Search results

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

This study builds on previous theoretical work that considered artificial intelligence (AI) and its potential for creating “teacher-centaurs” whose labor could be accelerated through the use of generative AI (Fassbender, in review). The purpose of this paper is to use empirical methods to study centaur teachers and the division of labor (Durkheim, 1893/2013) that arise from outsourcing teaching tasks to AI.

Multiple case study (Stake, 2006) was used to collect data on two secondary English teachers who were early adopters of generative AI. Data included semi-structured interviews as well as ChatGPT chat logs, which helped in describing how teaching approaches evolved using AI technology.

Results showed that teachers used AI for planning, instruction and assessment. AI-augmented teaching practices allowed teachers to complete tasks with greater speed, which in turn increased stamina and short-term work–life balance. Given the novelty of AI, concerns about data privacy and academic integrity raised ethical questions.

ChatGPT’s rise to popularity in 2023 brought with it significant discussions about education, specifically how students would use AI primarily as a tool for plagiarism. This study takes a different focus, considering how early adoption of AI has begun changing teacher labor, offering implications for the future of the teaching profession.

This paper aims to consolidate empirical studies between 2013 and 2022 to investigate the impact of artificial intelligence (AI) in higher education. It aims to examine published research characteristics and provide insights into the promises and challenges of AI integration in academia.

A systematic literature review was conducted, encompassing 44 empirical studies published as peer-reviewed journal papers. The review focused on identifying trends, categorizing research types and analysing the evidence-based applications of AI in higher education.

The review indicates a recent surge in publications concerning AI in higher education. However, a significant proportion of these publications primarily propose theoretical and conceptual AI interventions. Areas with empirical evidence supporting AI applications in academia are delineated.

The prevalence of theoretical proposals may limit generalizability. Further research is encouraged to validate and expand upon the identified empirical applications of AI in higher education.

This review outlines imperative implications for future research and the implementation of evidence-based AI interventions in higher education, facilitating informed decision-making for academia and stakeholders.

This paper contributes a comprehensive synthesis of empirical studies, highlighting the evolving landscape of AI integration in higher education and emphasizing the need for evidence-based approaches.

Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.

Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).

The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.

Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.

The deployment of artificial intelligence (AI) technologies in travel and tourism has received much attention in the wake of the pandemic. While societal adoption of AI has accelerated, it also raises some trust challenges. Literature on trust in AI is scant, especially regarding the vulnerabilities faced by different stakeholders to inform policy and practice. This work proposes a framework to understand the use of AI technologies from the perspectives of institutional and the self to understand the formation of trust in the mandated use of AI-based technologies in travelers.

An empirical investigation using partial least squares-structural equation modeling was employed on responses from 209 users. This paper considered factors related to the self (perceptions of self-threat, privacy empowerment, trust propensity) and institution (regulatory protection, corporate privacy responsibility) to understand the formation of trust in AI use for travelers.

Results showed that self-threat, trust propensity and regulatory protection influence trust in users on AI use. Privacy empowerment and corporate responsibility do not.

Insights from the past studies on AI in travel and tourism are limited. This study advances current literature on affordance and reactance theories to provide a better understanding of what makes travelers trust the mandated use of AI technologies. This work also demonstrates the paradoxical effects of self and institution on technologies and their relationship to trust. For practice, this study offers insights for enhancing adoption via developing trust.

The data for the case is a mix of both primary and secondary data, from the following sources: – personal interviews with the protagonist, Sofana Dahlan; – Tashkeil website; – official documents provided by the company: ■ “Tashkeil – Corporate Brief,” ■ “Saudi National Creative Initiative – Activities Report 2016”; and ■ “Tashkeil Global Company”. – published media sources.

