Collaborative Problem-solving Process Research Articles

Understanding student teachers’ collaborative problem solving: Insights from an epistemic network analysis (ENA)

Collaborative problem solving, as a key competency in the 21st century, includes both social and cognitive processes with interactive, interdependent, and periodic characteristics, so it is difficult to analyze collaborative problem solving by traditional coding and counting methods. There is a need for a new analysis approach that can capture the temporal and dynamic process of collaborative problem solving in diversity online collaborative learning context to provide some insights into online collaborative learning design. During an eight-week semester, a total of 42 student teachers participated in two online collaborative learning activities. Student teachers' discourse data were collected, and the data were coded based on a collaborative problem solving assessment model. This study used Epistemic Network Analysis (ENA) to explore the collaborative problem solving processes of student teachers in different online collaborative learning tasks. The results showed that both the high and low academic performance groups worked to maintain positive communication, but the students in the high academic performance groups negotiated on ideas while the students in the low academic performance groups focused on sharing resources/ideas. Moreover, fine-grained centroid analysis on a weekly basis showed that the high academic performance groups began by maintaining positive communication, and ended by negotiating ideas, while the low academic performance groups began by sharing resources/ideas and ended by regulating problem solving activities. Finally, the implications, limitations, and future research were discussed.

\u201cAnything taking shape?\u201d Capturing various layers of small group collaborative problem solving in an experiential geometry course in initial teacher education

Collaborative problem solving (CPS) is widely recognized as a prominent 21st-century skill to be mastered. Until recently, research on CPS has often focused on problem solution by the individual; the interest in investigating how the theorized problem-solving constructs function as broader social units, such as pairs or small groups, is relatively recent. Capturing the complexity of CPS processes in group-level interaction is challenging. Therefore, a method of analysis capturing various layers of CPS was developed that aimed for a deeper understanding of CPS as a small-group enactment. In the study, small groups of teacher education students worked on two variations of open-ended CPS tasks—a technology-enhanced task and a task using physical objects. The method, relying on video data, encompassed triangulation of analysis methods and combined the following: (a) directed content analysis of the actualized CPS in groups, (b) process analysis and visualizations, and (c) qualitative cases. Content analysis did not show a large variation in how CPS was actualized in the groups or tasks for either case, whereas process analysis revealed both group- and task-related differences in accordance with the interchange of CPS elements. The qualitative cases exemplified the interaction diversity in the quality of coordination and students’ equal participation in groups. It was concluded that combining different methods gives access to various layers of CPS; moreover, it can contribute to a deeper articulation of the CPS as a group-level construct, providing divergent ways to understand CPS in this context.

IVisit-Collaborate: Collaborative problem-solving in multiuser 360-degree panoramic site visits

Collaborative problem-solving skills are required from learners in the 21st century, particularly in construction graduates upon entering the workforce. However, challenges associated with spatiotemporal contexts of construction sites and resource limitations of educational programs reduce the opportunities available for students to practice these skills. This study focuses on using 360-degree panoramic virtual environments enhanced with virtual humans to produce realistic site visits for practicing collaborative problem-solving opportunities (iVisit-Collaborate). The goal of this phenomenological research study is to understand the collaborative problem-solving process of student dyads within iVisit-Collaborate. The findings suggest that student collaborative behaviors did not directly result in successful problem-solving. A hierarchical relationship between student problem-solving and collaborative behaviors was observed, indicating that problem-solving behaviors must take place to enable the occurrence of collaborative behaviors. Moreover, it was also observed that instructor scaffolding helped reduce the degrees of freedom in complex problem-solving activities. Finally, it was observed that student discussion engagement supported the creation and maintenance of shared mental models.

