Search results

The study aimed to identify the best practices for open educational resources (OER) management in Nigerian open education university libraries and the implications for policymakers.

A mixed-methods approach was used, which included a survey questionnaire administered via Google Forms to academic librarians and other library staff of the National Open University of Nigeria (NOUN). The study’s population was 398 and 273 participants responded to the survey. The study included all academic librarians and other library staff representing the six geopolitical zones in Nigeria. The data were analyzed using both qualitative and quantitative methods. The study’s results were presented using frequency counts, percentages tables and the qualitative data analysis was done thematically.

The findings of the study are consistent with existing literature on best practices for managing OER, which emphasized the importance of establishing clear policies and strategies for OER management practices, such as guidelines for acquiring, creating, curating and disseminating OER.

The originality of the study concludes by recommending that policymakers should develop policies that support the implementation of best practices in OER management to improve access to educational resources and reduce costs for students.

This theoretical paper introduces a conceptual framework for Personal Cultural Heritage Management (PCHM), derived from prior research on migrants' information practices. It elaborates on the literature background and the development of the PCHM framework, highlighting the role of personal information management (PIM) and personal collections in the creation, access and utilization of cultural heritage information.

The study describes and explains the construction of the PCHM framework as a structured and self-motivated approach to personal heritage and identity learning.

Following the theoretical background and assumptions, along with the presentation of the key building blocks, the paper describes the key components of the framework, outlines their definitions and provides examples.

Theoretically, PCHM extends the current literature by encapsulating processes and actions employed by individuals to manage personal collections for cultural identity purposes, thereby underscoring the critical role personal collections play in both preserving and communicating cultural heritage.

PCHM can guide the development of support systems and policies to enhance cultural continuity and integration, thus empowering individuals to navigate their cultural identities confidently.

The PCHM framework creates a unique intersection between PIM and cultural heritage, providing a new perspective for understanding the dynamic evolution and formation of cultural identity among migrants.

This paper aims to trace how Asian American girls engaged with civic learning in a virtual out-of-school literacy community featuring a curriculum of diverse literary texts.

The researcher used practitioner inquiry to construct a virtual literacy education community dedicated to the civic learning of Asian American girls.

The paper explores how participants mobilized critical practices of textual consumption and production rooted in their intersectional identities and embodied experiences to make meaning of the civic constraints and affordances of marginalized identities and to read and (re)design author choices for civic purposes. These findings – examples of youths’ critical civic meaning-making – indicate how they claimed space for Asian American civic girlhoods in literacy education.

This paper foregrounds how Asian American girls mobilize critical processes of text consumption and production to assert civic identities in literacy education – a significantly under-examined topic in literacy studies. This work has implications for how literacy practitioners and scholars can prioritize Asian American civic girlhoods through pedagogy and research.

The primary objective of this research is to draw a comparative analysis between Turkey and Italy in terms of how festival events function as catalysts for the endorsement of regional culinary delicacies. The study endeavours to elucidate the role of these festivals in fortifying the regional gastronomic landscape of both nations.

Adopting a comprehensive comparative methodology, this study meticulously scrutinises the gastronomy festivals spanning diverse geographical locales in both Turkey and Italy. Consideration is given to the standout food and beverage items spotlighted at these events and the venues where they are hosted. The research design takes into account the extensive cultural and geographical spectrum that characterises Turkey and Italy. The primary research method comprises web content analysis techniques. This method involves analysing textual data from online sources pertaining to gastronomy festival events in both countries. Web content analysis is instrumental in evaluating how such festivals are deployed in promoting indigenous gastronomic products and exploring the intricate dynamics between brand identity and brand image.

The research outcomes underscore the pivotal role that festival events play in elevating regional gastronomic products' profile in Turkey and Italy. It highlights the top 10 festivals and the most popular local culinary items on digital platforms. Additionally, the study offers a side-by-side comparison of the most celebrated gastronomic products in Turkey versus those that receive prominence in Italy.

This study enriches academic understanding by dissecting the nuances of how festivals contribute to the promotion of local gastronomic treasures. By juxtaposing Turkey and Italy, this research provides valuable insights into the influence of festivals on regional culinary promotion across diverse cultural milieus. This study makes substantial contributions to the fields of gastronomy, tourism, and brand promotion.

Data storytelling courses position students as agents in creating stories interpreted from data about a social problem or social justice issue. The purpose of this study is to explore two research questions: What themes characterized students’ iterative development of data story topics? Looking back at six years of iterative feedback, what categories of data literacy pedagogy did instructors engage for these themes?.

