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The purpose of this study is to investigate the effectiveness of diagrammatic visualisation techniques versus sentential learning contexts in an accounting subject using the theoretical lens of cognitive load theory (CLT).

The present study used four groups of students; two groups completed a task using diagrammatic visualisation learning materials, with one of the groups undertaking their leaning activities collaboratively and another on an individual basis, whereas two comparison groups were given a sentential learning context without diagrams, with one group undertaking their leaning activities collaboratively and the other individually. In addition to performance grades, cognitive load self-report scores were also elicited from participants.

The findings of this study indicate support for diagrammatic visualisation techniques for students working collaboratively. Compared with sentential learners, the authors find significantly improved test performance for students who work collaboratively in a diagrammatic visualisation environment. Students in the visualisation environments obtained higher grades than those in the sentential group. In terms of mental effort, students in the visualisation conditions reported the lowest cognitive load.

The authors conclude that diagrammatic visualisation learning techniques enhance student performance outcomes, particularly for those who work collaboratively. CLT assists in the understanding of the mental processes involved in learning. Instructional designers need to consider CLT when developing diagrammatic visualisation material to enable students to obtain the best possible learning outcomes.

This study addresses a gap in the literature by examining the use of diagrammatic visualisation materials as an alternative to text when learning accounting. The study explores the effect of visualisation material on students’ cognitive load by analysing their mental effort. The study contributes useful findings on visualisation as a conduit to enhancing the understanding of accounting using CLT principles.

The purpose of this paper is to enhance the quality of new reducing sentence in sentence-generation-based summarizing method by establishing consequence relationship between two action, state or process Vietnamese sentences.

First, types of pairs of Vietnamese sentences based on presupposition about the consequence relationship is classified: the verb indicating action or state at the first sentence is considered as the consequence of the verb indicating action, state or process at the second sentence. Then main predicates in Discourse Representation Structure – a logical form which represents the semantic of a given pair of sentences – is analyzed and inner- and inter-sentential relationships are determined. The next step is to generate the syntactic structure of the new reducing sentence. Finally, a combination with the built set of lexicons is done to complete the new meaning-summarizing Vietnamese sentence.

This method makes the new meaning-summarizing Vietnamese sentence satisfy two requirements: summarize the semantic of the given pair of Vietnamese sentences and have naturalism in common Vietnamese communication. In addition, it is possible to extend the method and apply for the purpose of summarizing the more complex Vietnamese paragraphs as well as paragraphs in other languages.

At the first step, only inter-sentential consequence relationship is considered and this is applied to the limit types of pairs of Vietnamese sentences which have a simple structure.

This study presents improvements in sentence-generation-based summarization method to enhance the quality of new meaning-summarizing Vietnamese sentences. This method proves effective in summarizing the considered pairs of sentences.

With the increasing number of online multilingual resources, cross-language information retrieval (CLIR) has drawn much attention from the information retrieval (IR) research community. However, few studies have examined how and why multilingual searchers seek information in two or more languages, specifically how they switch and mix language in queries to get satisfying results. The purpose of this paper is to focus on Chinese–English bilinguals’ intra-sentential code-switching behaviors in online searches. The scenarios and reasons of code-switching, factors that may affect code-switching, the patterns of mixed language query formulation and reformulation and how current IR systems and other search tools can facilitate such information needs were examined.

In-depth semi-structured interviews were used as the research method. In total, 30 participants were recruited based on their English proficiency, location and profession, using a purposive sampling method.

Four scenarios and four reasons for using Chinese–English mixed language queries to cover information needs were identified, and results suggest that linguistic and cultural/social factors are of equivalent importance in code-switching behaviors. English terms and Chinese terms in queries play different roles in searches, and mixed language queries are irreplaceable by either single language queries or other search facilitating features. Findings also suggest current search engines and tools need greater emphasis in the user interface and more user education is required.

This study presents a qualitative analysis of bilinguals’ code-switching behaviors in online searches. Findings are expected to advance the theoretical understanding of bilingual users’ search strategies and interactions with IR systems, and provide insights for designing more effective IR systems and tools to discover multilingual online resources, including cross-language controlled vocabularies, personalized CLIR tools and mixed language query assistants.

While in agreement with the broad coherentist approach of Evers and Lakomski, the position taken here is that coherentism, in itself, does not provide a sufficiently developed normative framework to underpin an ethics of educational administration. The coherentist approach to ethics is that the requirements of survival and social problem solving ensure the development of neurally‐based moral prototypes. Following writers such as Clark and Flanagan, argues that the normative resources of coherentism should be enriched by sententially expressed normative standards, and that the approach to such standards taken by virtue ethicists is fruitful. Virtue ethicists reject a rule‐based approach to morality and embrace the idea of moral prototypes. This is consistent with a naturalised epistemology, including the learning of ethical administrative practice.

