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Effectiveness of technology-enhanced learning in Endodontic education: a systematic review and meta-analysis

机译：技术增强学习在牙髓教育中的有效性：系统审查与荟萃分析

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摘要

The aim of the present systematic review was to evaluate the effectiveness of technology-enhanced learning (TEL) in the field of Endodontics to improve educational outcomes compared to traditional learning methods. Randomized controlled studies published in English were identified from two electronic databases (PubMed and Scopus) up to May 2018. Two authors independently performed study selection, data extraction and assessed the risk of bias (ROB). Any teaching method using TEL was considered as the intervention, and this was compared to traditional methods. The outcome measuring the effectiveness of learning activities was evaluated by Kirkpatrick's four-level training evaluation model. The four levels of training outcomes are as follows: Reaction, Learning, Behaviour and Results. A meta-analysis was performed to estimate the standardized mean difference (SMD) by the random effects model. In total, 13 studies were included in the systematic review. Only three studies were assessed as low' ROB. A meta-analysis could not be performed in the domains of Reaction and Behaviour. No significant difference was observed in knowledge gain (Learning domain) between TEL and traditional methods (SMD, 0.14 (95% CI -0.10 to 0.39) I-2=62.7%). Similarly, no difference was observed in performance (Behaviour domain). A variable response was found in attitude (Reaction domain). From the available evidence, it can be concluded that TEL is equally as effective as traditional learning methods.
机译：目前系统审查的目的是评估技术增强学习（Tel）在牙盖学领域的有效性，以改善与传统学习方法相比的教育结果。从2018年5月的两种电子数据库（PubMed和Scopus）出版英语的随机对照研究。两位作者独立地进行了学习选择，数据提取并评估了偏见（ROB）的风险。使用Tel的任何教学方法被认为是干预，这与传统方法进行了比较。测量学习活动有效性的结果是由Kirkpatrick的四级培训评估模型评估的。四个级别的培训结果如下：反应，学习，行为和结果。进行META分析以通过随机效应模型估计标准化平均差异（SMD）。共有13项研究纳入系统审查中。只评估了三项研究，低于“抢劫”。在反应和行为的结构域中无法进行META分析。在电话和传统方法（SMD，0.14（95％CI -0.10至0.39）I-2 = 62.7％之间，在知识增益（学习领域）中没有观察到显着差异。同样，在性能（行为域）中没有观察到差异。在态度（反应域）中发现了可变响应。从可用证据中，可以得出结论，以传统的学习方法同样有效。

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