Running Toward Network Models of Individuals and Their Contexts

被引:0
|
作者
Ram, Nilam [1 ,2 ]
Gatzke-Kopp, Lisa [3 ]
机构
[1] Stanford Univ, Dept Psychol, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Commun, Stanford, CA 94305 USA
[3] Penn State Univ, human dev & family studies, State Coll, PA USA
关键词
D O I
10.3102/0091732X231219237
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
We note two possibilities for how our science might capitalize on advances in computing that harness and weave "big data" into the rich tapestry of how human development unfolds. First, we propose that the classic theoretical models that have guided developmental research since the 1970s and the hierarchical analytical models used to operationalize those theories might both be replaced with new network models that capture multidirectional interplay among many facets of a person and their context. Second, we suggest that contemporary person-specific (idiographic) network models based on newly available streams of data about a human's ongoing activities and experiences can reshape what we discover about individuals and how those discoveries are injected back into people's lives.
引用
收藏
页码:181 / 184
页数:4
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