Article

A Framework to Analyze Argumentative Knowledge Construction in Computer-Supported Collaborative Learning

January 2006
Computers & Education 46(1)

DOI:10.1016/j.compedu.2005.04.003

Authors:

Armin Weinberger

Saarland University

Frank Fischer

Ludwig-Maximilians-Universität in Munich

Computer-supported collaborative learning (CSCL) is often based on written argumentative discourse of learners, who discuss their perspectives on a problem with the goal to acquire knowledge. Lately, CSCL research focuses on the facilitation of specific processes of argumentative knowledge construction, e.g., with computer-supported collaboration scripts. In order to refine process-oriented instructional support, such as scripts, we need to measure the influence of scripts on specific processes of argumentative knowledge construction. In this article, we propose a multi-dimensional approach to analyze argumentative knowledge construction in CSCL from sampling and segmentation of the discourse corpora to the analysis of four process dimensions (participation, epistemic, argumentative, social mode).

Improving Students’ Argumentation Skills Using Dynamic Machine-Learning–Based Modeling

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Argumentation is an omnipresent rudiment of daily communication and thinking. The ability to form convincing arguments is not only fundamental to persuading an audience of novel ideas but also plays a major role in strategic decision making, negotiation, and constructive, civil discourse. However, humans often struggle to develop argumentation skills, owing to a lack of individual and instant feedback in their learning process, because providing feedback on the individual argumentation skills of learners is time-consuming and not scalable if conducted manually by educators. Grounding our research in social cognitive theory, we investigate whether dynamic technology-mediated argumentation modeling improves students’ argumentation skills in the short and long term. To do so, we built a dynamic machine-learning (ML)–based modeling system. The system provides learners with dynamic writing feedback opportunities based on logical argumentation errors irrespective of instructor, time, and location. We conducted three empirical studies to test whether dynamic modeling improves persuasive writing performance more so than the benchmarks of scripted argumentation modeling (H1) and adaptive support (H2). Moreover, we assess whether, compared with adaptive support, dynamic argumentation modeling leads to better persuasive writing performance on both complex and simple tasks (H3). Finally, we investigate whether dynamic modeling on repeated argumentation tasks (over three months) leads to better learning in comparison with static modeling and no modeling (H4). Our results show that dynamic behavioral modeling significantly improves learners’ objective argumentation skills across domains, outperforming established methods like scripted modeling, adaptive support, and static modeling. The results further indicate that, compared with adaptive support, the effect of the dynamic modeling approach holds across complex (large effect) and simple tasks (medium effect) and supports learners with lower and higher expertise alike. This work provides important empirical findings related to the effects of dynamic modeling and social cognitive theory that inform the design of writing and skill support systems for education. This paper demonstrates that social cognitive theory and dynamic modeling based on ML generalize outside of math and science domains to argumentative writing.

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Computer-mediated environments provide an arena for learning to argue. We investigate to what extent student dyads’ online argumentation can be facilitated with collaboration scripts that (1) prompt learners to prepare individually, (2) create conflict, and (3) encourage productive collaboration and argumentation. A process analysis of the chats of the dyads showed that the scripted treatment group used significantly more words and broadened and deepened their discussions significantly more than the unscripted group. Qualitative analysis indicates that scripted learners engaged in more critical and objective argumentation than non-scripted learners.

The role of individual preparation before collaboration: An exploratory study on students’ computer-supported collaborative argumentation in a primary classroom

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THE NATURE OF COLLABORATION IN GRADE 6 NATURAL SCIENCE AND TECHNOLOGY ROBOTICS AND CODING LEARNER GROUP PROJECTS

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Sep 2024

Patrick Thabo Makhubalo

Advances in technologies in the Fourth Industrial Revolution have seen schools include robotics and coding in the existing curricula, requiring teachers to reconsider their teaching and learning methodologies for incorporating new information into existing curricula. Collaborative Learning, as one of these strategies, require learners to work together, using the resources made available to jointly solve problems. Using unfamiliar technology in Collaborative Learning activities such as robotics, adds complexity to learners' learning in smaller groups. The aim of the study was to determine the nature of collaboration in Grade 6 Natural Science and Technology group projects that include robotics technologies. This study is informed by the Computer-Supportive Collaborative Learning as a conceptual framework, where learners can interact and engage in smaller groups using technology such as robotics as mediating tools. Following a qualitative research design, 40 leaners participated in groups of 5 to complete collaborative project-based learning tasks. Each of these sessions were observed and video recorded. Seven teachers were purposively sampled from four participating schools and participated in semi-structured interviews to capture their observations of learner collaboration in Natural Science and Technology Gr 6 classes. Findings indicate that collaboration was typified by high energy, where learners use physical gestures and freely show their emotions when working on projects-based tasks. Learners engaged effectively in verbal interactions as they brainstorm ideas to raise innovative ideas while engaging in active discussions. They remained focused and are more willing to share ideas to support those that were struggling. A clear division of labour emerged early in the task with a team leader that naturally assumed responsibility for keeping the task on track. As such, this study underscores the importance of incorporating robotics technology into learners' group projects to increase their understanding of subject knowledge and allow opportunities to develop 21st-century skills. Keywords: Collaborative learning, project-based learning, 21st Century skills, robotics and coding, robotics kit

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In this study we focus on the collaborative processes developed within an asynchronous small group activity carried out through an instant messaging platform. To investigate the ways students communicate and collaborate during the asynchronous activity, we refer to the theoretical lenses provided by the dimensions introduced by Weinberger and Fischer (2006) to study the processes realised within computer-supported collaborative learning environments. In particular, we develop a combined analysis that takes into account both the quantity of students' interventions and their social modes of co-construction. This analysis has revealed two main macro-categories of collaborative processes activated by the groups of students who participated in the study, which mainly differ in the level of sharing and comparison within the groups and in the aim that guided their work.

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In the past decade, Computational Thinking (CT) education has received growing attention from researchers. Although many reviews have provided synthesized information on CT teaching and learning, few have paid particular attention to collaborative learning (CL) strategies. CL has been widely implemented in CT classes and has become the most popular pedagogy among educators. Therefore, a systematic review of CL in CT classes would provide practical guidance on teaching strategies to enhance CT interventions and improve the quality of teaching and learning, ultimately benefiting students’ CT skills development. To address this gap, this study examined 43 empirical studies that have applied CL strategies, ranging from 2006 to 2022. Several findings were revealed in the analysis. First, a wide range of theories and frameworks were applied to inform research questions, pedagogical design, and research methodologies. Second, despite the acknowledged importance of group composition in effective CL, a large number of studies did not provide details on how the students were grouped. Third, six types of CL activities and instructional designs have been identified in CT classrooms. The synthesized information provides valuable insights that can inform future research directions and guide the design and implementation of CL activities in future CT classes.

Improving argumentation quality on MOOC discussion forums: does learning to identify components of arguments help?

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Constructive argumentation among learners is integral to effective learning. In the context of Massively Open Online Classes (MOOCs), such peer interactions can only occur in discussion forums, where they often prove to be sparse and of poor quality. To address these challenges, we developed and experimentally tested an intervention (nparticipants = 110, narguments = 270) aimed at improving the quality of learners’ written arguments in MOOC forums, taking into account MOOC platform constraints (e.g., self-paced participation and the impossibility of providing personalised feedback). In the first chapter of a management MOOC, participants randomly assigned to the experimental group (vs control) were introduced to the formal components of arguments: claims, justifications and qualifications. They were then asked to identify these components in a series of examples. We found no significant impact of this intervention on learners’ responses to individual open-ended questions directly following the intervention, or in their contributions to discussion forums. Instead, we observed variation in argument quality based on the specific questions prompting argumentation. Our findings prompt further discussion and exploration of strategies to enhance argumentation quality in MOOC discussion forums.

Collaborative Problem-Solving in Knowledge-Rich Domains: A Multi-Study Structural Equation Model

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Collaborative skills are crucial in knowledge-rich domains, such as medical diagnosing. The Collaborative Diagnostic Reasoning (CDR) model emphasizes the importance of high-quality collaborative diagnostic activities (CDAs; e.g., evidence elicitation and sharing), influenced by content and collaboration knowledge as well as more general social skills, to achieve accurate, justified, and efficient diagnostic outcomes (Radkowitsch et al., 2022). However, it has not yet been empirically tested, and the relationships between individual characteristics, CDAs, and diagnostic outcomes remain largely unexplored. The aim of this study was to test the CDR model by analyzing data from three studies in a simulation-based environment and to better understand the construct and the processes involved ( N = 504 intermediate medical students) using a structural equation model including indirect effects. We found various stable relationships between individual characteristics and CDAs, and between CDAs and diagnostic outcome, highlighting the multidimensional nature of CDR. While both content and collaboration knowledge were important for CDAs, none of the individual characteristics directly related to diagnostic outcome. The study suggests that CDAs are important factors in achieving successful diagnoses in collaborative contexts, particularly in simulation-based settings. CDAs are influenced by content and collaboration knowledge, highlighting the importance of understanding collaboration partners’ knowledge. We propose revising the CDR model by assigning higher priority to collaboration knowledge compared with social skills, and dividing the CDAs into information elicitation and sharing, with sharing being more transactive. Training should focus on the development of CDAs to improve CDR skills.