Gives a broad understanding of multi‐agent systems and relates it to the generative paradigm of studying complex systems. Demonstrates the functioning of the multi‐agent paradigm in some approaches in artificial intelligence and in some closely related fields. After sketching a specific approach to formalization of multi‐agent systems using tools and techniques of the theory of formal grammars and languages, gives a preview of the main developmental lines of the theory of grammar systems.

This research is a critical discourse analysis (CDA) of Trump's speech on January 6, 2021, which results in his supporters' storming the US Capitol in order to challenge certifying Biden's victory. The Democrats accused Trump of incitement of insurrection. Consequently, Trump was impeached. This article investigates Trump's speech to label it as hate speech or free speech.

Analytical framework is tri-dimensional. The textual analysis is based on Halliday's notion of process types and Huckin's discourse tools of foregrounding and topicalization. The socio-cognitive analysis is based on Van Dijk's ideological square and his theory of mental models. The philosophical dimension is founded on Habermas's theory of discourse. These parameters are the cornerstones of the barometer that will be utilized to reach an objective evaluation of Trump's speech.

Findings suggest that Trump usually endows “I, We, You” with topic positions to lay importance on himself and his supporters. He frequently uses material process to urge the crowds' action. He categorizes Americans into two conflicting poles: He and his supporters versus the media and the Democrats. Mental models are created and activated so that the other is always negatively depicted. Reports about corruption are denied in court. Despite that, Trump repeats such reports. This is immoral in Habermas's terms. The study concludes that Trump delivered hate speech in order to incite the mob to act in a manner that may change the election results.

The study is original in its tri-dimensional framework and its data of analysis.

This paper aims to investigate how Bruneian secondary school students employ code-switching in peer interactions. The functions of students' code-switching were analysed using Reyes' (2004) and Appel and Muysken's (2005) typologies.

The data collected are based on audio-recorded group discussions designed to elicit students’ code-switched utterances.

The results indicate that the students used 11 functions of code-switching: referential, discourse marker, clarification, expressive, quotation imitation, turn accommodation, insistence, emphasis, question shift, situation shift and poetic.

As the study only focusses on a specific secondary school, results from this school will not represent secondary school students in Brunei.

This paper hopes to provide insight into how students' code-switching can be seen in a positive light. Moreover, understanding how students use code-switching in the classroom is essential for successful knowledge transfer and for cultivating competent bilinguals, which is what the country's education system aims for.

The purpose of this paper is to propose an automatic method to generate semantic annotations of football transfer in the news. The current automatic news integration systems on the Web are constantly faced with the challenge of diversity, heterogeneity of sources. The approaches for information representation and storage based on syntax have some certain limitations in news searching, sorting, organizing and linking it appropriately. The models of semantic representation are promising to be the key to solving these problems.

The approach of the author leverages Semantic Web technologies to improve the performance of detection of hidden annotations in the news. The paper proposes an automatic method to generate semantic annotations based on named entity recognition and rule-based information extraction. The authors have built a domain ontology and knowledge base integrated with the knowledge and information management (KIM) platform to implement the former task (named entity recognition). The semantic extraction rules are constructed based on defined language models and the developed ontology.

The proposed method is implemented as a part of the sport news semantic annotations-generating prototype BKAnnotation. This component is a part of the sport integration system based on Web Semantics BKSport. The semantic annotations generated are used for improving features of news searching – sorting – association. The experiments on the news data from SkySport (2014) channel showed positive results. The precisions achieved in both cases, with and without integration of the pronoun recognition method, are both over 80 per cent. In particular, the latter helps increase the recall value to around 10 per cent.

This is one of the initial proposals in automatic creation of semantic data about news, football news in particular and sport news in general. The combination of ontology, knowledge base and patterns of language model allows detection of not only entities with corresponding types but also semantic triples. At the same time, the authors propose a pronoun recognition method using extraction rules to improve the relation recognition process.

Drawing on the theoretical domain of speech act theory (SAT) and a discussion of its suitability for setting the agenda for social media research, this study aims to explore a range of research directions that are both relevant and conceptually robust, to stimulate the advancement of knowledge and understanding of online verbatim data.

Examining previously published cross-disciplinary research, the study identifies how recent conceptual and empirical advances in SAT may further guide the development of text analytics in a social media context.

Decoding content and function word use in customers’ social media communication can enhance the efficiency of determining potential impacts of customer reviews, sentiment strength, the quality of contributions in social media, customers’ socialization perceptions in online communities and deceptive messages.

Considering the variety of managerial demand, increasing and diverging social media formats, expanding archives, rapid development of software tools and fast-paced market changes, this study provides an urgently needed, theory-driven, coherent research agenda to guide the conceptual development of text analytics in a social media context.

This paper assesses the degree to which established practices in terminology can provide the translation industry with the lexical means to support mediation of information between languages, especially where such mediation involves modification. The effects of term variation, collocation and sublanguage phraseology present problems of term choice to the translator. Current term resources cannot help much with these problems; however, tools and techniques are discussed which, in the near future, will offer translators the means to make appropriate choices of terminology.