The ability of Islamic Religious Education to deliver Citizenship Education in elementary schools in the Kingdom of Saudi Arabia

This empirical study endeavours to shed light on the ability of Islamic Religious Education to deliver Citizenship Education in elementary schools (pupils aged 13 to 15) in the Kingdom of Saudi Arabia. The aims of the study are to explore teachers’ and students’ perceptions of the knowledge, skills, values and attitudes that Saudi citizens need in the 21st century. As part of this, it investigates the views of Social Studies and Islamic Religious Education teachers and students with a view to understanding where in the curriculum they think Citizenship Education should best occur. The study identifies and explores the challenges and opportunities of including Citizenship Education within both Islamic Religious Education and Social Studies. The merits of each approach are discussed. There then follows a series of recommendations regarding the sort of changes to the curriculum that may be required. The research underpinning this study followed a mixed-method approach. It employed an closed-ended questionnaire with two parts of open questions completed by over 266 students (ages 13 to 15), and 20 Islamic Religious Education and 20 Social Studies teachers. Semi-structured interviews were also undertaken with nine students, and nine Islamic Religious Education and nine Social Studies teachers. The findings from this study indicate that participants linked many of the knowledge components, skills, values and attitudes associated with Saudi citizenship to the Islamic religion. Responses from the participants indicate that students’ voices are absent in school, as they are anxious about expressing their opinions and believe their sole purpose for coming to school is to acquire knowledge. In addition, this study provides evidence of different views amongst the participants that reflect current tensions in the Kingdom of Saudi Arabia regarding tolerance, outside influences, faith and extremism. Many students, for example, appeared to be intolerant towards other faiths or ideas, which is arguably not in accordance with the Islamic religion. The study argues that, as it is currently taught, Citizenship Education in the Kingdom of Saudi Arabia can be perceived as limited in comparison to Western conceptions of Citizenship Education, and that it is not meeting the needs of future Saudi citizens. The study proposes that the Kingdom of Saudi Arabia needs to change its education system to keep pace with change in the wider world and within Saudi society, and concludes by making recommendations for such change and for future research in Islamic Religious Education and Citizenship Education

Association between shammah use with periodontal disease and shammah-induced leukoplakia-like lesion among adult males in dawn valley, Yemen

Background: The traditional type of smokeless tobacco (SLT) used in the Arabian Peninsula, especially common in Yemen is called shammah. Shammah and other risk factors play an important role in development of oral diseases. Objectives: The present study has been undertaken to determine the prevalence of shammah use and to determine the association between shammah use with periodontal disease and oral leukoplakia-like lesions. Other associated factors with periodontal disease as well as with oral leukoplakia-like lesions were also determined. Materials and Methods: A cross sectional study was conducted on 346 randomly selected adult males. Multistage random sampling was used to select the study location. After completing the structured questionnaire interviews, all the participants underwent clinical exanimation for periodontal health status and oral leukoplakia-like lesions. Periodontal status was recorded using the Community Periodontal Index (CPI). Clinical features of oral leukoplakia- like lesions were characterized based on the grades of Axéll et al. (1976). Chi-square test was used for assessing significant differences in shammah status in respect to periodontal disease and oral leukoplakialike lesions. Univariable logistic regression and multivariable logistic regression were selected for assessing potential associated factors. Results: Out of 346 male participants aged 18 years and older, 68 reported being current shammah users. The prevalence of current shammah use was 19.7% (95% CI: 15.6%, 24.2%). Chi-square test detected that significant differences exists between the study groups (i.e., never, former, and current shammah users) in respect to the presence of periodontal disease (P= 0.001) as well as to the presence of oral leukoplakia-like lesion (P=0.001). Multivariable logistic regression analysis revealed that age, family income, former shammah user, current shammah user, and annual duration of shammah use were statistically associated with the presence of periodontal disease [Adjusted odds ratio (AOR)= 1.05; 95% CI: 1.03, 1.07; P= 0.001], (AOR= 2.01; 95% CI: 1.16, 3.47; P= 0.012), (AOR= 2.92; 95% CI: 1.20, 7.10; P= 0.018), (AOR= 7.25; 95% CI: 3.84, 13.70; P= 0.001), and (AOR= 2.19; 95% CI: 1.47, 3.24; P= 0.001), respectively. The multivariable analysis also revealed that age, no formal or primary level of education, former shammah user, current shammah user, and frequency of shammah use per day were statistically associated with the presence of oral leukoplakia-like lesion ( AOR= 1.03; 95% CI: 1.01, 1.06; P= 0.006), (AOR= 8.65; 95% CI: 2.81, 26.57; P= 0.001), (AOR= 3.65; 95% CI: 1.40, 9.50; P= 0.008), (AOR= 12.99; 95% CI: 6.34, 26.59; P= 0.001), and (AOR= 1.17; 95% CI: 1.02, 1.36; P= 0.026), respectively. Conclusion: The results revealed that periodontal disease and oral leukoplakia-like lesions were significantly associated with shammah use. Therefore, it is important to develop comprehensive shammah prevention programmes in Yemen

