Aim/Purpose: The study examined how the developed mobile courseware can be used as instructional material to improve senior high school statistics and probability learning, particularly during distance learning caused by the COVID-19 pandemic. The study also aims to assess the gamified mobile courseware’s engagement, functionality, aesthetics, and information quality using the Mobile App Rating Scale (MARS) and a researcher-made Gamified Mobile Courseware Assessment Tool (GMCET). Background: The need to investigate the effectiveness of incorporating game-based elements into mathematics courses through innovative instructional materials inspired the study. The COVID-19 pandemic has made distance learning a necessity, and gamified mobile courseware is a potential solution to improve learning outcomes and engagement in mathematics courses. Methodology: The study employed a descriptive-evaluative method with quantitative and qualitative data to achieve its objectives. Five IT practitioners assessed the developed courseware using the MARS regarding engagement, functionality, aesthetics, and information. A researcher-made GMCET was also used to evaluate the app’s content quality, learning objectives, content presentation, learning assessment, and usability. Five math experts and 12 math teachers rated the app using the GMCET. The study used weighted mean to analyze the quantitative data and content analysis for the qualitative data. Contribution: The study provides insights into the strengths and weaknesses of gamified mobile courseware from the perspective of IT practitioners, math experts, and math teachers. The study’s findings can inform improvements in future iterations of courseware, and the study provides a valuable guide for practitioners looking to develop gamified mobile courseware for mathematics courses. Findings: The quantitative results based on the weighted mean indicate that the IT practitioners had a moderately positive perception of the developed courseware across all categories. At the same time, the math teachers and math experts showed highly positive perceptions of the gamified mobile courseware in Statistics and Probability, rating it highly across all categories. The qualitative data analysis through content analysis highlights the need for improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of the developed app. Recommendations for Practitioners: Practitioners can use the study’s findings to improve the design of gamified mobile courseware for mathematics courses and other content areas. The study recommends that practitioners focus on improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of gamified mobile courseware. Recommendation for Researchers: Future research can build on this study’s findings by exploring the use of gamified mobile courseware in other mathematical courses and other subject areas. Further research can also examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Impact on Society: The study’s findings could improve the effectiveness of gamified mobile courseware in enhancing student learning outcomes in mathematics courses. This can lead to better student performance, improved engagement, and increased interest in mathematics courses, positively impacting society. Future Research: Future research can explore using gamified mobile courseware in other mathematics courses and other subject areas. Additionally, future studies can examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Further research can also investigate the impact of gamified mobile courseware on student motivation, interest, and performance in mathematics courses.

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students’ performance and ascertain successful teaching objectives. In pedagogical design, assessment planning is vital in lesson content planning to the extent that curriculum designers and instructors primarily think like assessors. Assessment aids students in redefining their understanding of a subject and serves as the basis for more profound research in that particular subject. Positive results from an evaluation also motivate learners and provide employment directions to the students. Assessment results guide not just the students but also the instructor. Methodology: A modified methodology was used for carrying out the study. The revised methodology is divided into two major parts: the text-processing phase and the classification model phase. The text-processing phase consists of stages including cleaning, tokenization, and stop words removal, while the classification model phase consists of dataset training using a sentiment analyser, a polarity classification model and a prediction validation model. The text-processing phase of the referenced methodology did not utilise tokenization and stop words. In addition, the classification model did not include a sentiment analyser. Contribution: The reviewed literature reveals two major omissions: sentiment responses on using the Moodle for online assessment, particularly in developing countries with unstable internet connectivity, have not been investigated, and variations of the k-fold cross-validation technique in detecting overfitting and developing a reliable classifier have been largely neglected. In this study we built a Sentiment Analyser for Learner Emotion Management using the Moodle for assessment with data collected from a Ghanaian tertiary institution and developed a classification model for future sentiment predictions by evaluating the 10-fold and the 5-fold techniques on prediction accuracy. Findings: After training and testing, the RF algorithm emerged as the best classifier using the 5-fold cross-validation technique with an accuracy of 64.9%. Recommendations for Practitioners: Instead of a closed-ended questionnaire for learner feedback assessment, the open-ended mechanism should be utilised since learners can freely express their emotions devoid of restrictions. Recommendation for Researchers: Feature selection for sentiment analysis does not always improve the overall accuracy for the classification model. The traditional machine learning algorithms should always be compared to either the ensemble or the deep learning algorithms Impact on Society: Understanding learners’ emotions without restriction is important in the educational process. The pedagogical implementation of lessons and assessment should focus on machine learning integration Future Research: To compare ensemble and deep learning algorithms

Aim/Purpose: This paper describes a technologies education model for introducing Simulation Learning and Extended Reality (XR) solution creation skills and knowledge to students at the tertiary education level, which is broadly applicable to higher education-based contexts of teaching and learning. Background: This work is made possible via the model’s focus on advancing knowledge and understanding of a range of digital resources, and the processes and production skills to teach and produce playable educational digital content, including classroom practice and applications. Methodology: Through practice-based learning and technology as an enabler, to inform the development of this model, we proposed a mixed-mode project-based approach of study within a transdisciplinary course for Higher Education students from the first year through to the post-graduate level. Contribution: An argument is also presented for the utility of this model for upskilling Pre-service Teachers’ (PSTs) pedagogical content knowledge in Technologies, which is especially relevant to the Australian curriculum context and will be broadly applicable to various educative and non-Australian settings. Findings: Supported by practice-based research, work samples and digital projects of Simulation Learning and XR developed by the authors are demonstrated to ground the discussion in examples; the discussion that is based around some of the challenges and the technical considerations, and the scope of teaching digital solutions creation is provided. Recommendations for Practitioners: We provide a flexible technologies teaching and learning model for determining content for inclusion in a course designed to provide introductory Simulation Learning and XR solution creation skills and knowledge. Recommendation for Researchers: The goal was to provide key criteria and an outline that can be adapted by academic researchers and learning designers in various higher education-based contexts of teaching and inclusive learning design focused on XR. Impact on Society: We explore how educators work with entities in various settings and contexts with different priorities, and how we recognise expertise beyond the institutional interests, beyond discipline, and explore ‘what is possible’ through digital technologies for social good and inclusivity. Future Research: The next step for this research is to investigate and explore how XR and Simulation Learning could be utilised to accelerate student learning in STEM and HASS disciplines, to promote knowledge retention and a higher level of technology-enhanced learning engagement.

