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This study aims to examine how teacher candidates (TCs) in Türkiye and the USA navigate their intercultural communication skills in a telecollaboration project.

Forty-eight TCs participated (26 in Türkiye and 22 in the USA) in the study. TCs discussed critical issues in multicultural education on an online learning platform for six weeks. Their discussions were analyzed using content and discourse analysis.

The findings indicated that TCs approached the telecollaborative space as a translingual contact zone and positioned themselves and their interlocutors in the discourse by using the personal pronouns; I, we, you and they. When they positioned themselves using we (people in Türkiye/USA), they spoke on behalf of everyone included in the scope of we. Their interlocutors responded to these positionings either by accepting this positioning and responding with a parallel positioning or by engaging in translingual negotiation strategies to revise the scope of we and sharing some differences/nuances in beliefs and practices in their community.

When TCs talk about their culture and community in a singular manner using we, they frame them as the same across every member in that community. When they ask questions to each other using you, the framing of the questions prime the respondents to sometimes relay their own specific experiences as the norm or consider experiences from different points of view through translingual negotiation strategies. A singular approach to culture(s) may affect the marginalized communities the most because they are lost in this representation, and their experiences and voices are not integrated in the narratives or integrated with stereotypical representation.

Teachers and teacher educators should first pay attention to their language choices, especially use of pronouns, which may communicate inclusion or exclusion in intercultural conversations. Next, they should prepare their students to adopt and practice language choices that communicate respect for cultural diversity and are inclusive of marginalized populations.

Speakers’ pronoun use includes identity construction in discourse by drawing borders around and between communities and cultures with generalization and particularity, and by patrolling those borders to decide who is included and excluded. As a response, interlocutors use pronouns either to acknowledge those borders and respond with corresponding ones from their own context or negotiate alternative representations or further investigate for particularity or complexity. In short, pronouns could lead the direction of intercultural conversations toward criticality and complexity or otherwise, and might be reasons where there are breakdowns in communication or to fix those breakdowns.

This study shows that translingual negotiation strategies have explanatory power to examine how speakers from different language backgrounds negotiate second and third order positionings in the telecollaborative space.

The use of augmented reality (AR) and experiential learning go hand in hand. Although AR learning opportunities have been well discussed, there is limited empirical research on the use of AR within higher education settings. Drawing from the uses and gratifications theory (U&GT), this study aims to explore the use of AR for learning satisfaction and student engagement, while also examining differences in learning styles.

This study used experiments with higher education students in the UK to explore the use of AR as part of the learning experience. Data from 173 students who experienced AR as part of their learning experience were analysed using partial least square analysis.

The authors found that hedonic, utilitarian, sensual and modality gratifications influence AR learning satisfaction and student engagement. Furthermore, the authors found differences between active and passive learners with regards to utilitarian (information seeking, personalisation) and sensual gratifications (immersion, presence) and effects on learning satisfaction.

This study developed and validated a U&GT framework incorporating different learning styles rooted in Kolb’s learning cycle. Findings provide important implications for the use of commercial AR applications as part of the learning experience within higher education settings.

The rise of cryptocurrencies and other digital assets has triggered concerns about regulation and security. Governments and regulatory bodies are challenged to create frameworks that protect consumers, combat money laundering and address risks linked to digital assets. Conventional approaches to confiscation and anti-money laundering are deemed insufficient in this evolving landscape. The absence of a central authority and the use of encryption hinder the identification of asset owners and the tracking of illicit activities. Moreover, the international and cross-border nature of digital assets complicates matters, demanding global coordination. The purpose of this study is to highlight that the effective combat of money laundering, legislative action, innovative investigative techniques and public–private partnerships are crucial.

The focal point of this paper is Australia’s approach to law enforcement in the realm of digital assets. It underscores the pivotal role of robust confiscation mechanisms in disrupting criminal networks operating through digital means. The paper firmly asserts that staying ahead of the curve and maintaining an agile stance is paramount. Criminals are quick to embrace emerging technologies, necessitating proactive measures from policymakers and law enforcement agencies.

It is argued that an agile and comprehensive approach is vital in countering money laundering, as criminals adapt to new technologies. Policymakers and law enforcement agencies must remain proactively ahead of these developments to efficiently identify, trace and seize digital assets involved in illicit activities, thereby safeguarding the integrity of the global financial system.

This paper provides a distinctive perspective by examining Australia’s legal anti-money laundering and counterterrorism financing framework, along with its law enforcement strategies within the realm of the digital asset landscape. While there is a plethora of literature on both asset confiscation and digital assets, there is a noticeable absence of exploration into their interplay, especially within the Australian context.

This study aims to explore how university language students evaluate different sustainability themes and examine the overall relevance of ecological, social, cultural and economic sustainability dimensions in language education.

A questionnaire was designed to study Finnish university language students’ (n = 55) order of priority for sustainability dimensions and their sub-themes and the justifications for the priority orders using a mixed methods design. Qualitative content analysis was conducted using NVivo software, and weighted rankings were used to analyse the quantitative data.

The findings of the study showed that language students evaluated the social and cultural dimensions as the most relevant in language teaching. In all dimensions, students approached sustainability mainly by prioritising larger issues and advancing towards smaller ones. Most non-directional responses appeared in the economic dimension. In addition, individual prioritising and justification approaches varied between different sustainability dimensions.

To the best of the authors’ knowledge, no previous studies have examined language students’ evaluations of and justifications for all four sustainability dimensions. The results highlight the need to use multiple, holistic approaches and systems thinking to incorporate education for sustainable development.

