Publication
Reviewing Theoretical and Generalizable Text Network Analysis: Forma Mentis Networks in Cognitive Science
Publisher:
Center for Open Science
Date:
30-05-2022
DOI:
10.31234/OSF.IO/Y789N
Abstract: Recommendations for network studies in learning analytics (LA) emphasize that network construction requires careful definitions of nodes, relationships between them, and network boundaries. Thus far, LA researchers have discussed how to operationalizeinterpersonal networks in learning settings. Analytical choices used in constructing networks of text have not been examined as much. By reviewing ex les of text network analysis in LA, we demonstrate that convenience-based decisions for network construction are common, particularly when the ties in the text networks are defined as the co-occurrences of words or ideas. We argue that such an approach is limited in its potential to contribute to theory or generalize across studies. This submission presents an alternative approach to network representations of the text in learning settings, using the concept of Forma Mentis Networks (FMN). As reported in previous studies, FMNs are network representations either (1) elicited from in iduals through free association tasks that capture valence or (2) constructed by analysts creating shared mental maps derived from text. FMN is a theory-based and scalable approach complementary to the existing set of tools available for the analysis of teaching and learning.