Search Results (281)

In the context of accelerating digitalization, this study investigates how electronic commerce performance is influenced by Web 2.0 instruments in the 27 EU member states. Analyzing literature reviews and performing our own bibliometric review, we identified a gap related to the measurable economic results of e-commerce. The scope of this study was to analyze the relationship between Web 2.0 tools and the level of turnover generated by e-commerce, applying robust econometric models based on panel data regression with random effects and fixed effects (Arellano–Bond). The results highlight that the online paid advertisement and social media usage variables have significant, positive effects on e-commerce performance, confirming the first and second hypotheses. “Use the enterprise’s blog or microblogs” and “use of multimedia content sharing websites” do not influence enterprises’ total turnover from e-commerce sales to a valid and statistically significant extent. Thus, the third and fourth hypotheses are not confirmed by the results of the research conducted, possibly due to limited innovation and platform ownership in Europe. This study makes a notable empirical and methodological contribution, embedding digital sustainability in the analysis, which implies that the findings can be used for updating e-commerce policies. Full article

A citizen’s ability to thrive in today’s technologically advanced society necessitates robust and nimble scientific literacy. The development of such literacy is rooted in science instruction that engages students with appropriate cognitive tools that enable active knowledge construction through scientific practices. One such instructional approach with proven positive science learning outcomes is project-based learning. However, little is known about future teachers’ takeaways from participation in project-based learning science methods courses and how those takeaways connect to teachers’ developing pedagogical content knowledge. In this qualitative study, we examined pre-service teachers’ end-of-semester reflective blogs and identified the main themes and connections to the five dimensions of pedagogical content knowledge (PCK). Across three cohorts of pre-service science teachers, we found nine common themes connected to the four dimensions of PCK that involve teachers’ orientations towards science teaching, their knowledge of science curricula, instructional strategies, and students’ understanding of science. We found no prominent connections to the dimension that emphasizes a teacher’s knowledge of the scientific literacy assessment. These findings suggest the asymmetrical development of pre-service teachers’ PCK. Teacher educators should explicitly address the scientific literacy assessment and support pre-service teachers as they develop their knowledge of it. We discuss additional implications for research and practice. Full article

This study investigates the feasibility of using GPS data and frequency of COVID-19-related blog words to forecast new infection trends through a linear regression analysis. By employing time series’ trend decomposition and Spearman’s rank correlation, we identify and select a set of significant variables from the GPS and blog data to construct two models: a fixed-period model and a sequential adaptive model that updates with each new wave of infections. Our findings reveal that the adaptive model more effectively captures long-term trends, achieving approximately 90% accuracy in forecasting infection rates seven days in advance. Despite challenges in forecasting exact values, this research demonstrates that combining GPS and blog data through a dynamic, wave-based learning model offers a promising direction for enhancing the forecasting accuracy of COVID-19 spread. This approach has significant implications for public health preparedness. Full article

This article introduces a freely available Spanish–Mixtec parallel corpus designed to foster natural language processing (NLP) development for an indigenous language that remains digitally low-resourced. The dataset, comprising 14,587 sentence pairs, covers Mixtec variants from Guerrero (Tlacoachistlahuaca, Northern Guerrero, and Xochapa) and Oaxaca (Western Coast, Southern Lowland, Santa María Yosoyúa, Central, Lower Cañada, Western Central, San Antonio Huitepec, Upper Western, and Southwestern Central). Texts are classified into four main domains as follows: education, law, health, and religion. To compile these data, we conducted a two-phase collection process as follows: first, an online search of government portals, religious organizations, and Mixtec language blogs; and second, an on-site retrieval of physical texts from the library of the Autonomous University of Querétaro. Scanning and optical character recognition were then performed to digitize physical materials, followed by manual correction to fix character misreadings and remove duplicates or irrelevant segments. We conducted a preliminary evaluation of the collected data to validate its usability in automatic translation systems. From Spanish to Mixtec, a fine-tuned GPT-4o-mini model yielded a BLEU score of 0.22 and a TER score of 122.86, while two fine-tuned open source models mBART-50 and M2M-100 yielded BLEU scores of 4.2 and 2.63 and TER scores of 98.99 and 104.87, respectively. All code demonstrating data usage, along with the final corpus itself, is publicly accessible via GitHub and Figshare. We anticipate that this resource will enable further research into machine translation, speech recognition, and other NLP applications while contributing to the broader goal of preserving and revitalizing the Mixtec language. Full article