This paper aims to shed light on how the composition of future blended learning (BL) courses can be changed to provide students with quality academic learning experiences. The model suggested in this study will guide instructors on how to design their course learning outcomes to ensure effective delivery.

The new model has been developed by combining Bloom's taxonomy and Carman's model. Later, a new framework entitled “PATHCO” based on an extensive literature review is applied to enhance the quality of all five components of Carman's model.

The PATHCO conceptual framework has been developed to ensure quality in the five main teaching and learning factors. This framework covers criteria like pedagogical, assessments, technical, health care and organizational. Further research is required to broaden the main elements of the suggested framework and to validate this research through a case study.

The COVID-19 pandemic has transformed the landscape of the education sector by encouraging an extensive acceptance of technology-enhanced learning and teaching. Blended learning (BL) has become the most appropriate medium to deliver online learning (OL). However, educators and students have reported dissatisfaction with the BL mode of delivery. To address this dissatisfaction, this study outlines, using the PATHCO model, all the essential building blocks which are required to find the right blend of both face-to-face and online components.

This study aims to delve into the interplay between didactic audiovisual translation (DAT) and computer-assisted language learning (CALL), exploring their combined impact on the development of intercultural competence (IC) among learners of English as a foreign language (EFL).

Using a quasi-experimental approach with a quantitative research design, the study analyses the outcomes of a questionnaire answered by 147 students across 15 language centres in Spanish Universities. These participants actively engaged in completing the lesson plans of the Traducción audiovisual como recurso didáctico en el aprendizaje de lenguas extranjeras project, a Spanish-Government funded research initiative aimed at assessing the effects of DAT on language learning.

The current study confirms the reliability of the instrument developed to measure students’ perceived improvement. Beyond validating the research tool, the findings of the current study confirm the significant improvement in intercultural learning achieved through DAT, effectively enhancing students’ motivation to engage in language learning.

The current research solely examines students enrolled in higher education language centres. This paper closes with a CALL for additional research, including participants from other educational stages, such as primary or secondary education. In the broader context of CALL research, this study serves as a valuable contribution by exploring the potential of DAT in fostering IC in EFL settings.

This research confirms the potential of DAT and CALL to promote students’ learning process, as the combination of these approaches not only yields linguistic benefits but also intercultural learning.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

This article focuses on the assessment of entrepreneurship competence by selected vocational teachers in Italy. The exploratory research question addresses the extent to which entrepreneurship assessments are competence based, and the research seeks to identify fully fledged assessment programmes with both a formative and summative component, and the use of assessment rubrics. It also explores the extent to which entrepreneurship competence is referred to in school documentation and later assessed, and the tools and strategies used for such assessment.

This case study is part of a larger European research project promoted by Cedefop; in Italy it focused on six selected vocational IVET and CVET programmes and apprenticeship schemes. It used a wide range of instruments to ensure triangulation and multiple perspectives: analysed policy documents and undertook online interviews with experts and policy makers. At VET providers' premises it deployed: analysis of school documents; observations of learning environments; interviews and focus groups with (in schools) teachers, directors and vice directors, learners and alumni (in companies) instructors, company tutors and employers, apprentices and alumni.

Assessment tasks were rarely embedded within fully fledged assessment programmes involving both formative and summative tasks, and assessment rubric for grading. Most of the time, entrepreneurship programmes lacked self-assessment, peer assessment and structured feedback and did not involve learners in the assessment process. Some instructors coached the students, but undertook no clear formative assessment. These findings suggest institutions have a testing culture with regard to assessment, at the level of both policy and practice. In most cases, entrepreneurship competence was not directly assessed, and learning outcomes were only loosely related to entrepreneurship.

One limitation concerned the selection of the VET providers: these were chosen not on a casual basis, but because they ran programmes that were relevant to the development of entrepreneurship competence.

At the policy level, there is a need for new guidelines on competence development and assessment in VET, guidelines that are more aligned with educational research on competence development. To ensure the development of entrepreneurship competence, educators need in-service training and a community of practice.

So far, the literature has concentrated on entrepreneurship education at the tertiary level. Little is known about how VET instructors assess entrepreneurship competence. This study updates the picture of policy and practice in Italy, illustrating how entrepreneurship competence is developed in selected IVET and CVET programmes and apprenticeships.

Highly developed and agile learners who can clearly convey and call on their skills are sought in all walks of life. Diverse demand for these capacities has called attention to how the skills and knowledge gained during doctoral study can be conveyed, translated and leveraged in non-academic settings; however, the complex learning reality underneath doctoral development is challenging to convey.

The data set for this particular analysis was obtained from 245 in-depth telephone interviews with PhD candidates collected prior to COVID-19. Candidates were asked about learning processes, challenges and changes, and both the questions and thematic analysis were guided by theories of doctoral development and transformational learning.

For many participants, learning and development were not familiar topics, while a small proportion deflected questions about learning altogether. One fifth of participants presented rich and lucid accounts of learning in which cognisance of complexity, metacognitive processes and transformational experiences were embedded and multiple avenues of development were in evidence. They were well-placed to convey the complexion of doctoral development. Candidates more deeply engaged in learning also commented more about changes they noticed in themselves. The most identified avenue of development was in understanding and approach to knowledge.

Candidate communication about learning and development is an under-explored dimension of doctoral experience and skill that is relevant to advancing knowledge about doctoral development and illuminating graduate potential both within and outside academe. This must constitute a key element of the re-vitalisation of the doctorate post-pandemic. The salience of framing transferable skills within a learning development perspective is discussed.

Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.