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Discusses the authors’ approach to experiential learning in a two‐semester “engineering physics” course at a large metropolitan university in the USA. A student‐centered methodology stressing teamwork while incorporating individual creativity is used in an interdisciplinary course setting. Students practice transferable skills relevant to today’s technological workplace. Discusses the methodology and lessons learned in the context of higher education in the USA and abroad.

In today’s digital age, technology is advancing at an unprecedented pace, and businesses that fail to keep up risk falling behind their competitors. This requires not only investing in technological resources but also creating a culture that values and encourages women in technological learning and innovation in the tourism and hospitality sector. This study aims to investigate the consequences of organizational learning on firm innovation directly and indirectly with cultural and technological perspectives.

The study carries out a quantitative approach, and data is collected from 398 women entrepreneurs from Thailand’s tourism and hospitality sectors. The statistical software Smart-PLS was used to analyze the data.

The findings revealed that organizational learning (the learning orientation and learning process) significantly influence firm innovation and organizational culture. Organizational culture also significantly mediates learning orientation, learning process and firm innovation, while learning leadership was found to be insignificant in relationship with organizational culture and firm innovation. However, technological knowledge has a significant moderating influence between organizational culture and firm innovation.

This study’s focus on the role of learning practices among women-owned small medium enterprises is a valuable contribution to the literature on innovation and entrepreneurship. These provided dimensions that can be helpful for women entrepreneurs to enhance firm innovation. The study shed light on the importance of diverse kinds of learning practices that change the patterns of innovation. This study also provides directions to practitioners to develop and implement business innovation strategies from women’s perspectives.

The purpose of this paper is to develop a framework for studying organizational learning, firm innovation and firm financial performance.

This paper examines the effects of organizational learning on innovation and performance among 287 listed Chinese companies.

The results indicate a positive association between organizational learning dimensions and firm performance (both objective financial performance and perceptual innovation measure).

The sample includes only firms for which secondary data are available. Different results might have been obtained if we include smaller, private firms into the sample. This paper only includes a limited number of measures of financial performance to assess the relationship between organization learning dimensions and firm performance. Therefore, researchers are encouraged to test the proposed propositions further with different performance measures.

The results showed that it is the combination of several learning characteristics and not a single dimension that influenced the variance of firm performance. The findings reinforce the notion that systemic interventions that address a variety and different combinations of learning organization characteristics will be more likely to be successful than interventions that solely focus on singular or a limited number of dimensions.

The integration of objective measures of firms’ financial performance with perceptual survey data represents a unique methodology that has not been widely used in the organizational learning literature. The positive correlations between the eight learning dimensions and the measures of firms’ performance lend credence to the efficacy of the organizational learning concepts.

The purpose of this paper is to identify the factor structure of safety culture construct among engineering students at university context and to examine the measurement invariance of this instrument across different socio-demographic groups in a sample of engineering students in the United Arab Emirates (UAE).

An exploratory online questionnaire was completed by 770 undergraduate and postgraduate engineering students across the UAE. Data were analyzed using a diversified multi-group and a robust and sophisticated cross-validation testing strategy. Confirmatory factor analysis (CFA) was used to test factor structures identified in previous studies. Multi-group invariance testing was conducted to determine the extent to which factor structure is comparable across groups (i.e. gender, educational and experiential background).

Three-factor model was preferred for its parsimony. The results showed that the level of safety awareness and attitude is relatively satisfactory, whereas safety behaviour is inadequate. No significant difference was showed in multi-group invariance between demographic groups.

This research is a cross-sectional study and limited to the views of engineering students (informal group). The study would benefit from both informal and formal groups in assessing safety culture at university for a robust empirical evidence. The research highlights relevant implications for policy and program development, by pointing to the need to promote safety culture and mitigate safety-related accidents among engineering students.

This paper offers insight into benefit of understanding the level of safety culture among engineering students and extend knowledge of informal group involvement in safety-related accidents at university level.

The purpose of this paper is to study the preparation of polyvinyl alcohol (PVA)/CuS composite nanofibres, and the effects of solution and process parameters on the resulting nanofibres.

A facile method coupling self‐assembly and electrospinning technology was used to prepare PVA/CuS nanofibres from PVA/CuCl₂ · 2H₂O solution.

CuS nanoparticles were well dispersed in the composite nanofibres, the dimension of which was in the range of 4‐9 nm. Low amount of salt in electrospinning solutions and high‐applied voltage were beneficial for forming smooth and small sized nanofibres. The tip‐to‐collector distance has not affected the morphology of resulting nanofibres.

The orientation of the composite nanofibres was hardly controlled and the diameter distribution of nanofibres was not uniform enough.

The method combining electrospinning and self‐assembly provided an effective strategy for preparing nanoparticles doped composite nanofibres.

The morphology of composite nanofibres was well controlled via adjusting the solution and process parameters, therefore, the fibres obtained will have potential applications as controllable nano‐optoelectronic materials.

Construction companies are increasingly adopting sensing technologies like laser scanners, making it necessary to upskill the future workforce in this area. However, limited jobsite access hinders experiential learning of laser scanning, necessitating the need for an alternative learning environment. Previously, the authors explored mixed reality (MR) as an alternative learning environment for laser scanning, but to promote seamless learning, such learning environments must be proactive and intelligent. Toward this, the potentials of classification models for detecting user difficulties and learning stages in the MR environment were investigated in this study.

The study adopted machine learning classifiers on eye-tracking data and think-aloud data for detecting learning stages and interaction difficulties during the usability study of laser scanning in the MR environment.

The classification models demonstrated high performance, with neural network classifier showing superior performance (accuracy of 99.9%) during the detection of learning stages and an ensemble showing the highest accuracy of 84.6% for detecting interaction difficulty during laser scanning.

The findings of this study revealed that eye movement data possess significant information about learning stages and interaction difficulties and provide evidence of the potentials of smart MR environments for improved learning experiences in construction education. The research implication further lies in the potential of an intelligent learning environment for providing personalized learning experiences that often culminate in improved learning outcomes. This study further highlights the potential of such an intelligent learning environment in promoting inclusive learning, whereby students with different cognitive capabilities can experience learning tailored to their specific needs irrespective of their individual differences.

The classification models will help detect learners requiring additional support to acquire the necessary technical skills for deploying laser scanners in the construction industry and inform the specific training needs of users to enhance seamless interaction with the learning environment.