Teaching Pragmatics to Indonesian Learners of English

Pragmatic competence constitutes a significant factor in determining the success of communication. In real life interaction, a language learner is not only expected to use language and produce utterances which are understandable or grammatically correct, but is also expected to produce utterances which are socioculturally appropriate. However, for students who learn English as a Foreign Language (EFL), the pragmatic competence, which can actually be acquired naturally through social interaction, is quite difficult to acquire due to the limited, if not absent at all, use of English to reach a communication goal in an authentic social interaction/setting (not in a role-play classroom activity). This paper aims to figure out some of those issues of teaching pragmatics in EFL classrooms in Indonesia and to explore the possible solutions based on the concept and approaches informed by the previous studies. The importance of the use of authentic materials, input and production activity, along with understandable feedback are highlighted as some of the ways to fill the lacking space in EFL learners\u27 pragmatic knowledge.erimental class and controlled class. The mean score of post-test (77.3) in experimental class was greater than the mean score of post-test (71.9) in controlled class and from t-test, the researcher found that the value of t-test (3.176) was greater than t-table (2.000) at the level of significances. It means that this is a significant difference between the result of the students\u27 pre-test and post-test. Therefore, H0 was rejected and H1was accepted. Based on the finding and discussion of the research, the researcher had drawn a conclusion that the use of Small Group Discussion Strategy in Improvingthe student\u27s reading comprehension at the Eleventh Grade Students of SMA Negeri 11 Bulukumba was effective

Suppressing sensorimotor activity modulates the discrimination of auditory emotions but not speaker identity

Our ability to recognize the emotions of others is a crucial feature of human social cognition. Functional neuroimaging studies indicate that activity in sensorimotor cortices is evoked during the perception of emotion. In the visual domain, right somatosensory cortex activity has been shown to be critical for facial emotion recognition. However, the importance of sensorimotor representations in modalities outside of vision remains unknown. Here we use continuous theta-burst transcranial magnetic stimulation (cTBS) to investigate whether neural activity in the right postcentral gyrus (rPoG) and right lateral premotor cortex (rPM) is involved in nonverbal auditory emotion recognition. Three groups of participants completed same-different tasks on auditory stimuli, discriminating between the emotion expressed and the speakers' identities, before and following cTBS targeted at rPoG, rPM, or the vertex (control site). A task-selective deficit in auditory emotion discrimination was observed. Stimulation to rPoG and rPM resulted in a disruption of participants' abilities to discriminate emotion, but not identity, from vocal signals. These findings suggest that sensorimotor activity may be a modality-independent mechanism which aids emotion discrimination. Copyright © 2010 the authors

Computing Scalable Multivariate Glocal Invariants of Large (Brain-) Graphs

Graphs are quickly emerging as a leading abstraction for the representation of data. One important application domain originates from an emerging discipline called "connectomics". Connectomics studies the brain as a graph; vertices correspond to neurons (or collections thereof) and edges correspond to structural or functional connections between them. To explore the variability of connectomes---to address both basic science questions regarding the structure of the brain, and medical health questions about psychiatry and neurology---one can study the topological properties of these brain-graphs. We define multivariate glocal graph invariants: these are features of the graph that capture various local and global topological properties of the graphs. We show that the collection of features can collectively be computed via a combination of daisy-chaining, sparse matrix representation and computations, and efficient approximations. Our custom open-source Python package serves as a back-end to a Web-service that we have created to enable researchers to upload graphs, and download the corresponding invariants in a number of different formats. Moreover, we built this package to support distributed processing on multicore machines. This is therefore an enabling technology for network science, lowering the barrier of entry by providing tools to biologists and analysts who otherwise lack these capabilities. As a demonstration, we run our code on 120 brain-graphs, each with approximately 16M vertices and up to 90M edges.Comment: Published as part of 2013 IEEE GlobalSIP conferenc

Human listeners' perception of behavioural context and core affect dimensions in chimpanzee vocalizations

Vocalizations linked to emotional states are partly conserved among phylogenetically related species. This continuity may allow humans to accurately infer affective information from vocalizations produced by chimpanzees. In two pre-registered experiments, we examine human listeners' ability to infer behavioural contexts (e.g. discovering food) and core affect dimensions (arousal and valence) from 155 vocalizations produced by 66 chimpanzees in 10 different positive and negative contexts at high, medium or low arousal levels. In experiment 1, listeners (n = 310), categorized the vocalizations in a forced-choice task with 10 response options, and rated arousal and valence. In experiment 2, participants (n = 3120) matched vocalizations to production contexts using yes/no response options. The results show that listeners were accurate at matching vocalizations of most contexts in addition to inferring arousal and valence. Judgments were more accurate for negative as compared to positive vocalizations. An acoustic analysis demonstrated that, listeners made use of brightness and duration cues, and relied on noisiness in making context judgements, and pitch to infer core affect dimensions. Overall, the results suggest that human listeners can infer affective information from chimpanzee vocalizations beyond core affect, indicating phylogenetic continuity in the mapping of vocalizations to behavioural contexts