Teaching and Learning arts in school: Perspectives of teachers and students in China

Teaching and Learning arts in school: Perspectives of teachers and students in China The discipline-based art education (DBAE) was implemented in schools as art can improve learners’ expressiveness and elaboration, creative ability (Burton, Horowitz, & Abeles, 2000), critical thinking (Geahigan, 1997; Lampert, 2006), and their learning in other subjects (Barby & Catterall, 1994). Although the Chinese education system has undergone continuous reform, discipline-based art education (DBAE) does not match the 1) speed of economic development, 2) the blueprint of constructing the quality-oriented educational system, as well as 3) the learning needs of students (Niu, 2005). Additionally, the prosperous art education market on the school outside mirrors the dissatisfaction of students and parents for the art education provided by the school curriculum (Li, 2018). This proposed qualitative case study aims to explore the learning experience of students enrolled in elementary schools in China to understand their perspectives and expectations of DBAE. The theoretical framework of this study is the environment and development of creativity.Eglinton (2003) proposes a theoretical model where art-making, encounters with art, and aesthetic experiences are integrated and equally weighted. Based on this model, The DBAE is important because schools can provide art aesthetic teaching, art-making experience, and an active learning atmosphere with students. This study focuses on the following three research questions: 1) How do students and their parents perceive their learning in art classes in school? 2) What factors affect their evaluation of the DBAE? 3) What expectations do they have for discipline-based art education? The participants in this study are elementary students who enrolled in elementary schools in Tianjin, China. All of these participants have experienced art instruction in school. Some of them have taken extra-curriculum art tutoring. Based on their experiences in terms of the time arrangement, course content, teaching pedagogy, and evaluation methods, a qualitative study for analyzing the deficiencies of DBAE will be conducted. The researcher will 1) survey participants to gather their demographic background and 2) interview them to obtain more in-depth information regarding their arts learning experience in school, including instructions they got, challenges they experienced, and expectations they have. In Canada, the DBAE is also threatened because of the rising impact of neoliberalism. According to Statistic Canada, only 46% of elementary schools reported that they have a music teacher, either full time or part-time in 2018. Only 16% of elementary schools with grades 7 or 8 reports having a visual arts teacher, and just 8% of schools have access to a specialist drama teacher (Arts education, 2018). The role of education is to provide an equal educational opportunity for students no matter where they live and what economic background they have. When students are not free to learn what they want, and teachers cannot carry out new pedagogies, education is not what it should be. With the economic globalization nowadays, there is a need for educators and to communicate and share educational experiences across a range of cultures and countries. It is my hope that this poster presentation will benefit the audience and provide a stepping stone for my future comparative research between Canada and China within this field

Implementation of Virtual Learning Community and Web 2.0 Technologies under COVID-19 Pandemic in High Education: Opportunities and Challenges

Educational systems worldwide are facing unprecedented challenges that have arisen due to the COVID-19 pandemic. In response to the pandemic, many higher education institutions suspended face-to-face courses and shifted to distance teaching and learning. This major paper reviews the challenges higher education institutions faced after the COVID-19 outbreak, the necessity of implementation of virtual learning communities, and the use of Web 2.0 technologies in teaching and learning. The findings indicate the implementation of virtual learning communities in higher education can reduce the sense of isolation, encourage interactions, and build a support network during the pandemic

Spatial variation in aragonite saturation state and the influencing factors in Jiaozhou Bay, China

Both natural processes and human activities affect seawater calcium carbonate saturation state (Ωarag), while the mechanisms are still far from being clearly understood. This study analysed the seawater surface Ωarag during summer and winter in Jiaozhou Bay (JZB), China, based on two cruises observations performed in January and June 2017. The ranges of Ωarag values were 1.55~2.92 in summer and 1.62~2.15 in winter. Regression analyses were conducted to identify the drivers of the change of Ωarag distribution, and then the relative contributions of temperature, mixing processes and biological processes to the spatial differences in Ωarag were evaluated by introducing the difference between total alkalinity (TA) and dissolved inorganic carbon (DIC) as a proxy for Ωarag. The results showed that biological processes were the main factor affecting the spatial differences in Ωarag, with relative contributions of 70% in summer and 50% in winter. The contributions of temperature (25% in summer and 20% in winter) and the mixing processes (5% in summer and 30% in winter) were lower. The increasing urbanization in offshore areas can further worsen acidification, therefore environmental protection in both offshore and onshore is needed

Unfolding-model-based visualization: theory, method and applications

Multidimensional unfolding methods are widely used for visualizing item response data. Such methods project respondents and items simultaneously onto a low-dimensional Euclidian space, in which respondents and items are represented by ideal points, with personperson, item-item, and person-item similarities being captured by the Euclidian distances between the points. In this paper, we study the visualization of multidimensional unfolding from a statistical perspective. We cast multidimensional unfolding into an estimation problem, where the respondent and item ideal points are treated as parameters to be estimated. An estimator is then proposed for the simultaneous estimation of these parameters. Asymptotic theory is provided for the recovery of the ideal points, shedding lights on the validity of model-based visualization. An alternating projected gradient descent algorithm is proposed for the parameter estimation. We provide two illustrative examples, one on users’ movie rating and the other on senate roll call voting

A note on likelihood ratio tests for models with latent variables

The likelihood ratio test (LRT) is widely used for comparing the relative fit of nested latent variable models. Following Wilks’ theorem, the LRT is conducted by comparing the LRT statistic with its asymptotic distribution under the restricted model, a χ 2 distribution with degrees of freedom equal to the difference in the number of free parameters between the two nested models under comparison. For models with latent variables such as factor analysis, structural equation models and random effects models, however, it is often found that the χ 2 approximation does not hold. In this note, we show how the regularity conditions of Wilks’ theorem may be violated using three examples of models with latent variables. In addition, a more general theory for LRT is given that provides the correct asymptotic theory for these LRTs. This general theory was first established in Chernoff (J R Stat Soc Ser B (Methodol) 45:404–413, 1954) and discussed in both van der Vaart (Asymptotic statistics, Cambridge, Cambridge University Press, 2000) and Drton (Ann Stat 37:979–1012, 2009), but it does not seem to have received enough attention. We illustrate this general theory with the three examples

A note on exploratory item factor analysis by singular value decomposition

We revisit a singular value decomposition (SVD) algorithm given in Chen et al. (Psychometrika 84:124–146, 2019b) for exploratory item factor analysis (IFA). This algorithm estimates a multidimensional IFA model by SVD and was used to obtain a starting point for joint maximum likelihood estimation in Chen et al. (2019b). Thanks to the analytic and computational properties of SVD, this algorithm guarantees a unique solution and has computational advantage over other exploratory IFA methods. Its computational advantage becomes significant when the numbers of respondents, items, and factors are all large. This algorithm can be viewed as a generalization of principal component analysis to binary data. In this note, we provide the statistical underpinning of the algorithm. In particular, we show its statistical consistency under the same double asymptotic setting as in Chen et al. (2019b). We also demonstrate how this algorithm provides a scree plot for investigating the number of factors and provide its asymptotic theory. Further extensions of the algorithm are discussed. Finally, simulation studies suggest that the algorithm has good finite sample performance