Learning experience network analysis for design-based research

被引:2
作者
Donaldson, Jonan Phillip [1 ,2 ]
Han, Ahreum [3 ]
Yan, Shulong [4 ]
Lee, Seiyon [5 ]
Kao, Sean [6 ]
机构
[1] Texas A&M Univ Coll Stn, Ctr Teaching Excellence, College Stn, TX 77843 USA
[2] Univ Alabama Birmingham, Sch Educ, Birmingham, AL 35294 USA
[3] Univ Illinois, Dept Curriculum & Instruct, Chicago, IL USA
[4] Univ Calif Davis, Sch Educ, Ctr Community & Citizen Sci, Davis, CA 95616 USA
[5] Univ Penn, Grad Sch Educ, Philadelphia, PA 19104 USA
[6] Texas A&M Univ, Dept Educ Psychol, College Stn, TX 77843 USA
关键词
Research methodology; Design-based research; Network analysis; Design moves; Data-driven decision-making; Theory-driven decision-making; Complex systems; Learning experience design;
D O I
10.1108/ILS-03-2023-0026
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Purpose Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.Design/methodology/approach This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.Findings The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.Research limitations/implications LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.Practical implications LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.Originality/value To the best of the authors' knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.
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页码:22 / 43
页数:22
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