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This study aims to examine the relationship between tool adoption and information literacy within smallholder farmers (SHFs).

A structured questionnaire was used to gather data for this quantitative study from 225 SHFs. Structural equation modelling was done to test the hypotheses.

The findings established that tool adoption dimensions (Information and communication technologies (ICT) acceptance, language use and information culture) positively and significantly influenced information literacy. Information culture had the strongest impact.

The study enriches the situated learning theory (SLT) literature by introducing tool adoption as a predictor of information literacy in a new context of SHFs. Use of tools as independent variables is a positive deviation from previous studies that have used them as mediating variables. Despite the contributions, the cross-sectional design study undermines the ability to solicit more detailed perspectives from the lived in experience of the respondents.

Managers should promote usage of context-specific tools like local radio stations and mobile phones, but also use language tailored to farmer contexts when disseminating information. Policymakers should leverage on social and cultural settings when designing information interventions.

The study highlights critical factors that significantly promote information use for improved productivity for SHFs, cumulatively increasing the country’s gross domestic product (GDP). Socially, findings may reduce on their poverty levels of farmers.

This study offers a novel perspective in information literacy domain by using the SLT to delineate contextual tools that are paramount in predicting of information literacy in an under research informal context of SHFs.

By examining types of literacies taught by public libraries and the modes through which these programs were offered, this study aims to explore how public libraries might integrate data literacy training for the general public into existing library educational programs.

This study examined programs offered in 30 US public libraries during 2019 and 2020 to better understand types of literacy education announced to the public through library website listings and Facebook Events pages.

While public libraries offered educational programs in literacy areas ranging from basic reading and writing to technology, vocational skills, health literacy and more, data literacy training was not widely offered. However, this study identified many already-existing programs highly compatible for integrating with data literacy training.

This study offered new insights into both the literacies taught in public library programs as well as ways for public libraries to integrate data literacy training into existing educational programming, in order to better provide data literacy education for the general public.

This analysis of chat reference transcripts assesses differences in how librarians and graduate assistants (GAs) incorporate teaching strategies in responding to chat reference inquiries in social sciences, health sciences, humanities, STEM and business/economics at a large, public R1 university in the United States.

Researchers with disciplinary assignments in five different subject domains conducted qualitative analysis of a purposive sample of 982 transcripts of chat interactions during four semesters in 2021 and 2022.

Some form of information literacy instruction (ILI) occurred in 58% of the transcripts, with slightly less teaching occurring in social sciences inquiries than in other subject areas. Of transcripts that included teaching strategies, search procedures predominated, followed by a mix of concepts and procedures, and the least with concepts only. Chat providers taught concepts specific to social sciences, health sciences and humanities, but not to STEM or business.

The study compares transcripts at one institution; findings may be most applicable to large, research institutions that seek to incorporate ILI in online reference services.

Chat reference training should include best practices for ILI relevant to specific subject domains for providers without background in those disciplines and recommendations for referrals to subject specialists.

Existing ILI literature does not address the question of how chat providers teach concepts rooted in a specific subject domain or offer a comparison of teaching strategies employed in different disciplines, by librarians versus GAs or staff.

Artificial intelligence (AI) is constantly evolving and is poised to significantly transform the world, affecting nearly every sector and aspect of society. As AI continues to evolve, it is expected to create a more dynamic, efficient and personalized education system, supporting lifelong learning and adapting to the needs and pace of each student. In this research, we focus on testing the model of AI acceptance in higher education (HE) through human interaction-based factors including attitudes, competencies and openness to experience. Perceived benefits were our expectation to enhance AI acceptance in HE.

To test the model, we collected data from Arab HE institutions by spreading an online questionnaire. The sample consisted of 1,152 of teaching staff and students in Arab region, which were selected randomly. Partial least squares structural equation modeling (PLS-SEM) was employed to determine the interrelated dependence of relationships among variables. Furthermore, processing analysis was conducted to ensure the reliability and validity of questionnaires, multicollinearity and factor loading, in which the items were tested one more time to ensure their validity after translation into Arab language.

