Search for: All records

This study explored the Idea Wall, a collaborative knowledge-building tool to support students’ collaboration in small groups during a plant biology science curriculum. We examined the affordances and challenges of the Idea Wall and found the effective use of the tool's spatial organization capabilities by students, particularly the Yup Zone and the intermediary neutral spaces, for collaboratively organizing notes. But there's also a need for improvements in some features of the tool’s design and instructional guidance. 

This study investigates small group collaborative learning with a technologysupported environment. We aim to reveal key aspects of collaborative learning by examining variations in interaction, the influence of small group collaboration on science knowledge integration, and the implications for individual knowledge mastery. Results underscore the importance of high-quality science discourse and user-friendly tools. The study also highlights that group-level negotiations may not always affect individual understanding. Overall, this research offers insights into the complexities of collaboration and its impact on science learning. 

TalkMoves is an AI assistive tool that provides automated feedback to educators to support their daily teaching practices. While originally designed for classroom math teachers, this tool can be useful in a broader context. The University of Colorado Boulder and Saga Education formed a co-design team tasked with re-contextualizing TalkMoves for coaches of novice math tutors to use in their ongoing professional development. To effectively adapt an existing technology to a new problem space, the co-design team iteratively exchanged ideas of what exactly TalkMoves could achieve, as well as the specific needs of the coaches. Facilitators used strategies such as communal orientation, expansive dreaming, backcasting, and revoicing to promote productive collaboration. Three main goals emerged: maximize opportunities for user agency, center design around goal setting, and integrate the tool into the existing workflow. Any adaptation of an AI tool would benefit from this approach. 

TalkMoves is an AI assistive tool that provides automated feedback to educators to support their daily teaching practices. While originally designed for classroom math teachers, this tool can be useful in a broader context. The University of Colorado Boulder and Saga Education formed a co-design team tasked with re-contextualizing TalkMoves for coaches of novice math tutors to use in their ongoing professional development. To effectively adapt an existing technology to a new problem space, the co-design team iteratively exchanged ideas of what exactly TalkMoves could achieve, as well as the specific needs of the coaches. Facilitators used strategies such as communal orientation, expansive dreaming, backcasting, and revoicing to promote productive collaboration. Three main goals emerged: maximize opportunities for user agency, center design around goal setting, and integrate the tool into the existing workflow. Any adaptation of an AI tool would benefit from this approach. 

This research applies the Epistemic Network Analysis (ENA) method to analyze 11 families’ science talk as they engaged with mobile augmented reality (AR) to learn about cave formation. Results show that the design features in the Cave Explorers mobile AR app triggered four types of families’ science talk. Families with high pre-post gain knowledge scores of the app content engaged in more frequent and detailed describing and identification talk styles when encountering the science content and the place-based observation prompts. Children in these families read more science content aloud and used it to make sense of their observations in the cave exhibit by making explanations and inferences. 

TalkMoves is an AI assistive tool that provides automated feedback to educators to support their daily teaching practices. While originally designed for classroom math teachers, this tool can be useful in a broader context. The University of Colorado Boulder and Saga Education formed a co-design team tasked with re-contextualizing TalkMoves for coaches of novice math tutors to use in their ongoing professional development. To effectively adapt an existing technology to a new problem space, the co-design team iteratively exchanged ideas of what exactly TalkMoves could achieve, as well as the specific needs of the coaches. Facilitators used strategies such as communal orientation, expansive dreaming, backcasting, and revoicing to promote productive collaboration. Three main goals emerged: maximize opportunities for user agency, center design around goal setting, and integrate the tool into the existing workflow. Any adaptation of an AI tool would benefit from this approach. 

In collaborative problem-solving (CPS), students work together to solve problems using their collective knowledge and social interactions to understand the problem and progress towards a solution. This study focuses on how students engage in CPS while working in pairs in a STEM+C (Science, Technology, Engineering, Mathematics, and Computing) environment that involves open-ended computational modeling tasks. Specifically, we study how groups with different prior knowledge in physics and computing concepts differ in their information pooling and consensus-building behaviors. In addition, we examine how these differences impact the development of their shared understanding and learning. Our study consisted of a high school kinematics curriculum with 1D and 2D modeling tasks. Using an exploratory approach, we performed in-depth case studies to analyze the behaviors of groups with different prior knowledge distributions across these tasks. We identify effective information pooling and consensus-building behaviors in addition to difficulties students faced when developing a shared understanding of physics and computing concepts.