PDF(Pubmed)
Abstract：
To provide students of veterinary medicine with the necessary day 1 competences, e-learning offerings are increasingly used in addition to classical teaching formats such as lectures. For example, virtual patients offer the possibility of case-based, computer-assisted learning. A concept to teach and test clinical decision-making is the key feature (KF) approach. KF questions consist of three to five critical points that are crucial for the case resolution. In the current study usage, learning success, usability and acceptance of KF cases as neurological virtual patients should be determined in comparison to the long cases format. Elective courses were offered in winter term 2019/20 and summer term 2020 and a total of 38 virtual patients with neurological diseases were presented in the KF format. Eight cases were provided with a new clinical decision-making application (Clinical Reasoning Tool) and contrasted with eight other cases without the tool. In addition to the evaluation of the learning analytics (e.g., processing times, success rates), an evaluation took place after course completion. After 229 course participations (168 individual students and additional 61 with repeated participation), 199 evaluation sheets were completed. The average processing time of a long case was 53 min, while that of a KF case 17 min. 78% of the long cases and 73% of KF cases were successfully completed. The average processing time of cases with Clinical Reasoning Tool was 19 min. The success rate was 58.3 vs. 60.3% for cases without the tool. In the survey, the long cases received a ranking (1 = very good, 6 = poor) of 2.4, while KF cases received a grade of 1.6, 134 of the respondents confirmed that the casework made them feel better prepared to secure a diagnosis in a real patient. Flexibility in learning (n = 93) and practical relevance (n = 65) were the most frequently listed positive aspects. Since KF cases are short and highlight only the most important features of a patient, 30% (n = 70) of respondents expressed the desire for more specialist information. KF cases are suitable for presenting a wide range of diseases and for training students\' clinical decision-making skills. The Clinical Reasoning Tool can be used for better structuring and visualizing the reasoning process.
摘要：
为兽医学学生提供必要的第1天能力，除了讲座等经典教学形式之外，电子学习产品也越来越多地使用。例如,虚拟患者提供了基于病例的可能性，计算机辅助学习。教导和测试临床决策的概念是关键特征(KF)方法。KF问题由三到五个关键点组成，这些关键点对于案件解决至关重要。在目前的研究使用中，学习成功,KF病例作为神经系统虚拟患者的可用性和接受度应与长例格式进行比较。2019/20年冬季学期和2020年夏季学期提供选修课程，共有38名神经系统疾病虚拟患者以KF格式呈现。为8例病例提供了新的临床决策应用程序（临床推理工具），并与其他8例没有该工具的病例进行了对比。除了学习分析的评估(例如，处理时间,成功率)，课程完成后进行了评估。参加了229门课程（168名学生和另外61名学生反复参加），完成199张评价表。长案的平均处理时间为53分钟，而KF案件17分钟。78%的长病例和73%的KF病例均顺利完成。使用临床推理工具的病例平均处理时间为19分钟。成功率为58.3vs.没有工具的情况下为60.3%。在调查中,长期病例获得排名(1=非常好，6=差）为2.4，而KF病例的评分为1.6，134名受访者证实，病例工作使他们感觉更好，可以在真实患者中进行诊断。学习的灵活性（n=93）和实际相关性（n=65）是最常列出的积极方面。由于KF病例短，只突出患者最重要的特征，30％（n=70）的受访者表示希望获得更多专家信息。KF病例适用于广泛的疾病和培训学生的临床决策技能。临床推理工具可用于更好地构建和可视化推理过程。
