Relevant Concepts Research Articles

Development of Digital Literacy Evaluation Model for Tourism Management of Undergraduate Students

Background and Aims: The digital economy, digital transformation of tourism enterprises, and new forms of employment have created new demands for the study and future career development of tourism management among undergraduate students. The digital literacy level of these students directly impacts their future employment opportunities, skill development, and even the pace of digital development in tourism professional education. The objectives of this research are 1) to extract the components of digital literacy in the tourism management of undergraduate students and 2) to develop a digital literacy evaluation model for the tourism management of undergraduate students. Methodology: The research reviews relevant theoretical concepts, including digital literacy and information literacy. The processes in this research are as follows: 1) reviewing the theoretical basis of the study 2) defining related concepts such as digital literacy, information literacy, etc. Reviewed research on the digital literacy for tourism management of undergraduate students, providing a theoretical and practical foundation for this paper's research. 2) To take 1,308 tourism management undergraduate students in China as the survey subjects, the current status of their digital literacy was investigated. To analyze the survey results and extract the components of digital literacy among tourism management undergraduate students. 3) We selected 21 experts, used the Delphi method to determine the components of the digital literacy evaluation model, and then used the network analysis method to determine the weight of each component. Finally, we designed a digital literacy evaluation model that is suitable for undergraduate students studying tourism management. Results: The study's results indicate that the model clearly demonstrates the relationships and relative importance of the components of tourism management for undergraduate students. Teachers can effectively use this model to assess students' digital literacy levels and provide them with personalized support and guidance. Students can use this model to improve their digital literacy levels and adapt to the digital age's development sequentially and purposefully. Conclusion: The model clearly shows how tourist management instructional features are weighted. Teachers can measure students' digital literacy with this strategy. Students' digital tourist management skills are improving as teachers customize aid and advise. This method could streamline and personalize education to better prepare students for tourism.

Understanding student engagement in vaccination education: an interview-based multi-stakeholder study

The COVID-19 pandemic has underscored the importance of informed decision-making, especially concerning vaccination for disease prevention. This highlights the need for scientific literacy, trust, and understanding of relevant concepts such as pathogens, immune responses, and transmission pathways. Additionally, societal and ethical considerations are integral for a comprehensive approach. While collaborating with medical professionals and fostering argumentation and decision-making skills hold promise for enhancing engagement with these topics in educational settings, understanding students’ perspectives is essential for maintaining their motivation to learn and their interest in such complex subjects. Therefore, a qualitative study involving interviews with secondary school students, experienced educators, and vaccination experts familiar with school environments was conducted to identify factors fostering student engagement and interest in immunobiology and vaccines. The findings highlight focal areas of student interest in the topic and the value of involving students in lesson planning. They also underscore the importance of real-world relevance and the need for clear, student-centered communication with medical professionals. Recommendations for educators include integrating interactive learning activities, real-world examples, and case studies.

A systematic review and mapping exercise to assess the content validity of patient-reported outcome measures for adults having reconstructive surgery of the lower limb.

Lower limb reconstruction (LLR) has a profound impact on patients, affecting multiple areas of their lives. Many patient-reported outcome measures (PROMs) are employed to assess these impacts; however, there are concerns that they do not adequately capture all outcomes important to patients, and may lack content validity in this context. This review explored whether PROMs used with adults requiring, undergoing, or after undergoing LLR exhibited content validity and adequately captured outcomes considered relevant and important to patients. A total of 37 PROMs were identified. Systematic searches were performed to retrieve content validity studies in the adult LLR population, and hand-searches used to find PROM development studies. Content validity assessments for each measure were performed following Consensus-based Standards for the selection of health measurement Instruments (COSMIN) guidelines. A mapping exercise compared all PROMs to a conceptual framework previously developed by the study team ('the PROLLIT framework') to explore whether each PROM covered important and relevant concepts. The systematic searches found 13 studies, while hand searches found 50 PROM development studies, and copies of all 37 measures. Although several studies discussed content validity, none were found which formally assessed this measurement property in the adult LLR population. Development of many PROMs was rated as inadequate, no PROM had sufficient content validity in the study population, and none covered all areas of the PROLLIT framework. The LIMB-Q was the most promising and comprehensive measure assessed, although further validation in a wider sample of LLR patients was recommended. Current PROMs used in adults requiring, undergoing, or after undergoing LLR lack content validity and do not assess all important and relevant outcomes. There is an urgent need for improved outcome measurement in this population. This can be achieved through development of a new PROM, or through validation of existing measures in representative samples.