Aim/Purpose: This research explores the influence of organizational-level and individual-level creativity and innovation and the technology acceptance model toward the higher education creative environment that consists of research creativity and teaching creativity. Background: Creativity and innovation are essential pillars for higher education institutions (HEIs). The two terms are interconnected, where creativity is referring to finding better ideas to do the work, while innovation is referring to how to do and implement these creative ideas. Choosing the optimal creative process and the organizational support needed to develop it is an important goal in achieving a creative and inventive environment. For the success of the creative environment to ensure the improvement of higher education institutions, information technology as social networking sites plays a crucial part in the creative process within universities. However, assessing the creativity and innovation of Saudi higher education institutions has not been well recognized. Universities today serve as knowledge-based institutions because they are at the forefront of cutting-edge R&D and scientific innovations. Creating such a productive research environment in universities, however, necessitates a work culture that encourages employees to be more creative while also encouraging the creation of new ideas and innovations. Methodology: A survey instrument was utilized as a quantitative method for this research to gather data from the study sample on the influencing variables employed in the research framework. Respondent data were analyzed using a disjoint two-stage method using PLS-SEM path modelling. Contribution: The results of this research contribute to the theoretical and scientific literature by offering a model of creativity and innovation in higher education institutions. The model proposes an optimal blend of organizational, individual, and technology variables that contribute to the development of the Higher Education Creative Environment in HEIs via creativity in teaching and research and a culture of innovation. In another way, the proposed framework especially helps to comprehend the challenges regulating establishing teaching and research creativity in HEIs via the adoption of organizational, individual, and technology enablers identified as part of this study. Findings: According to the results, organizational factors such as organizational encouragement, freedom, and challenging work have a positive relationship with the higher education creative environment. However, realistic work pressure, a lack of organizational impediments, managerial encouragement, and work group support is insufficient to affect the creative environment in higher education in Saudi Arabia. Individual variables (creative thinking skills and expertise, for example) also have a positive impact on the higher education creative environment. In the higher education creative environment, however, the influence of intrinsic motivation is insignificant. Finally, technology factors such as social networking site adoption intention, perceived usefulness, and perceived ease of use have the potential to influence the higher education creative environment. Recommendations for Practitioners: On the practical front, the obvious recommendation of this research is that it enables top leadership in Saudi HEIs to rethink the norms of creativity and innovation in their institutions, thereby instilling a mindset guided by a flourishing culture of creativity in the HEI environment with a specific focus on creativity practices in research and teaching domains. Furthermore, to promote the environment’s creativity within Saudi Arabian HEIs, university leaders must consider the suggested Organizational, Individual, and Technology factors as key enablers of creativity and innovation, which will guide them in revisiting their strategic actions in terms of further augmenting the creative performance of their academic’s staff, thereby sustaining a culture of Higher Education Creative Environment (HECE). Recommendation for Researchers: This study addressed many organizational, individual, and technology variables that facilitate Saudi Arabian HECE accomplishment in the form of research and teaching creativity. Furthermore, fresh insights for Saudi public HEIs are revealed when the success aspects of the creative environment are considered. If academic leadership at Saudi HEIs is to encourage the creative environment in general and creativity in teaching and research, it would be suitable for them to highlight individual, organizational, and technology success elements. As a result, their HEIs will be able to produce more innovative research, products, and services that can support and meaningfully achieve national transformation initiatives, opening the path for a transition into a knowledge-based economy. Impact on Society: In fact, this research is based on a quantitative research method, and the findings were also significant especially considering the current global crises. It is clearly understood by this process that includes organizational, individual, and technology factors as key enablers of the creative performance of academic staff, thereby sustaining a culture of HECE. Future Research: While providing the research model, it is probable that this study overlooked any other crucial aspects influencing creativity and innovation. As a result, future research should look at additional variables that may impact HECE in Saudi Arabian HEIs. Furthermore, while this study focused on deriving HECE with a particular emphasis on research and teaching creativity as results, future research might look at deriving other creativity outcomes (e.g., entrepreneurial creativity) within the investigated HECE dimension.

Table of Contents of the Journal of Information Technology Education: Innovations in Practice, Volume 22, 2023

Aim/Purpose: This article explores the critical need for adaptable educational models in times of crisis, focusing on strategies to overcome infrastructural and digital inequalities exacerbated by the COVID-19 pandemic. Background: By examining a case study of an offline digital library project implemented in South Sudan, this paper seeks to examine the impact of an offline digital educational solution for low-resource and crisis situations. Methodology: The authors utilize a mixed-methods approach, integrating both qualitative interviews and quantitative data analysis, to evaluate the use and impact of the SolarSPELL Initiative’s offline digital libraries in South Sudan. Contribution: This study contributes to our understanding of digital and information literacy within crisis contexts, highlighting the vital role of localized, offline content. Findings: The findings demonstrate that offline digital solutions can effectively mitigate educational disruptions by providing an accessible means to continue education during emergencies. Recommendations for Practitioners: Recommendations for practitioners include the adoption of robust offline digital learning solutions to promote educational continuity. Recommendation for Researchers: The authors recommend that researchers continue investigating the potential of offline digital educational solutions for low-resource and crisis situations. Impact on Society: Ultimately, this article finds that offline digital libraries, when paired with skill-building, are a viable means to lessen digital disparities and promote educational continuity in times of crisis and beyond. Future Research: The study suggests further exploration into the long-term impacts of such interventions on learning outcomes.

Aim/Purpose: The study seeks to utilize Augmented Reality (AR) in creating virtual laboratories for engineering education, focusing on enhancing teaching methodologies to facilitate student understanding of intricate and theoretical engineering principles while also assessing engineering students’ acceptance of such laboratories. Background: AR, a part of next-generation technology, has enhanced the perception of reality by overlaying virtual elements in the physical environment. The utilization of AR is prevalent across different disciplines, yet its efficacy in facilitating Science, Technology, Engineering, and Mathematics (STEM) education is limited. Engineering studies, a part of STEM learning, involves complex and abstract concepts like machine simulation, structural analysis, and design optimization; these things would be easy to grasp with the help of AR. This restriction can be attributed to their innovative characteristics and disparities. Therefore, providing a comprehensive analysis of the factors influencing the acceptance of these technologies by students - the primary target demographic – and examining the impact of these factors is essential to maximize the advantages of AR while refining the implementation processes. Methodology: The primary objective of this research is to develop and evaluate a tool that enriches the educational experience within engineering laboratories. Utilizing Unity game engine libraries, digital content is meticulously crafted for this tool and subsequently integrated with geo-location functionalities. The tool’s user-friendly interface allows both faculty and non-faculty members of the academic institution to establish effortlessly the virtual laboratory. Subsequently, an assessment of the tool is conducted through the application of the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, involving the administration of surveys to university students to gauge their level of adaptability. Contribution: The utilization of interactive augmented learning in laboratory settings enables educational establishments to realize notable savings in time and resources, thereby achieving sustainable educational outcomes. The study is of great importance due to its utilization of student behavioral intentions as the underlying framework for developing an AR tool and illustrating the impact of learner experience on various objectives and the acceptance of AR in Engineering studies. Furthermore, the research results enable educational institutions to implement AR-based virtual laboratories to improve student experiences strategically, align with learner objectives, and ultimately boost the adaptability of AR technologies. Findings: Drawing on practice-based research, the authors showcase work samples and a digital project of AR-based Virtual labs to illustrate the evaluation of the adaptability of AR technology. Adaptability is calculated by conducting a survey of 300 undergraduate university students from different engineering departments and applying an adaptability method to determine the behavioral intentions of students. Recommendations for Practitioners: Engineering institutions could leverage research findings in the implementation of AR to enhance the effectiveness of AR technology in practical education settings. Recommendation for Researchers: The authors implement a pragmatic research framework aimed at integrating AR technology into virtual AR-based labs for engineering education. This study delves into a unique perspective within the realm of engineering studies, considering students’ perspectives and discerning their behavioral intentions by drawing upon previous research on technology utilization. The research employs various objectives and learner experiences to assess their influence on students’ acceptance of AR technology. Impact on Society: The use of AR in engineering institutions, especially in laboratory practicals, has a significant impact on society, supported by the UTAUT2 model. UTAUT2 model assesses factors like performance, effort expectancy, social influence, and conditions, showing that AR in education is feasible and adaptable. This adaptability helps students and educators incorporate AR tools effectively for better educational results. AR-based labs allow students to interact with complex engineering concepts in immersive settings, enhancing understanding and knowledge retention. This interactive augmented learning for laboratories saves educational institutions significant time and resources, attaining sustainable learning. Future Research: Further research can employ a more comprehensive acceptance model to examine learners’ adaptability to AR technology and try comparing different adaptability models to determine which is more effective for engineering students.

