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 authors designed a science and engineering curricular program that includes design features that promote student interest and motivation and examined teachers' and students' views on meaningfulness, motivation and interest.

The research approach consisted of mixed methods, including content analyses and descriptive statistics.

The curricular program successfully included all four of the US National Academies of Sciences' design features for promoting interest and motivation through scientific investigation and engineering design. During interviews, teachers and students expressed evidence of design features associated with interest and motivation. After experiencing the program, more than 60% of all students scored high on all four science and engineering meaningfulness and interest survey items.

A curricular program that extends science learning through the engineered design of solutions is an innovative approach to foster both conceptual knowledge development and interest and motivation in science and engineering.

Identifying factors that impact workers’ health and performance is extremely important for companies and, in particular, for companies in the construction sector. Despite the evidence, knowledge about the relationship between commuting, health and worker performance is still limited. More specifically on the relationship with work engagement, studies focus on work-related aspects, neglecting individual and behavioral factors. This study aims to verify the relationship between the commuting patterns of workers, their health and their work engagement in a civil construction company located in São José dos Campos, Brazil.

A structured questionnaire was applied to 43 civil construction workers. The participants’ physical and mental health was evaluated using the 12-item short-form health survey. Employees’ work engagement was assessed through the UWES-17 scale. A descriptive statistical analysis was performed on the relationship between physical and mental health, engagement and commuting to work.

The result corroborated the literature showing that the use of active transport positively influenced the mental health of construction workers and negatively affected those who use individual motorized transport. People working from home had the lowest values for total engagement, vigor and dedication.

This study provides evidence and a prior understanding of this relationship, serving as a basis for decision-making processes in the area of transport that contribute to the health and better functioning of companies in the construction sector. This work also contributes to the state of the art on the relationship between commuting, health and worker engagement.

Research has shown that science, technology, engineering and mathematics (STEM) self-beliefs and enjoyment are critical factors for predicting female students’ persistence in STEM degrees and careers. Studies have shown the positive effects of informal STEM learning experiences on female students’ self-beliefs. However, with the rise of all-female STEM learning experiences, such as summer camps, considering the potential advantages and disadvantages of co-ed options is important. Further, prior STEM education research has focused on sex differences in students’ self-efficacy and STEM career interests. Our study aims to examine within sex differences in secondary, female students (n = 104) who attend either a co-ed STEM camp or a same-sex STEM camp.

To examine potential differences, we conducted independent sample t-tests.

Results of the study include statistically significant differences in mathematics and science self-efficacy as well as STEM career interest after participating in their respective camps.

Further, prior research in STEM education has focused on between sex differences in students’ self-efficacy and STEM career interest.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.