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This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms.

This paper describes a pedagogical approach that uses a data science framework the research team developed to assist teachers in providing data science instruction to elementary-aged students. Using phenomenological case study methodology, the authors use classroom observations, student focus groups, video recordings and artifacts to detail ways learners engage in data science practices and understand how they perceive their engagement during activities and learning.

Findings suggest student engagement in data science is enhanced when data problems are contextualized and connected to students’ lived experiences; data analysis and data-based decision-making is practiced in multiple ways; and students are given choices to communicate patterns, interpret graphs and tell data stories. The authors note challenges students experienced with data practices including conflict between inconsistencies in data patterns and lived experiences and focusing on data visualization appearances versus relationships between variables.

Data science instruction in elementary schools is an understudied, emerging and important area of data science education. Most elementary schools offer limited data science instruction; few elementary schools offer data science curriculum with embedded CT practices integrated across disciplines. This research assists elementary educators in fostering children's data science engagement and agency while developing their ability to reason, visualize and make decisions with data.

This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.

Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.

The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.

This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.

Few empirical studies examined the relationship between life expectancy and income in India. This study aims to examine the impact of life expectancy on economic growth in India by incorporating all the major states of India.

This study is based on secondary data and includes 16 major states of India covering the periods 2000–2014. The author used panel fixed effect model (FEM) to examine the impact of life expectancy on economic growth.

Empirical analysis revealed a positive trend in life expectancy in India. In association with life expectancy, the author found continuous growth in the elderly population. The result of the FEM shows that gains in life expectancy positively affect economic growth in India. The empirical findings do not support any negative impact of life expectancy gains on economic growth.

This study is the outcome of the independent and original research work of the authors and contributes significantly to the literature on the demography–economic relationship. The findings of this study help the author to understand that life expectancy gain is in no way a constraint, rather the skill and experience of the workforce are crucial to determining economic growth.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2022-0422.

The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.

The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.

A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.

This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

The purpose of this study is to provide a nuanced understanding of the marketing placebo effect (MPE) of products with reduced sugar labeling and how it forms certain perceptual underpins (perceived healthiness (PH) and perceived tastiness (PT)), with the potential effect of product category and social class in consideration.

The proposed model is tested using a sample of 822 participants by employing partial least squares structural equation modeling (PLS-SEM). Hypothetical relationships among MPE, PH, PT, purchase intention (PI) and social class are examined for both hedonic and utilitarian products.

The results highlight the positive role of MPE in leveraging consumer PI through the parallel mediation of PH and PT. The positive effect of MPE on PH and PT was more pronounced for the utilitarian product. In addition, social class negatively moderated the relationship between PH and PI only in the case of the utilitarian product.

This paper contributed to the MPE literature in the food industry by challenging the conventional intuition of “Unhealthy = Tasty” and highlighting the potential of perceived food healthiness to positively influence perceived food tastiness under the effect of MPE. An upper social class would attenuate the positive effect of perceived food healthiness on PI.

This study is designed to investigate a critical association between social media addiction and employee sleep while considering its implications for employee well-being and performance in the hospitality industry.

Based on adapted measures for the study variables, an electronic questionnaire was designed and used for the survey administered in the chain-restaurants of Pakistan. Through a non-probability convenient sampling survey, a total of 347 usable responses were obtained and analyzed for testing the hypothesized research model.

Results reveal negative associations between social media addiction, sleep quality, employee performance and well-being. The results have further shown sleep quality as an underlying mediating reason that explains the associations between social media addiction, employee performance and well-being.

The study addresses a gap in the literature by examining rarely explored factors such as social media addiction and sleep quality at the same time investigating its impact on performance and well-being of service employees. Significant implications for scholars and practitioners of the hospitality industry have been discussed while highlighting limitations and directions for future research.