Aim/Purpose: Despite playing a critical role in shaping the future, 70% of undergraduate engineers report low levels of motivation. Student disengagement and a lack of ownership of their learning are significant challenges in higher education, specifically engineering students in the computer science department. This study investigates the various causes of these problems among first-year undergraduate engineers. Background: Student disengagement has become a significant problem, especially in higher education, leading to reduced academic performance, lower graduation rates, and less satisfaction with learning. The study intends to develop approaches that encourage a more interesting and learner-motivated educational environment. Methodology: This research uses a mixed methods approach by combining quantitative data from a survey-based questionnaire with qualitative insights from focus groups to explore intrinsic and extrinsic motivators, instructional practices, and student perceptions of relevance and application of course content. The aim of this method is to make an all-inclusive exploration into undergraduate engineering students’ perspectives on factors contributing to this disengagement and the need for more ownership. Contribution: Inculcating passion for engineering among learners seems demanding, with numerous educational programs struggling with issues such as a lack of interest by students and no personal investment in learning. Understanding the causes is of paramount importance. The study gives suggestions to help teachers or institutions create a more engaged and ownership-based learning environment for engineering students. Findings: The findings revealed a tangled web influencing monotonous teaching styles, limited opportunities and applications, and a perceived gap between theoretical knowledge and real-world engineering problems. It emphasized the need to implement more active learning strategies that could increase autonomy and a stronger sense of purpose in their learning journey. It also highlights the potential use of technology in promoting student engagement and ownership. Further research is needed to explore optimal implementation strategies for online simulations, interactive learning platforms, and gamification elements in the engineering curriculum. Recommendations for Practitioners: It highlights the complex interplay of intrinsic and extrinsic motivation factors and the need to re-look at instructional practice and emphasize faculty training to develop a more student-centered approach. It also stresses the need to look into the relevance and application of the course content. Recommendation for Researchers: More work needs to be done with a larger, more diverse sample population across multiple institutions and varied sociocultural and economic backgrounds. Impact on Society: Enhancing learners’ educational experience can result in creating a passionate and competent team of engineers who can face future obstacles fearlessly and reduce the production of half-baked graduates unprepared for the profession’s challenges. Future Research: Conduct long-term studies to assess the impact of active learning and technology use on student outcomes and career readiness. Investigate scaling up successful strategies across diverse engineering programs. See if promising practices work well everywhere.

Aim/Purpose: This review’s main objective was to examine the existing literature on the use of 3D printers in primary education, covering students aged six to twelve across general, special, and inclusive educational environments. Background: A review of the literature indicated a significant oversight – prior reviews insufficiently distinguish the application of 3D printing in primary education from its utilization at higher educational tiers or focused on particular subject areas and learning domains. Considering the distinct nature and critical role of primary education in developing young students’ cognitive abilities and skills, it is essential to concentrate on this specific educational stage. Methodology: The scoping review was selected as the preferred research method. The methodological robustness was augmented through the utilization of the backward snowballing technique. Consequently, a total of 50 papers were identified and subjected to thorough analysis. Contribution: This review has methodically compiled and analyzed the literature on 3D printing use among elementary students, offering a substantial addition to academic conversations. It consolidated and organized research on 3D printers’ educational uses, applying robust and credible criteria. Findings: Many studies featured small sample sizes and limited research on inclusive and special education. The analysis revealed 82 distinct research goals and 13 educational fields, with STEM being the predominant focus. Scholars showed considerable interest in how 3D printers influence skills like creativity and problem-solving, as well as emotions such as engagement and motivation. The majority of studies indicated positive outcomes, enhancing academic achievement, engagement, collaboration, creativity, interest, and motivation. Nonetheless, challenges were noted, highlighting the necessity for teacher training, the expense of equipment, technical difficulties, and the complexities of blending new methods with traditional curricula. Recommendations for Practitioners: To capitalize on the benefits that 3D printers bring, curriculum planners are urged to weave them into their programs, ensuring alignment with educational standards and skill development. The critical role educators play in the effective implementation of this technology necessitates targeted professional development programs to equip them with the expertise for successful integration. Moreover, 3D printing presents a unique opportunity to advance inclusive education for students with disabilities, offering tailored learning experiences and aiding in creating assistive technologies. In recognizing the disparities in access to 3D printing, educational leaders must address the financial and logistical barriers highlighted in the literature. Strategic initiatives are essential to democratize 3D printing access, ensuring all students benefit from this educational tool. Recommendation for Researchers: Comparative studies are critical to elucidate the specific advantages and limitations of 3D printing technology due to the scarcity of research contrasting it with other tools. The variability in reporting durations of interventions and research environments underscores the necessity for uniform methodologies and benchmarks. Because research has predominantly focused on STEM/STEAM education, expanding into different educational areas could provide a comprehensive understanding of 3D printing’s capabilities. The existence of neutral and negative findings signals an opportunity for further investigation. Exploring the factors that impede the successful integration of 3D printing will inform the creation of superior pedagogical approaches and technological refinements. Future Research: As the review confirmed the significant promise of 3D printing technology in enriching education, especially in the context of primary education, the imperative for continued research to refine its application in primary education settings is highlighted.

