The research is about physical factors influencing students engagement and satisfaction with classroom environment. 14 factors retrieved from previous researches and the method is quantitative. the Pearson correlation shows a significant relationship between all factors and students engagement and satisfaction with classroom environment.
MULTIFILE
Objective In voice assessment, the evaluation of voice quality is a major component in which roughness has received wide acceptance as a major subtype of abnormal voice quality. The aim of the present study was to develop a new multivariate acoustic model for the evaluation of roughness. Method In total, 970 participants with dysphonia and 88 participants with normal voice were included. Concatenated voice samples of continuous speech and sustained vowel [a:] were perceptually judged on roughness severity. Acoustic analyses were conducted on the voiced segments of the continuous speech sample plus sustained vowel as well. A stepwise multiple linear regression analysis was applied to construct an acoustic model of the best acoustic predictors. Concurrent validity, diagnostic accuracy, and cross-validation were verified on the basis of Spearman correlation coefficient (rs), several estimates of the receiver operating characteristics plus the likelihood ratio, and iterated internal cross-correlations. Results Six experts were included for perceptual analysis based on acceptable rater reliability. Stepwise multiple regression analysis yielded a 12-variable acoustic model. A marked correlation was identified between the model and the perceptual judgment (rs = 0.731, P = 0.000). The cross-correlations confirmed a high comparable degree of association. However, the receiver operating characteristics and likelihood ratio results showed the best diagnostic outcome at a threshold of 2.92, with a sensitivity of 51.9% and a specificity of 94.9%. Conclusions Currently, the newly developed roughness model is not recommended for clinical practice. Further research is needed to detect the acoustic complexity of roughness (eg, multiplophonia, irregularity, chaotic structure, glottal fry, etc).
LINK
Purpose Over the last 5 decades, many acoustic measures have been created to measure roughness and breathiness. The aim of this study is to present a meta-analysis of correlation coefficients (r) between auditory-perceptual judgment of roughness and breathiness and various acoustic measures in both sustained vowels and continuous speech. Method Scientific literature reporting perceptual–acoustic correlations on roughness and breathiness were sought in 28 databases. Weighted average correlation coefficients (r w) were calculated when multiple r-values were available for a specific acoustic marker. An r w ≥ .60 was the threshold for an acoustic measure to be considered acceptable. Results From 103 studies of roughness and 107 studies of breathiness that were investigated, only 33 studies and 34 studies, respectively, met the inclusion criteria of the meta-analysis on sustained vowels. Eighty-six acoustic measures were identified for roughness and 85 acoustic measures for breathiness on sustained vowels, in which 43 and 39 measures, respectively, yielded multiple r-values. Finally, only 14 measures for roughness and 12 measures for breathiness produced r w ≥ .60. On continuous speech, 4 measures for roughness and 21 measures for breathiness were identified, yielding 3 and 6 measures, respectively, with multiple r-values in which only 1 and 2, respectively, had r w ≥ .60. Conclusion This meta-analysis showed that only a few acoustic parameters were determined as the best estimators for roughness and breathiness.