Development of Group Cognition in Online Collaborative Problem-Solving Processes

Group cognition is a cognitive science concept that studies how groups think, learn, and work. Most research investigates group cognition as a qualitative-oriented phenomenon. From a quantitative perspective, this research proposes a measure equation of group cognition, conducts empirical research during online collaborative problem-solving, and uses multiple quantitative methods to examine group cognition complemented with qualitative microanalysis. Specifically, social network analysis, behavioral pattern analysis, and quantitative content analysis are used to measure three groups’ group cognition. Results show that only one group successfully develops group cognition through synergistic coordination of social, behavioral, and cognitive activities. Students in the other two groups either take separate responsibilities to cooperate or have unequal participations, which indicates an inadequacy of group cognition. The extent that three groups develop group cognition is consistent with the order of groups’ final performance scores. Research analytical and pedagogical implications are provided to advance research and practice of group cognition.

Exploring the effect of three scaffoldings on the collaborative problem-solving processes in China\u2019s higher education

Collaborative problem-solving (CPS) engages students in solving ill-structured problems, creating group knowledge, and developing self-regulation and collaboration skills. Different scaffoldings, such as minimal-guided, task-oriented, and idea-oriented, can be used to facilitate students’ CPS activities, but their effects have not been comprehensively explored. In this research, we use minimally-guided, task-oriented, and idea-oriented scaffoldings to promote Chinese university students’ online CPS activities and use a multi-method approach to analyze the effects of three scaffolding on collaboration. The results indicate relatively complicated collaborative processes and outcomes supported by three scaffoldings. It is initially shown that the idea-centered scaffolding strengthens students’ connections between idea contribution, metacognitive regulation, and knowledge artifact behaviors, which are critical factors for improving the CPS quality. Based on the empirical research results, we conclude that future instructional design should carefully consider the educational culture, time constraint, and student regulation to better facilitate CPS practices.

Examining Student Regulation of Collaborative, Computational, Problem-Solving Processes in Open-Ended Learning Environments

The integration of computational modelling in science classrooms provides a unique opportunity to promote key 21st century skills including computational thinking (CT) and collaboration. The open-ended, problem-solving nature of the task requires groups to grapple with the combination of two domains (science and computing) as they collaboratively construct computational models. While this approach has produced significant learning gains for students in both science and CT in K–12 settings, the collaborative learning processes students use, including learner regulation, are not well understood. In this paper, we present a systematic analysis framework that combines natural language processing (NLP) of collaborative dialogue, log file analyses of students’ model-building actions, and final model scores. This analysis is used to better understand students’ regulation of collaborative problem solving (CPS) processes over a series of computational modelling tasks of varying complexity. The results suggest that the computational modelling challenges afford opportunities for students to a) explore resource-intensive processes, such as trial and error, to more systematic processes, such as debugging model errors by leveraging data tools, and b) learn from each other using socially shared regulation (SSR) and productive collaboration. The use of such SSR processes correlated positively with their model-building scores. Our paper aims to advance our understanding of collaborative, computational modelling in K–12 science to better inform classroom applications.

Fantastic four! Problem-solving processes of a professional string quartet

The purpose of this study was to provide a rich multi-dimensional view of expert musical collaborative problem-solving processes. I analyzed the collaborative problem-solving process during three subsequent rehearsals by a professional string quartet, applying Roesler’s (2016) model of musical problem-solving components. As Roesler observed with shared problem solving during one-to-one instruction, problem-solving components were enacted by and distributed among members of the quartet in any combination. In addition, quartet members prompted problem-solving behavior from one another in a similar way that teachers prompted problem-solving behavior from students (Roesler, 2017). Leadership roles shifted fluidly among quartet members from moment to moment. Domain knowledge and musical context were a critical component of their decision-making process. Additional observed rehearsal strategies are outlined. Suggestions for future research and applications of these findings are discussed, including the learning of collaborative problem-solving skill through participation in small musical ensembles.

