Can EFL Speakers Communicate in English-mediated Classes?: A Case of a Liberal Arts Class for Engineering Students in Korea

The purpose of this paper is twofold: (1) to explore what factors prevent English as a foreign language (EFL) students from participating in English-medium instruction classes; and (2) to examine how dialogic teaching techniques enhance students’ participation in classroom interaction. Utilizing the notions of “communicative competence” and “truncated repertoire,” we first investigated the barriers to communication in classrooms. We next examined how EFL speakers are able to communicate in English-medium instruction (EMI) classes. The findings suggest that when the instruction was designed to reduce cultural barriers and to facilitate authentic discussion, EFL students were able to participate in classroom interaction, and they perceived discussion as a way to learn an unfamiliar subject taught in English.     

Designing a business model for financial products for cultural heritage in the Korean market

There are many contingent valuation (CV) studies to estimate the economic benefits of cultural heritage, but few provided advice on the design of financial products for cultural heritage assets. This paper conducted conjoint and willingness-to-pay (WTP) analyses for providing the design implication of these financial products. We calculated WTP for each attribute. The result of conjoint analysis shows that people prefer a short period of investment, high-expected rate of return and small amount of money invested. Only the amount invested and the rate of return on investment are significant to estimate WTP for these financial products.     

Naturalistic intervention for Asperger syndrome – a case study

On the basis of their cognitive abilities, children with Asperger syndrome are attractive candidates for inclusive education and, in Australia, most are in integrated settings. However, social interaction between children with Asperger syndrome and their peers remains problematic, with the children with Asperger syndrome often being left alone despite being among or near classmates. For classroom teachers, effective interventions in terms of class management are critical to facilitate positive social interaction between these two groups of children, and case studies can tell us a great deal about what works. In practice, a combination of intervention techniques may be best, in case a single one is ineffective, and in order to take advantage of potential synergies. In this article, Serene Choi, of the School of Education at the University of Newcastle (Australia) and Timo Nieminen, of the Centre for Biophotonics and Laser Science in the Department of Physics at the University of Queensland, report a naturalistic multiple-component intervention used to develop the social skills of a boy with Asperger syndrome in a mainstream school in Australia. This combined intervention, making use of social stories, simple peer modelling and individual lessons, appears to be a practical teaching method for inclusive education.     

Self-efficacy for self-regulated learning, academic self-efficacy, and internet self-efficacy in web-based instruction

Effects of student motivation on performance in Web-based instruction (WBI) were examined. In particular, applicability of the self-efficacy theory to WBI contexts was tested. A total of 152 junior high school students in Seoul, Korea, participated in WBI during regular science classes. Participants completed motivational surveys before the onset of WBI and took the written and search tests at the end of WBI. Path analyses revealed that students' self-efficacy for self-regulated learning positively related to their academic self-efficacy, strategy use, and Internet self-efficacy. Academic self-efficacy predicted students' performance on the written test, which comprised problems on topics covered during the previous WBI sessions. Students' scores on the WBI search test were significantly and positively predicted by their self-efficacy in using the Internet. More interesting, students' academic self-efficacy beliefs were not able to predict their search test performance, whereas students' Internet self-efficacy beliefs were not able to predict their written test performance.This research is based on data collected as part of Ha-Jeen Choi's master's thesis completed at Ewha Womans University.The authors thank Steven Ross and three anonymous reviewers for their helpful comments on earlier versions of this article.     

Age Differences in Online Social Networking: Extending Socioemotional Selectivity Theory to Social Network Sites

This article extends socioemotional selectivity theory to online social networking by examining age differences in the size and composition of Facebook networks across a wide age range of Facebook users (18 to 93 years old) in a nationally representative sample. Findings suggest increasing selectivity of Facebook social partners with age. Compared to younger adults, friend networks of older adults are smaller but contain a greater proportion of individuals who are considered to be actual friends. Moreover, a higher proportion of actual to total Facebook friends is associated with lower levels of social isolation and loneliness across the life span.     

Jamming and unjamming transition of oil-in-water emulsions under continuous temperature change

To analyze the jamming and unjamming transition of oil-in-water emulsions under continuous temperature change, we simulated an emulsion system whose critical volume fraction was 0.3, which was validated with experimental results under oscillatory shear stress. In addition, we calculated the elastic modulus using the phase lag between strain and stress. Through heating and cooling, the emulsion experienced unjamming and jamming. A phenomenon—which is when the elastic modulus does not reach the expected value at the isothermal system—occurred when the emulsion system was cooled. We determined that this phenomenon was caused by the frequency being faster than the relaxation of the deformed droplets. We justified the relation between the frequency and relaxation by simulating the frequency dependency of the difference between the elastic modulus when cooled and the expected value at the same temperature.     

Estimation fusion of nonlinear cost functions with application to multisensory Kalman filtering

This paper focuses on four fusion algorithms for the estimation of nonlinear cost function (NCF) in a multisensory environment. In multisensory filtering and control problems, NCF represents a nonlinear multivariate functional of state variables, which can indicate useful information of the target systems for automatic control. To estimate the NCF using multisensory information, we propose one centralized and three decentralized estimation fusion algorithms. For multivariate polynomial NCFs, we propose a simple closed-form computation procedure. For general NCFs, the most popular procedure for the evaluation of their estimates is based on the unscented transformation. The effectiveness and estimation accuracy of the proposed fusion algorithms are demonstrated with theoretical and numerical examples.     

Adaptive relevance feedback method of extended Boolean model using hierarchical clustering techniques

The relevance feedback process uses information obtained from a user about a set of initially retrieved documents to improve subsequent search formulations and retrieval performance. In extended Boolean models, the relevance feedback implies not only that new query terms must be identified and re-weighted, but also that the terms must be connected with Boolean And/Or operators properly. Salton et al. proposed a relevance feedback method, called DNF (disjunctive normal form) method, for a well established extended Boolean model. However, this method mainly focuses on generating Boolean queries but does not concern about re-weighting query terms. Also, this method has some problems in generating reformulated Boolean queries. In this study, we investigate the problems of the DNF method and propose a relevance feedback method using hierarchical clustering techniques to solve those problems. We also propose a neural network model in which the term weights used in extended Boolean queries can be adjusted by the users’ relevance feedbacks.     

Using growth models to monitor school performance: comparing the effect of the metric and the assessment

This paper investigates whether inferences about school performance based on longitudinal models are consistent when different assessments and metrics are used as the basis for analysis. Using norm-referenced (NRT) and standards-based (SBT) assessment results from panel data of a large heterogeneous school district, we examine inferences based on vertically equated scale scores, normal curve equivalents (NCEs), and nonvertically equated scale scores. The results indicate that the effect of the metric depends upon the evaluation objective. NCEs significantly underestimate absolute individual growth, but NCEs and scale scores yield highly correlated (r >.90) school-level results based on mean initial status and growth estimates. SBT and NRT results are highly correlated for status but only moderately correlated for growth. We also find that as few as 30 students per school provide consistent results and that mobility tends to affect inferences based on status but not growth – irrespective of the assessment or metric used.