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Using learning analytics to explore peer learning patterns in asynchronous gamified environments

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This study explored the dynamics of students' knowledge co-construction in an asynchronous gamified environment in higher education, focusing on peer discussions in college business courses. Utilizing epistemic network analysis, sequence pattern mining, and automated coding, we analyzed the interactions of 1,319 business students. Our findings revealed that externalization and epistemic activity were prevalent, demonstrating a strong link between problem-solving and conceptual understanding. Three primary discussion types were observed: argumentative, epistemic, and social, each with unique patterns of engagement and idea integration. Effective knowledge co-construction patterns included open-ended questions with an epistemic focus, debates serving as intense knowledge co-construction arenas, and social interactions fostering a supportive and collaborative learning environment. The introduction of gamification elements led to increased student engagement and participation. Our findings emphasize the significance of structured analysis, collaboration, and argumentation in promoting effective knowledge co-construction in peer learning settings. This study offers insights into the temporal interplay of discourse dimensions and their potential for collaborative learning, enhancing our understanding of how learning analytics can be employed to discover ways in which students co-construct knowledge in asynchronous gamified environments.

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In Collaborative Diagnostic Reasoning (CDR), good diagnostic outcomes depend on high quality diagnostic activities influenced by social skills, content, and collaboration knowledge. Analyzing data from three studies on simulation-based learning (504 medical students) using a structural equation model, our results challenge the current CDR model. We suggest prioritizing collaboration knowledge over social skills, emphasize the reduced impact of content knowledge in simulations, and distinguish between information elicitation and sharing, with the latter being more transactive.

Intertwining students’ social modes of co-construction and epistemic aspects of algebraic thinking in asynchronous mathematical discussions

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Educ Stud Math

In this article, we present the asynchronous phases of digital mathematical discussions conducted along a didactic path on proof through the use of algebraic language with Grade 9 classes. We aim at characterising the digital environments where these discussions unfold (chat and Padlet) by examining students’ asynchronous interactions, through the framework of social modes of co-construction, and identifying the epistemic aspects of algebraic thinking, that is the activation and coordination of conceptual frames and anticipating thoughts. The results of this study provide insights into the relationship between students’ interactions and the development of collective algebraic thinking in asynchronous mathematical discussions.

Temporal equal and active participation in synchronous collaborative learning: Antecedents and effect for learning

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For teaching 21st century skills, collaborative learning has been increasingly adopted in educational programs nowadays. However, learners often fail to engage in effective collaboration, which severely deteriorates learning gains. To develop support tools for collaborative learning, participation is one of the promising aspects considering its effect on learning gains and its viability for real-time measurement in modern learning environments. This study quantitatively and qualitatively examined the relationship between temporal equal and active participation and learning gains in synchronous collaboration. Our data included 10 teams that collaboratively learn analogical thinking in university coursework. Our result demonstrated the positive relationship between temporal equal and active participation and team learning gains. Detailed observation revealed that equal and active participation often reflected joint information processing which in turn affected learning gains, although this relationship depends on the discussion contents. The effect could be direct, indirect or absent depending on discussion topics and other factors. Our comparative analysis also proposed three antecedents for equal and active participation; maintaining a shared understanding of what to discuss and why to discuss, critical comments for extending discussion, and arguing without completion. We lastly summarized our theoretical implications for equal and active participation and practical implications for supporting collaborative learning.

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Understanding students’ emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables in CSCL. This study introduces new learning analytic methods based on student-subtask bipartite networks to gauge two conceptual dimensions—quantity and heterogeneity of individual contribution to subtasks—for understanding students’ emerging roles in online collaborative learning in small groups. We analyzed these two dimensions and explored the changes of individual emerging roles within seven groups of high school students (N=21) in two consecutive collaborative learning projects. We found a significant association in the changes between assigned leadership roles and changes in the identified emerging roles between the two projects, echoing the importance of externally-facilitated regulation scaffolding in CSCL. We also collected qualitative data through a semi-structured interview to further validate the quantitative analysis results, which revealed that students’ perceptions of their emerging roles were consistent with the quantitative analysis results. This study contributes new learning analytic methods for collaboration analytics as well as a two-dimensional theoretical framework for understanding students’ emerging roles in small group CSCL.

Analyzing Students' Emerging Roles Based on Quantity and Heterogeneity of Individual Contributions in Small Group Online Collaborative Learning Using Bipartite Network Analysis

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Feb 2025

Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning analytic methods based on student -- subtask bipartite networks to gauge two conceptual dimensions -- quantity and heterogeneity of individual contribution to subtasks -- for understanding students' emerging roles in online collaborative learning in small groups. We analyzed these two dimensions and explored the changes of individual emerging roles within seven groups of high school students (

N = 21

) in two consecutive collaborative learning projects. We found a significant association in the changes between assigned leadership roles and changes in the identified emerging roles between the two projects, echoing the importance of externally facilitated regulation scaffolding in CSCL. We also collected qualitative data through a semi-structured interview to further validate the quantitative analysis results, which revealed that student perceptions of their emerging roles were consistent with the quantitative analysis results. This study contributes new learning analytic methods for collaboration analytics as well as a two-dimensional theoretical framework for understanding students' emerging roles in small group CSCL.

Argumentative Knowledge Construction and Certainty Navigation: A Comparison between Individual and Group Work

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This study investigated (the extent to which levels of certainty impacted the argumentative knowledge construction in individual work and group work. Argumentative knowledge construction has been characterized into simple claims, grounds, qualifiers, counterarguments, and integrated replies to illustrate the components of argumentation and nature of resolving conflicts in argumentation where certainty levels have been divided into uncertain, neutral, and certain. Findings showed that individual and group work differed significantly in terms of levels of certainty for simple arguments and counterarguments. Study implications were discussed.

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Combining collaboration spaces: Identifying patterns of tool use for decision-making in a networked learning environment

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This paper describes a study that examines the processes of two groups using a combined collaboration space (a synchronous chat and an asynchronous wiki). It uses data from the combined space to analyse the way that group processes change over time. We examine the tasks about which students made decisions during a month-long collaborative learning project, undertaken as part of a larger course. In order to examine the processes of collaboration, particularly in relation to the tools used and the decisions made, both chat and wiki data were coded for the task, sub-task and decision being made by the students. The data were rendered as visual forms which allowed us to describe the different ways in which the two groups used the tools in their collaboration for different types of decisions. We make an argument for the value in identifying Alexandrian properties in the structure of the collaboration, using deep interlock and ambiguity as an example. Identification of such properties, we think, will aid the future development of educational design patterns. Deep interlock and ambiguity was identified in the structure of the groups’ collaboration. We discuss the structure in terms of the tools that the groups used – chat, wiki and email. For some tasks and subtasks, the use of the tools was simple, and decisions were made during a single chat. However, some decisions resulted in a complex use of both the wiki and the chat, and Group A in particular used both tools synchronously, tying the ideas they discussed in the chat back to the knowledge recorded in the wiki, as they chatted. We concluded that the flexibility that the two groups were given meant that they could determine the pattern of tool use and collaboration that best supported their collaboration. We found the visualisations to be extremely useful in identifying the collaboration of a group over time, and in visualising the multiple streams of data that were analysed. The identification of these patterns of learning and collaboration would support the patterns approach to educational design. We propose that this initial study be expanded to include other measures of process.

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Investigating the Impact of a Collaborative Conversational Agent on Dialogue Productivity and Knowledge Acquisition

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While teachers can potentially guide single student-student dialogue, scaling personalized guidance across multiple groups is challenging. Collaborative Conversational Agents (CCAs) emerge as a viable solution, for example, by utilizing learning analytics to identify patterns in student dialogue to trigger interventions grounded in dialogic instructional theory. This study investigates the impact of a CCA, named “Clair,” in a collaborative inquiry learning environment. Building on prior work with Clair, we explored its impact on dialogue productivity and knowledge acquisition. Student pairs were assigned to interact either with Clair (treatment) or without Clair (control), while working in dyads in an inquiry-based digital learning environment on the digestive system. In the analysis of dialogue productivity, a sequential pattern mining technique was employed to measure the frequency of key goals targeted by Clair. Knowledge acquisition was measured through post-tests. Our findings revealed that Clair promoted key goals of dialogue productivity, including: sharing thoughts; orienting and listening to one another; and engaging with each other’s reasoning, but did not have an impact on deepening reasoning. No effect on knowledge acquisition was found. Correlation analysis showed that engaging with each other’s reasoning was related to students’ post‑test scores, but exclusively in the control condition. This may imply that dialogue productivity gains from interacting with Clair did not directly transfer to knowledge acquisition as measured in the post‑test. Following these outcomes, we indicate possible paths for future work to contribute towards a more comprehensive impact of CCAs on dialogue productivity and knowledge acquisition in collaborative learning environments.