Collaborative Community Problem Solving: A Model and Recommendations to Support Community Practice

A comprehensive model for supporting community collaboration is proposed. The authors describe a model of community collaboration that consists of four components. First, the model is based on a community-centered approach. Second, the model consists of a formal decision making process. Third, collaboration as depicted in the model hinges on the performance of several roles related behaviors. Finally, actors in the collaborative community problem solving process comprise a system that must be skillfully managed. The potential of the approach described in this article to address limitations of current collaborative community problem solving processes as well as implications for community practice are discussed.

Multimodal modeling of collaborative problem-solving facets in triads

Collaborative problem-solving (CPS) is ubiquitous in everyday life, including work, family, leisure activities, etc. With collaborations increasingly occurring remotely, next-generation collaborative interfaces could enhance CPS processes and outcomes with dynamic interventions or by generating feedback for after-action reviews. Automatic modeling of CPS processes (called facets here) is a precursor to this goal. Accordingly, we build automated detectors of three critical CPS facets—construction of shared knowledge, negotiation and coordination, and maintaining team function—derived from a validated CPS framework. We used data of 32 triads who collaborated via a commercial videoconferencing software, to solve challenging problems in a visual programming task. We generated transcripts of 11,163 utterances using automatic speech recognition, which were then coded by trained humans for evidence of the three CPS facets. We used both standard and deep sequential learning classifiers to model the human-coded facets from linguistic, task context, facial expressions, and acoustic–prosodic features in a team-independent fashion. We found that models relying on nonverbal signals yielded above-chance accuracies (area under the receiver operating characteristic curve, AUROC) ranging from .53 to .83, with increases in model accuracy when language information was included (AUROCS from .72 to .86). There were no advantages of deep sequential learning methods over standard classifiers. Overall, Random Forest classifiers using language and task context features performed best, achieving AUROC scores of .86, .78, and .79 for construction of shared knowledge, negotiation/coordination, and maintaining team function, respectively. We discuss application of our work to real-time systems that assess CPS and intervene to improve CPS outcomes.

Expanding Transformative Agency: Learning Lab as a Social Change Intervention for Racial Equity in School Discipline

BackgroundIn the United States, students of color are more likely to receive disciplinary exclusion compared with their White peers. The racial disproportionality in exclusionary school discipline (e.g., office discipline referrals and suspension) marginalizes students from nondominant communities and further aggravates inequalities in academic, social, and behavioral outcomes. As a socially, historically, and geographically situated inequity issue, addressing racial disparities in disciplinary outcomes requires a transformative experiment in which local stakeholders can engage in situated problem identification and problem-solving efforts in response to their specific needs, goals, and local dynamics.Purpose of StudyThis study examined how Learning Lab, an inclusive, collaborative problem-solving process, created a collaborative problem-solving space wherein school stakeholders exercised their collective, transformative agency to bring about a qualitative transformation in the school discipline system at an urban middle school for the creation of culturally responsive and equity-oriented learning environments for all students.SettingThe research took place at Rogoff Middle School in Wisconsin, which has historically served students from urban, low-income families. The school community struggled with the overrepresentation of Black students in exclusionary school discipline.ParticipantsLearning Lab comprised 14 members. Three parents and 11 school staff— administrators, teachers, social workers, an after-school coordinator, and a parent/paraprofessional working in a special education classroom—participated in the Learning Lab.Research DesignThis study used the Learning Lab intervention, taking place at an urban middle school between November 2012 and May 2014, as an instrumental case to explore how the participatory, design-based intervention transformed a schoolwide behavioral support system. Data collected from 14 meetings include observations, ethnographic field notes, school disciplinary data, and photos. All meetings were video recorded and transcribed, then analyzed using a transformative agency framework.Findings/ResultsWith the aim of organizing inclusive problem-solving activities for shared, collaborative future-making learning experiences, the Learning Lab encouraged local stakeholders to exercise their collective, transformative agency in order to produce locally meaningful and emancipatory knowledge aimed at reshaping a dysfunctional, punitive system that historically has yielded racial injustice in school discipline.Conclusions/RecommendationsAs a community-driven, scaled-down design process, Learning Lab can be a powerful leadership tool for school leaders to unite school stakeholders by building authentic school–family–community partnerships and leveraging expertise, experiences, and ingenuity for the development of locally optimized solutions to inequity.

