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In an ever-interconnected world dominated by discourses on the internationalization and marketization of higher education, concerns related to language and employability have been the focus of recent debates. There is, however, a dearth of research investigating how these dimensions relate to one another in recent comparative and international higher education research. By focusing on how issues related to language and employability have been presented in recent higher education research worldwide, this chapter aims to contribute to our understanding of this concern. To achieve this goal, we conducted a scoping literature review using the Web of Science, Scopus, and the Education Resources Information Center (ERIC) databases, considering the years 2011–2020. The findings, perhaps not surprisingly, suggested that language skills are perceived to be valued by both graduates and employers though the discussions predominantly focused on one language, English. The research focus on English for employability in Anglophone contexts is understandable. However, the fact that the trend is observed in contexts where the language is not the primary or official language seems to indicate the influence of internationalization of higher education and global labor markets primarily dominated by English. The literature also suggested that (English) language training in higher education programs needs to move from solely linguistic and qualification-related content areas to a broader sphere of English for communication purposes that cover both specialized disciplinary content and broader generic employability skills. Considering this finding, we suggest that higher education systems and institutions incorporate recent developments in English for occupational purposes in their curriculum. We also recommend that there needs to be a shift from the overwhelmingly English language-dominated discussions to more inclusive research that assesses the impact of other dominant languages on employability-related concerns.

Limited research exists on the perceptions of police within specific ethnic minority groups. The primary purpose of this study is to investigate the experiences of Korean and Korean American residents in the Metro Atlanta area regarding their perceptions of cooperation with the police, particularly in relation to hate crimes, along with their perceptions of police legitimacy and other relevant factors. By focusing on this specific population, the study aims to shed light on their unique perspectives and contribute to a deeper understanding of the complex dynamics between ethnic minorities and law enforcement.

The authors’ sample comprised 128 Korean residents who were asked about their demographics, victimization experiences, self-rated English proficiency and police legitimacy. Multiple linear regression analyses were employed to investigate the impact of police legitimacy, victimization experiences and English-speaking skills on the participants' level of cooperation with the police.

Police legitimacy and self-rated levels of English proficiency emerged as the most significant factors in predicting the level of cooperation among residents with the police. Furthermore, individuals who have experienced crime victimization in the past were more willing to cooperate with the police compared to those who have not. Additionally, men showed a higher tendency to cooperate with the police compared to women participants.

The findings of this study suggest important implications for the policies and strategies aimed at enhancing the relationship between the Korean American community and the police. These implications include the need for improved language support for non-English speaking community members and the importance of building trust and fostering mutual understanding to cultivate positive police-community relations. By implementing measures based on these findings, it is recommended to promote a more inclusive and effective approach to policing within the Korean American population.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

A significant number of studies suggest that both international cooperation (IC) and English proficiency (EP) greatly assist internationalization of higher education (IHE). Yet, more evidence is required to confirm their relationship. Hence, this paper intends to investigate whether any association prevails between IC and EP, and if so, how both domains facilitate IHE.

This study employed a qualitative approach to examine how IC and EP potentially influence each other, as well as the way they shape IHE.

The main key finding reported in this study is that IC plays a significant role in internationalization efforts, with English serving as a critical medium.

The findings suggest that although IC can positively influence EP and the overall level of IHE, the newly built undergraduate institutions (NBUIs) in China should be careful not to fall into the dual traps of number-crunching and income-generation instruments. NBUIs in China may consider changing their IC strategies and seek to join some authoritative or high-reputation networks in other developing countries to expand their horizons.

This study contributes to the literature on IHE by exploring the connections between IC and EP and how they affect IHE, thus providing insights into advancing institutional internationalization. It is achieved through expanding institutions' IC or joining international networks while overcoming linguistic barriers.

This study examined subjective numeracy and its relationship with accounting judgements on probability issues.

A subjective numeracy scale (SNS) questionnaire was distributed to 231 accounting students to measure self-evaluated numeracy. Modified Bayesian reasoning tasks were applied in an accounting-related probability estimation, manipulating presentation formats.

The study revealed a positive relationship between self-evaluated numeracy and performance in accounting probability estimation. The findings suggest that switching the format of probability expressions from percentages to frequencies can improve the performance of participants with low self-evaluated numeracy.

Adding objective numeracy measurements could enhance results. Future numeracy research could add objective numeracy items and assess whether this influences participants' self-perceived numeracy. Based on this sample population of accounting students, the findings may not apply to large populations of accounting-information users.

Investors' ability to exercise sound judgement depends on the accuracy of their probability estimations. Manipulating the format of probability expressions can improve probability estimation performance in investors with low self-evaluated numeracy.

This study identified a significant performance gap among participants in performing accounting probability estimations: those with high self-evaluated numeracy performed better than those with low self-evaluated numeracy. The authors also explored a method other than additional training to improve participants' performance on probability estimation tasks and discovered that frequency formats enhanced the performance of participants with low self-evaluated numeracy.

This chapter explores how critical language theory could be applied to the language dynamics in higher education that is created by internationalization and university's traditional role in maintaining national languages. Language policy is an instrument of governance that is increasingly used to regulate the linguistic situation at the university, so it is at the center of my analysis. As a broad concept, language policy is not limited to the formulations of the policy text but includes interactions of different actors and addresses instruments mediating the university's linguistic situation. A critical approach highlights that language policy is permeated with power, which is unequally distributed between different actors. I suggest further conceptualization of the language dynamics of the internationalized university created by national language protection and internationalization through three layers of analysis. The first layer derives from the Bourdieu's approach to language in society focusing on the societal hierarchies that are underpinned by language use. It also includes a discussion about structure versus agency, and a conversation about the navigational capacities of individuals to challenge preestablished social structures. The second layer discusses dialogue as a theoretical approach to the process of negotiating language policy. This is where agency is being realized, depending on the relative power of different actors in the particular social context. The third layer explores the conception of language, how different ways to understand what language is are turned into policy principles.