Results reveal that adopted attitude, digital competency and openness to experience have positive and significant relationship with both perceived benefits and AI acceptance in HE in the Arab region. The results also demonstrate the indirect impact of digital factors on AI acceptance in existence of perceived benefits, which was important in the validation of the model.

The research contributes to AI acceptance theory and research by providing evidence of AI acceptance in the Arab region. As generative AI applications continue to expand and change, the way we accept and interact with them will be different. This model could be adopted by authorities to facilitate the acceptance of AI in Arab HE institutions.

The purpose of this paper is to propose a taxonomy of artificial intelligence (AI) literacy to support AI literacy education and research.

This study makes use of the facet analysis technique and draws upon various sources of data and information to develop a taxonomy of AI literacy. The research consists of the following key steps: a comprehensive review of the literature published on AI literacy research, an examination of well-known AI classification schemes and taxonomies, a review of prior research on data/information/digital literacy research and a qualitative and quantitative analysis of 1,031 metadata records on AI literacy publications. The KH Coder 3 software application was used to analyse metadata records from the Scopus multidisciplinary database.

A new taxonomy of AI literacy is proposed with 13 high-level facets and a list of specific subjects for each facet.

The proposed taxonomy may serve as a conceptual AI literacy framework to support the critical understanding, use, application and examination of AI-enhanced tools and technologies in various educational and organizational contexts.

The proposed taxonomy provides a knowledge organization and knowledge mapping structure to support curriculum development and the organization of digital information.

The proposed taxonomy provides a cross-disciplinary perspective of AI literacy. It can be used, adapted, modified or enhanced to accommodate education and learning opportunities and curricula in different domains, disciplines and subject areas.

The proposed AI literacy taxonomy offers a new and original conceptual framework that builds on a variety of different sources of data and integrates literature from various disciplines, including computing, information science, education and literacy research.

This study aims to examine how digital literacy competency can mitigate misinformation in social media among young adults. In recent years, concerns over misinformation have triggered a renewed interest in the aspect of digital literacy. Many young adults in Malaysia are not able to differentiate between real news and fake news. Although there are plenty of studies examining fake news, studies examining the mitigation of misinformation through the lens of digital literacy are still rudimentary.

This research adopted a quantitative approach by conducting a cross-sectional survey among university students in Malaysia to examine how their digital literacy competency influences misinformation. The sample size was estimated GPower software. A total of 134 respondents between the age of 19 and 25 were sampled because young adults in this age group tend to show little difference in their digital literacy level. Structural equation modelling (SEM) was used to examine the proposed model.

The study results reveal that two of the three domains of digital literacy competence, technical literacy and cognitive literacy, have a positive association in reducing misinformation among university students; however, socio-emotional literacy has the opposite effect. Additionally, the survey also explicates that hedonic motivation helps in misinformation mitigation, whereas habit does not.

Theoretically, this study contributes to the literature by revealing how digital literacy can help in identifying misinformation masquerading as valid information through proper verification and analysis, especially in the digital age where everyone is susceptible to misinformation. The results of the study also contribute to the development of a new digital literacy framework that can cultivate a digitally literate generation who can navigate the informational landscape smartly and therefore distinguish between facts and fake news.

The purpose of this study is to examine the mutual relationship between information literacy and information rights, focusing on how people with high information literacy recognize and use information rights.

This study explores how individuals with information literacy understand and use information rights. This research uses a dual approach. Quantitative surveys, involving 217 Master's and PhD students, delve into the dimensions of information rights. Rigorous stratified sampling ensures diversity. A comprehensive questionnaire, exhibiting high reliability and validity, is administered before and after a two-month online information literacy course. The t-test statistical tests analyze the quantitative data. For deeper insights, qualitative open-answer questionnaires with 50 top-performing participants uncover experiences and perceptions. A two-stage coding process is applied to identify themes.

