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This study makes an enquiry of the existing sustainable development goals (SDGs) knowledge of English language teacher trainers (ELTTs), who remain an overlooked stakeholder in education for sustainable development. Despite the literature on SDG integration into traditional teacher education curriculum, how massive open online courses (MOOCs) can help with capacity building of ELTTs is unclear. This study aims to further explore how the knowledge and capacities of ELTTs on SDGs could be promoted through MOOCs.

For the study’s action research approach, data of 28 ELTTs from higher education institutions in Ankara, Türkiye, were collected for six weeks using a survey, reflective reports and focus group interviews.

ELTTs with no previous training experience have a partially fragmented understanding of SDGs. MOOCs proved to be highly practical and cost-effective in building ELTTs’ capacity for building knowledge of and improving motivation to address SDGs in training programs. Further findings are drawn from ELTTs’ reflections on the lack of pedagogical content knowledge and collegial interactions in MOOCs.

There is little to no literature on ELTTs’ existing knowledge of SDGs and whether MOOCs can be used for their capacity building to achieve SDGs. The present findings may encourage higher education institutions to launch professional development programs that will equip ELTTs with the competencies to apply education for sustainable development in in-service English language teaching and teacher training programs.

This study was done to compare the modes of teaching mathematics in higher education in the United Arab Emirates (UAE). The three teaching methods were used as follow: before, during and after the COVID-19 pandemic. The three teaching methods are: (1). Normal on-campus face-to-face teaching and learning activity before the COVID-19 pandemic. (2). Full online teaching and learning activity during the COVID-19 pandemic. (3). Blended teaching and learning activity after the COVID-19 pandemic.

Over the last few years, there has been a considerable amount of literature investigating the efficacy of the various delivery modes: on-campus delivery (face-to-face), online delivery and blended learning (hybrid), in helping college students improve their mathematical skills. However, the extent to which one learner learns best has been hotly debated among the researchers. Therefore, this study aims to compare the efficacy of implementing three teaching and learning delivery modes before, while, and after the COVID-19 pandemic: on-campus delivery (face-to-face), online delivery and blended learning (hybrid) on academic achievement in mathematics at a higher education institution in the UAE. The main research question explores whether there is a statistically significant difference (p = 0.05) in students’ academic based on the delivery methods: on-campus face-to-face, online and blended learning. The participants in the study were students from one of the largest higher education institutions in the UAE, and all of them studied the same mathematics course before, during and after the COVID-19 pandemic. Student scores in the three academic semesters were thoroughly compared and analyzed using the ANOVA test to check if there is a significant difference between the three groups followed by a Tukey test to identify the significant difference in favor of which group. The results showed that there were significant differences in the mean scores in the students’ achievement in the mathematics courses favoring the blended learning delivery mode. The findings also show that the students’ achievement in mathematics using the on-campus face-to-face teaching and learning was better than the students’ achievement in mathematics using online teaching and learning delivery modes.

The main study question was: is there a statistical significant difference at the significance level (a = 0.05) in students’ achievements in mathematics courses at higher education in the UAE, which can be attributed to the method of teaching? The descriptive statistics reveal that the average student’s score in the final exam after the COVID-19 pandemic is 65.7 with a standard deviation of 16.65, which are higher than the average student’s score in the final exam before the COVID-19 pandemic of 58.7 with a standard deviation 20.53, and both are higher than the average students’ score in the final exam during the COVID-19 pandemic 51.8 with standard deviation 21.48. Then, the ANOVA test reveals that there is a statistically significant difference between the three groups in the final exam marks. The researchers used the multiple comparison tests (Tukey test) to determine the difference. The Tukey test reveals that there is a statically significant difference between the average students’ score in the final exam after the COVID-19 pandemic and the average students’ score in the final exam during the COVID-19 pandemic, where p = 0.015 < 0.05 as well as there is a statically significant difference between the average students’ score in the final exam after the COVID-19 pandemic and the average students’ score in the final exam before the COVID-19 pandemic, where p = 0.000 < 0.05 in favor of the average students’ score in the final exam after the COVID-19 pandemic. On the other hand, there is a statically significant difference between the average students’ score in the final exam before the COVID-19 pandemic and the average students’ score in the final exam during the COVID-19 pandemic, where p = 0.016 < 0.05 in favor of the average students’ score in the final exam before the COVID-19 pandemic.

There are several limitations that may reduce the possibility of generalizing the expected results of the current study to students outside the study population: (1) The study is limited to students of a federally funded postsecondary education institution in the UAE, in which most students are studying in their non-native language. (2) The study is limited to the mathematics courses. (3) The achievement test used in the study is a standardized test developed by the college as a cross-campus summative assessment.