This work aims to use a suitable regression model to study a count response random variable, namely, the number of citations of a research paper, that is affected by some explanatory variables. The count variable exhibits substantial variation, as the sample variance is larger than the sample mean; thus, the classical Poisson regression model seems not to be appropriate. We concentrate our attention on the negative binomial regression model, which allows the variance of each measurement to be a function of its predicted value. Nevertheless, the process of citations of papers may be divided into two parts. In the first stage, the paper has no citations, while the second part provides the intensity of the citations. A hurdle model for separating documents with citations and those without citations is considered. The dataset for empirical application consisted of 43,190 research papers in the Economics and Business field from 2014–2021, which were obtained from The Lens database. Citation counts and social attention scores for each article were gathered from the Altmetric database. The main findings indicate that both collaboration and funding have positive impacts on citation counts and reduce the likelihood of receiving zero citations. Open access (OA) via repositories (green OA) correlates with higher citation counts and a lower probability of zero citations. In contrast, OA via the publisher’s website without an explicit open license (bronze OA) is associated with higher citation counts but also with a higher probability of zero citations. In addition, open access in subscription-based journals (hybrid OA) increases citation counts, although the effect is modest. There are clear disciplinary differences, with the prestige of the journal playing a significant role in citation counts. Articles with lower expert ratings tend to be cited less frequently and are more likely to be cited zero times. Meanwhile, news and blog mentions boost citations and reduce the likelihood of receiving no citations, while policy mentions also enhance citation counts and significantly lower the risk of being cited zero times. In contrast, patent mentions have a negative impact on citations. The influence of social media varies: X/Twitter and Wikipedia mentions increase citations and reduce the likelihood of being uncited, whereas Facebook and video mentions negatively impact citation counts. Full article

Generative AI tools offer opportunities for enhancing learning and assessment, but raise concerns about equity, academic integrity, and the ability to critically engage with AI-generated content. This study explores these issues within a psychology-oriented postgraduate programme at a UK university. We co-designed and evaluated a novel AI-integrated assessment aimed at improving critical AI literacy among students and teaching staff (pre-registration: osf.io/jqpce). Students were randomly allocated to two groups: the ‘compliant’ group used AI tools to assist with writing a blog and critically reflected on the outputs, while the ‘unrestricted’ group had free rein to use AI to produce the assessment. Teaching staff, blinded to group allocation, marked the blogs using an adapted rubric. Focus groups, interviews, and workshops were conducted to assess the feasibility, acceptability, and perceived integrity of the approach. Findings suggest that, when carefully scaffolded, integrating AI into assessments can promote both technical fluency and ethical reflection. A key contribution of this study is its participatory co-design and evaluation method, which was effective and transferable, and is presented as a practical toolkit for educators. This approach supports growing calls for authentic assessment that mirrors real-world tasks, while highlighting the ongoing need to balance academic integrity with skill development. Full article

As blended learning (BL) is becoming a new normal in the context of higher education, there is a growing need to attune pedagogies to this context. As reflective blogs were found to be supportive of pre-service student teachers’ (PSTs’) as well as teacher educators’ (TEs’) professional development, the current study aimed to explore PSTs’ and TEs’ perceptions regarding the potential of integrating blogs into the BL modality. Applying a qualitative approach, analyses of 528 PSTs’ blog posts, transcriptions of two focus groups with 11 PSTs, and 3 TEs’ reflections and discussion transcripts yielded four themes that related to both the PSTs’ and the TEs’ perspectives regarding the integration of blogs into BL: (1) keeping sequential learning, (2) supporting self-directed learning, (3) keeping a sense of a learning community, and (4) increasing motivation and critical thinking. Nevertheless, both the PSTs and TEs described unique roles for blogging in BL. The TEs indicated that blogs support a sense of control, reveal misconceptions, and model teaching, while the PSTs indicated that blogs increase or decrease self-confidence during BL. The implications pertain to the contribution of blogging in BL, as well as to the four pedagogical principles of effective BL design: (a) continuity in learning, (b) fostering autonomous learning, (c) building a learning community, and (d) reflectivity and professional development. Full article