Aim/Purpose: This study explores the subject structure, social networks, research trends, and issues in the domain that have the potential to derive an overview of the development of virtual reality-based learning media in vocational education. Background: Notwithstanding the increasingly growing interest in the application of virtual reality in vocational learning, the existing research literature may still leave out some issues necessary for a comprehensive understanding. This study will point out such areas that need more exploration and a more comprehensive synthesis of the literature by conducting a bibliometric analysis. It will be interesting to keep track of the changing concepts and methodologies applied in the development of VR-based learning media in vocational education research. Methodology: This review was carried out using bibliometric methodology, which can highlight patterns of publication and research activity in this hitherto little studied area. The results of the study have the potential to lead to evidence-based priority in VR development, which will tailor work for vocational contexts and set the compass against the growing worldwide interest in this area. The study provides a descriptive analysis of publications, citations, and keyword data for 100 documents published between the years 2013 and 2022 from the Scopus database, which is conducted to illustrate the trends in the field. Contribution: This study also counts as a contribution to understanding the research hotspots of VR-based learning media in vocational education. Through bibliometric analysis, this study thoroughly summarized the relevant research and literature laying a knowledge foundation for researchers and policy makers. Additionally, this analysis identified knowledge gaps, recent trends, and directions for future research. Findings: The bibliometric analysis revealed the following key findings: 1. A growing publication trajectory, with output increasing from 7 articles in 2013 to 25 articles in 2022. 2. The United States led the contributions, followed by China, and Germany. 3. The most prominent authors are affiliated with American medical institutions. 4. Lecture proceedings include familiar sources that reflect this nascent domain. 5. Citation analysis identified highly influential work and researchers. 6. Keyword analysis exposed technology-oriented topics rather than learning-oriented terms. These findings present an emerging landscape with opportunities to address geographic and pedagogical research gaps. Recommendations for Practitioners: This study will be beneficial for designers and developers of VR-based learning programs because it aligns with the most discussed and influential VR technologies within the literature. Such an alignment of an approach with relevant research trends and focus can indeed be very useful for the effective application and use of VR-based learning media for quality improvements in vocational students' learning. Recommendation for Researchers: In fact, in this bibliometric review of VR integration within vocational classrooms, a future call for focused research is presented, especially on teaching methods, course design, and learning impact. This is a framework that seeks to establish its full potential with effective and integrated use of VR in the various vocational curricula and settings of learners. Impact on Society: From the findings of the bibliometric analysis, it is evident that virtual reality technologies (VR) have significantly led to transformation within educational media. There is no denying that the growing interest and investment in the integration of virtual reality into vocational education has been well manifested in the substantive increase in publications in the last decade. This shows what the innovation driving factor is in the United States. At the same time the rapid contributions from China signal worldwide recognition of the potential of VR to improve technical skills training. This study points the way for more research to bridge critical gaps, specifically how VR tools can be used in vocational high school classrooms. Furthermore, research should be aligned to meet specific needs of vocational learners and even promote international cross-border partnerships, pointing out the potential of virtual reality to be a universally beneficial tool in vocational education. The examination of highly cited articles provides evidence of the potential of VR to be an impactful pedagogical tool in vocational education. The findings suggest that researchers need to move forward looking at the trajectory of VR in vocational education and how promising it is in defining the future for innovative and effective learning methodologies. Future Research: This study is an exceptionally valuable contribution, a true landmark in the field of dynamic development, and one that denotes very meaningful implications for the future course of research in the dynamically developing field of bibliometric analysis of VR-based learning media for vocational education. The increase in the number of publications emanates from growing interests in the application of virtual reality (VR) technologies in vocational education. The high concentration of authorship from the USA, along with the ever increasing contributions from China, spotlights the increasing worldwide recognition of the impact of immersive technologies in the enhancement of training in technical skills. These are emerging trends that call for research to exemplify the diverse views and global teamwork opportunities presented by VR technologies. The study also highlights critical areas that need focused attention in future research endeavors. The fact that the embedding of VR tools into classrooms in vocational high schools has been poorly researched points to the major gap in pedagogical research within authentic educational settings. Therefore, further investigations should evaluate teaching methods in VR, lesson designs, and the impacts of VR in specific vocational trades. This supports the need for learner-centered frameworks that are tailor-made to the needs of vocational learners. This calls for more direct and focused investigations into identified research gaps noting a growing dominance in the field of health-related research with the most cited articles in this field, to integrate virtual reality into additional vocational education contexts. In this way, the gaps present an opportunity for researchers to make significant contributions to the development of interventions responsive to the unique needs of vocational learners; this will contribute to strengthening the evidence base for the worldwide implementation of VR within vocational education systems. This was recommended as the intention of such a bibliometric analysis: supporting the potential of VR as a pedagogical tool in vocational contexts and providing grounding for a strong and focused future research agenda within this burgeoning area of educational technology.

Aim/Purpose: To conduct a needs assessment and subsequently create micro-storytelling media aimed at enhancing the Digital Intelligence Quotient (DQ) skills of young individuals. Background: In today's digital society, DQ has emerged as a vital skill that elevates individuals in all aspects of life, from daily living to education. To empower Thai youth, this study seeks to innovate DQ content by adapting it into a digital format known as micro-storytelling. This unique approach combines the art of storytelling with digital elements, creating engaging and effective micro-learning media Methodology: The methodology comprises three phases: 1) assessing the need for digital micro-storytelling development; 2) developing digital micro-storytelling; and 3) evaluating the DQ skills among young individuals. The sample group consisted of 55 higher education learners for needs assessment and 30 learners in the experiment group. Data analysis involves PNI modified, mean, and standard deviation. Contribution: This research contributes by addressing the urgent need for DQ skills in the digital era and by providing a practical solution in the form of digital micro-storytelling, tailored to the preferences and needs of Thai youth. It serves as a valuable resource for educators and policymakers seeking to empower young learners with essential digital competencies. Findings: The findings demonstrate three significant outcomes: 1) The learners wanted to organize their own learning experience with self-paced learning in a digital landscape, and they preferred digital media in the form of video. They were most interested in developing DQ to enhance their understanding of digital safety, digital security, and digital literacy; 2) according to a consensus of experts, digital micro-storytelling has the greatest degree of quality in terms of its development, content, and utilization, with an overall average of 4.86; and 3) the overall findings of the assessment of DQ skills indicate a favorable level of proficiency. Recommendations for Practitioners: Align materials with micro-learning principles, keeping content concise for effective knowledge retention. Empower students to personalize their digital learning and promote self-paced exploration based on their interests. Recommendation for Researchers: Researchers should continuously assess and update digital learning materials to align with the evolving digital landscape and the changing needs of students and investigate the long-term effects of DQ improvement, especially in terms of online safety and digital literacy in students' future lives and careers. Impact on Society: This study's impact on society is centered around fostering a DQ, promoting innovative educational approaches, and elevating Thai youth with essential digital skills. It contributes to a safer, more informed, and digitally literate generation prepared for the challenges of the digital era. Future Research: Undertake comparative studies to analyze the effectiveness of different digital learning formats and methodologies. Comparing micro-storytelling with other approaches can help identify the most efficient and engaging methods for enhancing DQ.

Aim/Purpose: The digital ecosystem has contributed to the acceleration of digital and mobile educational tools across institutions worldwide. The research displays educators’ perspectives on web applications on mobile devices that can be used to engage and challenge students while impacting their learning. Background: Explored are elements of technology in education and challenges and successes reported by instructors to shift learning from static to dynamic. Methodology: Insights for this study were gained through questionnaires and focus groups with university educators in the United Arab Emirates. Key questions addressed are (1) challenges/benefits, (2) types of mobile technology applications used by educators, and (3) strategies educators use to support student learning through apps. The research is assisted by focus groups and a sample of 42 completed questionnaires. Contribution: The work contributes to web/mobile strategic considerations in the classroom that can support student learning and outcomes. Findings: The results reported showcase apps that were successfully implemented in classrooms and provide a perspective for today’s learning environment that could be useful for instructors, course developers, or any educational institutions. Recommendations for Practitioners: Academics can integrate suggested tools and explore engagement and positive associations with tools and technologies. Recommendation for Researchers: Researchers can consider new learning applications, mobile devices, course design, learning strategies, and student engagement practices for future studies. Impact on Society: Digitization and global trends are changing how educators teach, and students learn; therefore, gaps need to be continually filled to keep up with the pace of ever-evolving digital technologies that can engage student learning. Future Research: Future research may focus on interactive approaches toward mobile devices in higher education learning and shorter learning activities to engage students.

Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians’ intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on academicians’ adoption behavior is limited. This study proposes an integrated model incorporating TTF factors and social network characteristics like density, homophily, and connectedness to understand academics’ continuance intentions. Methodology: A qualitative study involving 31 interviews of academics from India examined attitudes and the potential role of social network characteristics like density, homophily, and connectedness in adoption. Results showed positive sentiment towards chatbots and themes on how peer groups accelerate diffusion. In the second phase, a survey of 448 faculty members from prominent Indian universities was conducted to test the proposed research model. Contribution: The study proposes and validates an integrated model of TTF and social network factors that influence academics’ continued usage intentions toward AI chatbots. It highlights the nuanced role of peer networks in shaping adoption. Findings: Task and technology characteristics positively affected academics’ intentions to continue AI chatbot usage. Among network factors, density showed the strongest effect on TTF and perceived usefulness, while homophily and connectedness had partial effects. The study provides insights into designing appropriate AI tools for the academic context. Recommendations for Practitioners: AI chatbot designers should focus on aligning features to academics’ task needs and preferences. Compatibility with academic work culture is critical. Given peer network influences, training and demonstrations to user groups can enhance adoption. Platforms should have capabilities for collaborative use. Targeted messaging customized to disciplines can resonate better with academic subgroups. Multidisciplinary influencers should be engaged. Concerns like plagiarism risks, privacy, and job impacts should be transparently addressed. Recommendation for Researchers: More studies are needed across academic subfields to understand nuanced requirements and barriers. Further studies are recommended to investigate differences across disciplines and demographics, relative effects of specific network factors like size, proximity, and frequency of interaction, the role of academic leadership and institutional policies in enabling chatbot adoption, and how AI training biases impact usefulness perceptions and ethical issues. Impact on Society: Increased productivity in academia through the appropriate and ethical use of AI can enhance quality, access, and equity in education. AI can assist in mundane tasks, freeing academics’ time for higher-order objectives like critical thinking development. Responsible AI design and policies considering socio-cultural aspects will benefit sustainable growth. With careful implementation, it can make positive impacts on student engagement, learning support, and research efficiency. Future Research: Conduct longitudinal studies to examine the long-term impacts of AI chatbot usage in academia. Track usage behaviors over time as familiarity develops. Investigate differences across academic disciplines and roles. Requirements may vary for humanities versus STEM faculty or undergraduate versus graduate students. Assess user trust in AI and how it evolves with repeated usage, and examine trust-building strategies. Develop frameworks to assess pedagogical effectiveness and ethical risks of conversational agents in academic contexts.

Table of Contents of the Journal of Information Technology Education: Innovations in Practice, Volume 23, 2024

This research introduces a hybrid honeypot architecture to bolster security within software-defined networks (SDNs). By combining low-interaction and high-interaction honeypots, the proposed solution effectively identifies and mitigates cyber threats, including port scanning and man-in-the-middle attacks. The architecture is structured into multiple modules that focus on detecting open ports using Vilhala honeypots and simulating targeted and random attack scenarios. This hybrid approach enables comprehensive monitoring and detailed packet-level analysis, providing enhanced protection against advanced online threats. The study also conducts a comparative analysis of different attack detection methods using tools like KFSensor and networking shell commands. The results highlight the hybrid honeypot system's efficacy in filtering malicious traffic and detecting security breaches, making it a robust solution for safeguarding SDNs.

This study focuses on the importance of monitoring student attendance in education and the challenges faced by educators in doing so. Existing methods for attendance tracking have drawbacks, including high costs, long processing times, and inaccuracies, while security and privacy concerns have often been overlooked. To address these issues, the authors present a novel internet of things (IoT)-based self-lecture attendance system (SLAS) that leverages smartphones and QR codes. This system effectively addresses security and privacy concerns while providing streamlined attendance tracking. It offers several advantages such as compact size, affordability, scalability, and flexible features for teachers and students. Empirical research conducted in a live lecture setting demonstrates the efficacy and precision of the SLAS system. The authors believe that their system will be valuable for educational institutions aiming to streamline attendance tracking while ensuring security and privacy.

This study aims to examine the intellectual capital and its effect on the financial performance of Ethiopian private commercial banks using the pulic model. Quantitative panel data from audited annual reports of Ethiopian private commercial banks from 2011 to 2019 are collected. The robust fixed effect regression model has been adopted to investigate the effect of IC and the financial performance measures of the banks. The study results show a positive relationship between the value added intellectual coefficient (VAIC) and the financial performance of private commercial banks in Ethiopia. The study also revealed that the components of VAIC (i.e., human capital efficiency, capital employed efficiency, and structural capital efficiency) have a positive and significant effect on the financial performance of banks measured by return on asset and return on equity over the study periods. Practically, the results of the study could be useful for shareholders to consider IC as a strategic resource and hence emphasise these intangibles, and to the bank managers to benchmark themselves against the best competitors based on the level of efficiency rankings.

The purpose of this study is to explore the effect of electronic service quality subdimensions upon the behavioural and praising intentions of users engaged in internet banking. Using the survey method, 203 responses were collected from users of online banking in Turkey. A partial least square structural equation model was constructed to test both the reliability and validity of the measurement, as well as the structural model. The results indicated that emotional benefits, ease of use, and control subdimensions, which are influenced through graphical quality and layout clarity, have a significant and positive impact upon the behavioural and praising intentions of users of online banking. The study did not find support for the direct effect of layout clarity upon behavioural and praising intentions.

The present study attempts to find out the determinants of FinTech adoption for financial inclusion by a microfinance institution in India. The factors such as efficiency, consistency, convenience, reliability are taken as predictors of organisational attitude. Similarly, organisational attitude, ease of use, and perceived benefits are considered as antecedents of organisational adoption intention of FinTech in microfinance institutions of India. The purposive sampling technique was used to get a filled survey instrument by target samples. The results indicate that convenience and consistency in the use of FinTech applications build a favourable attitude to adopt it. Furthermore, perceived benefits are the most important antecedents of the adoption intention of FinTech in the microfinance institution in India. Additionally, the reliability of the application has a positive but insignificant impact on organisational attitude to adopt FinTech. The implications of the present study are discussed.

