TY - JOUR
T1 - Constructing networks of action-relevant episodes
T2 - An in situ research methodology
AU - Barab, Sasha A.
AU - Hay, Kenneth E.
AU - Yamagata-Lynch, Lisa C.
PY - 2001
Y1 - 2001
N2 - In this article, we advance a methodology for capturing and tracing the emergence, evolution, and diffusion of a practice, conceptual understanding, resource, or student-constructed artifact. The Constructing Networks of Action-Relevant Episodes (CN-ARE) methodology allows researchers to identify relevant data from a complex, evolving environment, and then to organize it into a web of action that can illuminate the historical development (evolving trajectory) of the phenomenon of interest (e.g., conception of an eclipse, applications of a mathematical formula, an evolving student-constructed Website). To accomplish this end, experiences are (a) sectioned into action-relevant episodes (AREs), (b) parsed down to codes in a database, and (c) then represented as nodes in a network so that the historical development of the particular phenomenon of interest can be traced. The CN-ARE methodology is especially useful for researchers interested in carrying out design experiments in which research findings with respect to one iteration of a course are cycled into the design of future course instantiations. In addition to setting the context and providing a theoretical rationale for the CN-ARE methodology, this discussion includes an in-depth description of the methodology along with its application to data sets. Following these examples, we close with a discussion of the scope and limitations of this methodology, touching on issues of trustworthiness, credibility, and usefulness.
AB - In this article, we advance a methodology for capturing and tracing the emergence, evolution, and diffusion of a practice, conceptual understanding, resource, or student-constructed artifact. The Constructing Networks of Action-Relevant Episodes (CN-ARE) methodology allows researchers to identify relevant data from a complex, evolving environment, and then to organize it into a web of action that can illuminate the historical development (evolving trajectory) of the phenomenon of interest (e.g., conception of an eclipse, applications of a mathematical formula, an evolving student-constructed Website). To accomplish this end, experiences are (a) sectioned into action-relevant episodes (AREs), (b) parsed down to codes in a database, and (c) then represented as nodes in a network so that the historical development of the particular phenomenon of interest can be traced. The CN-ARE methodology is especially useful for researchers interested in carrying out design experiments in which research findings with respect to one iteration of a course are cycled into the design of future course instantiations. In addition to setting the context and providing a theoretical rationale for the CN-ARE methodology, this discussion includes an in-depth description of the methodology along with its application to data sets. Following these examples, we close with a discussion of the scope and limitations of this methodology, touching on issues of trustworthiness, credibility, and usefulness.
UR - http://www.scopus.com/inward/record.url?scp=0035587263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0035587263&partnerID=8YFLogxK
U2 - 10.1207/S15327809JLS10-1-2_5
DO - 10.1207/S15327809JLS10-1-2_5
M3 - Article
AN - SCOPUS:0035587263
SN - 1050-8406
VL - 10
SP - 63
EP - 112
JO - Journal of the Learning Sciences
JF - Journal of the Learning Sciences
IS - 1-2
ER -