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INT J COMP-SUPP COLL

Computer-supported collaborative learning (CSCL) offers a modern setting for learners to engage in meaningful (meta)cognitive and socioemotional interactions. However, the task design, not technology alone, significantly shapes students’ learning interactions. This study investigates how a conceptual physics task and a hands-on robotics task promote collaborative knowledge construction (CKC) and group-level cognitive, as well as emotion–motivation, regulation among secondary school students. Utilizing video recordings of students’ collaborative interactions and process-oriented methods, we examined the occurrence and temporal interplay of these processes from the two tasks. Transmodal network analysis complemented by qualitative case examples revealed significant differences in the nature of CKC and regulation of learning during the tasks. Cognitive processes and strong interconnections between cognitive regulation and negotiation were more typical for the conceptual physics task. The hands-on robotics task featured more frequent, but shorter, sequences of initial CKC phases and emphasized socioemotional interactions for sustained positive collaboration. This study highlights task design’s importance in collaborative learning processes and provides insights for optimizing CSCL environments for effective collaboration.

From Individual Ideation to Group Knowledge Co-Construction: Comparison of High- and Low- performing Groups

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This study compares the high- and low-performing groups’ knowledge co- construction process in the context of computer-supported collaborative argumentation from epistemic, argument, and social perspectives. Product analysis, lag sequential analysis, Sankey diagram visualization, and social network analysis were used to analyze groups’ written argumentation artefacts, on-screen behaviors, and online interactions. Results show that the high-performing group students demonstrated a higher level of engagement and cognitive elaboration than the low-performing group. The high-performing group was more competent in integrating various argumentation elements than the low-performing group. And the students in the high-performing group tended to contribute equally to their group work. The implications of the findings in designing and implementing knowledge co-construction activities are discussed.

The role of individual preparation for knowledge construction in collaborative argumentation: An Epistemic Network Analysis

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Dec 2023

Through collaborative argumentation, students gain in-depth understanding of learning content when they build on one another’s knowledge. Although individual preparation (IP) is found to be effective to foster collaborative learning, the mechanism of how IP influence the knowledge construction behavior is underexplored. This study investigated how IP influenced secondary school students in relation to knowledge construction behavioral patterns when participating in online collaborative argumentation activities. 20 students participated in two computer-supported collaborative argumentation lessons with one group with IP, and the other group without. Screen video recordings of students constructing arguments in groups during two lessons were collected and analyzed. Epistemic Network Analysis was conducted to examine students’ knowledge construction behaviors in the two lessons with and without IP. The results show that there were significant impact on students’ knowledge construction characteristics between the two lessons. Students who did not go through the IP phase tended to exhibit behaviors related to ideas refinement more than the students who went through the IP phase. The implications of how to design and implement effective knowledge construction are discussed.

CSCL Discussion Support with Emphasizing Feature of Main Sentence

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In this paper the authors propose a method and a system to support CSCL discussion with use of a developed function to emphasize the main sentence of each utterance. Generally, CSCL discussion environment has a difficulty to read huge volume of many utterances. The authors propose a function to provide two parts of input text fields, one is for main sentence of conclusion of an utterance, the other is for details or justifications of the utterance. At the time of representation, the proposing system first shows a list of main sentences. When members want to see details of an utterance, he or she clicks a link attached to the target main sentence. With use of the proposed function, a member of CSCL discussion will become easy to grasp a big picture of a discussion. It is expected to provide deep understanding of discussion and prompt to write meaningful utterances on CSCL. In order to verify an effect of the proposing system, the authors conducted a controlled experiment. The result shows that members of a target group tend to use various types of utterance roles rather than ones of a control group. From this result, the proposing system is thought to provides a CSCL environment for deeper understanding of discussion and utterances.

Automating the Assessment of Collaborative Engagement Using Natural Language Processing

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This study explores the use of natural language processing to automate the evaluation of collaborative group engagement in collaborative learning settings. We evaluated two approaches involving large-language models (LLMs) and a set of interpretable linguistic markers to predict the four dimensions---behavioral, social, cognitive, and conceptual-to-consequential engagement---of the quality of collaborative group engagement (QCGE) model. Analyzing conversation transcripts from three-person student groups engaged in a computer-supported collaborative design task produced four major findings. First, natural language processing successfully predicted out-of-sample about 10\% of variance in collaborative engagement, suggesting that assessment can be automated. Second, interpretable linguistic markers explained more of this variance than did ratings from an intransparent LLM. Third, the best linguistic markers were not specifically related to any individual dimension of QCGE, suggesting a common core of collaborative engagement. Fourth, the QCGE's manual rating model was limited due to its lack of granularity and insensitivity to natural variability in engagement. Overall, our analysis demonstrates both how natural language processing approaches can be leveraged to successfully automate the assessment of collaborative engagement and how these approaches can reveal key insights into the drivers of collaborative engagement.

Argumentation Mining in User-Generated Web Discourse

Preprint

Jan 2016

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.

Analyzing first-semester chemistry students’ transactive talk and problem-solving activities in an intervention study through a quantitative coding manual

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Introduction During the COVID-19 pandemic, digital video conferencing formats temporarily became the new norm at universities. Due to social distancing, these environments were often the only way for students to work together. In the present study, we investigated how first-semester chemistry students dealt with new, challenging content, i.e., quantum theories of chemical bonding such as molecular orbital (MO) theory, in such an unfamiliar collaboration environment. Studies in the field of Computer-Supported Collaborative Learning (CSCL) suggest that small groups working on complex tasks are particularly effective when students actively build on the ideas and reasoning of their peers, i.e., when they engage in transactive talk and when they structure their work on a metacognitive level by following typical problem-solving patterns. Methods To operationalize these constructs, we developed a coding manual through quantitative content analysis, that we used to analyze a total of N = 77 students working together in 21 small groups on two consecutive tasks: the creation of glossaries and the construction of concept maps on MO theory. Our manual showed very good characteristics in terms of internal consistency and inter-coder reliability. Based on the data obtained, it was possible to not only describe the student’s transactive communication and problem-solving activities, but to correlate it with other variables such as knowledge development in MO theory, which allowed us to compare the two different collaborative phases as well as different treatment groups. Results and discussion Students showed a higher proportion of transactivity and problem-solving activities when constructing the concept maps than when creating glossaries. In terms of knowledge gains, a multiple linear regression analysis revealed that students in groups that derived consequences from their collaborative work showed greater improvements than students who did not, although the students’ prior knowledge remained the most influential factor. As for the different treatments, our data did not reveal any noticeable difference when students from a small group worked with either complementary or identical material before collaboration, neither in terms of transactive talk nor problem-solving patterns. All in all, we were able to develop and test a powerful tool to quantify transactive communication and problem-solving activities in a collaborative context.

Collaborative online learning in higher education—quality of digital interaction and associations with individual and group-related factors

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Collaborative online learning became a necessity for universities during the COVID-19 pandemic. Even though it is known from research that online collaboration is an effective way of learning, digital interaction can be challenging for learners. Group members have to create a high-quality interaction to ensure the success of the collaborative learning process. Based on a theoretical model of collaborative learning, high-quality interaction can be determined with regard to cognitive group activities (prior knowledge activation, transactivity), meta-cognitive group activities (organization of the work process), and relational group activities (group climate, participation and task-related communication). Our study aims to examine how students manage a self-directed collaborative learning setting, how they perceive the process quality of digital interaction and how the interaction quality is related to self-reported outcomes (learning gain and satisfaction). We use a newly developed questionnaire to assess the quality of digital interaction in terms of the aforementioned dimensions. Furthermore, we focus on associations with the beliefs about web-based learning and the ability of perspective-taking at the individual level as well as the sense of community at the group level. We conducted a quantitative study within online university courses that were implemented asynchronously due to the COVID-19 pandemic. N = 298 undergraduate students in teacher education rated the quality of a digital collaborative learning settings (response rate of 72%). The students worked on collaborative tasks autonomously without any guidance from the teacher. We find differences between (meta-)cognitive and relational factors of interaction quality, and differences in the strength of the associations with outcomes and individual and group-related factors. Our study provides insights into students´ collaborative online learning and examines the relationships between different dimensions of group interaction quality and the input and outcome variables. Limitations and areas for further research are discussed.