Examining Trajectories of Elementary Students’ Computational Thinking Development Through Collaborative Problem-Solving Process in a STEM-Integrated Robotics Program

Developing K-12 students’ computational thinking (CT) skills is essential. Building on the existing literature that has emphasized programming skill development, this study expands the focus to examine students’ use of underlying CT cognitive skills during collaborative problem-solving processes. A case study approach was employed to examine video data of 5th graders engaging in an integrated-STEM robotics curriculum. The findings reveal that students applied algorithmic thinking most frequently and prediction the least. They recorded most debugging behaviors initially in the problem-solving process, but after accumulating more experiences their uses of other CT skills, including algorithmic thinking, pattern recognition, and prediction, increased. Implications for developing young learners’ CT skills to solve real-world problems are discussed.

Exploring the role of off-task activity on students’ collaborative dynamics.

Off-task activity is ubiquitous in classrooms, yet little understood. Building on recent work that illustrates the utility of off-task activity to disrupt relations of power among students, this article explores the potential functions of off-task participation during collaborative mathematics problem-solving. We examined 56 instances of off-task participation across 12 collaborative problem-solving sessions in a fourth grade classroom during a collaborative inquiry unit on place value. Results show that the majority of instances functioned to support the collaborative problem-solving process. Further, off-task participation often succeeded in shifting collaborative dynamics after on-task bids to shift dynamics failed. Off-task activity seemed to introduce new storylines that served as discursive tools to navigate local social hierarchies. We close by situating an understanding of the resources that students bring into collaborative learning through off-task activity within conversations on inclusive pedagogies. (PsycINFO Database Record (c) 2020 APA, all rights reserved)

Exploring Factors that Influence Collaborative Problem Solving Awareness in Science Education

This study designed a science course following collaborative problem solving (CPS) processes, and examined the effect on students’ CPS awareness. The Limnic Eruption CPS course was implemented using a Moodle system in a tenth-grade class. Considering the complex and coordinated nature of CPS, in order to improve CPS skills, it is important to identify what are related with the development of all sub-skills of CPS. Thus this study aimed to determine potential factors that affect the use of CPS skills in students’ motivational and behavioral dimensions. Multiple data sources including learning tests, questionnaire feedback, and learning logs were collected and examined by learning analytics approach. The relationships between students’ CPS awareness with their learning motivation and learning behaviors were explored. The research findings indicated a significant positive correlation between CPS awareness and certain learning motivation factors and learning behavior factors. Considering the students’ individual differences in learning abilities, we also compared the results of high and low performance groups. As a result, low performers’ learning motivation and learning behaviors were correlated with the social domain of CPS awareness, while those of high performers were correlated with their cognitive awareness.

Understanding Collaborative Problem-Solving on the Move: A Design Science Research Journey

Abstract The emergence of globally distributed teams and the evolution of mobile technologies have increased the number of mobile knowledge workers (MKW). MKW are professionals who frequently work on the move, far from a fixed workplace, performing knowledge-intensive activities. MKW often work alone, which leads them to face constant challenges in their work practices and difficulties to get timely knowledge to solve their problems alone. Still, little is known about how the collaborative problem-solving is carried out in the MKW’s context. To address this gap, we adopted the Design Science Research (DSR) as a research method, and we applied activity theory (AT) and expansive learning as theoretical foundations to understand the MKW’s context. We created an artifact - a method implemented via a mobile app - to support collaborative problem-solving processes on the move, which allowed us to understand better how these processes occur, contributing not only to problems resolutions but also to organizational learning.

