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This research investigates students’ information-seeking behaviours at the Indian Maritime University (IMU) and assesses the impact of AI chatbots on their marine science knowledge and awareness. The study aims to provide insights into the role of AI-driven solutions in enhancing knowledge sharing and the challenges faced in using AI tools for marine information retrieval.

The study used a stratified random sampling method, encompassing 152 respondents from IMU’s B.Sc. in Nautical Science and B. Tech in Marine Engineering programs. Data collection involved a structured electronic survey questionnaire. The analysis encompassed descriptive statistics using SPSS.

Information needs were met through diverse channels, with 57.9% of respondents using AI-driven chatbots for marine information retrieval. AI significantly recommended research papers (61.8%). The chatbot positively impacted marine science awareness and knowledge, with a mean satisfaction rating of approximately 3.3. Challenges included insufficient access to AI tools, data privacy concerns and accuracy issues.

This study contributes original insights into the information-seeking behaviours of marine students at IMU and the impact of AI chatbots on their knowledge and awareness. It highlights the multifaceted nature of marine information retrieval, the effectiveness of AI-driven solutions in enhancing knowledge sharing and the challenges that need to be addressed for the broader adoption of AI tools in this context.

This study examines education for sustainability (EfS) within the Chinese context, to specifically enrich the understanding on how EfS is structured and implemented to nurture citizenship in the policy practices of universities in Mainland China and Hong Kong.

A cross-case analysis is recruited to examine the commonalities and differences between two universities and identify patterns in cultivating sustainability citizenship within higher education institutions (HEIs) in China. Data were collected through reviewing documents, including two universities’ strategic plans, action plans, department meeting memos, program introductions, course outlines and publicity coverage. Observation was also adopted to enrich the data for analysis, covering meetings, speeches by senior management, university events and informal conversations about university operations.

Citizenship and sustainability in university strategic planning, curriculum and instruction, carriers of EfS institutionalization, and resources and impacts of EfS beyond the institutes were analyzed in a comparative manner, offering valuable insights into how EfS can be institutionalized in different universities based on their unique appeals, existing curriculum and management systems.

By exploring these intra-national distinctions in EfS, the study sheds light on the variation within China's citizenship education, which is traditionally seen as highly unified with limited room for differences. The detailed exploration of university strategies and program/course content enriches the literature of sustainability as an educational phenomenon on an international scale and modernized citizenship education in China.

Current knowledge and research on students’ utilization and interaction with generative artificial intelligence (AI) tools in their academic work is limited. This study aims to investigate students’ engagement with these tools.

This research used survey-based research to investigate generative AI literacy (utilization, interaction, evaluation of output and ethics) among students enrolled in a four-year public university in the southeastern USA. This article focuses on the respondents who have used generative AI (218; 47.2%).

Most respondents used generative AI to generate ideas for papers, projects or assignments, and they also used AI to assist with their original ideas. Despite their use of AI assistance, most students were critical of generative AI output, and this mindset was reflected in their reported interactions with ChatGPT. Respondents expressed a need for explicit guidance from course syllabi and university policies regarding generative AI’s ethical and appropriate use.

Literature related to generative AI use in higher education specific to ChatGPT is predominantly from educators’ viewpoints. This study provides empirical evidence about how university students report using generative AI in the context of generative AI literacy.

Reflexive thematic analysis was used to analyze the data. The study’s aims were to (1) Explore challenges, barriers and successes of students of color, as a result of the instructor’s approach to teaching in a remote learning environment; and (2) Determine what types of practices and approaches students of color found supportive in adjusting to a remote learning environment.

This qualitative study used in-depth interviews to explore the experiences of students of color, reflecting on in-person and remote learning environments. A total of 18 students from a large public university participated in the study.

The findings suggest significant adjustments were made by both students and professors during the pandemic. Although academics were important to students, there was an emphasis on the impact on social interactions with peers and the ability to build meaningful relationships with professors. Students displayed a sense of compassion and empathy toward professors and themselves.