The case outlines the story of Sofana Dahlan (Sofana) (she/her), a social entrepreneur and one of the first few women lawyers in the Kingdom of Saudi Arabia. She established Tashkeil as a social enterprise, helping creative entrepreneurs (creatives) with strategic, operational and legal inputs, thus enabling the creative industry in different parts of the Arab world, focussing on Saudi Arabia and Lebanon. Her story can be used to inspire students on how a female entrepreneur fought against an extremely restrictive social and cultural environment and achieved her goals. It helps them to understand the challenges faced by women in the context of the Arab world and the key attributes required for them to succeed as an entrepreneur, especially in the context of certain social and cultural barriers. It also helps to understand the importance of resilience in entrepreneurs and to discuss how entrepreneurs can become more resilient.

The case can be used mainly in undergraduate Business Management Programs in courses such as Entrepreneurship, with specific reference to Women Entrepreneurship. The case would be a good fit for courses on Social Entrepreneurship and Creative Businesses.

Women entrepreneurs are often categorized and assessed for various outcomes based on their start-up motivations. It is generally assumed that entrepreneurs with opportunity motivation have better performance when compared to necessity entrepreneurs. This study aims to test these suppositions through the lens of the entrepreneur’s motivation to learn (MTL) and level of female entrepreneurial competencies (FECs), namely, business and management, entrepreneurial, human relations (HR) and personal.

Data collected from 344 respondents through a survey questionnaire was analyzed using the structural equation modelling – partial least squares method using SmartPLS 4.

The findings highlight the need of recognizing the differentials between necessity and opportunity entrepreneurs as they were found to influence performance and learning outcomes. Opportunity entrepreneurship was found to significantly impact both MTL and the FECs. The authors also observed that business and management skills along with HR competencies played a greater role in the firm performance.

The findings demonstrate a case for specialized, tailor-made policy approaches rather than the “one size fits all” approach as evident in many government programs. As necessity entrepreneurs form a vital part of the Indian entrepreneurial ecosystem, apart from mentoring, need-based competency development programs may be looked at. Opportunity entrepreneurs may need support and encouragement through advanced skilling and uncomplicated funding options.

To the best of the authors’ knowledge, empirical studies related to women-owned micro, small and medium enterprises in India establishing the relationship between start-up motivation and business performance are scarce. Even in the global context, this is one of the initial studies to examine the relationship through the lens of MTL and competencies.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

Emphasizing the critical role of technology-enabled distribution in tourism, this study, a viewpoint, aims to highlight the potential of democratized technologies in readdressing the competitive imbalance between small- and medium-sized tourism enterprises (SMTEs) and their larger peers in today’s online marketplace. By enhancing competitiveness and performance, democratized technologies can strengthen the resilience, sustainability and competitive position of the SMTEs on which tourism depends, helping to support the Horizon 2050 agenda and UN’s Sustainable Development Goals.

Examining the development of online and electronic distribution in tourism, the viewpoint identifies the key challenges to the successful use of technology-based distribution systems by SMTEs, as well as highlights the trend toward democratized technologies as a potential solution to help improve technology take-up and performance.

With no/low initial capital or operating costs, and little need for technical expertise, democratized technologies have the potential to overcome two of the three key challenges limiting the successful adoption and use of distribution technologies by SMTES. The key blockage remains one of managerial awareness and acceptability. With informal organization structures, little managerial or technical training and an ingrained reluctance to change, SMTE managers remain unfamiliar of the possibilities offered by this developing trend. While this challenge could be addressed by awareness building and training, in the longer run, it is likely that more substantial progress will arise from generational change in SMTE management, with digitally native successors more likely to exploit this development to improve competitiveness and performance.

Emphasizing the pivotal role that democratized technology can potentially play in redressing the competitive imbalance between SMTEs and their larger peers in the distribution space, this viewpoint serves as a call for action for tourism businesses to re-examine their approach to technology adoption and leverage democratized technologies to address current deficiencies in their distribution approach, helping to improve competitiveness and performance, thus supporting the Horizon 2050 initiative and furthering the UN’s Sustainable Development Goals.

