Javascript must be enabled to continue!
Integrating beyond the Surface: Conceptual Disambiguation and Conversational Learning for Shared Meaning-Making in Interdisciplinary Teamwork
View through CrossRef
Abstract
Integrating knowledge from different disciplines is considered key to realizing the potential of interdisciplinary collaboration and is central to many interdisciplinary research and education initiatives. However, how to stimulate knowledge integration remains elusive. As a middle ground between metatheories that provide all-encompassing conceptualizations of integration and accounts of specific interventions and methodologies to support integration, we set out to identify principles that govern a specific form of knowledge integration: conceptual integration. Using an action research approach, we studied conceptual integration processes in a team of eight students enrolled in diverse Master’s programs. We found that they often made quick decisions about concepts, definitions, and relationships between concepts. However, there were several instances where such decisions were later turned out to be false senses of shared understanding. We considered these instances to be indicative of a lack of ‘conceptual disambiguation’. Instead of first thoroughly making sense of the overlap and non-overlap between their conceptual understandings, they immediately jumped to agreeing on the terminology they used. At surface level, their work appeared to be integrated. We continued to explore how we could stimulate conceptual disambiguation and integration. We used Conversational Learning Theory and found that its five dialectics proved helpful in identifying, understanding and addressing the dynamics that hindered conceptual integration. Based on these findings, we argue that conceptual disambiguation should be granted greater attention in facilitating and training conceptual integration, and that conversational learning theory can be adopted as a guiding principle to recognize and address bottlenecks in conceptual integration.
Title: Integrating beyond the Surface: Conceptual Disambiguation and Conversational Learning for Shared Meaning-Making in Interdisciplinary Teamwork
Description:
Abstract
Integrating knowledge from different disciplines is considered key to realizing the potential of interdisciplinary collaboration and is central to many interdisciplinary research and education initiatives.
However, how to stimulate knowledge integration remains elusive.
As a middle ground between metatheories that provide all-encompassing conceptualizations of integration and accounts of specific interventions and methodologies to support integration, we set out to identify principles that govern a specific form of knowledge integration: conceptual integration.
Using an action research approach, we studied conceptual integration processes in a team of eight students enrolled in diverse Master’s programs.
We found that they often made quick decisions about concepts, definitions, and relationships between concepts.
However, there were several instances where such decisions were later turned out to be false senses of shared understanding.
We considered these instances to be indicative of a lack of ‘conceptual disambiguation’.
Instead of first thoroughly making sense of the overlap and non-overlap between their conceptual understandings, they immediately jumped to agreeing on the terminology they used.
At surface level, their work appeared to be integrated.
We continued to explore how we could stimulate conceptual disambiguation and integration.
We used Conversational Learning Theory and found that its five dialectics proved helpful in identifying, understanding and addressing the dynamics that hindered conceptual integration.
Based on these findings, we argue that conceptual disambiguation should be granted greater attention in facilitating and training conceptual integration, and that conversational learning theory can be adopted as a guiding principle to recognize and address bottlenecks in conceptual integration.
Related Results
Autonomy on Trial
Autonomy on Trial
Photo by CHUTTERSNAP on Unsplash
Abstract
This paper critically examines how US bioethics and health law conceptualize patient autonomy, contrasting the rights-based, individualist...
State-of-the-art in Open-domain Conversational AI: A Survey
State-of-the-art in Open-domain Conversational AI: A Survey
We survey SoTA open-domain conversational AI models with the purpose of presenting the prevailing challenges that still exist to spur future research. In addition, we provide stati...
State-of-the-Art in Open-Domain Conversational AI: A Survey
State-of-the-Art in Open-Domain Conversational AI: A Survey
We survey SoTA open-domain conversational AI models with the objective of presenting the prevailing challenges that still exist to spur future research. In addition, we provide sta...
The empirical research of teamwork competency factors and prediction on academic achievement using machine learning for students in Thailand
The empirical research of teamwork competency factors and prediction on academic achievement using machine learning for students in Thailand
Introduction. Teamwork competencies are important for achieving the success of education, developing a meaningful and lifelong career, bringing new ideas, helping to solve problems...
The assessment of teamwork competencies for students focuses on dimensionality and mixed-method assessment
The assessment of teamwork competencies for students focuses on dimensionality and mixed-method assessment
The challenges of assessing teamwork competency, which internal structures can be multidimensional and complex. It is necessary to assess of the teamwork competency as unidimension...
What Do We Know About Teamwork in Chinese Hospitals? A Systematic Review
What Do We Know About Teamwork in Chinese Hospitals? A Systematic Review
Background and Objective: Improving quality of care is one of the primary goals in current Chinese hospital reforms. Teamwork can play an essential role. Characteristics of teamwor...
Semi-Supervised Word Sense Disambiguation via Context Weighting
Semi-Supervised Word Sense Disambiguation via Context Weighting
Word sense disambiguation as a central research topic in natural language processing can promote the development of many applications such as information retrieval, speech synthesi...
Teamwork Cognitive Diagnostic Modeling
Teamwork Cognitive Diagnostic Modeling
Teamwork involves the collaboration of individuals to achieve shared goals that surpass individual capabilities. As a team-level construct, team cognition underpins effective teamw...