IMPORTANCE OF INDUSTRIAL SYMBIOSIS STRATEGIES ON ENERGY EFFICIENCY IMPROVEMENT IN ORGANIZED INDUSTRIAL ZONES: KONYA OIZ CASE

Industrial symbiosis (IS) refers to the integration and optimization of numerous industrial systems and processes and is inspired by the nature. By allowing the exchange of materials, energy, other resources, byproducts or valuable waste among companies, the goal is to increase resource efficiency and decrease potential waste. In this study, the IS relevant concepts and examples from the literature are briefly discussed, and a survey is conducted in Konya organized industrial zone. The primary obstacle faced during the survey study is the companies' reluctance to communicate and share information. The survey explores the current level of knowledge, existing energy efficiency efforts, and organizations' willingness to address the topic if grants and subsidies are available. Following the survey, exchange opportunities from the literature are compiled, considering the sectoral structure of the selected zone. Sectoral pairings are formed to encourage businesses and to demonstrate applicability and symbiosis opportunities. Hence, outcomes show how industrial symbiosis has an impact on energy and resource efficiency and waste reduction within selected industrial zone. In addition, its connection and relationship with government incentives, investments and energy efficiency networks are also discussed. As a result, it has been found that there is significant symbiosis potential in a growing and developing region like the Konya industrial zone, through sectoral matching of companies. By increasing awareness among companies, providing financial and legal support, and assisting them in setting targets, inter-company symbiosis efforts can be facilitated and expanded.

Unpacking pre-service teachers’ conceptualization of logarithmic differentiation through the APOS theory

Logarithmic differentiation is an effective method that aids the process of finding the derivatives of complex exponential functions. However, there has been a scarcity of studies, particularly in the South African context, that have provided evidence on pre-service mathematics teachers’ understanding of the concept of logarithmic differentiation. This study explored pre-service teachers’ conceptualization of logarithmic differentiation through action-process-object-schema (APOS) theory. We employed a qualitative case study design involving 90 first-year pre-service teachers enrolled in a mathematics teacher education program at a university in South Africa’s Eastern Cape Province. Overall, the analysis showed that 63.9% of the participants demonstrated a substantial understanding of logarithmic differentiation processes, including 46.1% who had reached the schema stage. Nonetheless, common misconceptions and errors persisted, particularly among those who operated at action and beginning process stages. Errors and misconceptions such as the misapplication of differentiation rules, calculation errors in combining derivatives, and conceptual misunderstanding were evident. These findings highlight the need for mathematics teacher preparation programs to emphasize both conceptual and procedural understanding of differentiation. Achieving this goal may involve targeted instruction on relevant foundational concepts, continuous professional development, and integration of active learning strategies, such as the activities, classroom discussions, and exercises (ACE) teaching cycles to address common misconceptions.

Research on the Application of Artificial Intelligence in Museum Exhibition Design

With the rapid development of information technology, artificial intelligence has developed rapidly, and is gradually widely used in all walks of life, which has a profound impact on social development. In the field of museum exhibition design, artificial intelligence also plays a role that cannot be ignored. Relevant designers should pay attention to the role of high-tech in the information age in promoting the development of the museum industry, innovatively introduce artificial intelligence technology, and promote the development of the museum to follow the pace of the time and better cater to the needs of the audience. In this context, this paper will first briefly expound the relevant concepts of artificial intelligence and museum exhibition design, then briefly discuss the application principles of artificial intelligence in museum application in museum exhibition design, and finally explore the relevant application paths, aiming to give full play to the application value of artificial intelligence in museum exhibition design, innovative design direction, and create diversified design forms. To provide visitors with a more novel tour experience, improve the recognition of the museum at the social level, and strengthen its role in cultural construction through scientific and technological means.

Electret Production and Applications with Special Regard to Health Physics Dosimetry: A Review.