I Say, You Say, We Say

Collaborative problem solving (CPS) is a crucial 21st century skill; however, current technologies fall short of effectively supporting CPS processes, especially for remote, computer-enabled interactions. In order to develop next-generation computer-supported collaborative systems that enhance CPS processes and outcomes by monitoring and responding to the unfolding collaboration, we investigate automated detection of three critical CPS process ? construction of shared knowledge, negotiation/coordination, and maintaining team function ? derived from a validated CPS framework. Our data consists of 32 triads who were tasked with collaboratively solving a challenging visual computer programming task for 20 minutes using commercial videoconferencing software. We used automatic speech recognition to generate transcripts of 11,163 utterances, which trained humans coded for evidence of the above three CPS processes using a set of behavioral indicators. We aimed to automate the trained human-raters' codes in a team-independent fashion (current study) in order to provide automatic real-time or offline feedback (future work). We used Random Forest classifiers trained on the words themselves (bag of n-grams) or with word categories (e.g., emotions, thinking styles, social constructs) from the Linguistic Inquiry Word Count (LIWC) tool. Despite imperfect automatic speech recognition, the n-gram models achieved AUROC (area under the receiver operating characteristic curve) scores of .85, .77, and .77 for construction of shared knowledge, negotiation/coordination, and maintaining team function, respectively; these reflect 70%, 54%, and 54% improvements over chance. The LIWC-category models achieved similar scores of .82, .74, and .73 (64%, 48%, and 46% improvement over chance). Further, the LIWC model-derived scores predicted CPS outcomes more similar to human codes, demonstrating predictive validity. We discuss embedding our models in collaborative interfaces for assessment and dynamic intervention aimed at improving CPS outcomes.

Assessing individual contributions to Collaborative Problem Solving: A network analysis approach

Collaborative Problem Solving (CPS) is an interactive, interdependent, and temporal process. However, current methods for measuring the CPS processes of individuals, such as coding and counting, treat these processes as sets of isolated and independent events. In contrast, Epistemic Network Analysis (ENA) models how the contributions of a given individual relate to the contributions of others. This article examines the communications of air defense warfare teams from an experiment comparing two different computer-based decision support systems, using this data to ask whether ENA provides a more ecologically valid quantitative model of CPS than coding and counting. Qualitative analysis showed that commanders using one system asked questions to understand the tactical situation, while commanders using an experimental system focused more on actions in response to the tactical situation. Neither of the coding and counting approaches we tested corroborated these findings with statistically significant results. In contrast, ENA created models of the individual contributions of commanders that (a) showed statistical differences between commanders using the two systems to corroborate the qualitative analysis, and (b) revealed differences in individual performance. This suggests that ENA is a more powerful tool for CPS assessment than coding and counting approaches.

Advancing the Science of Collaborative Problem Solving

Collaborative problem solving (CPS) has been receiving increasing international attention because much of the complex work in the modern world is performed by teams. However, systematic education and training on CPS is lacking for those entering and participating in the workforce. In 2015, the Programme for International Student Assessment (PISA), a global test of educational progress, documented the low levels of proficiency in CPS. This result not only underscores a significant societal need but also presents an important opportunity for psychological scientists to develop, adopt, and implement theory and empirical research on CPS and to work with educators and policy experts to improve training in CPS. This article offers some directions for psychological science to participate in the growing attention to CPS throughout the world. First, it identifies the existing theoretical frameworks and empirical research that focus on CPS. Second, it provides examples of how recent technologies can automate analyses of CPS processes and assessments so that substantially larger data sets can be analyzed and so students can receive immediate feedback on their CPS performance. Third, it identifies some challenges, debates, and uncertainties in creating an infrastructure for research, education, and training in CPS. CPS education and assessment are expected to improve when supported by larger data sets and theoretical frameworks that are informed by psychological science. This will require interdisciplinary efforts that include expertise in psychological science, education, assessment, intelligent digital technologies, and policy.