This study employed Linguistic Inquiry and Word Count (LIWC-22) software, a language analysis tool, to examine Spanish-language pro-NSSI Tumblr posts. Pro-NSSI, or “pro non suicidal self-injury”, refers to online content that normalizes or supports self-harming behaviors. Given the strong associations between NSSI and conditions such as post-traumatic stress disorder (PTSD), anxiety, and depression, understanding how these behaviors are discussed online can help improve interventions. A year’s worth of public posts were collected, focusing on captions and hashtags that included NSSI-related terms. Using Linguistic Inquiry and Word Count (LIWC) software, we analyzed linguistic and psychological markers. Log-likelihood ratio tests revealed significantly higher frequencies of words related to negative emotions, sadness, health, and death compared to standard blog norms. Mixed-language posts showed notable code-switching, suggesting a possible emotional distancing mechanism when discussing self-harm. The findings indicate that Spanish-speaking adolescents engaging in pro-NSSI communities exhibit unique linguistic and psychological characteristics, with important implications for clinical assessment and intervention. Mental health counselors and educators can use these insights to develop culturally and linguistically responsive strategies for prevention and support. Full article

In response to escalating environmental concerns and the imperative for a transition to a more sustainable economy, the European Union enacted a new regulation on the electric battery market in July 2023. This regulation integrates the principles of the circular economy, as outlined in the European Green Deal, addressing all phases of the battery life cycle, including the mining of raw materials, product design, production processes, reuse, and recycling. In light of this development, the principal manufacturers of electric vehicles (EVs) and hybrid electric vehicles (HEVs) have undertaken various circular economy (CE) and life cycle (LC) strategies. Their objective is to align their operations with these new regulatory requirements and enhance their sustainability credentials. The global automotive industry, encompassing thousands of entities with an annual turnover exceeding USD 3 trillion, is a significant economic sector. Within this industry, it is estimated that more than 50 manufacturers are involved in the production of EVs, ranging from established automakers to emerging startups. This study applies content analysis to obtain qualitative and quantitative information from data disclosed by companies and organizations, with a specific focus on entities that currently feature EVs or HEVs. The methodology involves examining publicly available reports and corporate disclosures to assess industry trends and regulatory compliance. For this purpose, the analysis selected the 10 largest EV manufacturers in the world, based on sales reports provided by the manufacturers themselves and their respective market shares, as reported by automotive news portals and blogs. The evaluation of their actions was derived from the annual sustainability reports of these companies, with the aim of identifying the practices already implemented and their anticipated contributions to extending battery life and minimizing environmental impact. Full article

Students with disabilities often face challenges in participating in classroom activities with normal students. Assistive technologies powered by Artificial Intelligence (AI) or Machine Learning (ML) can provide vital support to ensure inclusive and equitable learning environments. In this paper, we identify AI or ML-powered inclusive education tools and technologies, explore the factors required for developing personalized learning plans using AI, and propose a real-time personalized learning framework. We have identified inclusive education tools and technology driven by AI or ML as well as factors impacting the creation of AI-based personalized learning based on our exploration of Google Database, blog sites, company sites, tools, and techniques used in different centers. This study proposes a system model that includes engagement and adaptive learning components. The system uses Bloom’s taxonomy to continuously track the learner’s development. We identified a comprehensive list of AI- or ML-powered inclusive education tools and technologies and determined key factors for developing personalized learning plans, including emotional state, student progress, preferences, learning styles, and outcomes. Based on this research, AI-based inclusive education has the potential to improve educational experiences for students with disabilities by creating a more equitable and inclusive learning environment. Full article

Urban tourism resilience has become an important issue in light of the recent COVID-19 crisis, and heritage tourism represents an opportunity to recover from recent losses and develop resilient, sustainable planning for this sector. Important cities in CEE countries, such as Bucharest, are particularly affected, as in their case, the recent recovery in tourism overlaps with efforts to promote a positive image to replace identity labels associated with their communist past. In this context, online digital exposure to cultural heritage is of significant interest for resilient, sustainable tourism planning. Analyzing the most frequently online-promoted objectives through a mixed-methods approach, this study is an innovative empirical attempt to statistically uncover the online projected image of Bucharest. The main results show that despite the intended image projection, the Romanian capital’s communist heritage remains one of its most important landmarks, especially for international tourists. Other essential features that influence the frequent promotion of heritage objectives that represent the Romanian national culture include the representativeness of the monuments or institutions (e.g., museums) and their accessibility (i.e., their location in the center of Bucharest or close to local attractions). These results are important for the strategic planning of urban tourism in the region. Full article