An electret detector is a piece of dielectric material film charged or polarized by a specific charging method to induce a quasi-permanent electric field. Electret films perform unique characteristics for production and applications in many areas of science and technology, especially in health physics dosimetry. A charged electret detector, when placed in an ionized environment, collects negative or positive ions depending on its original charging state, which reduces its original charge. The number of charges reduced in the ionized field is usually proportional to the absorbed radiation dose. In this paper, the state-of-the-art information on the type of electrets, production methods, some applications in particular in health physics dosimetry, and relevant concepts are reviewed.

The Atopic Dermatitis Control Tool: Adaptation and Content Validation for Children and Caregivers of Children with Atopic Dermatitis.

The Atopic Dermatitis Control Tool (ADCT) assesses six concepts regarding patient-perceived control of atopic dermatitis (AD) in adults and adolescents with AD. This study aimed to develop two modified ADCT versions, one for children with AD aged 8-11years and another for caregivers of children with AD aged 6months to 11years. Following the US Food and Drug Administration patient-reported outcomes guidance, the ADCT was modified to produce draft Child and Caregiver ADCT versions, maintaining the original six concepts. The instruments were refined and finalized through an iterative process using input from children with AD and caregivers of children with AD via qualitative interviews. Inclusion criteria were clinician diagnosis of AD, prescription treatment use in the past 3months, and itching/scratching or rash in the past month. Interviews consisted of concept elicitation to identify perceptions of AD control and cognitive debriefing to test and refine the ADCT items. In total, 19 children (mean age 9.2years, 74% male) and 17 caregivers (mean age 36.3years, 100% female) were interviewed. During concept elicitation, children and caregivers reported similar symptoms and described the cycling and unpredictability of AD. Most participants reported that daily activities were impacted negatively by AD symptoms. The concept of AD control resonated with children and caregivers, and respondents were able to describe their experiences related to AD symptom severity. Children were unfamiliar with the term AD, so the Child ADCT version was named the Child Eczema Control Tool (ECT). Children and caregivers both reported that the instruments assessed relevant concepts, comprehensively measured AD control, and demonstrated content and face validity. The Child ECT and Caregiver ADCT were developed and qualitatively validated for assessing AD control in patients aged 6months to 11years and may offer simple ways to assess disease control and optimize treatment decisions. Video Abstract.

I-SIRch: AI-powered concept annotation tool for equitable extraction and analysis of safety insights from maternity investigations

BackgroundMaternity care is a complex system involving treatments and interactions between patients, healthcare providers, and the care environment. To enhance patient safety and outcomes, it is crucial to understand the human factors (e.g. individuals' decisions, local facilities) influencing healthcare. However, most current tools for analysing healthcare data focus only on biomedical concepts (e.g. health conditions, procedures and tests), overlooking the importance of human factors. MethodsWe developed a new approach called I-SIRch, using artificial intelligence to automatically identify and label human factors concepts in maternity investigation reports describing adverse maternity incidents produced by England's Healthcare Safety Investigation Branch (HSIB). These incident investigation reports aim to identify opportunities for learning and improving maternal safety across the entire healthcare system. Unlike existing clinical annotation tools that extract solely biomedical insights, I-SIRch is uniquely designed to capture the socio-technical dimensions of patient safety incidents. This innovation enables a more comprehensive analysis of the complex systemic issues underlying adverse events in maternity care, providing insights that were previously difficult to obtain at scale. Importantly, I-SIRch employs a hybrid approach, incorporating human expertise to validate and refine the AI-generated annotations, ensuring the highest quality of analysis. FindingsI-SIRch was trained using real data and tested on both real and synthetic data to evaluate its performance in identifying human factors concepts. When applied to real reports, the model achieved a high level of accuracy, correctly identifying relevant concepts in 90% of the sentences from 97 reports (Balanced Accuracy of 90% ± 18% (Recall 93% ± 18%, Precision 87% ± 34%, F-score 96% ± 10%). Applying I-SIRch to analyse these reports revealed that certain human factors disproportionately affected mothers from different ethnic groups. In particular, gaps in risk assessment were more prevalent for minority mothers, whilst communication issues were common across all groups but potentially more for minorities. InterpretationOur work demonstrates the potential of using automated tools to identify human factors concepts in maternity incident investigation reports, rather than focusing solely on biomedical concepts. This approach opens up new possibilities for understanding the complex interplay between social, technical and organisational factors influencing maternal safety and population health outcomes. By taking a more comprehensive view of maternal healthcare delivery, we can develop targeted interventions to address disparities and improve maternal outcomes. Targeted interventions to address these disparities could include culturally sensitive risk assessment protocols, enhanced language support, and specialised training for healthcare providers on recognising and mitigating biases. These findings highlight the need for tailored approaches to improve equitable care delivery and outcomes in maternity services. The I-SIRch framework thus represents a significant advancement in our ability to extract actionable intelligence from healthcare incident reports, moving beyond traditional clinical factors to encompass the broader systemic issues that impact patient safety.