Exploring students' computer‐supported collaborative argumentation with socio‐scientific issues

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J COMPUT ASSIST LEAR

Background This study examined the effect of computer‐supported collaborative argumentation (CSCA) on secondary school students' understanding of socio‐scientific issues (SSI). Engaging students in collaborative argumentation is known to help with deepening their understanding of SSI. Methods In this study, a mixed‐method design is used to investigate 84 students' collaborative argumentation processes and outcomes. The statistical analysis, epistemic network analysis and qualitative uptake analysis results showed that CSCA was effective in supporting secondary school students' evidence‐based argumentation skills on SSI. Findings and Conclusion Several cases were presented to show how students engaged in CSCA to explore meaningful learning opportunities and how CSCA helped students' learning on SSI. Implications The findings provided insights for future innovative teaching and learning SSI in authentic classroom settings.

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Erfassung gruppenbezogener Lernprozesse – Validierung eines standardisierten Fragebogens für kooperative Lernsettings

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Full-text available

Aug 2024

Zusammenfassung: Im vorliegenden Beitrag wird ein standardisierter Fragebogen zur Erfassung kooperativer Lernprozesse in (Hoch-)Schulen präsentiert, der unter Bezugnahme auf bisherige Erkenntnisse gruppenbezogene Lernprozesse in der Selbsteinschätzung von Lernern multidimensional abbildet. Die Prozesse wurden im Hinblick auf kognitive, metakognitive und sozial-relationale Gruppenaktivitäten erfasst. Nach Pilotierungsstudien wurde der Fragebogen mit insgesamt 30 Items im Rahmen eines kooperativen Lernsettings in Universitätsseminaren eingesetzt. Die durchgeführte kooperative Lernphase wurde von den Studenten ( N = 333 in 114 Gruppen) entlang der genannten Dimensionen bewertet. Darüber hinaus wurden der Lerngewinn und die Zufriedenheit sowie die Fähigkeit zur Perspektivenübernahme in der Selbsteinschätzung erfasst. Die Ergebnisse der faktorenanalytischen Validierung zeigen, dass auf Individualebene zwischen den unterschiedlichen Dimensionen differenziert werden kann; auf Gruppenebene gelingt dies nur mit Einschränkungen. Dass Zusammenhänge mit der Perspektivenübernahme sowie dem Lernzuwachs und der Zufriedenheit aufgezeigt werden können, verweist auf die weitere Konstrukt- und Kriteriumsvalidität. Dennoch müssen bei der Interpretation einige Limitationen berücksichtigt werden.

Application of Prompt Learning Models in Identifying the Collaborative Problem Solving Skills in an Online Task

Preprint

Full-text available

Jul 2024

Collaborative problem solving (CPS) competence is considered one of the essential 21st-century skills. To facilitate the assessment and learning of CPS competence, researchers have proposed a series of frameworks to conceptualize CPS and explored ways to make sense of the complex processes involved in collaborative problem solving. However, encoding explicit behaviors into subskills within the frameworks of CPS skills is still a challenging task. Traditional studies have relied on manual coding to decipher behavioral data for CPS, but such coding methods can be very time-consuming and cannot support real-time analyses. Scholars have begun to explore approaches for constructing automatic coding models. Nevertheless, the existing models built using machine learning or deep learning techniques depend on a large amount of training data and have relatively low accuracy. To address these problems, this paper proposes a prompt-based learning pre-trained model. The model can achieve high performance even with limited training data. In this study, three experiments were conducted, and the results showed that our model not only produced the highest accuracy, macro F1 score, and kappa values on large training sets, but also performed the best on small training sets of the CPS behavioral data. The application of the proposed prompt-based learning pre-trained model contributes to the CPS skills coding task and can also be used for other CSCW coding tasks to replace manual coding.

IoT in Education: Using Open Data

Chapter

Jul 2024

https://link.springer.com/chapter/10.1007/978-3-031-63235-8_23

The Impact of Attribute Noise on the Automated Estimation of Collaboration Quality Using Multimodal Learning Analytics in Authentic Classrooms

Article

Full-text available

Jun 2024

Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the practical applicability and performance of these automated models in authentic settings remains largely anunder-researched area. In such settings, the quality of data features or attributes is often affected by noise, which is referred to as attribute noise. This paper undertakes a systematic exploration of the impact of attribute noise on the performance of different collaboration-quality estimation models. Moreover, we also perform a comparative analysis of different ML algorithms in terms of their capability of dealing with attribute noise. We employ four ML algorithms that have often been used for collaboration-quality estimation tasks due to their high performance: random forest, naive Bayes, decision tree, and AdaBoost. Our results show that random forest and decision tree outperformed other algorithms for collaboration-quality estimation tasks in the presence of attribute noise. The study contributes to the MMLA (and learning analytics (LA) in general) and CSCL fields by illustrating how attribute noise impacts collaboration-quality model performance and which ML algorithms seem to be more robust to noise and thus more likely to perform well in authentic settings. Our research outcomes offer guidance to fellow researchers and developers of (MM)LA systems employing AI techniques with multimodal data to model collaboration-related constructs in authentic classroom settings.

Semiempty collaborative concept mapping in history education: students’ engagement in historical reasoning and coconstruction

Article

Full-text available

May 2024
INSTR SCI

There is abundant research on the use of concept maps in education. However, the most notable efforts have focused on learning outcomes as a consequence of individually constructed concept mapping for science concept learning. In the less explored field of history, some studies have found positive effects of collaborative concept mapping. However, student interaction has not been analyzed. This study employed quantitative and qualitative methods based on classroom discourse analysis to examine the extent to which students engage in historical reasoning and transactive interaction when they collaboratively complete a semiempty concept map, versus when they collaboratively write a summary, about 19th-century Western imperialism. The participants were 20 secondary education students from two history classes with an average age of 16 years. Within each class, the students were randomly assigned to the different conditions: collaborative concept mapping and collaborative summary writing. Student interaction was analyzed at two different levels: the content level and modes of co-construction. The results show that the students in the semiempty concept mapping condition engaged significantly more in causal explanation and argumentation and used more historical and metahistorical concepts in their reasoning than the students in the summary writing condition. Interaction in the semiempty concept mapping condition included a much higher percentage of utterances which denoted the convergence and integration of the knowledge contributed by the partners in the dyad. This kind of transactive interaction not only reflected co-construction but also historical reasoning.

Scripted interventions versus reciprocal teaching in collaborative learning: A comparison of pedagogical and teachable agents using a cognitive architecture

Article

Apr 2025
LEARN INSTR

Dyads Composed of Members with High Prior Knowledge are Most Conducive to Digital Game-based Collaborative Learning

Article

Feb 2025
COMPUT EDUC

Exploring differences in learners' learning processes across collaborative knowledge construction tasks of diverse complexity: A multiple analysis

Article

Jun 2025
Think Skills Creativ

Automatic Detection of Negotiation in Collaborative Complex Problem Solving Interactions

Article

Dec 2023

When learners collaborate on complex problems and open-ended tasks, the mechanism of negotiation plays a crucial role in establishing a common understanding and achieving a shared goal among them. Research has shown that negotiation improves problem-solving processes, making it an essential skill to be developed among learners. In this study, we propose a method for automating the identification of negotiation in learners' discourse during collaboration. We leverage language models like BERT, RoBERTa, and GPT2 along with traditional machine learning models like logistic regression to detect utterances of negotiation in learners' discourse while they collaboratively solve engineering estimation problem in an Open-Ended Learning Environment (OELE) called Modeling Based Estimation Learning Environment (MEttLE). Our findings suggest that our approach can accurately identify negotiation utterances with a high accuracy of 0.924 and 0.781 kappa value with a relatively smaller training set. Our method is the first step in real-time detection of negotiation, thereby enabling educators to design scaffolds and environments to help learners engage in effective negotiations.