The purpose of this study is to explore mental health difficulties, including risk and protective factors, which may impact on symptom severity after exposure to crisis situations (war, terrorism and/or natural disasters), among first responders from uniformed services.

Peer-reviewed journal articles published in English between January 2012 and March 2022 were searched in ProQuest, Wiley, Google Scholar and PubMed databases. In total, 12 articles were obtained from an original screening of 94,058 articles. Full article texts were screened for content and quality by two reviewers, with high agreeability.

Post-traumatic stress disorder and depression were the most common diagnoses. Risk factors identified were pre-deployment factors of overweight, low cognitive ability and social support, existing emotional difficulties, negative childhood experiences and stressful life events; during crisis situations factors of higher frequency and subjective severity of combat, increased rates of combat stress reaction, high levels of concerns for life and family, more stressful mission position, threat of death/severe injury and high rate of killing the enemy; and post-deployment factors, such as low social support and physical health, lack of coping mechanisms and use of avoidance strategies and social stigma. Protective factors increasing resilience and lessening symptom severity were reported as pre-deployment cognitive ability, high social support, stable physical health, effective coping, post-traumatic growth and high levels of perceived adequacy in pre-deployment preparation and training. In addition to main findings, data about author(s), publication type, population, age, type of crisis and evaluation measures were extracted. Key findings and related theories, gaps in literature and recommendations are discussed.

As yet, however, research into the factors that could serve as risk and/or protective factors are not clearly indicated in terms of post-crisis recovery. As per the authors’ knowledge, this study is an initial approach to considering this area.

This study aims to explore if and to what extent an online avatar-assisted virtual classroom can work to alleviate groups of Japanese university students’ anxiety around giving spoken presentations. It also explores how to create a more inclusive language learning environment and encourage interaction between the students in the virtual classroom.

A self-reported survey compares the same group of students’ responses to three learning contexts: an everyday in-person or conventional English learning classroom; an online videoconferencing-based classroom, via Zoom; and an online “virtual” or avatar-based classroom simulation, via the software “Gather”.

The findings suggest that the avatar-assisted virtual classroom helps students experience the least amount of fear and apprehension when speaking out loud in English and improves their speaking confidence. Similar to the findings in terms of everyday in-person lessons, the overwhelming majority of students attending Zoom lessons showed high levels of anxiety toward speaking out loud.

Challenges making use of the target language remain a persistent source of stress for Japanese students. The global shift toward online learning and the associated technologies have created opportunities to experiment with novel approaches to teaching. The discussion considers the data in the context of online classroom environments and existing speaking anxiety research. While the sample size is small, this study seeks to provide a safe and non-threatening learning environment for disadvantaged and diverse students, as well as suggestions for further research.

The authors explore the under-researched area of post-decision evaluation in PPPs (public–private partnerships), focusing upon how and whether Post-decision Project Evaluation (PdPE) is considered and provided for in United Kingdom (UK) public infrastructure projects.

The authors’ research design sought insights from overviewing UK PPP planning and more focused exploration of PPP operational practice. The authors combine the extensive analysis of planning documents for operational UK PPP projects with interviews of different stakeholders in PPP projects in one city. Mobilising an open critical perspective, documents were analysed using ethnographic content analysis (ECA) and interviews were analysed using thematic analysis consistent therewith. The authors theorise the absence and ambiguities of PdPE drawing on the sociology of ignorance.

The authors find a long-standing absence and lack of PdPE in PPP projects throughout planning and operational practice, reflecting a dynamic, multi-faceted ignorance. Concerning planning practice, the authors’ documentary analysis evidences a trend in PdPE from its absence in the early years (which may indicate some natural or genuine ignorance) to different levels or forms of weak inclusion later. Regarding this inclusion, the authors find strategic ignorance played a substantive role, involving “deliberate engineering” by both public sector and private partners. Interview findings indicate lack of clarity over PdPE and its under-development in PPP practice, deficiencies again suggestive of natural and strategic ignorance.

The authors draw from the sociology of ignorance vis-à-vis accounting's absence and ambiguity in the context of PPP, contributing to an under-researched area.

The purpose of this study is to investigate the reasons behind the persistent preference for printed content among Arabic-speaking library patrons in Jordan. Specifically, this study highlights the availability of reading materials in print, electronic and audible formats in Arabic as an intervening factor shaping reading behavior. More broadly, it aims to contribute to a deeper understanding of how language preference can impact reading format preferences.

This study’s research design revolves around understanding reading format preferences among registered members of Jordan’s largest and oldest private library. This approach involved the examination of secondary library user survey data collected from N = 313 of its patrons in 2022. To gain a greater understanding of the preference for printed materials, this study conducted semistructured interviews over the phone with n = 31 participants of the library’s survey.

The findings of this study indicate a strong preference for print books among Arabic-speaking library patrons in Jordan. However, the availability of content in electronic and audible formats in Arabic, their preferred reading language, emerged as a potentially significant factor in the persistent preference for printed reading materials.

This study offers new insights into the specific role that the availability of content in Arabic, and possibly languages other than English, may play in shaping reading format preferences. By shedding light on this aspect of reading behavior, this research offers valuable information for libraries and publishers seeking to cater to the needs and preferences of Arabic readers.