Love your wet grass! Dry season grazing reserves show highest grass regrowth in communal semi-arid rangelands of Tanzania.

Land management by seasonal migratory herding, traditionally implemented by pastoralists, has allowed semi-arid rangeland ecosystems to remain productive and resilient to highly erratic, seasonal rainfall patterns. Changing pastoralist practices and rainfall patterns due to climate change have the potential to negatively influence the resilience of rangelands. To test the impact of different communal rangeland practices and increasing frequency of disturbance on the rangelands' vegetation, we established a clipping experiment in three rangeland management types: rainy season rangeland, dry season rangeland and seasonal exclosures, in the Maasai Steppe, northern Tanzania. Across these rangeland management types, we tested two clipping frequencies monthly vs. once per growing period and either fenced or open to grazing (herbivory) over two consecutive growing periods. We found that rainy season rangeland exhibited lowest regrowth rates and highest proportion of bare ground across herbivory, clipping frequency and growing period. When rainfall was low, seasonal exclosures showed lowest proportion of bare ground across herbivory and clipping frequency and plots that were seasonally clipped and excluded herbivores generated significantly more grass biomass, higher grass regrowth rates and lowest proportion of bare ground compared to all other treatments. Excluding herbivores had little impact on the vegetation biomass and cover but had a positive impact on grass regrowth rates when rainfall was high. Seasonal clipping allowed for lower proportion of bare ground, and in most cases higher regrowth rates and higher biomass compared to monthly clipping. We conclude that traditional seasonal migratory herding is a relevant concept to sustain rangeland productivity and resilience under increasing intensity of disturbance if grazing pressure on rainy season rangelands is adapted to rainfall conditions and sufficient resting time after heavy defoliation is granted. Dry season grazing (including rainy season resting) proved to be the most sustainable concept to maintain regrowth and control erosion.

Promoting integrated STEM education among students via fabrication of interactive exhibit

Few studies in the education literature have focused on integrated STEM in a comprehensive manner and, even among these, there does not seem to be a significant emphasis on all the four disciplines. In addition, there are hardly any studies that focus on transitioning across prototype variants to demonstrate students’ understanding of what they must grapple with, including STEM concepts while coming up with a product. This qualitative study explored how a group of high school students harnessed the constituent disciplines of STEM to fabricate an interactive exhibit on laminar flow in an iterative manner. It was found that in the process of prototyping a working model of the exhibit, the students were able to demonstrate a working understanding of 37 relevant concepts in the four STEM disciplines, with science (14) and engineering (10) predominating, followed by technology (8) and mathematics (5). The students were able to incorporate four levels of interactivity in the exhibit, and this allowed visitors to explore the factors affecting laminar flow in the exhibit during a public exhibition in the school. Examination of the STEM dispositions of the students indicated a positive influence as a result of the activity. To the best of our knowledge, this study has incorporated the highest number of STEM concepts. We argue for the need for more studies that integrate all the four constituent disciplines of STEM in promoting integrated STEM education.

Improving Mental Health Literacy Among Law Enforcement: A Pilot Study on Mental Health First Aid for Public Safety

Mental Health First Aid (MHFA) is an 8-h curriculum conducted in various communities to improve mental health literacy. Given the high rates of suicide among law enforcement professionals and the frequency of interactions between police and corrections officers with the severely mentally ill, mental health literacy is a relevant concept for the law enforcement field. This study examined the effectiveness of MHFA in improving mental health literacy in a small sample (n = 56) of law enforcement employees. A preexperimental one-group posttest-only design using nonprobability convenience sampling was used to analyze secondary data from courses taught by the author. The sample was comprised of law enforcement officers in various law enforcement agencies, including community police departments and corrections employees. Based on the posttest, the course improves participants’ confidence in recognizing signs of mental illness, asking about suicide, being aware of personal views, and assisting people in obtaining support.