Argümantasyon Odaklı Sosyal Bilgiler Öğretiminin Öğrencilerin Eleştirel Düşünme ve İnformel Muhakeme Becerileri Üzerine Etkisi

Article

Nov 2024

Bu araştırmanın amacı Argümantasyon Odaklı Öğretim yönteminin öğrencilerin eleştirel düşünme ve informel muhakeme becerilerine etkisinin incelenmesidir. Bu amaç doğrultusunda araştırma, karma yöntem araştırma desenlerinden yakınsayan paralel karma yöntem deseni ile yürütülmüştür. Araştırmanın nitel boyutunda durum çalışması türlerinden “bütüncül çoklu durum deseni” ve nicel boyutunda ise yarı deneysel yöntem içerisinde yer alan “eşitlenmemiş kontrol gruplu desen” esas alınmıştır. Araştırmanın çalışma grubunu Ankara ilinde bulunan bir devlet ortaokulunun iki farklı şubesinde 2021-2022 eğitim-öğretim yılında öğrenimlerine devam eden 61 beşinci sınıf öğrencisi oluşturmaktadır. Bu kapsamda araştırma, argümantason odaklı öğretim yöntemine dayalı deney grubu (f=30) ve geleneksel öğretime dayalı kontrol grubu (f=31) ile gerçekleştirilmiştir. Araştırmada veri toplama araçları olarak Cornell Eleştirel Düşünme Becerisi Testi Düzey X (CEDTD-X) ve İkilem İçeren Senaryo kullanılmıştır. Araştırma sonunda elde edilen nicel verilerin analizinde Tek yönlü ANCOVA ve Nokta çift serili korelasyon tekniği; nitel verilen analizinde ise frekans, yüzde ve içerik analizi kullanılmıştır. Araştırmadan elde edilen bulgulara göre; deney grubu öğrencileri ile kontrol grubu öğrencilerinin eleştirel düşünme ön-test puanları kontrol altına alındığında son-test puanları açısından gruplar arasında anlamlı bir farklılık bulunduğu tespit edilmiştir. Bunun yanı sıra Argümantasyon Odaklı Öğretim yönteminin öğrencilerin informel muhakeme becerilerinin gelişimi üzerinde etkisi olduğu ve öğrencilerin eleştirel düşünme becerileri ile informel muhakeme seviyeleri arasında pozitif yönde anlamlı bir ilişki bulunduğu görülmüştür. Araştırmadan elde edilen bu bulgular doğrultusunda Argümantasyon Odaklı Öğretim yönteminin öğrencilerin eleştirel düşünme ve informel muhakeme becerilerinin gelişimine olumlu katkı sağladığı sonucuna ulaşılabilir.

Examining the Dynamics of Knowledge Convergence in Online Learning Context: A Network Perspective

Article

Dec 2024
COMPUT EDUC

Knowledge convergence, originating from computer-supported collaborative learning (CSCL), is often defined as building a shared cognitive understanding through social interactions. With an increasing focus on large-scale collaboration and online learning in CSCL, it is crucial to examine how knowledge convergence occurs in online settings. This study investigates how learners develop cognitive consensus in online discussions and assess how social interactions and learners’ role influence these dynamics in a MOOC using video-based social annotation. Mixed-methods, including Epistemic Network Analysis (ENA), Simulation Investigation for Empirical Network Analysis (SIENA), and role trajectory clustering were employed. The findings suggest that cognitive consensus in discussions originates from sharing similar experiences and evolves into more advanced levels over time. Reciprocity and transitivity are crucial for establishing network cohesion while achieving cognitive consensus. Learners with similar role trajectories tend to interact together. This study expands the traditional CSCL paradigm by examining how social interactions shape discussion network dynamics and how learners’ role trajectories influence these dynamics. We argue that network cohesiveness should be included in the framework of online knowledge convergence, alongside cognitive consensus. Dynamic network analysis is essential for understanding the complex mechanisms driving online knowledge convergence occurring, where the cognitive and social attributes of learning are interwoven.

Application of Prompt Learning Models in Identifying the Collaborative Problem Solving Skills in an Online Task

Article

Nov 2024

The effectiveness of Gen AI in assisting students’ knowledge construction in humanities and social sciences courses: learning behaviour analysis

Article

Oct 2024

Chapter 1. Plural conversations about argumentation: A bibliometric and corpus analysis

Chapter

Oct 2024

The volume aims to advance understanding of argumentative practices in different communicative contexts, with special regard for those with heightened public resonance: politics, media, and public debate in general. Furthermore, it intends to explore the linguistic aspects of argumentation, including both explicit codification, with the related issue of indicators, and the activation of implicit meanings. Bringing together different paradigms to account for the relations between contextual factors and discourse realizations, the contributions articulate around three foci, placing emphasis on one or more of them: the communicative purpose within a given genre or activity type; the argumentative and linguistic features of the investigated discourses, among which prototypical patterns, argumentative styles, and implicit meanings; the assessment of argumentation quality and strategies to cope with illegitimate practices.

Improving Student Online Interactions and Teacher’s Ability to Manage Them with the Quick Chat Moodle Plugin

Chapter

Sep 2024

Using Digital Concept Maps to Promote Argumentation Skills and Epistemological Beliefs Among Healthcare Management Students

Chapter

Aug 2024

Transforming traditional classroom activities into effective online learning experiences is a critical advancement in educational pedagogy. This chapter examines the application of constructivist pedagogy to problem-solving, specifically through the use of argumentation in distance learning contexts. It describes an undergraduate health system management course where a traditional face-to-face activity was replaced with an online argumentation-based learning exercise during the COVID-19 pandemic. The chapter explores the challenges and opportunities of this novel approach, incorporating digital concept mapping to enhance learning. The primary objective is to foster lifelong learning skills, such as higher-order thinking, critical thinking, and problem-solving abilities, among health management students.

Comparing the effectiveness of CSCL scripts for shared task perceptions in socially shared regulation of collaborative learning

Article

Aug 2024
INT J COMP-SUPP COLL

Towards a Human-in-the-Loop LLM Approach to Collaborative Discourse Analysis

Chapter

Jul 2024

IoT in Education: Using Open Data

Chapter

Jul 2024

An Attributional Theory of Achievement Motivation and Emotion

Article

Full-text available

Jan 1986

Bernard Weiner

In this chapter a theory of motivation and emotion developed from an attributional perspective is presented. Before undertaking this central task, it might be beneficial to review the progression of the book. In Chapter 1 it was suggested that causal attributions have been prevalent throughout history and in disparate cultures. Studies reviewed in Chapter 2 revealed a large number of causal ascriptions within motivational domains, and different ascriptions in disparate domains. Yet some attributions, particularly ability and effort in the achievement area, dominate causal thinking. To compare and contrast causes such as ability and effort, their common denominators or shared properties were identified. Three causal dimensions, examined in Chapter 3, are locus, stability, and controllability, with intentionality and globality as other possible causal properties. As documented in Chapter 4, the perceived stability of a cause influences the subjective probability of success following a previous success or failure; causes perceived as enduring increase the certainty that the prior outcome will be repeated in the future. And all the causal dimensions, as well as the outcome of an activity and specific causes, influence the emotions experienced after attainment or nonattainment of a goal. The affects linked to causal dimensions include pride (with locus), hopelessness and resignation (with stability), and anger, gratitude, guilt, pity, and shame (with controllability).

Computer-Mediated Argumentative Interactions for the Co-Elaboration of Scientific Notions

Article

Full-text available

Jan 2003

Michael James Baker

It is now well recognised that argumentative interactions can be vehicles of collaborative learning, especially on a conceptual plane (see e.g. Andriessen & Coiner, 1999). Information and communication technologies such as Computer-Supported Collaborative Learning (“CSCL”) environments can play an important role in such learning to the extent that they enable task sequences and interpersonal communication media to be structured in ways that favour the co-elaboration1 of knowledge (e.g. Baker, 1996, 1999; Baker, de Vries, Lund & Quignard, 2001).

Producing Equal-Status Interaction in the Heterogeneous Classroom

Article

Full-text available

Mar 1995

Emphasis on tracking and ability grouping as sources of inequality and as goals for reform ignores processes of stratification within heterogeneous classrooms. Research literature on effects of classroom status inequality is reviewed. The article presents a test of two interventions derived from expectation states theory and designed to counteract the process of stratification in classrooms using academically heterogeneous small groups. The design focuses on variation in the frequency with which teachers carried out status treatments in 13 elementary school classrooms, all of which were using the same curriculum and the same system of classroom management. There was good support for the hypotheses that the use of status treatments would be associated with higher rates of participation of low-status students and would have no effect on the participation of high-status students. Analysis at the classroom level revealed that more frequent use of these treatments was associated with more equal-status interaction.

The Tension Between Theories of Learning and Instruction in Mathematics Education

Article

Full-text available

Mar 1988

Paul Cobb

This article addresses the contradiction between the assumption that the goal of mathematics instruction is to transmit knowledge to students and the view that students construct mathematical knowledge by reorganizing their cognitive structures. Transmission and constructivist analyses of communication are contrasted. It is concluded that the task of accounting for successful instruction is not one of explaining how students take in and process information transmitted by the teacher. Instead, it is to explain how students actively construct knowledge in ways that satisfy constraints inherent in instruction. A brief case study is presented to support this contention, and general implications that take account of both cognitive and noncognitive instructional goals are discussed.

Two Wrongs May Make a Right ... If They Argue Together!

