Designing for learning across disciplines: leveraging graphs to improve knowledge integration in science

IF 2.6 3区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Instructional Science Pub Date : 2024-07-13 DOI:10.1007/s11251-024-09673-9

Phillip A. Boda, Shruti Bathia, Libby Gerard, Marcia C. Linn

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Abstract

Advances in graphing technologies and learning sciences pedagogy have the potential to equitably support students when exploring complex systems depicting dynamic relationships across multiple disciplinary topics in Science, Technology, Engineering, and Mathematics (STEM). We report on the cumulative impact of science units designed in a Research Practice Partnership (RPP) that leveraged Knowledge Integration (KI) pedagogy to support middle school students to generalize insights to new graph representations and science topics. Teachers across 11 schools incorporated the graph-science units into their curriculum plans. We analyzed ~ 8000 responses to validated and reliable graph-science KI assessment items administered before the first year and after one, two, or three years of instruction aligned with KI pedagogy. With random coefficient, multi-level, mixed-effect regression modeling, we analyzed performance after one-, two-, and three-years of graph-science KI instruction. We also analyzed the growth trajectories of subgroups, i.e., multilingual learners. Data suggest two years of graph-science KI instruction is needed to make significant impacts on student learning and ameliorated the disparity between students with different native language fluencies. These results illustrate the value of technology-enhanced, pedagogically aligned K-12 science instruction that is designed to support connecting diverse graph data and science knowledge comprehensively and cumulatively.

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跨学科学习设计：利用图表改进科学知识整合

图形技术和学习科学教学法的进步有可能为学生探索描述科学、技术、工程和数学（STEM）多个学科主题动态关系的复杂系统提供公平支持。我们报告了在研究实践合作项目（RPP）中设计的科学单元所产生的累积影响，这些单元利用知识整合（KI）教学法，支持初中学生将见解归纳到新的图形表示法和科学主题中。11 所学校的教师将图形科学单元纳入了他们的课程计划。我们分析了约 8000 份对经过验证且可靠的图形科学 KI 评估项目的回复，这些评估项目分别在第一年之前以及与 KI 教学法相匹配的一年、两年或三年教学之后进行。通过随机系数、多层次、混合效应回归模型，我们分析了图形科学 KI 教学一年、两年和三年后的成绩。我们还分析了子群体（即多语言学习者）的成长轨迹。数据表明，需要两年的图形科学 KI 教学才能对学生的学习产生显著影响，并能改善母语流利程度不同的学生之间的差距。这些结果说明了技术增强型、与教学相一致的 K-12 科学教学的价值，这种教学旨在支持将不同的图表数据与科学知识全面、累积地联系起来。

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来源期刊

Instructional Science Multiple-

CiteScore

4.80

自引率

4.00%

发文量

期刊介绍： Instructional Science, An International Journal of the Learning Sciences, promotes a deeper understanding of the nature, theory, and practice of learning and of environments in which learning occurs. The journal’s conception of learning, as well as of instruction, is broad, recognizing that there are many ways to stimulate and support learning. The journal encourages submission of research papers, covering a variety of perspectives from the learning sciences and learning, by people of all ages, in all areas of the curriculum, in technologically rich or lean environments, and in informal and formal learning contexts. Emphasizing reports of original empirical research, the journal provides space for full and detailed reporting of major studies. Regardless of the topic, papers published in the journal all make an explicit contribution to the science of learning and instruction by drawing out the implications for the design and implementation of learning environments. We particularly encourage the submission of papers that highlight the interaction between learning processes and learning environments, focus on meaningful learning, and recognize the role of context. Papers are characterized by methodological variety that ranges, for example, from experimental studies in laboratory settings, to qualitative studies, to design-based research in authentic learning settings. The Editors will occasionally invite experts to write a review article on an important topic in the field. When review articles are considered for publication, they must deal with central issues in the domain of learning and learning environments. The journal accepts replication studies. Such a study should replicate an important and seminal finding in the field, from a study which was originally conducted by a different research group. Most years, Instructional Science publishes a guest-edited thematic special issue on a topic central to the journal''s scope. Proposals for special issues can be sent to the Editor-in-Chief. Proposals will be discussed in Spring and Fall of each year, and the proposers will be notified afterwards. To be considered for the Spring and Fall discussion, proposals should be sent to the Editor-in-Chief by March 1 and October 1, respectively. Please note that articles that are submitted for a special issue will follow the same review process as regular articles.