Quality of work life (QWL) is a generic term that includes an employee's feeling about various aspects of their work including the compensation and rewards, job security, interpersonal relations and the intrinsic meaning of being satisfied in their workplace. This research paper was documented with an intention to understand the influence of the QWL on the productivity of employees working in the banking arena. The study examined the most clout able factors that contributed to the quality of work-life of employees and its correlation on their productivity. A multi-stage sampling method was used to draw a sizeable sample from ten major banks situated in the Karnataka state of India. A total of 756 personnel spread across various branches belonging to rural, semi-urban and urban were covered. The study was validated further by testing various hypotheses drawn based on a review of the literature. The study empirically identified eight major attributes that influence the QWL of bankers. The relationship between QWL and productivity was investigated with notable results using SEM approach.

The present study is a modest attempt to investigate the impact of gender diversity on firm performance of BSE 200 listed companies. The study is based on the secondary data collected from the EMIS database and the corporate governance reports for a period of eight years, i.e., from 2012 to 2019. Sample size of the present study is 174 Indian companies listed in the Bombay Stock Exchange. The study has employed multiple regression models by considering the endogeneity issue to empirically test the impact of gender diversity on firm performance in Indian context. Based on the multiple regression models, we find that the impact of gender diversity is positive and significant on the market-based measure of firm performance. However, the impact becomes negative significant when firm performance was measured by accounting based measure of firm performance.

Corporate social responsibility (CSR) and sustainability are gaining worldwide recognition. The question of whether CSR and sustainability programs benefit an organisation's financial success is still being debated. This study aims to verify this phenomenon by examining the current literature pattern on this relationship using bibliometric and systematic review analysis. It further provides a taxonomy for understanding this association. VOSviewer is used to obtain comprehensive dataset mapping and clustering in the field. The manuscript offers promising insights regarding academia by assessing the pattern of publication trends, the most influential author in the area, and analysing the methodological and theoretical underpinnings of CSR, sustainability and firm performance linkage. The outcome of this study provides exploratory insights into research gaps and avenues for future research.

Nostalgia has an intrinsic association with consumer behaviour. Retrieval of memories drives emotions among consumers and reinforces experience-led buying decisions. Despite nostalgia, and consumption being a common practice at various times in life, issues regarding the nostalgia stimuli on customers' perceptions and buying decisions remain less explored. This article aims at exploring the consumption pattern of adult consumers by analysing the influence of nostalgic behaviour referring to the autobiographic memories and social motivations. It describes the purchase intentions and consumption pattern among adult consumers in the context of self-reference criteria based on nostalgic memories and social motivations. This article offers constructive understanding on establishing relationship between nostalgic memories and consumption pattern over the temporal framework and establishing the brand loyalty and hedonic satisfaction. It contributes to the existing literature by critically examining the theoretical concepts and empirical findings of previous studies on perceptions of consumers on nostalgic emotions and their role in making buying decisions.

Smart home devices are vulnerable to various attacks, including distributed-denial-of-service (DDoS) attacks. Current detection techniques face challenges due to nonlinear thought, unusual system traffic, and the fluctuating data flow caused by human activities and device interactions. Identifying the baseline for 'normal' traffic and suspicious activities like DDoS attacks from encrypted data is also challenging due to the encrypted protective layer. This work introduces a concept called synoptic crow search with recurrent transformer network-based DDoS attack detection, which uses the synoptic weighted crow search algorithm to capture varying traffic patterns and prioritise critical information handling. An adaptive recurrent transformer neural network is introduced to effectively regulate DDoS attacks within encrypted data, counting the historical context of the data flow. The proposed model shows effective performance in terms of low false alarm rate, higher detection rate, and accuracy.

Badminton, as a fast and highly technical sport, requires high accuracy in identifying athletes' swing movements. Accurately identifying different swing movements is of great significance for technical analysis, coach guidance, and game evaluation. To improve the recognition accuracy of badminton players' swing movements, this text is based on an improved dense trajectory algorithm to improve the accuracy of recognising badminton players' swing movements. The features are efficiently extracted and encoded. The results on the KTH, UCF Sports, and Hollywood2 datasets demonstrated that the improved algorithm achieved recognition accuracy of 94.2%, 88.2%, and 58.3%, respectively. Compared to traditional methods, the innovation of research lies in optimised feature extraction methods, efficient algorithm design, and accurate action recognition. These results provide new ideas for the research and application of badminton swing motion recognition.

In the competitive landscape of globalised markets, businesses must prioritise cost reduction for sustained competitiveness. This study delves into the dynamic facility layout problem (DFLP) within a cable production company in Kerala, emphasising adaptability to changing production demands. Addressing material handling costs and rearrangement expenses, the research evaluates the efficacy of the current static layout and explores the benefits of transitioning to a dynamic layout. The case study reveals potential cost savings through the strategic restructuring of machine arrangements. The innovative machine learning-based genetic algorithm (ML-GA) integrates machine learning algorithms, genetic algorithms, and a local search method, offering a cutting-edge solution to dynamic facility layout challenges. By considering demand variability and relocation costs, the study provides insights for informed decision-making, emphasising the significance of material flow patterns. This research contributes to enhancing efficiency and profitability, providing practical implications for businesses navigating the complexities of modern manufacturing.

Action recognition plays a vital role in analysing human body behaviour and has significant implications for research and education. However, traditional recognition methods often suffer from issues such as inaccurate time and spatial feature vectors. Therefore, this study addresses the problem of inaccurate recognition of aerobic gymnastics action image data and proposes a visualised three-dimensional convolutional neural network algorithm-based action recognition model. This model incorporates unsupervised visualisation methods into the traditional network and enhances data recognition capabilities through the introduction of a random noise perturbation enhancement algorithm. The research results indicate that the data augmented with noise perturbation achieves the lowest mean square error, reducing the error value from 0.3352 to 0.3095. The use of unsupervised visualisation analysis enables clearer recognition of human actions, and the algorithm model is capable of accurately recognising aerobic movements. Compared to traditional algorithms, the new algorithm exhibits higher recognition accuracy and superior performance.

This paper explores innovative ideas and strategies for promoting environmental sustainability within the hotel industry, with the goal of streamlining these concepts for practical application in the industry and facilitating future academic research. The research methodology encompassed extensive online desk research, yielding a collection of 87 articles that were subject to thorough analysis. Additionally, personal consultations were conducted with industry experts to align their insights with the identified innovative ideas. To facilitate comprehension, appropriate terminology was assigned to these concepts. Subsequently, a post-discussion phase was conducted, engaging in one-on-one sessions with five industry experts to distil these insights into four distinct directions. This paper holds potential value for both industry stakeholders and academics, serving as a structured compendium of ideas and innovations crucial for advancing sustainability in the hotel sector. Moreover, it provides a solid foundation for further academic research.

This research aims to establish a valid and accurate measurement scale and identify consumer-driven characteristics for minimalism. The study has employed a hybrid approach to produce items for minimalism. Expert interviews were conducted to identify the items for minimalism in the first phase followed by consumer survey to obtain their response in second phase. A five-point Likert scale was used to collect the data. Further, data was subjected to reliability and validity check. Structural equation modelling was used to test the model. The findings demonstrated that there are five dimensions by which consumers perceive minimalism: decluttering, mindful consumption, aesthetic choices, financial freedom, and sustainable lifestyle. The outcome also revealed a high correlation between simplicity and well-being. This study is the first to provide a reliable and valid instrument for minimalism. The results will have several theoretical and practical ramifications for society and policymakers. It will support policymakers in gauging and encouraging minimalistic practices, which enhance environmental performance and lower carbon footprint.