Article

Full-text available

Dec 2000

Several studies have investigated the cognitive development of interacting peers. This study focuses on a phenomenon that has not yet been studied: the cognitive gains of 2 children with low levels of competence who fail to solve a task individually but who improve when working in peer interaction. We show that this phenomenon (which we call the two-wrongs-make-a-right phenomenon) may occur when (a) the 2 wrongs disagree, (b) they have different strategies, and (c) active hypothesis testing is made possible. In a preliminary study, 30 Grade 10 low-achieving students were tested about the rules they use to compare 2 decimal fractions in a questionnaire. The students who were diagnosed as wrongs were invited to solve a task (the 6-cards task) with peers. Three kinds of pairs were formed: 7 W1-W2 pairs in which the 2 wrongs have different conceptual bugs; 4 W1-W1 pairs in which the 2 wrongs have the same conceptual bugs; 4 R-W pairs in which a wrong interacted with a right student. The 6-cards task was designed to create conflicts between students with different conceptual bugs and between wrong and right students. Two days after solving the 6-cards task, the students were asked to answer a similar questionnaire individually. The preliminary study revealed the two-wrongs-make-a-right phenomenon: Among the 7 W1-W2 pairs, at least 1 wrong became right. In contrast, in the 4 R-W pairs, only 1 wrong became right, and in the 3 W1-W1 pairs, no change was detected. In a case study that replicated the phases of the preliminary study, disagreement, argumentative operations (such as challenge and concession), hypothesis testing (with a calculator), and the internalization of social interactions mediated the change of peers from wrongs to rights. We then replicated the initial study with 72 low-achieving Grade 10 and 11 students, confirming the two-wrongs-make-a-right effect.

The Construction of Shared Knowledge in Collaborative Problem Solving

Article

Full-text available

Jan 1995

This paper focuses on the processes involved in collaboration using a microanalysis of one dyad’s work with a computer-based environment (the Envisioning Machine). The interaction between participants is analysed with respect to a ‘Joint Problem Space’, which comprises an emergent, socially-negotiated set of knowledge elements, such as goals, problem state descriptions and problem solving actions. Our analysis shows how this shared conceptual space is constructed through the external mediational framework of shared language, situation and activity. This approach has particular implications for understanding how the benefits of collaboration are realised and serves to clarify the possible roles of the computers in supporting collaborative learning.

INTERNAL AND EXTERNAL COOPERATION SCRIPTS IN WEB-BASED COLLABORATIVE INQUIRY LEARNING Effects on the acquisition of domain-specific and general knowledge

Article

Full-text available

Jan 2004

Cooperation scripts are a powerful means to improve collaborative learning. Scripts can be designed to support argumentative knowledge construction. However, not only externally induced cooperation scripts but also the learners' internal scripts on argumentative knowledge construction influence argumentative processes and what kind of knowledge is acquired during collaboration. In this study, 98 students (49 dyads) of two German secondary schools participated. We implemented two versions (high vs. low structured) of an external cooperation script directed towards supporting argumentative knowledge construction into a web-based collaborative inquiry learning environment. Further, we classified the learners' internal scripts as either high or low structured, thereby establishing a 2x2-factorial design. We investigated how external and internal scripts as well as their interaction influenced the acquisition of both domain-specific and general knowledge. Results suggest that learners' internal scripts are more important for acquiring domain-specific knowledge, whereas external scripts are more influential for the acquisition of general knowledge.

Narative Structure, Information Certainty, Emotional Content, and Gender as Factors in a Pseudo Jury Decision-Making Task

Article

Full-text available

Nov 2001

Argumentation was studied in a courtroom context in which the prosecuting attor- ney's summary is assumed to be an argument with "X is guilty" as the claim and the narrative, which contains the evidence of the case, providing support for the claim. In Experiment 1, quality of evidence, narrative coherence, and gender were studied. In Experiments 2A and 2B the role of uncertainty of narrative information, emo- tional expressions in the narrative, and gender were studied. Both crime-related and non-crime-related uncertain information produced lower guilt ratings and lower rat- ings of narrative goodness than the baseline, suggesting jury doubt occurs with any narrative uncertainty. Victim-related emotional expressions produced lower guilt ratings than the baseline, although these were mediated by the particular story read. Effects of defendant-related emotional expressions depended on gender and narra- tive contents. The gender results suggest men respond more heuristically, focusing primarily on evidence, whereas women process the narrative more comprehen- sively.

From practice fields to communities of practice

Conference Paper

Full-text available

Jan 2000

Knowledge Building as a Mediator of Conflict in Conceptual Change

Article

Full-text available

Mar 1997

This study examined how individuals and peers process scientific information that contradicts what they believe and assessed the contribution of this activity to conceptual change. Participants included 54 students in Grade 9 and 54 students in Grade 12, who were randomly assigned to four conditions: (a) individual conflict, (b) peer conflict, (c) individual assimilation, and (d) peer assimilation. Depending on the condition, students were asked to think aloud or discuss with their peers eight scientifically valid statements, which were presented in an order that either maximized or minimized the conflict between new information and existing beliefs. Pretest and posttest measures of prior knowledge and conceptual change were obtained, and student verbalizations were tape-recorded and coded for five levels of knowledge-processing activity. Two major approaches were identified from this analysis: direct assimilation, which involved fitting new information with what was already known, and knowledge building, which involved treating new information as something problematic that needed to be explained. A path analysis indicated that the level of knowledge-processing activity exerted a direct effect on conceptual change and that this activity mediated the effect of conflict. Knowledge building as a mediator of conflict in conceptual change helps to explicate previous equivocal research findings and highlights the importance of students' constructive activity in learning.

Dispensability of member effort and group motivation losses: Free-rider effects

Article

Full-text available

Jan 1983

Three experiments tested the hypothesis that group members exert less effort as the perceived dispensability of their efforts for group success increases. The resultant motivation losses were termed "free-rider effects." In Exp I, 189 undergraduates of high or low ability performed in 2-, 4-, or 8-person groups at tasks with additive, conjunctive, or disjunctive demands. As predicted, member ability had opposite effects on effort under disjunctive and conjunctive task demands. The failure to obtain a relationship between group size and member effort in Exp I was attributed to a procedural artifact eliminated in Exp II (73 Ss). As predicted, as groups performing conjunctive and disjunctive tasks increased in size, member motivation declined. This was not a social loafing effect; group members were fully identifiable at every group size. Exp III (108 Ss) explored the role that performance feedback plays in informing group members of the dispensability of their efforts and encouraging free riding. Results are generally consistent with those of Exps I and II. (24 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Real education in non-real time: The use of electronic message systems for instruction

Article

Full-text available

Jan 1983

Education in different communication media takes place with functional differences that have consequences for the course of instructional interaction. In this paper, we examine instructional interaction among people using a computer-based electronic message system, contrasting it with conventional face-to-face discussion in a college level class. Interaction via the non-real time message system contained multiple threads of discourse, a higher proportion of student turns to teacher turns, and other deviations from the initiation-response-evaluation sequences usually found in face-to-face classroom interactions. Based on the results of our contrast, we describe ways to organize instruction using electronic message systems to take advantage of new properties and to avoid shortcomings of these new instructional media.

Problem based learning: Cognitive and metacognitive processes during problem analysis

Article

Full-text available

Sep 1996

An important phase of problem-based learning in a tutorial group is problem analysis. This article describes a study investigating the ongoing cognitive and metacognitive processes during problem analysis, by analysing the verbal communication among group members, and their thinking processes. Thinking processes were tapped by means of a stimulated recall procedure. Verbatim transcripts of both the verbal interaction in the group and the recall protocols were analysed. The goal of this research is two-fold, i.e., to investigate whether PBL indeed leads to conceptual change and to develop a method that is sensitive to these phenomena. The results suggest that the verbal interaction in a group shows only the tip of the iceberg of the cognitive and metacognitive processes on which it is based. The verbal interaction in the small group discussion mainly concerned theory building, and to a lesser extent, data exploration and meta-reasoning. Stimulated recall of the thinking process during that discusion, however, provides more and unique information about hypothesis evaluation and meta-reasoning. In the protocols of stimulated recall, the process of conceptual change by students could be made visible. The ways of dealing with anomalous data could be described as well as the conditions that determine how students deal with anomalous data. These results suggest that the method was sensitive for detecting conceptual change during problem analysis.

