医学生个性化学习资源推荐系统偏好与其自主学习水平的相关性研究

目的 了解医学生对个性化学习资源推荐系统的性能、功能和推荐方式的偏好，以及与医学生自主学习能力的相关性，为进一步构建有效的学习平台和学习资源工具提供参考。方法 以某医科大学大一至大三医学生482人为研究对象，使用电子版自主学习量表及自制医学教育学习资源推荐系统的性能、功能及推荐方式量表进行问卷调研。使用SPSS 26.0进行t检验、单因素方差分析、秩和检验、Pearson相关分析。使用Pearson相关分析探究医学生信息资源推荐系统的性能、功能及推荐方式偏好与自主学习能力的相关性。结果 医学生对于学习资源推荐系统的学习性（4.35±0.58）分]、准确性（4.32±0.62）分]和时效性（4.32±0.62）分]具有较高的需求和偏好。对于推荐系统的功能方面，在社交功能中的关注（4.10±0.71）分]、分享（3.94±0.82）分]，在交互功能中的搜索（4.35±0.59）分]、反馈（4.09±0.73）分]、发表（3.80±0.88）分]都得到了较高的评分。对于推荐方式偏好，基于学科联系（4.07±0.66）分]、基于时间线（4.02±0.74）分]等方面得分更高。与自主学习相关性较高的有信息资源推荐系统的时效性（r=0.367）、社交属性（r=0.361），以及基于类似人群维度（r=0.316）。结论 医学生对学习资源推荐系统的各类性能、功能和推荐方式较为熟悉且态度积极，具有学习资源推荐系统构建及相关资源平台建设的认知基础。该系统与医学生自主学习能力具有一定的相关性，推进医学教育信息资源建设有利于促进学生自主学习能力的发展。

Research on the correlation between the preference of personalized learning resource recommendation system and self-directed learning level of medical students

Objective To understand the preferences of medical students for the performance, function and recommendation method of personalized learning resource recommendation system, as well as the correlation with the self-directed learning ability of medical students, so as to provide a reference for further building an effective learning platform and learning resource tool.Methods A total of 482 first-year to third-year medical students in a medical university were selected as the research subjects. The electronic self-directed learning scale and the self-designed medical education learning resources recommendation system of performance, function and recommendation method scale were used to conduct a questionnaire survey. Pearson correlation analysis was used to explore the correlation between the performance, function and recommendation method preference of medical students'' information resource recommendation system and self-directed learning ability.Results Medical students had high demand and preference for learning (4.35±0.58) points], accuracy (4.32±0.62) points] and timeliness (4.32±0.62) points] of learning resource recommendation system. In terms of the function of the recommendation system, the following (4.10±0.71) points] and sharing (3.94±0.82) points], and searching (4.35±0.59) points], feedback (4.09±0.73) points] and publication (3.80±0.88) points] in the interactive function were all highly rated. For the preference of recommendation methods, the scores of discipline connection (4.07±0.66) points] and time line (4.02±0.74) points] were higher. The dimensions with high relevance to self-directed learning included timeliness (r=0.367), social attributes (r=0.361), and the basis of similar groups (r=0.316).Conclusion Medical students are familiar with and have a positive attitude towards the performance, functions and recommendation methods of the learning resource recommendation system, and have a cognitive foundation for the construction of the learning resource recommendation system and related resource platforms. This system has a certain correlation with the self-directed learning ability of medical students. Promoting the construction of medical education information resources is conducive to promoting the development of self-directed learning ability of medical students.