevertheless, electronic insurance is preferred for the convenience brought by SST channels, and because it provides greater discounts and offers product–channel matching through self-consultation in the absence of agents. Being middle-aged and having a high income are factors that significantly influence electronic insurance purchases.

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