The results from the study provide some insight into how higher education can move forward, potentially conducting future research that includes the perspectives of both students and professors to determine how to best provide support in the aftermath of a pandemic.

This qualitative study used in-depth interviews to explore the experiences of students of color, reflecting on in-person and remote learning environments.

A methodological approach is required that complements studies based on surveys, providing a perspective with greater truthfulness and coverage. The study aims to develop a methodology to validate psychological/managerial constructs using data from Google Trends, taking as a case study a critical thinking (CT) scale in organizational domains previously supported by survey data.

The developed methodology consists of eight stages, in which the following is integrated: (1) Internet search interest data (19 Spanish-speaking countries); (2) deductive research processes (e.g. theoretical model, linguistic manifestations, fieldwork, data matrix, analysis statistical, reporting); (3) psychometric properties (e.g. construct validity, criterion validity, reliability) and (4) objective data to examine criterion validity (e.g. unemployment rate).

The application of the methodology produces evidence that supports the reliability (Cronbach’s alpha, Guttman’s λ₄), construct validity (intra-correlations and correlations with reference variables: “entrepreneurship,” “critical thinking,” “soccer,” “beer,” “pornography”) and criterion validity (prediction of unemployment rate) of the CT scale.

The methodology makes it possible to support or invalidate the quality of construct measurement scales by planning, capturing and processing data available on the internet.

This manuscript is useful for research in business management (and related areas), which is intensive in the use of psychological/managerial constructs.

The methodology uses a new type of evidence; it is noninvasive, usually more truthful than responses to surveys, and has greater coverage of people participating indirectly in the study.

Exploring trust's impact on AI project success. Companies can't leverage AI without employee trust. While analytics features like speed and precision can build trust, they may also lower it during implementation, leading to paradoxes. This study identifies these paradoxes and proposes strategies to manage them.

This paper applies a grounded theory approach based on 35 interviews with senior managers, users, and implementers of analytics solutions of large European companies.

It identifies seven paradoxes, namely, knowledge substitution, task substitution, domain expert, time, error, reference, and experience paradoxes and provides some real-life examples of managing them.

The limitations of this paper include its focus on machine learning projects from the last two years, potentially overlooking longer-term trends. The study's micro-level perspective on implementation projects may limit broader insights, and the research primarily examines European contexts, potentially missing out on global perspectives. Additionally, the qualitative methodology used may limit the generalizability of findings. Finally, while the paper identifies trust paradoxes, it does not offer an exhaustive exploration of their dynamics or quantitative measurements of their strength.

Several tactics to tackle trust paradoxes in AI projects have been identified, including a change roadmap, data “load tests”, early expert involvement, model descriptions, piloting, plans for machine-human cooperation, learning time, and a backup system. Applying these can boost trust in AI, giving organizations an analytical edge.

The AI-driven digital transformation is inevitable; the only question is whether we will lead, participate, or fall behind. This paper explores how organizations can adapt to technological changes and how employees can leverage AI to enhance efficiency with minimal disruption.

This paper offers a theoretical overview of trust in analytics and analyses over 30 interviews from real-life analytics projects, contributing to a field typically dominated by statistical or anecdotal evidence. It provides practical insights with scientific rigour derived from the interviews and the author's nearly decade-long consulting career.

The study aims to assess Oman's preparedness for digital competency on three parameters: knowledge, technology, and future readiness. Second, it aims to identify critical areas of implementation of digital competency concerning HEIs.

Knowledge shall be assessed for talent, training and education, and scientific concentration. Technology will be evaluated based on regulatory, capital, and technological frameworks. Future readiness shall be examined based on adaptive attitude, business agility, and IT integration. The overall status in all three areas will be evaluated, considering contributions made by various stakeholders, such as the government, public agencies, corporations, educational institutions, etc. The data for this exploratory exercise shall be cogenerated from various secondary sources that are available openly.