The Kumaraswamy Generalized Power Weibull Distribution

A new family of distributions called Kumaraswamy-generalized power Weibull (Kgpw) distribution is proposed and studied. This family has a number of well known sub-models such as Weibull, exponentiated Weibull, Kumaraswamy Weibull, generalized power Weibull and new sub-models, namely, exponentiated generalized power Weibull, Kumaraswamy generalized power exponential distributions.  Some statistical properties of the new distribution include its moments, moment generating function, quantile function and hazard function are derived. In addition, maximum likelihood estimates of the model parameters are obtained. An application as well as comparisons of the Kgpw and its sub-distributions is given.   Keywords: Generalized power Weibull distribution, Kumaraswamy distribution, Maximum likelihood estimation, Moment generating function, Hazard rate function.

Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings

Models of acoustic word embeddings (AWEs) learn to map variable-length spoken word segments onto fixed-dimensionality vector representations such that different acoustic exemplars of the same word are projected nearby in the embedding space. In addition to their speech technology applications, AWE models have been shown to predict human performance on a variety of auditory lexical processing tasks. Current AWE models are based on neural networks and trained in a bottom-up approach that integrates acoustic cues to build up a word representation given an acoustic or symbolic supervision signal. Therefore, these models do not leverage or capture high-level lexical knowledge during the learning process. In this paper, we propose a multi-task learning model that incorporates top-down lexical knowledge into the training procedure of AWEs. Our model learns a mapping between the acoustic input and a lexical representation that encodes high-level information such as word semantics in addition to bottom-up form-based supervision. We experiment with three languages and demonstrate that incorporating lexical knowledge improves the embedding space discriminability and encourages the model to better separate lexical categories.Comment: Accepted in INTERSPEECH 202

Cross-Domain Adaptation of Spoken Language Identification for Related Languages: The Curious Case of Slavic Languages

State-of-the-art spoken language identification (LID) systems, which are based on end-to-end deep neural networks, have shown remarkable success not only in discriminating between distant languages but also between closely-related languages or even different spoken varieties of the same language. However, it is still unclear to what extent neural LID models generalize to speech samples with different acoustic conditions due to domain shift. In this paper, we present a set of experiments to investigate the impact of domain mismatch on the performance of neural LID systems for a subset of six Slavic languages across two domains (read speech and radio broadcast) and examine two low-level signal descriptors (spectral and cepstral features) for this task. Our experiments show that (1) out-of-domain speech samples severely hinder the performance of neural LID models, and (2) while both spectral and cepstral features show comparable performance within-domain, spectral features show more robustness under domain mismatch. Moreover, we apply unsupervised domain adaptation to minimize the discrepancy between the two domains in our study. We achieve relative accuracy improvements that range from 9% to 77% depending on the diversity of acoustic conditions in the source domain.Comment: To appear in INTERSPEECH 202

An Information-Theoretic Analysis of Self-supervised Discrete Representations of Speech

Self-supervised representation learning for speech often involves a quantization step that transforms the acoustic input into discrete units. However, it remains unclear how to characterize the relationship between these discrete units and abstract phonetic categories such as phonemes. In this paper, we develop an information-theoretic framework whereby we represent each phonetic category as a distribution over discrete units. We then apply our framework to two different self-supervised models (namely wav2vec 2.0 and XLSR) and use American English speech as a case study. Our study demonstrates that the entropy of phonetic distributions reflects the variability of the underlying speech sounds, with phonetically similar sounds exhibiting similar distributions. While our study confirms the lack of direct, one-to-one correspondence, we find an intriguing, indirect relationship between phonetic categories and discrete units.Comment: Accepted in Interspeech 202