scholarly journals Exploring Tertiary ESL learners’ Affective Attributes Toward Online Reading

2021 ◽  
Vol 10 (2) ◽  
pp. 137
Author(s):  
Kangxing Dong ◽  
Chiam Kee Swan ◽  
Hafizoah Kassim
Keyword(s):  
Higher Education ◽  
Principal Components Analysis ◽  
Survey Data ◽  
Principal Components ◽  
Self Report ◽  
Online Reading ◽  
Affective Factors ◽  
New Knowledge ◽  
Components Analysis ◽  
Esl Learners

The Covid-19 pandemic has significantly accelerated digitization of higher education worldwide and reading online has become vital for students to grasping new knowledge and understanding course contents. As educators, it is important to understand our students’ affective attributes towards the new normal of reading online. Within this scope, the study aims to develop a self-report instrument on affective attributes towards online reading among tertiary ESL learners, and to examine the specific affective attributes students display towards online reading. The Survey of Online Reading Affective Attributes was adapted and developed to measure tertiary ESL learners’ affective attributes towards online reading for academic and study-related purposes. This questionnaire was administered to 130 tertiary ESL learners. Principal components analysis was performed and the results confirmed the three affective factors were self-efficacy, motivation, and anxiety. In addition, the analysis of the survey data revealed that the majority of students, in general, were relatively self-efficacious, motivated, and less anxious towards online reading. However, it was discovered that nearly one-third of students were relatively anxious towards online reading and one-fifth of them were less self-efficacious. The limitations of this study and pedagogical recommendations are further discussed in this paper.

Another Femininity Scale?

1994 ◽  
Vol 75 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Katherine S. Greene ◽  
Malcolm D. Gynther
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Self Report ◽  
Personal Attributes ◽  
Initial Sample ◽  
Common Variance ◽  
Good Internal Consistency ◽  
Components Analysis ◽  
Personal Attributes Questionnaire ◽  
Test Retest Reliability

The construction and validation of the Behavioral Self-report of Femininity is described. An initial sample of 32 male and 63 female undergraduates indicated the frequency of engaging in 91 “feminine” behaviors. The 59 items which showed good internal consistency as well as differentiation between genders were retained. Test-retest reliability over a 2-wk. period was .90. Convergent and discriminant validities were examined by comparing our results with those obtained from the Hyperfemininity Scale and the Personal Attributes Questionnaire. Responses of women in traditional and nontraditional majors were significantly different, indicating good within-sex validity. Finally, a principal components analysis identified six primary factors, accounting for 60% of common variance.

Principal Components Analysis as a Tool for Interpreting Nure Aerial Radiometric Survey Data

1980 ◽  
Vol 88 (1) ◽  
pp. 57-67 ◽  
Author(s):  
Fredric L. Pirkle ◽  
Katherine Campbell ◽  
George W. Wecksung
Keyword(s):  
Principal Components Analysis ◽  
Survey Data ◽  
Principal Components ◽  
Radiometric Survey ◽  
Components Analysis

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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