The hybrid education model, also known as blended learning, combines traditional face-to-face instruction with online learning components. When applied to teaching mathematics in higher education, this approach can have several implications and benefits. Here are some key points supported by references: (1) Enhanced Accessibility and Flexibility: hybrid models offer flexibility in learning, allowing students to access course materials, lectures and resources online. This flexibility can accommodate diverse learning styles and preferences. A study by Means et al. (2013) in “Evaluation of Evidence-Based Practices in Online Learning” highlights how blended learning can improve accessibility and engagement for students in higher education. (2) Personalized Learning Experience: by incorporating online resources, instructors can create a more personalized learning experience. Adaptive learning platforms and online quizzes can provide tailored feedback and adaptive content based on individual student needs (Freeman et al., 2017). This individualization can improve student performance and understanding of mathematical concepts. (3) Increased Student Engagement: the integration of online components, such as interactive simulations, videos and discussion forums, can enhance student engagement and participation (Bonk and Graham, 2012). Engaged students tend to have better learning outcomes in mathematics. (4) Improved Assessment and Feedback Mechanisms: hybrid models allow for the implementation of various assessment tools, including online quizzes, instant feedback mechanisms and data analytics, which can aid instructors in monitoring students’ progress more effectively (Means et al., 2013). This timely feedback loop can help students identify areas needing improvement and reinforce their understanding of mathematical concepts. (5) Cost-Effectiveness and Resource Optimization: integrating online materials can potentially reduce overall instructional costs by optimizing resources and enabling efficient use of classroom time (Graham, 2013). (6) Challenges and Considerations: despite the benefits, challenges such as technological barriers, designing effective online materials and ensuring equitable access for all students need to be addressed (Garrison and Vaughan, 2014). It requires thoughtful course design and continuous support for both students and instructors. When implementing a hybrid education model in teaching mathematics, instructors should consider pedagogical strategies, technological infrastructure and ongoing support mechanisms for students and faculty.

The research is the first research in the UAE to discuss the difference in teaching mathematics in higher education before, during and after the COVID-19 pandemic.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

The purpose of this study was to explore how my gradually growing teacher knowledge has changed and shaped a new interpretation of the same interview data through those years of learning and teaching in different cultural contexts, and furthermore, to deeply understand how the shift of teacher identity impacts the comprehension of Schwab's (1973) commonplaces theories. Through the interview data, I shared students' and teachers' experiences in a new culture and lay alongside my own stories as an international student, a teacher, and a researcher. This research reveals the perceived future needs consist of teachers' higher English proficiency, more classes on professional communication skills courses, more opportunities for professional instructors' professional development, more ESL teacher assistance, scaffolded instruction within mainstream classes, and a better educational atmosphere. The investigation process itself was important but more important was whether or not the discussions and results provided useful information to the community. Having an overall outlook of commonplaces is as essential as the curriculum design. This dialectical shift caused me to investigate the balance among Schwab's commonplaces and the findings will contribute to the future developments in curriculum design as a researcher. Upon reflection, I utilized this research by investigating the equilibrium between the four common places and the current curriculum as well as comparing all the stakeholders' perspectives to the common places identified within the target curriculum.

As live streaming becomes a widely used online sales mode, previously content-centred anchors are attempting to switch to e-commerce live streaming. The purpose of this research was to explore the mechanisms that prompt consumers to stay or leave after content anchors transfer to live e-commerce broadcasts. In addition, we explored the factors affecting consumption from the perspectives of anchors, consumers and the external environment.

We distributed questionnaires to a group of fans who had experienced the transition of content anchors to live streaming and received back 375 valid questionnaires. Using psychological contract theory, we constructed a theoretical model for the scenario in which content anchors transition to live e-commerce broadcasting and analysed the data using partial least squares structural equation modelling (PLS-SEM).

The results show that circle culture, mainstream culture, initial trust and live streaming content all positively influenced consumers’ attitudes, whilst consumers’ past shopping experiences negatively influenced consumers’ attitudes. The personal charm of the content anchors did not have a significant effect on consumers’ attitudes. Additionally, we found that only anchors with a significant circle culture and good trust levels amongst fans were able to transition to live e-commerce streaming successfully.

This study extends the application of psychological contract theory to the field of e-commerce and describes the transformation of different types of psychological contracts. The paper’s conclusions provide a reference for decision-making and the implementation of transformation by content-based anchors to live streaming, helping them to coordinate their relationships with fans more effectively.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

While most language departments of the university offer service-learning (SL) subjects based on language teaching, such as “Teaching Chinese as a Second Language in Local Schools” and “Serving the Community through Teaching English,” this paper aims to argue that teaching students to teach language(s) is yet to be the best strategy to serve the service recipients.

SL is widely understood as an experiential learning pedagogy that integrates academic focus, reflection and community service and is shown to be impactful. In Hong Kong, the first university that has made SL a graduation requirement is the Hong Kong Polytechnic University (the University). Considering this, new SL courses have proliferated over the past decade. Adopting a narrative inquiry approach, this paper examines personal narratives from a new SL subject aiming to raise awareness of refugees in Hong Kong. The data includes students’ reflective journals, co-created personal narratives and podcasts and semi-structured interviews.

This paper finds that crafting and recording narratives of shared experiences deepens cultural understanding, cultivates empathy and facilitates language learning in a genuine setting.

Ultimately, this paper advocates a well-designed SL that combines language, content and technology as a powerful, transformational experience for both college students and service recipients.

This paper focuses on a brand new SL course, “Storytelling for Understanding: Refugee Children in Hong Kong,” offered in Semester 1, 2022–2023. The subject was developed by the two authors from a language division affiliated to the University. The deliverables were podcast recordings, co-authored and co-edited by the students and the children.

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.

We use design thinking in the context of accounting pedagogy to exploit recent advances in cybernetics in the form of generative artificial intelligence technology. Relying on the intuition that supplementing or augmenting human argumentation (natural intelligence or NI) with parallel AI output can produce better student written assignments, we posit the “augmentation premise,” that is, ((NI + AI) > AI > NI). To test the augmentation premise, we compare student written submissions in an Accounting Information Systems (AIS) course with and without the benefit of parallel generative AI output. We then evaluate how the generative AI output enhances student-crafted revisions to their initial submissions. Using a summative quality improvement index (QII) consisting of quantitative and qualitative assessments, we present preliminary evidence supporting the augmentation premise. The augmentation premise likely extends to other accounting subdisciplines and merits generalization for enriching accounting pedagogy.