From practice fields to communities of practice

Article

Jan 2000

Restructuring the Classroom: Conditions for Productive Small Groups

Article

Mar 1994

E.G. Cohen

Moving beyond the general question of effectiveness of small group learning, this conceptual review proposes conditions under which the use of small groups in classrooms can be productive. Included in the review is recent research that manipulates various features of cooperative learning as well as studies of the relationship of interaction in small groups to outcomes. The analysis develops propositions concerning the kinds of discourse that are productive of different types of learning as well as propositions concerning how desirable kinds of interaction may be fostered. Whereas limited exchange of information and explanation are adequate for routine learning in collaborative seatwork, more open exchange and elaborated discussion are necessary for conceptual learning with group tasks and ill-structured problems. Moreover, task instructions, student preparation, and the nature of the teacher role that are eminently suitable for supporting interaction in more routine learning tasks may result in unduly constraining the discussion in less structured tasks where the objective is conceptual learning. The research reviewed also suggests that it is necessary to treat problems of status within small groups engaged in group tasks with ill-structured problems. With a focus on task and interaction, the analysis attempts to move away from the debates about intrinsic and extrinsic rewards and goal and resource interdependence that have characterized research in cooperative learning.

Doctors begin to separate twins

Article

Jan 2003

M. Baker

Talking About Reasoning: How Important Is the Peer in Peer Collaboration?

Chapter

Jan 1997

Stephanie Teasley

Using data from two studies of scientific reasoning, this chapter explores whether transactive discussion is the basis of productive peer collaborations and questions what role the partner plays in the apparent effectiveness of this type of discussion. In the first study, dyads who engaged in transactive discussion showed more improvement than dyads who did not have transactive discussions. In the second study, both dyads and children working alone showed improvement related to talk in general. However, dyads produced more transactive types of talk and showed a more complex understanding of the problem that they generated more quickly. Having a partner was not a necessary or sufficient condition for producing transactive talk but increased likelihood that it would occur. The data from these studies suggest that the value of peer collaborations may be that the presence of a partner provides a natural context for elaborating one’s own reasoning.

The New Media: Communication, Research, and Technology.

Article

Sep 1986

The Psychology of Interpersonal Relations

Article

Jun 1959

Restructuring Classroom Interaction with Networked Computers: Effects on Quantity and Characteristics of Language Production

Article

Dec 1995

Richard G. Kern

This study describes the use of Daedalus InterChange, a local area computer network application, to facilitate communicative language use through synchronous, written classroom interaction. The study compares the quantity and characteristics of the discourse produced by two groups of second‐semester French students during an InterChange session and during an oral class discussion on the same topic. Students had over twice as many turns, produced two to four times more sentences, and used a much greater variety of discourse functions when working in InterChange than they did in their oral discussion. Furthermore, the distribution and direction of turns were radically different in the two conditions, with much more direct student‐to‐student exchange in the InterChange condition. Students' and instructors' responses to using InterChange were assessed: both groups responded favorably, although students more enthusiastically so than the instructors. Features of InterChange that may be unsettling for teachers include: decentering of teacher authority, lesser attention to grammatical accuracy, and less clear coherence and continuity of discussions.

Kategoriensystem für eine Multi-Ebenenanalyse der Prozesse der gemeinsamen Wissenskonstruktion [Coding system for a multi-level analysis of collaborative knowledge construction]

Book

Jan 2001

Grounding in Communication

Chapter

Jan 1991

Social-cognitive behaviors and higher-order thinking in educational computer environments

Article

Dec 1992
LEARN INSTR

We examined group differences in social-cognitive behaviors exhibited by 48 3rd graders in Logo or computer-based writing environments and the role of these behaviors in accounting for posttreatment differences in higher-order thinking. Logo children exhibited more work-related and off-task behavior, information seeking from partner and cognitively-based resolution of cognitive conflicts and less typing and social negotiation of cognitive conflict. Support was provided for the mediational role of information seeking, social negotiation of social conflict and especially cognitively-based resolution of cognitive conflict. Thus, Logo may foster cognitive growth by engendering cognitively-based resolution of cognitive conflicts.

Chapter 1: Individual and Social Aspects of Learning

Article

Jan 1998

The Potential of Argument in Knowledge Building

Article

Nov 2000

Selma Leitão

It is a matter of quasi-consensus among argumentation researchers that engaging in argumentation sets the scene for changes in people’s views. However, the actual process by which such changes occur has not yet been entirely understood. This article represents an effort towards understanding how processes of knowledge building and transformation evolve in argumentation. To achieve this goal, it outlines a unit of analysis designed to capture the process by means of which knowledge is continuously updated through argumentation. Then, the analysis of fragments of people’s argumentation illustrates how this unit of analysis can be utilized. It also provides an account of some of the ways in which reasoning is organized in face-to-face argumentation as well as in the speaker’s own discourse.

Problem-Solving Strategies and Group Processes in Small Groups Learning Computer Programming

Article

Jun 1986

This study investigated the planning and debugging strategies and group processes that predicted learning of computer programming in small groups. Thirty students aged 11 to 14 learned Beginners All-Purpose Symbolic Instructional Code (BASIC) in 2-person groups. Students showed little advance planning; their style of planning and debugging was opportunistic. Specific planning and debugging variables that predicted learning included high-level planning of chunks of the program, and low-level planning and debugging of single statements. Group interaction variables related to learning included giving and receiving explanations, receiving responses to questions, and verbalizing input aloud while typing at the keyboard. Student demographic characteristics, aptitudes, and cognitive style measures did not predict planning, debugging, or verbal interaction.

Commitment in Dialogue: Basic Concepts in Interpersonal Reasoning

Article

Jan 1995

Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning

Book

Jan 1995

Guiding Knowledge Construction in the Classroom: Effects of Teaching Children How to Question and How to Explain

Article

Jun 1994

Alison King

Following teacher-presented science lessons, pairs of fourth and fifth graders studied the material by asking and answering each others’ self-generated questions. In one condition students’ discussion was guided by questions designed to promote connections among ideas within a lesson. In a second condition discussion was guided by similar lesson-based questions as well as ones intended to access prior knowledge/experience and promote connections between the lesson and that knowledge. All students were trained to generate explanations (one manifestation of complex knowledge construction). Analysis of post-lesson knowledge maps and verbal interaction during study showed that students trained to ask both kinds of questions engaged in more complex knowledge construction than those trained in lesson-based questioning only and controls. These findings, together with performance on comprehension tests for material studied, support the conclusion that, although both kinds of questions induce complex knowledge construction, questions designed to access prior knowledge/experience are more effective in enhancing learning.

Construction of knowledge and group learning

Article

Jan 1993

Psychology Interpersonal Relations Pod

Article

Jan 1958

F. Heider

Arguing and Reasoning in Understanding Historical Topics

Article

Nov 1993

Social interaction provides a social support system, particularly for the acquisition of procedural knowledge. If learning is mainly a social process, what is learned is mainly a process of behaving. Innovative learning settings, called discussions, were used in this research to provide a cognitive apprenticeship in scholarly ways of arguing and reasoning. Children can learn to direct these discussions, a kind of collective discourse based on more general conversational skills that are already found in preschool settings, toward the scientific way of knowing when functional features of social interaction are mediated through a symbolic system of scientific tools. In this study, discursive data were analyzed, taken from six small group discussions by fourth graders about historical documents concerning Germanic people. The use of different procedures is identified within frames, which am characterized by a dominant cognitive-linguistic activity, and sequences as argumentative contexts in which epistemic actions are carried out. Epistemic operations linked to historical strategies are autonomously activated by the children, who are practicing historical thinking. These operations and strategies are built into an argumentative flow of reasoning that is governed by complex justification structures.

A glance behind the scenes: The state of the art in the study of argumentation

Article

Jan 2003

Frans H. van Eemeren

The Social Development of The Intellect

Article

Jan 1988

The Psychology Of Interpersonal Relation

Article

Jan 1958

Fritz Heider

• As the title suggests, this book examines the psychology of interpersonal relations. In the context of this book, the term "interpersonal relations" denotes relations between a few, usually between two, people. How one person thinks and feels about another person, how he perceives him and what he does to him, what he expects him to do or think, how he reacts to the actions of the other--these are some of the phenomena that will be treated. Our concern will be with "surface" matters, the events that occur in everyday life on a conscious level, rather than with the unconscious processes studied by psychoanalysis in "depth" psychology. These intuitively understood and "obvious" human relations can, as we shall see, be just as challenging and psychologically significant as the deeper and stranger phenomena. The discussion will center on the person as the basic unit to be investigated. That is to say, the two-person group and its properties as a superindividual unit will not be the focus of attention. Of course, in dealing with the person as a member of a dyad, he cannot be described as a lone subject in an impersonal environment, but must be represented as standing in relation to and interacting with another person. The chapter topics included in this book include: Perceiving the Other Person; The Other Person as Perceiver; The Naive Analysis of Action; Desire and Pleasure; Environmental Effects; Sentiment; Ought and Value; Request and Command; Benefit and Harm; and Reaction to the Lot of the Other Person. (PsycINFO Database Record (c) 2012 APA, all rights reserved) • As the title suggests, this book examines the psychology of interpersonal relations. In the context of this book, the term "interpersonal relations" denotes relations between a few, usually between two, people. How one person thinks and feels about another person, how he perceives him and what he does to him, what he expects him to do or think, how he reacts to the actions of the other--these are some of the phenomena that will be treated. Our concern will be with "surface" matters, the events that occur in everyday life on a conscious level, rather than with the unconscious processes studied by psychoanalysis in "depth" psychology. These intuitively understood and "obvious" human relations can, as we shall see, be just as challenging and psychologically significant as the deeper and stranger phenomena. The discussion will center on the person as the basic unit to be investigated. That is to say, the two-person group and its properties as a superindividual unit will not be the focus of attention. Of course, in dealing with the person as a member of a dyad, he cannot be described as a lone subject in an impersonal environment, but must be represented as standing in relation to and interacting with another person. The chapter topics included in this book include: Perceiving the Other Person; The Other Person as Perceiver; The Naive Analysis of Action; Desire and Pleasure; Environmental Effects; Sentiment; Ought and Value; Request and Command; Benefit and Harm; and Reaction to the Lot of the Other Person. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Teaching Students to Generate Questions: A Review of the Intervention Studies