This project examines six years of data storytelling final projects using thematic analysis and three years of instructor feedback. Ten themes in final projects align with patterns in feedback. Reflections on pedagogical approaches to students’ topic development suggest extending data literacy pedagogy categories – formal, personal and folk (Pangrazio and Sefton-Green, 2020).

Data storytelling can develop students’ abilities to move from being consumers to creators of data and interpretations. The specific topic of personal data exposure or risk has presented some challenges for data literacy instruction (Bowler et al., 2017). What “personal” means in terms of data should be defined more broadly. Extending the data literacy pedagogy categories of formal, personal and folk (Pangrazio and Sefton-Green, 2020) could more effectively center social justice in data literacy instruction.

Implications for practice include positioning students as producers of data interpretation, such as role-playing data analysis or decision-making scenarios.

Data storytelling has the potential to address current challenges in data literacy pedagogy and in teaching critical data literacy.

Course descriptions provide a template for future data literacy pedagogy involving data storytelling, and findings suggest implications for expanding definitions and applications of personal and folk data literacies.

The purpose of this research paper was to determine which needs for incentives influence positive word-of-mouth (PWOM) among international tourists and how these needs differ based on the cultural orientation toward individualism and collectivism.

This research used online surveys to gather data from 959 Australian, US, UK, Japanese and Korean respondents who had visited Beijing. A random sampling method was used, and data were analyzed using SmartPLS 4.0. By adopting the existence relatedness growth theory, the findings explain how cultural orientation affects the impact of needs for incentives in generating PWOM.

Three hypothesized relationships were significant for Australia/UK/USA and Japan/Korea – the effect of needs for incentives on motivation, the effect of motivation on PWOM and the effects of needs for incentives on PWOM were significant and positive for Australia/UK/USA and Japan/Korea. The effect of needs for incentive type on motivation varied across national populations, and the intensity of the effects of needs for incentive type on PWOM was also different. For Australian, UK and the US tourists, the honorary title was the most influential need to stimulate word-of-mouth motivation. The need for cultural learning was the most influential for Japanese and Korean tourists.

This research contributes to the literature by exploring and comparing the needs for incentives that influence PWOM among tourists from the perspective of individualism and collectivism. The results also increase the understanding of the relationships among needs for incentives, motivation and PWOM.

本研究旨在确定哪些激励需求会影响国际旅游者的积极口碑（PWOM）, 以及这些激励方式的影响在个人主义和集体主义文化取向的群体中有何不同。

本研究通过在线调查收集了 959 名曾到访北京的澳大利亚、美国、英国、日本和韩国的国际游客数据。研究采用了随机抽样的方法, 使用 SmartPLS 4.0 对数据进行了分析。基于ERG理论, 本研究解释了文化如何影响激励类型对积极口碑的影响。

研究结果显示, 三个假设关系在澳大利亚/英国/美国和日本/韩国两个群组中均显著, 即激励需求对动机的影响、动机对积极口碑的影响、以及激励需求对积极口碑的影响在澳大利亚/英国/美国和日本/韩国群组中都是显著和正向的。激励需求类型对动机和积极口碑的影响在不同国家群体中存在差异。对于澳大利亚、英国和美国的国际游客, 满足名誉需求的激励对产生积极口碑动机的影响更大。对于日本和韩国的国际游客, 满足文化学习需求的激励对产生积极口碑动机的影响更大。

本研究从个人主义和集体主义的角度, 探讨比较了影响国际旅游者积极口碑的激励需求, 为相关领域研究做出了贡献。研究结果加深了对激励需求、动机和积极口碑之间关系的理解。

El objetivo de esta investigación era determinar qué necesidades de incentivación influyen en el boca a boca positivo (PWOM por sus siglas en inglés) entre los turistas internacionales y cómo difieren estas necesidades en función de la orientación cultural hacia el individualismo y el colectivismo.

Esta investigación utilizó encuestas en línea para recopilar datos de 959 encuestados australianos, estadounidenses, británicos, japoneses y coreanos que habían visitado Pekín. Se empleó un método de muestreo aleatorio y los datos se analizaron con SmartPLS 4.0. Adoptando la teoría del Crecimiento de la Relación con la Existencia (ERG por sus siglas en inglés), los resultados explican cómo afecta la orientación cultural al impacto de las necesidades de incentivos en la generación del PWOM.

