Search results

Artificial intelligence (AI) is a growing paradigm and has made considerable changes in many fields of study, including medical education. However, more investigations are needed to successfully adopt AI in medical education. The purpose of this study was identify the determinant factors in adopting AI-driven technology in medical education.

This was a descriptive-analytical study in which 163 faculty members from Tabriz University of Medical Sciences were randomly selected by nonprobability sampling technique method. The faculty members’ intention concerning the adoption of AI was assessed by the conceptual path model of task-technology fit (TTF).

According to the findings, “technology characteristics,” “task characteristics” and “TTF” showed direct and significant effects on AI adoption in medical education. Moreover, the results showed that the TTF was an appropriate model to explain faculty members’ intentions for adopting AI. The valid proposed model explained 37% of the variance in faulty members’ intentions to adopt AI.

By presenting a conceptual model, the authors were able to examine faculty members’ intentions and identify the key determining factors in adopting AI in education. The model can help the authorities and policymakers facilitate the adoption of AI in medical education. The findings contribute to the design and implementation of AI-driven technology in education.

The finding of this study should be considered when successful implementation of AI in education is in progress.

This paper aims to examine the extent to which performance indicators (PIs) reported by New Zealand (NZ) higher education institutions (HEIs) correspond with accounting standards and guidance and the effects issuance of principles-based authoritative guidance and early adoption of Public Benefit Entity Financial Reporting Standard 48 (PBE FRS 48) have on the PIs disclosed.

Using a content analysis index derived from accounting standards and guidance, we conduct a longitudinal assessment of the 2016 and 2019 statements of service performance published by 22 NZ HEIs.

The PIs reported extend beyond the service performance elements proposed by standard-setters. Despite few indicators on intermediate and broader outcomes, the measures disclosed by HEIs are reflective of their role in the NZ economy and the national Tertiary Education Strategy. The results show that principles-based authoritative guidance and early adoption of PBE FRS 48 influence the focus and type of measures disclosed, while there is no evidence of improvements in the reporting of impacts, outcomes and information useful for performance evaluation.

This paper provides timely insights for standard-setters and regulators on the influence principles-based accounting standards and guidance have on non-financial reporting practices.

This study contributes to the scant literature on HEIs’ service performance reporting. It presents a model for conceptualising HEIs’ PIs that can be used as a basis for future research on non-financial reporting. It also reflects on the tension between accountability and “accountingisation”, suggesting that, although the PIs reported support formal accountability, they do not communicate whether HEIs’ activities and outputs meet their social purpose.

In 2022, the International Network for Quality Assurance (QA) Agencies in Higher Education (INQAAHE) published the new guidelines by adding three QA modules in response to the changing higher education landscape. The paper aims to investigate the transformative focus of quality assurance in higher education globally as well as Asian response to three new QA modules according to the INQAAHE ISGs.

The research conducted a quantitative approach for data collection. An on-line survey was conducted to perceive QA practices, perceptions toward new emerging QA modules and challenges encountered. In total, there were 26 responses from 18 territories with 22 QA agencies. A total of 13 out of them have a national qualifications framework in place.

Three are three major findings in the study. First, national policy and criteria and standards in distance education have been developed in the majority of Asian nations. Second, non-signatories of the Tokyo Convention had a higher proportion of having related policies, regulations and criteria in CBHE and distance education. Third, national policies and regulations; and lack of professional staff are two common challenges implementing QA in new types of providers.

The findings are of value for policymakers, QA agencies and universities to advocate the new QA model as a systematic approach in response to changing higher education landscape in the post pandemic era.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

The purpose of this study is to scrutinize the influence of individual learning styles on the effectiveness of augmented reality (AR)-based learning in structural engineering. There has been a lack of research examining the correlation between learning efficiency and learning style, particularly in the context of quantitatively assessing the efficacy of AR in structural engineering education.

Using Kolb’s experiential learning theory (ELT), a model that emphasizes learning through experience, students from the construction management department are assigned four learning styles (converging, assimilating, diverging and accommodating). Performance data were gathered, appraised, and compared through the three dimensions from the Knowledge, Attitude and Practices (KAP) survey model across four categories of Kolb’s learning styles in both text-graph (TG)-based and AR-based learning settings.

The findings indicate that AR-based materials positively impact structural engineering education by enhancing overall learning performance more than TG-based materials. It is also found that the learning style has a profound influence on learning effectiveness, with AR technology markedly improving the information retrieval processes, particularly for converging and assimilating learners, then diverging learners, with a less significant impact on accommodating learners.

These results corroborate prior research analyzing learners' outcomes with hypermedia and informational learning systems. It was found that learners with an “abstract” approach (convergers and assimilators) outperform those with a “concrete” approach (divergers and accommodators). This research emphasizes the importance of considering learning styles before integrating technologies into civil engineering education, thereby assisting software developers and educational institutions in creating more effective teaching materials tailored to specific learning styles.

This paper aims to examine how the diversity of educational levels within bank boards influences the efficiency and stability of banks operating in the Middle East and North Africa (MENA) region. Unlike previous studies, this analysis also investigates the role of board gender diversity in moderating the relationship between board educational level diversity and bank efficiency and financial stability in MENA.

In this study, a sample of 77 banks in the MENA region spanning the years 2011 to 2018 is used. The relationship between the presence of highly educated directors on the board, bank efficiency and stability is assessed using the ordinary least squares method. Additionally, the authors use the Generalized Method of Moments technique to correct endogeneity problem.

This study establishes a positive association between the presence of directors with advanced educational backgrounds on bank boards and bank efficiency and stability. Furthermore, the inclusion of women on the board strengthens this relationship.

These findings have important implications for policymakers and regulators in the MENA region, suggesting that promoting diversity policies that encourage the participation of highly educated directors on bank boards can contribute to enhanced efficiency and financial stability. Policymakers may also consider implementing quotas or guidelines to improve gender diversity in board appointments, thereby fostering bank performance in the region.

This study stands out for its innovation and distinctiveness, as it delves into the connection between board educational level diversity and bank efficiency in the MENA region. Notably, it surpasses previous research by investigating the moderating role of board gender diversity, thus offering valuable insights into the complex interplay between these two facets of board diversity. This contribution enriches the existing literature by providing novel perspectives on board composition dynamics and its influence on bank efficiency and stability.

The study aims to identify the key advantages/enablers and disadvantages/barriers of augmented reality (AR) implementation in education through existing reviews. It also examines whether these factors differ across educational domains.

This study conducted a systematic review of reviews to synthesize evidence on the barriers and enablers influencing AR adoption in education. Searches were performed across five databases, with 27 reviews meeting the inclusion criteria. Data extraction and quality assessment were completed. Content analysis was conducted using the AR adoption factor model and consolidated framework for implementation research.

The findings reveal several enablers such as pedagogical benefits, skill development and engagement. Equally, multiple barriers were identified, including high costs, technical issues, curriculum design challenges and negative attitudes. Interestingly, duality emerged, whereby some factors served as both barriers and enablers depending on the educational context.

This review contributes a novel synthesis of the complex individual, organizational and technological factors influencing AR adoption in education across diverse domains. The identification of duality factors provides nuanced understanding of the multifaceted dynamics shaping AR integration over time. The findings can assist educators in tailoring context-sensitive AR implementation strategies to maximize benefits and minimize drawbacks. Further research should explore duality factors and their interrelationships in AR adoption.