Formiranje novih pravaca historiografije: Aktuelna konceptualizacija modernosti

The article deals with the modern problems of archival science, historiography, source studies in the post-Soviet space of science of the Russian Federation, summarizes the results of the science of the past century, determines the prospects of future relevant concept ology of modernity. The author examines the state of archival affairs in the Republic of Kalmykia on the problems of regional history, shows the main characteristics of modern historical science in the region, legitimate interests in the development of archeography. For the first time in the history of the state, a systemic failure of archival science as a form of manifestation of record keeping, the need to rebuild the archival system is shown, the urgency of the problem of the unified state archival fund (EGAF) is indicated: its formation, formation, preservation, responsibility for its preservation. One of the features of archival funds is their classification, the modern correct structure of preservation and their origin allows us to determine the place and their role in the history of the archival service, to show their genres and fields of knowledge. The author emphasizes the importance and world practice of modern archival science in the field of cognitive space, opens up the possibility of analyzing new facts in the history of Russian statehood, concluding that the actualization translation concluding that the actualization of modern conceptology makes it possible to form new directions in the science of historical knowledge of the past. With the historical development, the problems of knowledge aimed at its humanization are increasingly being considered.

O TRABALHO INFORMAL, A ECONOMIA INFORMAL E OS DEFASIOS ASSOCIADOS À PRECARIZAÇÃO DO TRABALHO

The lack of effective public policies to address the precariousness of informal work has profound consequences, including increased social inequality, economic vulnerability, and the violation of labor rights. This issue is relevant not only from an economic point of view, but also from a legal and social point of view, as it involves the protection of fundamental human rights, such as the right to decent work and social protection. By critically analyzing existing legislation, identifying gaps, and proposing new legislative approaches, the survey can offer valuable insights for the formulation of more effective public policies and for strengthening the legal framework for the protection of informal workers. Additionally, by considering the nuances and complexities of the legal issues involved, research can help develop more sophisticated and relevant legal theories and concepts to address emerging labor market challenges. Although there is a vast academic literature on informal work and the precariousness of work, there is a significant lack of studies that address these issues from an in-depth legal perspective. The proposed research will fill this gap by providing a detailed analysis of the legal issues related to informal work and identifying concrete legal strategies to address the challenges of job insecurity. In this way, it will contribute to the advancement of legal knowledge in this area and to the development of more effective approaches to address the challenges of informal work and precariousness.

Interpretation of the CDISC therapeutic area user guide for traditional Chinese medicine- acupuncture

Improving research data quality is a crucial aspect of high-quality clinical research of acupuncture and moxibustion. The Clinical Data Interchange Standards Consortium (CDISC) has developed a series of standards to support the collection, tabulation, and analysis of clinical research data. To enhance the efficiency and quality of clinical research in acupuncture, as well as to facilitate the integration, sharing, and secondary analysis of data from multiple similar studies, CDISC has developed and released the CDISC therapeutic area user guide for traditional Chinese medicine acupuncture (TAUG-TCM-Acupuncture). This paper introduced the TAUG-TCM-Acupuncture, including relevant concepts, main content, and its application in clinical research of acupuncture, with illustrative examples.

Exploration and Practice of Digital Technology and Virtual Reality Technology in the Creation of Public Art with Chinese Characters: Take Qingshan Hongfang as an Example

Abstract: In the modern context of rapid development of artificial intelligence, it provides a new direction for the development of public art in the new situation. The digital reconstruction of modern and contemporary public art has provided new experiences in terms of interaction and emotion. The popularization of interactive devices and virtual reality technologies has made the forms of public art more diverse and the audience's experience more personalized. As the carrier of Chinese civilization, Chinese characters have their special cultural significance and resonance. Translating Chinese characters through public art is a good form of expression. Currently, there is a lack of public art works with cultural identity in urban public spaces in China. This article will use a combination of quantitative and qualitative methods to analyze the public art and Chinese character design cases of the Red Steel City Red House architectural complex in Qingshan District by sorting out relevant concepts and combining case study methods. Ultimately exploring the combination of digital technology and virtual reality, incorporating Chinese characters as a creative element in contemporary art and design. Intended to provide reference and inspiration for art creators and related practitioners.

