当前位置: X-MOL 学术J. Res. Sci. Teach. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Data‐driven refinements of a genetics learning progression
Journal of Research in Science Teaching ( IF 3.6 ) Pub Date : 2020-05-11 , DOI: 10.1002/tea.21631
Moraima Castro‐Faix 1 , Ravit Golan Duncan 1 , Jinnie Choi 2
Affiliation  

Learning progressions are theoretical models that describe learning of scientific ideas and practices over time. These hypothetical progressions need to be tested and refined in order to productively inform instruction and assessment. In this paper, we report our attempts to revise a learning progression in genetics. In particular, we focused on two constructs that embody core ideas in classical genetics and one molecular construct. The revisions are based on analysis of pre‐ and postinterview data obtained from sixty 11th grade students before and after they engaged in a 10‐week unit that addressed these concepts. We found that while many of the students held ideas that aligned with the progression, there were several distinct dimensions of student reasoning that were not captured and led to substantial revisions of the constructs including: (a) the splitting of the construct dealing with meiosis (E) into two subconstructs (E1‐physical passage of genetic information and E2 – the role of sex cells), (b) the addition of new levels to constructs dealing with the universal nature and organization of the genetic code (A) and construct (F). For Construct A, the lower levels were expanded to include ideas about the localization of DNA in cells and to include ideas about the composition of DNA that were not captured in the progression. Revisions to Construct F included the expansion of existing levels and the addition of modes of inheritance such as codominance and incomplete dominance. The research we present offers insights about a methodological approach that can be used to test and refine progressions, as well as insights about student learning in genetics as we further describe and expand the stepping‐stone ideas in the progression and discuss further the multidimensional nature of learning progressions.

中文翻译:

遗传学学习进展的数据驱动改进

学习进度是描述随着时间推移对科学思想和实践的学习的理论模型。这些假想的过程需要进行测试和完善,以有效地指导和评估。在本文中,我们报告了我们试图修改遗传学学习进展的尝试。特别是,我们专注于体现经典遗传学核心思想的两种构建体和一种分子构建体。这些修订是基于对60名11年级学生在参加为期10周的单元以解决这些概念之前和之后获得的面试前后数据的分析而得出的。我们发现,尽管许多学生持有与进阶相吻合的想法,但学生推理有几个不同的方面没有被抓住,并导致结构的实质性修改,包括:(a)将处理减数分裂(E)的结构分为两个子结构(E1-遗传信息的物理传递和E2-性细胞的作用),(b)为处理普遍性的结构增加新的水平以及遗传密码的组织(A)和构建体(F)。对于构建体A,将较低的水平扩展到包括有关DNA在细胞中的定位的想法,并包括有关在进程中未捕获的DNA组成的想法。对结构F的修订包括扩展现有级别,以及增加继承模式,例如共统治和不完全统治。我们目前的研究提供了关于可用于测试和完善进展的方法论方法的见解,
更新日期:2020-05-11
down
wechat
bug