Pair interactions in online assessments of collaborative problem solving: case-based portraits

This exploratory case study focuses on how pairs of students can build a shared understanding and acquire collaborative problem-solving (CPS) practices during an online assessment of CPS skills, which is seen in the context of the CPS construct, in a symmetrical and asymmetrical task type. Even though CPS is widely recognised as a core twenty-first-century competency, its nature is not yet well understood. Also, until recently, most of studies have focused on the individual’s solution to a problem or on the skills individuals bring into a problem-solving space. This study extends from an individual- to group-level focus in CPS, emphasising the role and quality of the social aspects in CPS processes and outcomes. Focusing on the group level because it mediates multiple levels of learning, including individual cognition and socio-cultural practices, may provide us with a better understanding of how pairs establish CPS practices. Because of the complexity of CPS and the general challenges of remote collaboration in an online context, the study relies on the triangulation of multiple data sources and phases of analysis. In this paper, the aim is to explore and visualise through contrasting case-based portraits of two pairs how micro-interaction processes evolve at the pair level. The results show that despite students’ similar CPS performance outcome scores and task designs aimed to facilitate collaboration, variations in micro-interactions occur across pairs, for example as individual and joint solution endeavours and as balanced and unbalanced dynamics of group interactions. Studying these patterns at the pair level may provide new insights into CPS and support strategies for acquiring these practices.

Different Types of Collaborative Problem-Solving Processes in an Online Environment: Solution Oriented Versus Problem Oriented

The purpose of this study was to investigate the types of problem-solving behaviors and their effects on solution quality in an online collaborative learning context. A total of 12 preservice teachers enrolled in a computer education course participated in the study. Students in pairs, randomly assigned by the instructor, carried out a problem-solving task and then changed partners for subsequent tasks. The problem-solving processes of 25 pairings of students were analyzed. Data on their problem-solving behaviors, the quality of their solutions, and their domain knowledge were collected. Results revealed that students who demonstrated more solution-oriented behaviors led others to better solutions while collaborating. In contrast, students who had difficulty in understanding problems demonstrated more problem-oriented behaviors. The solution-oriented students also gained better domain knowledge at the end, compared with the problem-oriented ones. The effects of the student’s interactions during the problem-solving process were discussed.

“Do You See What I Hear?”: Designing for Collocated Patient–Practitioner Collaboration in Audiological Consultations

Patient-centered care encourages active involvement of patients in their own treatment and a collaborative perspective on the relationship between patient and practitioner. However, to achieve constructive patient–practitioner collaboration in medical consultations the partakers need to successfully interact across conceptual boundaries that can impede intersubjectivity, i.e., the construction of shared meanings and understandings in communicative activities. We present a synthesis of a user-centered approach to designing interactive technology supporting collaboration in face-to-face consultations related to audiological (hearing) rehabilitation. Specifically, we focus on the case of hearing aid tuning, and on the design and utility assessment of a prototype sound environment simulator intended to support the process by helping the patient and the practitioner build a joint understanding of the individual patient’s hearing problem and perceived effects of treatment actions. We describe an empirical and qualitative investigation that calls specific attention to the multi-dimensional boundaries involved in collocated patient–practitioner interactions, and to the explorative and situated nature of the consultation as a collaborative problem-solving process. Here, various micro-practices play a key role in gradually forming a better understanding of the problem at hand and in identifying appropriate treatment steps. Our findings suggest that patient–practitioner collaboration can benefit from interactive technology, which is sufficiently flexible or open-ended in terms of use to accommodate, or be appropriated, to the immediate needs of the situation. We argue that designing technology with the aim of enhancing existing practices of intersubjectivity, rather than doing away with them, improves the chances of enriching collocated patient–practitioner interaction and reduces risk of obstructing it. The main research contribution is an increased understanding of the medical consultation as an instance of collocated collaborative work and learning, and the challenges and opportunities that lie in co-designing interactive solutions that can help the patient take an active and contributing part in the situation.