eksplorasi gaya respons ekstrem dalam mengisi kuesioner

Clicks: 53
ID: 246485
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #11 of 17 articles by views in acta materialia turcica

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
This study aimed to apply the mixture Rasch Model Analysis techniques to identify the proportion of students who possess extreme response styles when completing the questionnaire. Total 2.981 high school students from 30 cities in 15 provinces were instructed to complete questionnaires measuring self-esteem. Self-Self-Esteem Scale consists of four self-reported sub-scales using Likert's model. Analysis suggest that based on how to respond to the scale, student in this study was grouped into three classes: extreme response style class, normal class, and mixture class. These numbers of class were consistent on all four sub-scales. The proportion of students who consistently gave an extreme response on four sub-scales was 4 percent; 6 percent was on three sub-scale, 13 percent on two sub-scales and 53 percent on one sub-scale. The small percentage of students who responded consistently gave an extreme responses suggest that high-school students appropriately choose an option response that represent their trait.
Reference Key
widhiarso2016jurnaleksplorasi Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Wahyu Widhiarso
Journal acta materialia turcica
Year 2016
DOI
10.22146/jpsi.8703
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.