Title:	ARE STUDENT ENGAGEMENT HIERARDCHIES CONSISTENT? A RANK-BASED ANALYSIS OF ONLINE VERSUS OFFLINE ATTENDANCE RATES
Author(s):	Victor K. Y. Chan
ISBN:	978-989-8704-72-6
Editors:	Demetrios G. Sampson, Dirk Ifenthaler and Pedro Isaías
Year:	2025
Edition:	Single
Keywords:	Rank Consistency, Online Attendance, Offline Attendance, Spearman's Rank Correlation Coefficient, Kendall's Tau, Wilcoxon Signed-Rank Test
Type:	Full Paper
First Page:	315
Last Page:	322
Language:	English
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Paper Abstract:	This paper extends the work of Chan (2023) by investigating the consistency of student attendance engagement patterns between online and offline lectures, not through direct attendance rate comparison, but through the analysis of student attendance rankings. While the previous study found no significant correlation between direct attendance rates, this research explores whether a student's relative position, or rank, within their cohort remains stable across different learning modalities. Using attendance rate data for four undergraduate courses (n = 78) from Macao Polytechnic University during the 2022/2023 academic year, a suite of non-parametric statistical methods were employ. The analysis reveals no statistically significant rank correlation between online and offline attendance (Spearman's ? = 0.192, p > 0.05; Kendall's ?-b = 0.161, p > 0.05). This indicates that the hierarchy of student engagement is not stable; a student's relative attendance rank in one modality does not predict their rank in the other. However, a Wilcoxon Signed-Rank Test shows a highly significant difference between the paired rates (Z = -4.631, p < 0.001), confirming that students systematically achieve higher attendance rates online. These combined findings suggest that while online learning provides a significant attendance boost, it also fundamentally reshuffles the student engagement hierarchy, with profound implications for identifying and supporting students in different learning environments. A word of caution is that this study targets attendance per se as opposed to attentiveness, which is a far broader concept yielding, for instance, deep learning and academic advancement.
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