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Using Social Network Analysis to Measure Student Collaboration in an Undergraduate Capstone Course

机译:使用社交网络分析来衡量本科生顶点课程中的学生合作

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Social network analysis offers a unique way for instructors to visualize collaboration and communication within a course and see relationships between individuals, groups, teams, or cliques. We used social network analysis to measure the growth of collaboration in the capstone AGEDS 450 Farm Management and Operation course at Iowa State University. With the strategic implementation of collaboratively intense assignments, student collaboration grew from the midpoint of the semester to the end of the semester. Overall density of the network increased from 0.25 at the midpoint to 0.35 at the end of the semester (40% growth). Each student's number of communication ties increased over the course of the semester to 17.2. Average geodesic distance betweennodes decreased 11.7% from the midpoint to the end of the semester, resulting in an average pathway length of 1.66 to connect any two students; this improved communication efficiency in the course. No outpoint existed at the midpoint or the end of semester, showing no risk of collapse in the network. The overall network became more complex, indicating a more inclusive collaborative environment. We recommend that instructors include structured activities that emphasize student collaboration to help develop strong information networks in other courses.
机译:社交网络分析为教师提供了一种独特的方式,使其可视化课程内的协作和交流,并查看个人,团体,团队或集团之间的关系。我们使用社交网络分析来衡量爱荷华州立大学的AGEDS 450农场管理和运营课程的顶峰。通过战略性地执行协作式作业,学生协作从学期的中点发展到了学期末。网络的总体密度从中点的0.25增加到学期末的0.35(增长40%)。每学期的每个学生的交流纽带数量增加到17.2。从中点到本学期末,节点之间的平均测地线距离减少了11.7%,因此连接任何两个学生的平均路径长度为1.66;在过程中提高了沟通效率。在学期中点或学期末不存在任何外露点,表明网络没有崩溃的风险。整个网络变得更加复杂,这表明了更具包容性的协作环境。我们建议讲师进行有组织的活动,强调与学生的协作,以帮助在其他课程中建立强大的信息网络。

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