An official website of the United States government
Abstract Considering the criticality of post-simulation debriefings for skill development, more evidence is needed to establish how specific feedback design features might influence teams’ cognitive and metacognitive processing. The current research therefore investigates the effects of multisource feedback (MSF) and guided facilitation with video review, for both cognitive processing and reflective (meta-cognitive) behaviors during post-simulation debriefings. With a sample of 174 s-year dental students, randomly assigned to 20 teams, the authors conducted high-fidelity simulations of patient emergencies, followed by post-simulation debriefings, using a 2 × 2 factorial design to test the effects of MSF (present vs. absent) and guided facilitation with video review (present vs. absent). According to an ordered network analysis, designed to examine feedback processing levels (individual vs. team) and depth (high vs. low), as well as the presence of metacognitive reflective behaviors (evaluative behaviors, exploration of alternatives, decision-oriented behaviors), teams that received both MSF and guided facilitation demonstrated significantly deeper, team-level processing and more frequent evaluative behaviors. Teams that received only guided facilitation exhibited the highest rates of low-level, individual processing. However, facilitation also produced an additive effect that fostered reflection and a shift from individual- to team-oriented processing. In contrast, MSF alone produced the lowest levels of evaluative behaviors; without facilitation, it does not support team reflection. These results establish that combining MSF with guided facilitation and video review creates synergistic effects for team reflection. Even if MSF can highlight perceived performance discrepancies, teams need facilitation to interpret and learn collaboratively from the feedback.
more »
« less
This content will become publicly available on June 10, 2026
Using Epistemic Network Analysis and Sequential Pattern Mining to Explore the Impacts of Human Facilitation on Collaborative Mathematical Problem Solving
Learning algebra concepts, particularly those involving functions, is crucial yet challenging in mathematics education. Research suggests that collaborative learning, where students work in small teams to solve math problems, can support conceptual learning. However, collaborative problem solving (CPS) is complex and requires students’ social and cognitive skills for success. This study investigates the impacts of guided facilitation on supporting CPS in mathematics tasks during small-team collaboration. Using epistemic network analysis and sequential pattern mining, we analyzed chat logs from student teams and human facilitators and compared the interactions in facilitated and unfacilitated teams. Results indicated that near-peer facilitation effectively promoted constructive behaviors like multiple turns of social negotiation, while reducing inappropriate communications. Different facilitation strategies, such as encouraging students to respond to each other or clarify their statements, elicited targeted CPS behaviors, possibly leading to improved team performance. Findings have practical implications for facilitating CPS in mathematics classrooms.
more »
« less
- Award ID(s):
- 2101393
- PAR ID:
- 10609788
- Publisher / Repository:
- International Society of the Learning Sciences Repository
- Date Published:
- Page Range / eLocation ID:
- 3 to 11
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)This study explored seven engineering graduate students’ collaborative problem-solving (CPS) skills while working in interdisciplinary teams. Students worked in two different teams, in face-to-face and online environments, to solve complex manufacturing design challenges posed by their instructor. The students were assessed using an observational rubric with four dimensions: peer interactions, positive communication, tools and methods and iteration and adaption, and scored via each dimension’s associated attributes, and subsequently interviewed. Six students scored emergent or proficient in CPS and had slightly higher CPS scores during the second observation. One student demonstrated a limited ability for CPS and the observable CPS skills decreased during the project. Interviews revealed the importance of (1) relying on instructor and student chosen technologies for collaborative tasks, (2) recognising and drawing on peer expertise early in the project, (3) building trust during and outside of team meetings and (4) valuing off-site and online collaborative work. Findings advance the understanding of how graduate students working in interdisciplinary teams rely on particular features of collaboration to solve engineering design challenges, which may assist in developing future skills and fostering productive teamwork.more » « less
-
Clarke-Midura, J; Kollar, I; Gu, X; D’Angelo, C (Ed.)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.more » « less
-
Manufacturing engineers work in teams with a wide range of skills and credentials. Teamwork and collaborative problem solving (CPS) skills enable higher productivity and efficiency. However, these skills are largely absent from engineering education curricula and research in contexts involving multi-educational teams inclusive of technical college engineering students. We address this gap in research and practice through a qualitative case study exploring the contributions, experiences, and perspectives of technical college students working in multi-educational level teams to solve real-world engineering manufacturing problems. Data analyses resulted in six themes: (1) positive team culture, (2) valuing industry skills, (3) sharing responsibilities to iteratively make changes, (4) applying technical roles, (5) peer interactions, and (6) career preparation. Technical college students’ perceptions of challenges and successes are also discussed. Results imply that to effectively promote CPS and teamwork in similar contexts educators and industry leaders should consider the importance of (1) valuing students’/workers’ current professional identities while promoting productive conflict, (2) respecting differing team roles while encouraging skill development, and (3) fostering future career skills.more » « less
-
Ability to effectively work in teams is one of the desired outcomes of engineering and engineering technology programs. Unfortunately, working in teams is still challenging for many students. Rather than contributing to team projects, some students resort to social loafing. Social loafing tends to destroy both teamwork performance and individual learning, especially in solving ill-structured problems, such as design. Furthermore, a bad experience on a past team is a significant concern as it could generate negative feelings toward future team projects. Formation of collaborative teams is a critical first step in team-project-based design courses as team composition directly affects not only teamwork processes and outcomes, but also teamwork skills and experience. This NSF-IUSE sponsored project aims to enhance students’ teamwork experiences and teamwork learning through 1) understanding how to form better student design teams and 2) identifying exercises that will effectively improve team member collaboration. We do this by comparing student characteristics and design task characteristics with the quality of the design team outcome, and examining the resulting correlations. Student characteristics cover six categories: 1) background information, 2) work structure preferences, 3) personality, 4) ability, 5) motivation, and 6) attitude. Task characteristics and design team outcomes are characterized using the Creative Product Semantic Scale. In this article, we present correlations between student/team characteristics and design project outcome, and correlations between task characteristics and design project outcome for 2020-2021 senior design teams at two institutions. For both institutions, we will present correlations between individual student characteristics and team outcome. For one institution, we will also present correlation between team-level characteristics and team outcomes.more » « less