Monetary policy is essential for sustainable growth where effective monetary policies can improve investment, employment, and consumption by fostering a balanced and resilient economy. However, sustainable development is vital for harmonising economic growth, social equity, and environmental preservation. A number of factors have been discussed in the literature that impact sustainable development. However, this study explicitly tries to investigate the nexus among the monetary policy (MP) toward sustainable development (SD) with the mediation of e-banking services (e-BS) and moderation of financial risk management (FRM) from China drawing on stakeholder theory. It discovered a significant connection between monetary policy and sustainable development along with sub-dimensions of SD. Likewise, this study confirmed a positive mediating influence of e-BS between monetary policy and sustainable development. Finally, the study additionally ensured a positive moderation of financial risk between monetary policy and sustainable development, respectively. These outcomes bestow several interesting insights into monetary policy, e-banking services, financial risk management, and sustainable development.

This study is unique in how it looks at how crowdfunding on the recurring pledge platform Patreon is associated with the frequency of video creation. It analyses factors that make video creators on YouTube more likely to crowdfund on Patreon. It finds channels that upload more frequently, younger channels, channels with more subscribers and views per video, and channels that shared their Facebook pages were more likely to crowdfund on that platform.

Numerous scandals due to unethical decisions occur despite the growing use of decision support systems (DSS). Several scholars recommend incorporating ethical attributes along with business requirements in DSS design. However, little guidance exists to indicate which ethical attributes to include and the importance ethical attributes should be given in comparison to business requirements. This study addresses this deficiency by identifying ethical requirements to integrate in DSS design drawn from the business ethics literature. This study conducted a large-scale empirical survey with information technology decision-makers to examine the relative importance of DSS fit with ethical and business requirements as well as the appropriate balance of those requirements on perceived DSS performance. The results show that decision makers perceive better DSS performance when the ethical and business requirements align with its organisation's beliefs than from ethical or business requirements alone.

A well-documented architecture can greatly improve comprehension and maintainability. However, shorter release cycles and quick delivery patterns results in negligence of architecture. In such situations, the architecture can be recovered from its current implementation based on considering dependency relations. In literature, structural and semantic dependencies are commonly used software features, and directory information along with co-change/change history information are among rarely utilised software features. But, they are found to help improve architecture recovery. Therefore, we consider investigating various features that may further improve the accuracy of existing architecture recovery techniques and evaluate their feasibility by considering them in different pairs. We compared five state-of-the-art methods under different feature subsets. We identified that two of them commonly outperform others but surprisingly with low accuracy in some evaluations. Further, we propose a new subset of features that reflects more accurate user perceptions and hence, results in improving the accuracy of architecture recovery techniques.

This research investigates the correlation between risk management and supply chain performance (SCP) along with moderation of AI-embedded technologies such as big data analytics, Internet of Things (IoT), virtual reality, and blockchain technologies. To calculate the results, this study utilised 644 questionnaires through the structural equation modelling (SEM) method. It is revealed using SmartPls that financial risk management (FRM) is positively linked with SCP. Second, it was observed that AI significantly moderates the connection between FRM and SCP. In addition, the study presents certain insights into supply chain and AI-enabled technologies and how these capabilities can beneficially advance SCP. Besides, certain implications, both managerial and theoretical are described for the supply chain managers along with limitations for future scholars of the world.

This study explores the connection between mentorship and sustainable development (SD) within three major perspectives of sustainable development, such as social, environmental, and economic perspectives from China. Second, the study revealed the relationship between entrepreneurship and SD. Third, a moderation influence of innovation management (IM) was observed among the proposed nexuses of mentorship, entrepreneurship, and SD. To this end, a total of 535 questionnaires were eventually utilised with the support of SmartPLS and the structure equation modelling (SEM) approach. A positive connection was confirmed between mentorship and SD. The outcome uncovered a positive correlation between entrepreneurship and SD. In addition, a moderation of IM was found between mentorship, entrepreneurship, and SD. The study enlists several interesting lines about mentorship, entrepreneurship, and IM that might help to improve SD in terms of social, environmental, and economic perspectives. Besides, the study provides various implications for management and states the weaknesses along with the future directions for worldly researchers.

The phenomenon of cloud computing and related innovations such as Big Data have given rise to many fundamental changes that are evident in information and data. Managing, measuring and developing business value from the plethora of this new data has significant impact on many corporate agendas, particularly in relation to the successful implementation of business intelligence and analytics (BI&A). However, although the influence of Big Data has fundamentally changed the IT application landscape, the metrics for measuring success and in particular, the quality of information, have not evolved. The measurement of information quality and the antecedent factors that influence information has also been identified as an area that has suffered from a lack of research in recent decades. Given the rapid increase in data volume and the growth and ubiquitous use of BI&A systems in organisations, there is an urgent need for accurate metrics to identify information quality.

Today, income management is one of the attractive and controversial issues in accounting investigation areas from both investigations and regulatory view. Managers do manage income either to distort information or to defer and report the information related to future incomes. This investigation aims at examining the effect of taxable income management on the information content of taxable income of firms. Tests of research hypotheses were performed with an empirical method based on econometric and using multivariate regression analysis, t-test, Wilcoxon total scores, and specifically by using the panel data model across 147 firms listed on the Tehran Stock Exchange between 2002 and 2011. Findings show that taxable income management reduces the information content of taxable income. In addition, firms manage accounting income to defer information.

To assess a country's economic outlook and achieve higher economic growth, econometric models and prediction techniques are significant tools. Policymakers are always concerned with the correct future estimates of economic variables to take the right economic decisions, design better policies and effectively implement them. Therefore, there is a need to improve the predictive accuracy of the existing models and to use more sophisticated and superior algorithms for accurate forecasting. Deep learning models like recurrent neural networks are considered superior for forecasting as they provide better predictive results as compared to many of the econometric models. Against this backdrop, this paper presents the feasibility of using different deep-learning neural network architectures for trade forecasting. It predicts export trade using different recurrent neural architectures such as 'vanilla recurrent neural network (VRNN)', 'bi-directional long short-term memory network (Bi-LSTM)', 'bi-directional gated recurrent unit (Bi-GRU)' and a hybrid 'bi-directional LSTM and GRU neural network'. The performances of these models are evaluated and compared using different performance metrics such as Mean Square Error (MSE), Mean Absolute Error (MAE) Root Mean Squared Error (RMSE), Root Mean Squared Logarithmic Error (RMSLE) and coefficient of determination <em>R</em>-squared (<em>R</em>²). The results validated the effective export prediction for India.

