计算机科学
分级(工程)
任务(项目管理)
多样性(控制论)
能力(人力资源)
培训(气象学)
数据收集
医学教育
知识管理
人工智能
心理学
工程类
医学
社会心理学
统计
土木工程
物理
数学
系统工程
气象学
作者
Barbara Buck,Elizabeth Biddle,Liz Gehr,Kristi Eager
标识
DOI:10.1007/978-3-031-34735-1_15
摘要
In the past several years, the shift from traditional task-based training to competency-based training has gained traction within the training community. Rather than the traditional one-size-fits-all training solution, a Competency-Based Training and Assessment (CBTA) approach encourages tailoring the learning experiences to the learner and using evidence of learning to determine the student’s competency for a variety of learning components. The challenge then is how best to assess student competency, and how to store this data and use it to adapt the training experience to the student’s needs. In order to establish an effective CBTA methodology, we need to understand the requirements for clearly and consistently evaluating competencies both across students and learning opportunities, but also across multiple instructors who might be assessing different students. This paper seeks to develop a vision towards a standardized approach for CBTA data collection, grading, and assessment.
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