Virtual Booth

Abstract

Students in library and information science (LIS) often learn bibliometrics as theory: they can define indicators such as citation counts, co-authorship and keyword co-occurrence, yet cannot carry out a bibliometric study on their own. This gap is widened by unfamiliarity with R, the language behind many standard bibliometric tools. BiblioLearn addresses the gap through an experiential learning framework that embeds Biblioshiny, the no-code graphical interface of the Bibliometrix R package, into a complete five-stage workflow: Search-Strategy Design, PRISMA-Based Systematic Screening, Data Extraction, Guided Visual Analysis and Reflective Reporting. The framework was piloted in Library Analytics and Metrics (IML630) with 32 Bachelor of Information Science (Hons) Library Management students, who conducted an authentic bibliometric study of 698 Scopus-indexed articles on libraries and student participation in open science. On the university's entrance-exit survey, students' mean self-rating across 10 course learning outcome items rose from 1.39 to 4.42 on a five-point scale (Wilcoxon signed-rank test, p < 0.001); 31 of 32 students improved, and the share of confident ratings (4 or 5) rose from 3.1% to 100%. Thematic analysis of 7 group reflections showed universal prior unfamiliarity with bibliometric software, with 3 groups fearing an R programming barrier; afterwards, 6 of 7 groups found Biblioshiny user-friendly and all 7 intended to use it again. Its novelty lies in replacing a passive, theory-only assessment with a repeatable, tool-based research workflow that takes non-programming learners from a research question to a reported bibliometric analysis. Protected by a registered MyIPO copyright, BiblioLearn offers a practical and transferable pathway for building research and open-science literacy among future library professionals, with potential for licensing as a teaching module and wider adoption across LIS and other research-methods courses.

Keywords: Bibliometrics; Biblioshiny; No-Code Analytics; Experiential Learning; LIS Education