Deb Eldridge
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引用次数: 0

摘要

随着夏季的结束,本期《JCBE》将涵盖全球和CBE的进程。前两篇文章强调了学生成功的因素和指标。欢迎关注学生成功的秋季特刊的好方法!吉尔默-埃克尔斯博士和她的同事在他们题为《Brandman大学影响学生成功和满意度的因素》的手稿中,为Brandman的能力为基础的教育(CBE)模型确定了对学生成功影响最大的因素。作者将成功定义为项目寿命,研究了各种学生服务(如学术指导和写作/数学中心)的学生满意度调查结果。讨论部分提供了一些可能对CBE研究人员感兴趣的进一步研究的机会。在他们的文章《基于技能能力的表现中的学习和个体差异:使用课程规划和学习工具作为学生成功的指标》中,西部州长大学的Sean Gyll博士和他的同事使用课程规划和学习工具(CPLT)来确定学生成功的因素,例如资源的使用或总结性评估。他们将学生的成功定义为通过计划和学习(使用课程计划工具),知识和信心/经验(使用课程预评估)来衡量。支持学生成功的含义包括通过使用CPLT评估学习者概况的重要性。第三篇文章《教师教育课程及其胜任力教育属性》来自坦桑尼亚,达累斯萨拉姆大学的Tarmo博士和他的同事对中学教育文凭进行了分析,以建立其与CBE属性的整合。通过对文献的定性内容分析,作者认为现在K-12学校强制要求实施CBE方法取决于教师的准备,并在文凭中发现了限制在K-12教室实施CBE的矛盾属性。第四篇文章开启了关于如何支持CBE的广泛采用的对话,在多个项目中实施基于能力的教育:使用ADDIE构建和监控项目优先级的研讨会。来自加拿大拉瓦尔大学医学院的LaFleur博士和他的同事报告了他们对29个医疗住院医师项目向CBE过渡的支持。他们描述了他们提供的9个研讨会,以及如何使用ADDIE教学模型来评估和监控CBE实施的水平。他们的工作的意义延伸到培训教师的CBE采用。第五篇也是最后一篇论文探讨了开发CBE模型的新方法,使用自然语言处理开发能力框架:一项探索性研究。来自拉什大学的Garman博士和来自伊利诺伊州橡树园以及爱达荷州立大学和德保罗大学的同事们,使用一种被称为潜在狄利克雷分配(Latent Dirichlet Allocation, LDA)的语言处理方法,生成了一套领导能力领域。将lda生成的能力域与一组人类生成的能力域进行比较,并评估其一致性。这些发现是有趣的,并提出了在建立和评估能力领域中改进LDA方法的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
JCBE editorial

As we wrap up summer, this issue of JCBE spans the globe and the process of CBE. The first two articles highlight factors in and indicators of student success. What a great way to welcome the fall issue with a focus on student success!

In their manuscript entitled Factors that Contribute to Student Success and Satisfaction at Brandman University, Dr. Gilmer-Echols and her colleagues identify factors that are most influential in student success for Brandman's model of Competency-Based Education (CBE). Defining success as program longevity, the authors explored the results of student satisfaction surveys of various student services, such as academic coaching and the writing/math center. The discussion section offers a number of opportunities for further study that may be of interest to CBE researchers.

In their article, Learning and Individual Differences in Skilled Competency-Based Performance: Using a Course Planning and Learning Tool as an Indicator for Student Success, Dr. Sean Gyll and his colleague at Western Governors University used a course planning and learning tool (CPLT) to identify factors in student success, such as the use of resources or the summative assessment. They defined student success as measured by planning and learning (using the course planning tool), knowledge, and confidence/experience (using a course preassessment). Implications for supporting student success include the importance of assessing the learner profile by using the CPLT.

The third article, The Teacher Education Curriculum and its Competency-Based Education Attributes, comes to JCBE from Tanzania where Dr. Tarmo and his colleague at the University of Dar Es Salaam provide an analysis of the Diploma of Secondary Education to establish its integration of CBE attributes. Using a qualitative content analysis of documents and arguing that implementation of the CBE approach now mandated in K-12 schools is dependent upon teacher preparation, the author(s) found contradictory attributes in the Diploma that constrain CBE implementation in K-12 classrooms.

The fourth article opens up the conversation about how to support widespread adoption of CBE, Implementing Competency-Based Education in Multiple Programs: A Workshop to Structure and Monitor Programs' Priorities Using ADDIE. Dr. LaFleur and his colleagues from Laval University Faculty of Medicine in Canada report on their support of the transition of 29 medical residency programs to CBE. They describe nine workshops they offered and how the ADDIE instructional model was used to assess and monitor levels of CBE implementation. Implications of their work extend to training faculty for CBE adoption.

The fifth and final manuscript explores a new approach to developing CBE models, Developing competency frameworks using natural language processing: An exploratory study. Dr. Garman from Rush University and colleagues from Oak Park, Illinois, as well as Idaho State and DePaul universities, generate a set of leadership competency domains using a language processing approach called Latent Dirichlet Allocation (LDA). The LDA-generated competency domains are compared to a set of human-generated domains and assessed for coherence. The findings are intriguing and suggest opportunities for refinement of an LDA approach in establishing and evaluating domains of competency.

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