Human behaviour, which is led by the human, emotional and occasionally fallible brain, is highly influenced by the environment in which choices are presented. This research paper explores the synergistic potential of the Internet of Behaviours (IoB) and digital nudges in the financial sector as new avenues for intervention while shedding light on the IoB benefits and the digital nudges' added value in these financial settings. Afterward, it proposes an IoB-Nudges conceptual model to explain how these two concepts would be incorporated and investigates their complementary relationship and benefits for this sector. Finally, the paper also discusses key challenges to be addressed by the IoB framework.

The traditional numerical simulation method of financial fluctuation cycle does not focus on the study of non-linear financial fluctuation but has problems such as high numerical simulation error and long time. To solve this problem, this paper introduces the non-linear equation of motion to optimise the numerical simulation method of financial fluctuation cycle. A comprehensive analysis of the components of the financial market, the establishment of a financial market network model and the acquisition of relevant financial data under the support of the model. Based on the collection of financial data, set up financial volatility index, measuring cycle, the financial wobbles, to establish the non-linear equations of motion, the financial wobbles, the influence factors of the financial volatility cycle as variables in the equation of motion, through the analysis of different influence factors under the action of financial volatility cycle change rule, it is concluded that the final financial fluctuation cycle, the results of numerical simulation. The simulation results show that, compared with the traditional method, the numerical simulation of the proposed method has high precision, low error and short time, which provides relatively accurate reference data for the stable development of regional economy.

Voice Activity Detection (VAD) distinguishes speech segments from noise or silence areas. An efficient and noise-robust VAD system can be widely used for emerging speech technologies such as wireless communication and speech recognition. In this paper, we propose two versions of an unsupervised Arabic VAD method based on the combination of the Short-Time Energy (STE) and the Spectral Centroid (SC) features for formulating a typical threshold to detect speech areas. The first version compares only the STE feature to the threshold (STE-VAD). In contrast, the second compares the SC vector and the threshold (SC-VAD). The two versions of our VAD method were tested on 770 sentences of the Arabphone corpus, which were recorded in clean and noisy environments and evaluated under different values of Signal-to-Noise-Ratio. The experiments demonstrated the robustness of the STE-VAD in terms of accuracy and Mean Square Error.

Conventional intelligent traffic congestion discrimination methods mainly use GPS terminals to collect traffic congestion data, which is vulnerable to the influence of vehicle time distribution, resulting in poor final discrimination effect. Necessary to design a new intelligent traffic congestion discrimination method based on wireless sensor network front-end data collection. That is to use the front-end data acquisition technology of wireless sensor network to generate a front-end data acquisition platform to obtain intelligent traffic congestion data, and then design an intelligent traffic congestion discrimination algorithm based on traffic congestion rules so as to achieve intelligent traffic congestion discrimination. The experimental results show that the intelligent traffic congestion discrimination method designed based on the front-end data collection of wireless sensor network has good discrimination effect, the obtained discrimination data is more accurate, effective and has certain application value, which has made certain contributions to reducing the frequency of urban traffic accidents.

This article presents a case study that outlines the potential of DigiBot technology, an interactive automated response program, in mobile open learning (MOL) for business subjects. The study, which draws on a project implemented in Sub-Saharan Africa, demonstrates the applications of DigiBots delivered via WhatsApp to over 650,000 learners. Employing a mixed-methods approach, the article reports on live event tracking, qualitative observations from facilitators and learning technologists, and a learner survey (<i>N</i> = 304,000). The research offers practical recommendations and proposes a model for scalable DigiBot learning. Findings reveal that in this case, DigiBot MOL had the potential to effectively address two key obstacles in open learning: accessibility and scalability. Leveraging mobile platforms such as WhatsApp mitigates accessibility restrictions, particularly in resource-constrained contexts, while tailored micro-learning enhances scalability.

Bright Lights has a history of success, but is at a pivotal point, facing the pains of strategic change. One salesperson has found a way to maintain sales and increase profit margin, but it requires operating between the lines of ethical boundaries. Ethics provides a choice between right and right as opposed to moral temptation of right and wrong (Kidder, 1996). As the case unfolds, Jim receives a mandate of which customers he can call on, reducing sales, profit margin, and customer satisfaction. A top performer, Jim finds a solution within company policy and the law, but although not hidden, is not entirely transparent. This creates two ethical decisions: 1) Should he be reprimanded or praised? 2) Should the company update policies to ban his actions, or promote his actions among other salespeople? This case clearly strikes the dilemma found in navigating the boundaries of a questionable business strategy.

In the perspective of institutional theory, business education is an institutional field, in which two major institutional forces are accreditations and rankings. In this context, French business schools (BS) have adopted an isomorphic response by starting to engage in research and publishing in academic journals. Studies have discussed their research as a new institutional trajectory. However, what remains unknown is how they differ from each other in such research dynamics. To bring new insights to the discussion, this quantitative study examines, over the period of 2008-2018, the evolution of research of French BS by systematically comparing the 'best' schools with other schools in all analyses. The results indicate a strong isomorphism in terms of publication quantity and productivity, scale of research collaboration and the internationalisation of research. However, these schools are heterogeneous in terms research quality and scale of international research collaboration, reflecting the diversity in their research strategy.

Though there have been many approaches to dealing with social problems in recent years, the concepts of social value have yet to be discussed thoroughly. Upon examining these concepts in existing studies and testing them with two case studies, the article shows that there is the possibility that a group's shared wants may not be widely recognised as a social problem, and targeting these unserved populations is a precondition for solving social issues. It is essential to identify hidden social problems by understanding what is still left, the number of people sharing the same want, the severity of the unmet want, and the possible resources for solution generation. Social value in its narrower definition means meeting the satisfaction of the group sharing the same want, while in its broader definition, it means meeting the satisfaction of wider society. Finding workable solutions involves not only the group of people sharing the same want but also others who do not have the same want but who do recognise the importance of acknowledging the want of the subgroup.

This study inquires about the COVID-19-generated momentum and how it resulted in transformative opportunities for the hard-hit tourism industry in Hawai'i. It also investigates the type of sustainability-based management strategies that were favoured by actors from the industry to help navigate uncertain times and capture transformative opportunities. Findings indicate that actors from the tourism industry in Hawai'i perceived the COVID-19 pandemic as a huliau, or a point of transformation, to reflect and re-evaluate the tourism industry's responsibility and shift toward a recovery focused on sustainability. This research confirms that the pandemic-driven momentum accelerated opportunities for changing and transforming traditional business models and indicators of progress within the tourism industry in Hawai'i. Further research may explore additional Pacific Island countries to gain a deeper understanding of the problem within the region's context.

Students in teaching-focused business-schools need a level of assistance and advisement broader and more profound than what is needed in R1&R2 schools. We investigate the informal interdependencies among marketing, finance, operation, and management core courses in these schools. By conducting hypothesis tests on a large dataset, we identify a flexible network showing the preferred sequencing of these courses to improve students' performance as measured by the course grade. Better performances in this context may also lead to higher retention-rates and lower time-to-degree. We recommend taking Finance or Finance and Management as the first course(s). Marketing should be the next course before or concurrent with Operations Management. Regarding the lower division courses, it is recommended to take Statistics before Economics and Accounting courses and Accounting before or concurrent with Economics. We also consider the significant role of a milestone course that links the lower division and core courses.