Causal Inference in Natural Language Processing: Application Status and Future Outlook

Abstract. Causal reasoning has received much attention in recent years. Unlike statistical learning that focuses on the correlation between variables, causal inference can analyze the causality between variables and avoid false causal relationships caused by confounding factors. The use of causal inference to help solve Natural Language Processing (NLP) problems has made great progress. Most existing studies have focused on exploring the application of causal relationships in downstream tasks of NLP, achieving good results. This article conducted a comprehensive survey, focusing on investigating the advantages of causal inference methods in solving specific NLP problems and applications, as well as their practical advantages compared to deep learning methods. Intended to provide researchers in the NLP field with more detailed perspectives and recommendations. Specifically, this article first introduces the relevant concepts of causal inference, including causal inference and related concepts of causal relationships, as well as the differences between causal inference and statistical machine learning; Then, existing research on the use of causal relationships in downstream applications was summarized, including bias removal, stock price prediction, document dialogue based, and continuous few shot learning. Finally, a summary was made on the development of future causal relationships.

Luokanopettajaopiskelijat kielellisiä havaintojaan selittämässä

In light of previous research, it is important to examine class teachers’ perceptions of language so that we can develop pedagogical practices to evoke pupils’ interest and enthusiasm towards the language. In this article, we study what student teachers perceive about language and how they conceptualise their perceptions. We examined 264 student teachers’ interpretations of two sentences with different ambiguities and a nonsense sentence. The data were analysed using both theory- and data-driven qualitative content analysis. The results showed that many students already had a high level of metalinguistic competence: they perceived the ambiguity of the sentences, approached the nonsense sentence with relevant concepts and were able to explicate their linguistic deduction. However, some of the students had challenges, for example in using metalanguage, or they perceived the sentences mainly from a normative perspective. The results can be utilized in developing teaching practices in teacher education and in enhancing the language awareness of student teachers.

The Evolution of EFL and ELL (2000-2024): Impact of Culture, Technology, and Innovative Pedagogies on Language Learning

For nearly a century, English language has consistently remained a global phenomenon with a continued business relevance; the mandatory inclusion of English Language Learning (ELL) in Asian, African and other non-native English-speaking countries is proof of the same. Consequently, research about English as a Foreign Language (EFL) has continued too. Despite ample empirical studies in the past that have examined the role of culture, linguistics, technology or digital tools in EFL, there are limited studied that holistically investigate and review the learning and successful implementation of EFL and its influencing factors. The current study is an attempt to systematically synthesize the findings from empirical studies undertaken between early 2000 and 2024 in the domains of EFL and ELL for a sample of 53 journal articles. The research also aims to draw a scientific relationship between the most relevant concepts surrounding ELL and EFL. To achieve this, the study conducted a systematic literature review coupled with Bibliometric mapping analysis. The study concluded that the upward surge of technological advancements and World Wide Web has transformed learning EFL. Cultural diversity, and technological or digital tools are key influencing factors and innovative teaching/learning pedagogies in EFL and ELL that can enhance the success rates in EFL and ELL in non-native English-speaking countries.

Application of Academic Analytical Models in Education Management

Objective: The primary objective of the current study is to provide an analytical systematic review on the application of academic analytical models in educational management and how the related techniques can be used to enhance quality outcomes and learning processes. Methodology: The study adopted the methodological framework outlined by the Joanna Briggs Institute (2015) and was informed by Arksey and O’Malley’s (2005) approach of summary and dissemination of research findings and, in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Findings: Learning analytics has emerged as the most relevant educational concept with the potential of collecting, analyzing and reporting data on learners, educators and administrators for efficient educational management processes. Analytics in education enhances the capabilities of the educators of determining the learners’ performances and identification of areas for improvement to make data-driven learning decisions. Conclusions: The application of analytical models in educational management is based on different domains such as customized learning, intelligent tutoring systems, predictive modelling, automated grading and assessments, and natural language processing. Received: 26 July 2024 / Accepted: 25 October 2024 / Published: 05 November 2024