Investigating how faculty social networks and peer influence relate to knowledge and use of evidence-based teaching practices
Investigating how faculty social networks and peer influence relate to knowledge and use of evidence-based teaching practices
复制标题
DOI：
10.1186/s40594-019-0182-3
复制
发表时间：
2019-08-14
影响因子：
6.7
通讯作者：
Stains, M.
中科院分区：
文献类型：
--
作者：
Lane, A. K.;Skvoretz, J.;Stains, M.
背景 美国几十年来一直呼吁科学教育改革。最近呼吁在 10 年内培养 100 万新的科学、技术、工程和数学 (STEM) 毕业生，这凸显了在本科 STEM 课程中采用循证教学实践 (EBIP) 的必要性，以创造引人入胜且有效的学习环境。 EBIP 是一种教学策略，经实证证明可以对学生在 STEM 学科中的学习、态度和成就产生积极影响。然而，教师了解和选择实施 EBIP 的机制和过程仍不清楚。为了探索这个问题领域，我们使用社交网络分析来研究教师的知识和 EBIP 的使用如何受到 STEM 系内同行的影响。我们调查了三所公立大学生物和化学系的教学讨论网络。结果我们报告说，部门之间的联系强度和联系多样性有所不同，但平均程度与组织排名或任期状态无关。我们还描述了教学讨论关系通常可以被描述为基于两种关系强度度量的强关系。此外，我们比较了同事影响模型，并找到了一致的证据，表明这些部门的同事影响遵循网络干扰模型。结论 我们关于关系强度和关系多样性的研究结果表明，这些部门的社交网络结构在有利于变革的程度方面有所不同。讨论伙伴和同伴影响模型在教学实践中的相关性表明，变革推动者在制定变革策略时应考虑当地社交网络的特征。特别是，变革推动者可以期望教师可以充当意见领袖，无论其学术排名如何，并且教师可以增加对 EBIP 的使用，即使他们谈论教学的人使用 EBIP 相对较少。
Background Calls for science education reform have been made for decades in the USA. The recent call to produce one million new science, technology, engineering, and math (STEM) graduates over 10 years highlights the need to employ evidence-based instructional practices (EBIPs) in undergraduate STEM classes to create engaging and effective learning environments. EBIPs are teaching strategies that have been empirically demonstrated to positively impact student learning, attitudes, and achievement in STEM disciplines. However, the mechanisms and processes by which faculty learn about and choose to implement EBIPs remain unclear. To explore this problem area, we used social network analysis to examine how an instructor's knowledge and use of EBIPs may be influenced by their peers within a STEM department. We investigated teaching discussion networks in biology and chemistry departments at three public universities. Results We report that tie strength and tie diversity vary between departments, but that mean indegree is not correlated with organizational rank or tenure status. We also describe that teaching discussion ties can often be characterized as strong ties based on two measures of tie strength. Further, we compare peer influence models and find consistent evidence that peer influence in these departments follows a network disturbances model. Conclusions Our findings with respect to tie strength and tie diversity indicate that the social network structures in these departments vary in how conducive they might be to change. The correlation in teaching practice between discussion partner and peer influence models suggest that change agents should consider local social network characteristics when developing change strategies. In particular, change agents can expect that faculty may serve as opinion leaders regardless of their academic rank and that faculty can increase their use of EBIPs even if those they speak to about teaching use EBIPs comparatively less.