Conferences

Permanent URI for this collectionhttp://localhost:4000/handle/20.500.12092/2593

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    Integrating Artificial Intelligence Literacy in Library and Information Science Training in Kenyan Academic Institutions
    (SCECSCAL, 2024-09) Chepchirchir, Sally
    With the rapid technological advancements, Library and Information Science (LIS) programs should evolve to equip students in academic institutions with Artificial Intelligence (AI) skills and knowledge to meet the demands of the information profession. The objectives of this paper were to establish the current state of AI literacy in LIS training in academic institutions in Kenya, examine the extent to which AI literacy has been integrated into LIS curricula in academic institutions, identify the challenges and opportunities associated with the integration of AI literacy in academic institutions in Kenya, and propose critical recommendations that the management in academic institutions should consider for integrating AI literacy in LIS training in Kenya. The study employed a mixed-methods approach, combining qualitative and quantitative data collection methods. Quantitative data was collected through bibliometrics analysis, while qualitative data was collected using a systematic literature review and observation. Data was collected from Google Scholar using Harzing’s “Publish or Perish” software and academic institutional websites. It was analysed using Microsoft Excel, Notepad, and VOSviewer and presented using tables, graphs, and figures. The findings reveal that LIS professionals must possess essential skills and competencies in AI to meet the evolving needs of the job market. The study highlighted valuable practical insights and recommendations to the management in academic institutions on a comprehensive understanding of the opportunities and challenges presented by AI literacy in LIS training, offering a foundation for future research, policy development, and pedagogical innovation in the field.
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    Effectiveness of Reference Management Software in Enhancing Research Quality in Universities in Nairobi County, Kenya
    (SCECSAL, 2024-04) Kairigo, Samuel; Anduvare, Everlyn
    Reference management software (RMS) application is highly emphasised in academic research to improve research quality. However, studies raise concerns about their effectiveness since they have errors in functionality, language limitations, and inaccuracy of the citations and references generated. This study aimed to establish how effective RMS is in improving research quality. The study objectives were to investigate what reference management software is in use in the universities in Nairobi County, Kenya and to establish if reference management software programmes are effective in enhancing the quality of research in the selected universities. The study adopted a descriptive research design. This assisted the researchers in gathering data through a survey where an online questionnaire was administered to 18 respondents. All the universities within the County of Nairobi constituted the target population. The unit of analysis was the University Librarians because of their crucial role in promoting research quality in Kenyan Universities. In the analysis, insights were derived using a computer-based statistical package for social science (SPSS). The study revealed high satisfaction with RMS, particularly in terms of necessity, visual appeal, integration capabilities, and automatic formatting of references. While University librarians reported ease of navigation, there was limited awareness of alternative referencing approaches. Continuous institutional training programs for librarians and researchers on RMS usage, covering basic and advanced functionalities, are recommended.
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    State of Libraries in Kenya
    (Karatina University, 2023-06) Gatiti, Peter; Anduvare, Everlyn
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    “The Quest for Quality in University Education in the Post COVID-19 Era: Do Anti-plagiarism Tools Still Matter?” 
    (2022-06) Kavulya, Joseph M.; Kiilu, Vincent Bob; Kyengo, Bernadetta N.
    Plagiarism is a major global challenge to quality assurance in higher education. Various efforts have been made to overcome the menace including the use of anti-plagiarism tools. At the same time, many questions have been raised about the efficacy of the current generation of tools in detecting, preventing plagiarism, and guaranteeing the quality of education. This paper examines the limitations of plagiarism detection tools in enhancing quality in academic outcomes and proposes measures for improvement. The paper argues that while anti-plagiarism software has a role in preventing plagiarism in academic writing and academic integrity, they are not the panacea to the plagiarism pandemic, especially in the COVID-19 era. It proposes that there is a need to reform methods of assessment and implement forward-looking policies to address the underlying causes of plagiarism, provide students with appropriate information literacy skills training, and above all cultivate a culture of academic integrity in higher education institutions (HEIs).