Tres relaciones hipotetizadas resultaron significativas en los dos grupos de Australia/Reino Unido/Estados Unidos y Japón/Corea: el efecto de las necesidades de incentivación en la motivación, el efecto de la motivación en la PWOM y los efectos de las necesidades de incentivación en la PWOM fueron significativos y positivos para Australia/Reino Unido/Estados Unidos y Japón/Corea. El efecto del tipo de necesidad de incentivación sobre la motivación varió entre las poblaciones nacionales, y la intensidad de los efectos del tipo de necesidad de incentivos sobre la PWOM también fue diferente. Para los turistas australianos, británicos y estadounidenses, el título honorífico fue la necesidad más influyente para estimular la motivación WOM. La necesidad de aprendizaje cultural fue la más influyente para los turistas japoneses y coreanos.

Esta investigación contribuye a la bibliografía al explorar y comparar las necesidades de incentivación que influyen en la motivación boca a boca entre los turistas desde la perspectiva del individualismo y el colectivismo. Los resultados también aumentan la comprensión de las relaciones entre las necesidades de incentivación, la motivación y el PWOM.

Artificial intelligence is one of the most significant and active fields of study in the last few years. Artificial intelligence-derived robotic technologies known as chatbots are gaining interest from both academic and industry sectors. By analyzing the development and patterns of research on the chatbot phenomena within the tourism field, this study seeks to develop a theoretical framework for the interaction between chatbots and tourism.

The Web of Science (WoS) database’s 33 articles on chatbots related to travel and hospitality were examined between 2019 and 2024 using VOSviewer software for bibliometric and thematic content analysis.

Research on chatbots for tourism and hospitality appears to be in its early stages. The factors influencing tourists' intentions to use chatbots have been thoroughly researched; the attitudes, perceptions and behavioral intentions of destinations, travel agencies and restaurant patrons regarding chatbots were examined, and it was found that the quantitative research approach was dominant. In addition, the majority of the studies are based on a particular theory or model.

This is one of the first attempts to directly comprehend and depict the interconnected structures of studies on the interaction between chatbots and tourism through the use of network analysis. Furthermore, the study’s findings can offer academics a comprehensive viewpoint and a reference manual for more accurate assessment and oversight of the chatbot-tourism interaction. Regarding the lack of research on the topic and the fragmented structure of the studies that exist, it is imperative to provide both a comprehensive overview and a roadmap for future investigations into the usage of chatbots in the travel and hospitality sector.

The purpose of this study is to examine approaches used by university libraries to enhance the visibility and utilization of research support services (RSSs) among doctoral students and to assess the competencies of library staff in delivering research support services.

This study used qualitative design approach, purposively sampled 40 librarians (8 university librarians and 32 librarians) in charge of RSSs and use of structured interview.

The findings of this study revealed three major themes: offline and online strategies, the need for upskilling and professional development programs and proactive empowerment.

This study focused on research support services in chartered public universities in Kenya; private universities were not included.

The need to enhance library staff's ongoing professional development programs, increasing funding to university libraries and proactivity by the libraries to improve the provision and promotion of RSSs to doctoral students in Kenya.

There are limited existing literature in the Kenyan context. This study will fill a knowledge gap and contribute to the literature on academic libraries support and doctoral students experience in Kenyan context.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

Many studies have investigated dynamic positions and their importance, but there is less attention paid to how to enter more central positions. Interorganizational relationships are an important factor in network structural change. In Chinese society, firms allocate significant human, financial and material resources towards cultivating guanxi. The purpose of this study is to explore whether and how the three aspects of guanxi, namely renqing, ganqing and xinyong, can make firms more central, and to examine the mediating role of interaction.

The study used a mixed method to collect data from 256 Chinese Cops (complex product systems) firms. And, hypotheses were tested using SPSS 25.0 and AMOS 26.0.

The results indicate that renqing, ganqing and xinyong have significant positive effects on the increase in centrality, but with varying magnitudes. Additionally, the interaction was found to mediate the relationship between the three aspects of guanxi (renqing, ganqing and xinyong) and the increase in centrality.

The study provides new insights to help firms become more central by combining guanxi (renqing, ganqing and xinyong) with change in centrality, enriching the literature on network dynamics and guanxi-related research. Moreover, the study provides managers with a clear understanding of how to use guanxi to make the firm more central in situations with limited resources.