Oman scores above average on parameters of technological and regulatory framework, adaptive attitudes, and IT integration, with an average score above 60 out of 100. Oman’s mean score for sub-factors like talent, training and education, capital, and business agility is average—between 50 and 60. The mean score for scientific concentration is 35.14—below average for this criterion.

Most of the studies in Oman have concentrated mainly on teachers' online awareness and competencies, particularly in schools during and after the post-COVID scenario. However, negligible studies are available for higher education. This is an original study for assessing digital competencies, particularly concerning higher education towards achieving Vision 2040 and diversifying the Sultanate of Oman as a knowledge economy.

College student’s mental health issues have emerged as a significant public health concern. The urban campus environment, being the primary habitat for college students, plays a crucial role in influencing their mental health.

Based on survey data from 34 Chinese universities and 1173 college students in 2021, this study utilized deep learning and street view images to explore the relationship between various urban campus landscapes, college students' exercise participation, and mental health.

The study revealed substantial variations in campus landscape features, particularly in terms of spatial openness. While green campus landscapes (measured by the Green View Index and Normalized Difference Vegetation Index) showed no significant impact on exercise participation or mental health, the Sky View Factor did. Higher levels of campus openness and exercise frequency were associated with better mental health. The study also underscored that the influence of urban campus landscapes on college students' mental health was mediated by their exercise participation. Notably, spatial openness emerged as the most prominent differentiating factor among urban campus landscape attributes, significantly affecting students' exercise participation and mental health.

Thus, fostering open campus environments and reducing spatial constraints are vital steps in creating a sustainable urban landscape that can help alleviate potential negative effects on college students' mental health issues.

This paper aims to explore the effects of parents’ support factors on Chinese university students’ digital entrepreneurship motivation on live streaming platforms. Based on the Social support theory, this study divides influencing factors into emotional, instrumental, informational and appraisal aspects. Meanwhile, considering the impact of China’s regional differences, the paper refers to the Regional difference theory and performs a multi-group analysis to assess the differences based on Chinese university students’ regional backgrounds.

By testing 556 samples based on the partial least squares path modelling and variance-based structural equation modelling, all support factors parents provide can stimulate Chinese university students’ digital entrepreneurship motivation.

Based on the multi-group comparison, parents’ informational support exerts a more substantial influence on the digital entrepreneurship motivation for university students from central and east regions rather than those from the western region, and parents’ instrumental support exerts a lower influence on digital entrepreneurship motivation for east university students than for west university students.

This paper applies the Social support theory as a theoretical framework to divide the impact factors, and it uses the Regional difference theory as a guide for the multi-group analysis of correlations, which is significant for online entrepreneurial motivation research and a better understanding of student groups. In addition to testing the hypotheses, the study also measures the importance–performance map analysis to explore additional findings of influencing factors and discuss managerial implications.

In this study, we aim to investigate entrepreneurial intention (EI) among potential entrepreneurs who were students at Pakistan’s higher education institutes (HEIs) of technical and vocational education and training (TVET).

We used a quantitative and correlational method in this study, and we based its theoretical framework on the theory of planned behavior (TPB) and the entrepreneurial event model (EEM). We based this study’s findings on 367 samples collected from Pakistan’s HEI TVET students who were potential entrepreneurs.

By employing path analysis, the findings reveal that TPB constructs, such as personal attitudes (PA), subjective norms (SN) and perceived behavioral control (PBC), have a positive and significant effect on EI. The findings show, also, that EEM constructs, such as perceived desirability (PD), perceived feasibility (PF) and propensity to act (PT) are positive and significant predictors of EI. Moreover, self-efficacy (SE) and the quality of TVET (QTT) positively and significantly affect EI.

This study’s findings support the improvement of Pakistan’s HEIs in developing TVET to enhance individuals’ skills and, ultimately, to create employment and socioeconomic circumstances. They also assist Pakistan’s HEIs in developing EI among their TVET potential entrepreneurs to ensure that they are sufficiently equipped for the job markets.

This study’s findings empirically confirm that TPB, EEM, SE and the QTT provide an integrated path for Pakistan’s entrepreneurs.