这篇观点论文强调了技术驱动的分销在旅游业中的关键作用, 强调了民主化技术在重新解决中小旅游企业（SMTEs）与其大型同行在当今在线市场中的竞争失衡方面的潜力。通过提高竞争力和绩效, 民主化技术可以加强旅游业所依赖的SMTE的韧性、可持续性和竞争地位, 有助于支持地平线2050议程和联合国可持续发展目标。

该观点论文考察了在线和电子分销在旅游业的发展, 确定了SMTE成功使用基于技术的分销系统的关键挑战, 并强调了将民主化技术作为帮助提高技术使用率和性能的潜在解决方案的趋势。

由于没有/较低的初始资本或运营成本, 也几乎不需要技术专业知识, 民主化技术有可能克服限制SMTES成功采用和使用分销技术的三个关键挑战中的两个。关键的障碍仍然是管理意识和可接受性。由于非正式的组织结构、很少的管理或技术培训以及根深蒂固的不愿改变, SMTE的管理人员仍然不熟悉这一发展趋势所提供的可能性。虽然这一挑战可以通过提高认识和培训来解决, 但从长远来看, SMTE管理的代际变革可能会带来更大的进展, 数字原生继任者更有可能利用这一发展来提高竞争力和绩效。

强调民主化技术在纠正SMTE与其在分销领域的大型同行之间的竞争失衡方面可能发挥的关键作用, 本文呼吁旅游企业采取行动, 重新审视其采用技术的方法, 并利用民主化技术来解决其分销方法中的当前缺陷, 帮助提高竞争力和绩效, 从而支持地平线2050倡议, 推动联合国的可持续发展目标。

Haciendo hincapié en el papel fundamental de la distribución posibilitada por la tecnología en el turismo, este punto de vista destaca el potencial de las tecnologías democratizadas para corregir el desequilibrio competitivo entre las Pequeñas y Medianas Empresas Turísticas (PYMETs) y sus homólogas de mayor tamaño en el mercado online actual. Al mejorar la competitividad y el rendimiento, las tecnologías democratizadas pueden reforzar la resistencia, la sostenibilidad y la posición competitiva de las PYMETS de las que depende el turismo, contribuyendo así a apoyar la agenda Horizonte 2050 y los Objetivos de Desarrollo Sostenible de la ONU.

Examinando el desarrollo de la distribución online y electrónica en el turismo, el punto de vista identifica los desafíos clave para el uso exitoso de los sistemas de distribución basados en la tecnología por parte de las PYMETs, así como destaca la tendencia hacia las tecnologías democratizadas como una solución potencial para ayudar a mejorar la adopción y el rendimiento de la tecnología.

Con unos costes iniciales de capital o de funcionamiento nulos o bajos, y poca necesidad de conocimientos técnicos, las tecnologías democratizadas tienen el potencial de superar dos de los tres retos clave que limitan la adopción y el uso con éxito de las tecnologías de distribución por parte de las PYMETs. El bloqueo clave permanece en la concienciación y la aceptación por parte de los directivos. Con estructuras organizativas informales, escasa formación técnica o de gestión y una arraigada reticencia al cambio, los directivos de las PYMETs permanecen desconocedores de las posibilidades que ofrece esta tendencia en desarrollo. Aunque este reto podría abordarse mediante la concienciación y la formación, a largo plazo es probable que surjan progresos más sustanciales del cambio generacional en la gestión de las PYMETs, con sucesores nativos digitales más propensos a explotar este desarrollo para mejorar la competitividad y el rendimiento.

Haciendo especial hincapié en el potencial y fundamental papel que la tecnología democratizada puede desempeñar a la hora de corregir el desequilibrio competitivo entre las PYMETs y sus homólogas de mayor tamaño en el espacio de la distribución, este punto de vista sirve de llamada a la acción para que las empresas turísticas reexaminen su enfoque de la adopción de tecnología y aprovechen las tecnologías democratizadas para subsanar las deficiencias actuales en su enfoque de la distribución, ayudando a mejorar la competitividad y el rendimiento, apoyando así la iniciativa Horizonte 2050 y fomentando los Objetivos de Desarrollo Sostenible de la ONU.