Major findings showcase the nuanced understanding of information rights shaped by education, experiences and strategic use. Recommendations include emphasizing online privacy education and active roles for information-literate individuals in policy advocacy.

This study contributes to the understanding of information rights, providing a foundation for informed policy and education.

The pandemic has necessitated employees to work virtually due to mandatory work-from-home setup. Since every employee is not comfortable working online owing to their individual differences which impact performance, thus, it is essential to identify individual characteristics governing performance. As per conventional theories, cognition and metacognition have a significant impact on employee performance, and the key to performance in a collaborative online environment also is metacognition. However, this has been scarcely explored in the context of virtual workspace. This study, therefore, empirically investigates the influence of metacognition and its sub-domains on employees' virtual performance given the challenges they face in a virtual work environment.

The cross-sectional study used a purposive sampling technique for data collection. Data collected from 534 professionals with high and low levels of metacognitive ability is analysed using univariate analysis to ascertain whether metacognitive ability helps employees deal with challenges associated with virtual work environments and perform better.

Results confirm a significant relationship between the level of metacognitive ability and virtual performance. Further, the findings also confirm the interaction effect of the level of metacognitive ability and challenge of maintaining work and non-work boundaries and the need for the physical presence of team member/s in predicting virtual performance.

This study is the first empirical attempt to examine the linkage between metacognitive ability and performance among professionals in the context of post-pandemic virtual work environment and challenges.

In November 2022, the commercial company, OpenAI, launched ChatGPT. Since then, university students have rapidly become regular users of this artificial intelligence (AI) platform. One reason for this is the powerful capability of this generative AI tool to produce textual content, which in many cases, is almost indistinguishable from human-generated content. Another reason is that ChatGPT easily gives anyone access to knowledge. However, there is a problem as the vast majority of its users have no idea how this AI platform works and thus overlook the importance of thinking critically about information communicated in ChatGPT. While some call for banning this generative AI tool, this study aims to provide evidence that science classrooms can become scenarios where students find explicit, concrete, and realistic opportunities to critically evaluate scientific information generated by ChatGPT.

An intervention study was conducted with 55 students (26 females and 29 males, 17–24 years old) during a university Spanish-English bilingual science course taught within an active learning environment. The data consist of the written critiques of the students about Spanish-English bilingual scientific texts produced by ChatGPT.

Results indicate that the intervention had a positive effect on students’ abilities to construct sound arguments in Spanish and in English while judging the quality of scientific texts produced by this AI bot. Moreover, the findings suggest that the intervention enriched students’ skills to make improvements to texts produced by this generative AI tool.

The evidence provided in this study contributes to the exploration of possibilities to help students become critical users of ChatGPT.

While higher education has been encouraging interdisciplinary research, few studies have been conducted to understand how interdisciplinarity shapes the identity construction of scholars, especially doctoral students who may already strive to socialize into academia.

Therefore, this study adopts the approach of autoethnography to analyze my lived experience of developing disciplinary literacy and constructing interdisciplinary identity as a Chinese international doctoral student at a North American university. Communication theory of identity (CTI) is the theoretical framework through which I understand the negotiation among my personal, enacted, relational and communal identities while communicating my research through diverse literacy practices.

This autoethnography reveals that interdisciplinary doctoral students can flexibly use discursive resources from different disciplines and literacy practices in both English and their first language to dynamically create interdisciplinary identities communicable to different discourse communities. Their identities in different disciplines can develop simultaneously, rather than suppressing one for the development of the other as they do interdisciplinary research.

This study first extends current scholarly discussion of disciplinary literacy to a less-investigated setting, i.e. doctoral education in higher education. Second, it adds an additive and current layer of interdisciplinarity to the existing understanding of international doctoral students’ identity construction. Third, it helps to understand how the development of disciplinary literacy can facilitate disciplinary identity construction and how disciplinary identity construction can facilitate the development of disciplinary literacy.