Abstract:

Threshold concepts are known as the representative level of conceptual understanding of students at different disciplines, mostly in Higher Education. First proposed by Meyer and Land in 2003, threshold concepts can be defined as ways of knowing central to the mastery of a subject.

Following Meyer & Land's proposal of Threshold concepts framework, numerous studies have sought to uncover threshold concepts across various disciplines, including physic (Meyer, J., & Land, R. (2003), biology (Dunn, M. J. (2019).), computer science (Shinners-Kennedy, D., & Fincher, S. A. (2013, August)) and others. To identify such concepts, diverse methodologies have been employed, primarily involving semi-structured interviews, analysis of exam responses, and observation of classroom behavior. While these methods are time-consuming and subjective, efforts have also been made to quantitatively assess these concepts.

Based on the threshold concepts definition, it should be integrative, so some researchers have turned to network analysis. For example, Walker (2013) utilized Anderson's schema theory and semantic networks to directly extract conceptual connections from both students and lecturers. Scott and Harlow delved into specific network analysis metrics and suggested that the degree of connectedness of nodes associated with threshold concepts will differ from that of non-threshold concepts, as indicated by an increased number of edges to those particular nodes. This approach not only highlights the importance of connectedness but also contributes to a more comprehensive understanding of the integrative nature of threshold concepts in various domains of study.

To explore the interrelationships between concepts, the method of conceptual mapping (Novak & Musonda, 1991) has been employed. Concept maps visually display the relationships between concepts and processes within a particular subject area, such as mathematics, physics, or biology. Concept maps are utilized to measure conceptual changes during the learning process (Thurn et al., 2020) and to highlight key concepts within a given topic (Koponen & Nousiainen, 2018). In the past decade, significant insights have also been gained regarding the use of specific metrics from network analysis to determine various characteristics of conceptual structures, such as connectivity (e.g. Kapuza et al., 2020).

Thus, using of concept mapping as a data collection tool and network analysis as analytical strategy could provide meaningful approach to identify threshold concepts. This approach not only aids in addressing the challenges associated with information processing and retention but also contributes to fostering a more comprehensive and nuanced comprehension of complex concepts.

This research is aimed to demonstrate the possibility of this approach by empirically validating threshold concepts in disciplines of Social Science at Middle School. All this is supposed to give a clear vision of new information accommodation (Kirschner, P., & Hendrick, C. (2020), but what is most important, such a map of threshold concepts, connections and relations could show the system of student’s conceptual understanding (Perkins, D. (1999) with the possibilities of evident-based assessment, which is less explored in School education.

Keywords:

Conceptual understanding, threshold concepts, network analysis, concept maps, social sciences, school curriculum.