This study, grounded in constructivist theory, presents an innovative artificial intelligence (AI) course framework for undergraduate students from the School of Artificial Intelligence at Anhui University. This research focuses on students’ perceptions and explores the impact of blogs as a platform for assignment submission in an AI course. Data are collected using structured questionnaires and analyzed quantitatively using a partial least squares structural equation model. Additionally, interviews are conducted to provide nuanced insights and contextual explanations, thus supplementing the quantitative findings. This study explores the specific impacts of blogs on students’ learning abilities, learning experiences, academic outcomes, and overall satisfaction within the AI course. By leveraging blogs as pedagogical tools, this study highlights their potential to transform traditional teaching methods and promote active learning and knowledge sharing in higher education. The proposed course framework also offers a scalable model that can be adapted for other science and engineering disciplines in colleges and universities. Full article

Background/Objectives: Appearance-related social media, such as “thinspiration” and “fitspiration” posts, have been shown to contribute to poor body image and disordered eating. Food-related social media is becoming increasingly popular; however, far less is known about its relationship to body image and disordered eating. Methods: The current review searched PsycNet and PubMed (Medline) for all the literature examining food-related social media and its relationship with body image and/or disordered eating outcomes. Results: From 796 initial hits, the search identified 16 relevant studies. The study designs and types of media examined varied widely, including mukbang videos, food blogs, and “What I Eat In A Day” videos. Findings on the relationship between food-related social media and outcome variables were quite mixed, perhaps speaking to the wide variety of media included in the review. Conclusions: The existing literature is sparce, but overall, it suggests a potential relationship between food-related social media, negative body image, and disordered eating. Additional experimental research is needed to clarify outcomes for different media types (e.g., food blogs versus mukbang videos) and to determine the direction of causality for each. Full article

Specifications grading is an alternative grading system that has been used with increasing frequency in higher education. Since first introduced by Linda Nilson in 2014, more than 90 publications on the design and implementation of specifications grading systems have been published. This work presents a systematic review of the current literature to analyze the variety of ways specifications grading systems are executed, including the diverse design and implementation considerations, as well as to present and discuss emergent themes. We analyzed 90 publications and present their relevant findings in the results. The following databases were last searched on 5 October 2024 for publications: IEEE Xplore, ACS Publications, ASEE PEER, PER, Scopus, ERIC, ACM, ScienceDirect, and Web of Science. All peer-reviewed journal articles, conference proceedings, and book chapters that implemented at least two structural features of specifications grading in an undergraduate or graduate course were included in this review. Theses, dissertations, conference abstracts, posters, workshops, blogs, opinion pieces, social media exchanges, and content provided on websites were not included. Additionally, reports of specifications grading systems in K-12 courses or those that only presented the design and/or implementation of less than two structural features of the grading system were similarly excluded. Our findings from the literature reveal that the following themes emerge from educators who use specifications grading: instructor commentary on time investment, academic performance, and student reactions to specifications grading. This review provides a resource for those interested in exploring this alternative grading system, and the emergent themes indicate that there are ripe opportunities for future study. Full article

Background: Preconception health is critical for improving maternal and child health. The main objective of the study was to explore medical students’ health habits, quality of life, and knowledge of preconception healthcare. Methods: We conducted a cross-sectional study between 15 March 2023 and 31 May 2024 among medical students at United Arab Emirates University. To determine awareness and knowledge of preconception health, we administered a survey consisting of an author’s questionnaire with 35 questions covering sociodemographic characteristics and general knowledge of preconception health, as well as the WHO Quality of Life Scale-BREF (WHOQOL-BREF). Results: The participants were predominantly under 25 years old (98.5%), Emirati (91.1%), single (92.6%), and female (95.8%); only 3.4% had been pregnant before. Regarding health awareness and behaviors, a significant number of females (58.0%) had never visited a gynecologist. The majority of students (72.4%) participated in sports activities. The overall level of knowledge was low, with a mean level of 7.5 (SD = 6.36) out of 24. The Internet (webpages, blogs, webinars) (64.5%) was the major source of knowledge regarding healthcare information, followed by social media platforms (Twitter, Facebook, TikTok, Instagram) and mobile applications (57.5%), books (48.6%), and family members (57.0%). There was a statistically significant correlation between knowledge levels and the Internet (p < 0.004) or family (p < 0.001) as a source of knowledge. Additionally, there was a statistically significant positive correlation between knowledge and quality of life across all four WHOQOL domains. Conclusions: Medical knowledge might positively affect general well-being. Fostering stronger social networks and support systems could benefit preconceptional awareness and knowledge. Full article