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Online learning resource preferences across learning stages: a cognitive load theory perspective in UK medical
Yizhen Wang1,2, Xiaomeng Zhang3, Chao Wang4
1Department of Clinical Medicine, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, Shandong, 266000, China. yizhen.wang@qdu.edu.cn.
Background:
Online learning resources (OLRs) have become an important part of the education for students in the early years of the medicine programme (Years 1-2) in the UK. There are a variety of OLRs. However, an excessive amount of resources can impose a significant cognitive load. Students selectively use OLRs to avoid cognitive load, forming their preferences for OLRs. When students use OLRs before and after class, as well as before exams, these distinct learning stages involve different learning objectives and challenges. Thus, students' preferences for OLRs may also differ. This study aims to identify how OLRs preferences change across different learning stages (pre-class, post-class, and pre-exam), enabling educators to provide more targeted OLRs support to learners based on an understanding of their cognitive needs.
Methods:
This cross-sectional study used a self-administered questionnaire. Participants were early-year medicine undergraduates (Years 1-2) at the University of Exeter. The questionnaire included Likert scales and open-ended questions. To examine undergraduates' OLRs preferences and attitudes, one- and two-way repeated-measures ANOVA analyses were conducted. Qualitative analysis of open-ended responses utilized a framework combining Braun and Clarke's reflexive thematic analysis with Krippendorff's principles of content validity.
Results:
The most preferred OLRs vary across different learning stages. The highest-scoring OLRs were interactive videos (3.16 ± 0.86, out of 4) in the pre-class stage, optional practice questions (3.65 ± 0.71, out of 4) in the post-class stage, and online mock exams (3.89 ± 0.38, out of 4) in the pre-exam stage. Personal study habits, content value, time cost, and resource delivery are crucial factors that influence learners' preferences.
Conclusions:
Learners' preferences for OLRs vary across different stages of the learning process. Understanding these patterns may help educators better align the design and delivery of OLRs with students' perceived needs. For example, providing interactive, vivid, and clearly structured materials during early learning stages and incorporating practice questions or self-assessment opportunities after classes and before examinations may better support learners' preparation and consolidation. While these findings reflect learners' reported preferences rather than objective measures of learning effectiveness, they offer insights that may inform the development of stage-appropriate OLRs.
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