Design and Understand Networked Knowledge Construction through Building Real Time Assessments for Learning

Project Summary:
With diverse Internet technologies, networked learning allows individuals or groups of learners to develop connections, form communities, and construct knowledge through interactive experiences (Judy et al., 2018). Learners, as well as the networked community, construct meanings and knowledge through networked interactions such as collaboration, argumentation, negotiation, socialization, and sharing resources (Natriello, 2015; Dennen et al., 2021). Therefore, it is important to understand how various interactions facilitate the development of individual and shared knowledge. Methodological development in quantitative ethnography has demonstrated promising results in how knowledge is constructed in various learning settings (e.g., Csanadi et al., 2018; Zhang et al., 2022). In this project, we will further explore how to design and understand networked knowledge construction through developing real-time assessment tools for learning with the combination of human intelligence (e.g., networked learning theories) and machine intelligence (e.g., NLP technologies).

Deliverables:
Learning context design prototypes, measurement model, essays

Preferred discipline(s):
Learning design or game design and data science or applied statistics

Project Essential Skills:
Learning design, natural language processing

Other Selection Criteria (if any):
collaboration skills and communication skills

Details of supervision arrangements:
Lab work is not required but will involve facilitating data collection. Regular progress meetings will happen primarily physically.