Article

Jun 1996

This is a review of intervention studies in which students have been taught to generate questions as a means of improving their comprehension. Overall, teaching students the cognitive strategy of generating questions about the material they had read resulted in gains in comprehension, as measured by tests given at the end of the intervention. All tests were based on new material. The overall median effect size was 0.36 (64th percentile) when standardized tests were used and 0.86 (81st percentile) when experimenter-developed comprehension tests were used. The traditional skill-based instructional approach and the reciprocal teaching approach yielded similar results.

Pursuing Scientific Literacy in the Middle Grades Through Collaborative Problem Solving

Article

May 1993

This article describes an instructional program designed to promote scientific literacy among middle grade students. The instruction focuses on problems that provide a context in which students working in small collaborative groups can bring to bear their knowledge regarding kinetic molecular theory. In keeping with contemporary notions of scientific literacy, engagement in a problem-solving activity is supported through instruction and guidance in the use of scientific explanation and social norms conducive to constructive interaction. After describing several activities used to introduce students to the curriculum, we examine the processes and outcomes of problem solving in the context of planning ''dissolving races'' (a problem in which students were asked to determine the quickest as well as slowest way in which to dissolve sugar). Differences in the way that this problem was configured over 2 years are traced in terms of the role that explanation played in students' discourse, the interplay of scientific and everyday concepts, and opportunities to experience the activity of science.

The Skills of Argument

Book

Jul 1991

Deanna Kuhn

The Skills of Argument presents a comprehensive empirical study of informal reasoning as argument, involving subjects across the life span. Subjects ranging in age from adolescence to late adulthood were asked to describe their views on social problems that people have occasion to think and talk about in everyday life, such as crime and unemployment. In addition to providing supporting evidence for their theories, subjects were asked to contemplate alternative theories and counterarguments and to evaluate new evidence on the topics. This is the first major study of informal reasoning across the life span. Highlighting the importance of argumentive reasoning in everyday thought, the book offers a theoretical framework for conceptualizing and studying thinking as argument. The findings address issues of major importance to cognitive and developmental psychologists, as well as educators concerned with improving the quality of people's thinking. The work is also relevant to philosophers, political scientists, and linguists interested in informal reasoning and argumentive discourse.

Restructuring the Classroom: Conditions for Productive Small Groups

Article

Jan 1992

Elizabeth G. Cohen

This paper offers a synthesis of research on cooperative learning in small groups. The main challenge for teachers who utilize cooperative learning is to stimulate the type of interaction desired according to their teaching objective. A generalization regarding student interactions is that if students are not taught differently, they will tend to operate at the most concrete level. Student participation in a task group that is structured to foster resource- or goal-interdependence appears to increase student motivation and performance. The effectiveness of the group structure depends on the task's complexity and uncertainty and on the extent to which the instructions attempt to micromanage the interaction process. Information is also offered on ensuring equity in interaction, managing the interaction, and unsettled issues, such as special curricula and assessment. Successful implementation of cooperative learning also requires staff development and principals who demonstrate effective managerial skills and instructional leadership. (LMI)

Discourse Patterns and Collaborative Scientific Reasoning in Peer and Teacher-Guided Discussions

Article

Dec 1999
COGNITION INSTRUCT

In this study we examined the discourse components, interaction patterns, and reasoning complexity of 4 groups of 12 Grade 8 students in 2 science classrooms as they constructed mental models of the nature of matter, both on their own and with teacher guidance. Interactions within peer and teacher-guided small group discussions were videotaped and audiotaped, transcribed, and analyzed in a variety of ways. The key act of participants in both peer and teacher-guided groups was working with weak or incomplete ideas until they improved. How this was accomplished differed somewhat depending on the presence or absence of a teacher in the discussion. Teachers acted as a catalyst in discussions, prompting students to expand and clarify their thinking without providing direct information. Teacher-guided discussions were a more efficient means of attaining higher levels of reasoning and higher quality explanations, but peer discussions tended to be more generative and exploratory. Students' discourse was more varied within peer groups, and some peer groups attained higher levels of reasoning on their own. Ideas for using the results of these analyses to develop teachers' and students' collaborative scientific reasoning skills are presented.

Mind in society: The development of higher mental processes

Book

Jan 1978

Lev Semenovich. Vygotsky

Judging the Quality of Peer-Led Student Dialogues

Article

Jan 1993

This research investigates the rational quality of students' discussion of literary texts. An ideal model of dialogue contexts is presented and compared with 12 fourth-grader peer discussions of literature at 2 different periods during the course of 1 academic year. Six groups consisting of 3 students each were videotaped while they discussed a novel previously read aloud and discussed with their teacher in class. The collabora-tive reasoning capabilities of these students were analyzed using a graphical coding system coupled with an analysis of the literary content of the students' argumentation. The 2 analyses were matched with the dialogue contexts and used to identify some im-portant features that foster productive dialogue in children's discussions of literature. There has been much recent emphasis on the role that classroom discourse can have in fostering students' cognitive development. Talk, many researchers now believe, constitutes the most important means by which children are induced into a cul-ture—an induction that occurs at first on an interpsychological and only second on an intrapsychological level (Vygotsky, 1978; Wertsch, 1985). A number of cogni-tive researchers have applied this theoretical insight to the analysis of instructional dialogues and classroom interactions (Brown et al.. An often repeated claim is that it is only by exposure to collaborative or conversational dialogue that stu-dents learn to think critically and independently about important issues and con-COGNITION AND INSTRUCTION, 18(1), 53–81 Copyright © 2000, Lawrence Erlbaum Associates, Inc.

Promoting reflective interactions in a CSCL environment

Article

Sep 1997
J COMPUT ASSIST LEAR

Engaging in reflective activities in interaction, such as explaining, justifying and evaluating problem solutions, has been shown to be potentially productive for learning. This paper addresses the problem of how these activities may be promoted in the context of computer-mediated communication during a modelling task in physics. The design principles of two different communication interfaces are presented. The first allows free text to be exchanged, and the second structures the interaction by providing a restricted set of communicative possibilities. Comparative analyses of interaction corpora produced with the two communication interfaces are then described. The analyses show that use of the second structured interface in performing the problem-solving task is feasible for students, and that it promotes a task-focussed and reflective interaction. In conclusion the different resources provided by different media and the relative degrees of effort that their use requires are discussed.

Learning of argumentation skills in networked and face-to-face environments

Article

Jan 2001

In a teaching experiment 16 face-to-face and 11 e-mailFinnish university students studied academic debatingin an argumentation course. The 19 students of thecontrol group did not engage in the course. The courseinvolved two lectures, exercises with argumentativetexts, and face-to-face or e-mail seminar discussionsbased on these texts. Free debate, role play,problem-solving and panel discussion were the devicesused in organizing the course. The level of thestudents' argumentation skills were measured in apretest before the course and in a post-test after it.The results were compared between and within thegroups. The results indicated that during the e-mailstudies the students learned to identify and chooserelevant grounds, while the face-to-face studentsimproved in putting forward counterargumentation. Thecontrol group did not improve in these skills. Thestudy suggests that argumentation skills can bepromoted by short-term e-mail and face-to-faceteaching, and that practising argumentation indifferent learning environments develops differentkinds of argumentation skills.

The Uses of Argument

Chapter

Jan 2000

Stephen Toulmin

Scripting argumentation in computer-supported learning environments

Chapter

Jan 2004

Group Decision Making and Technology

Article

Feb 1992
ORGAN BEHAV HUM DEC

Advances in computing and telecommunications technology are changing how people can meet and make group decisions. Technological changes help people cross physical, social, and psychological boundaries, and have secondary effects on group behavior and decision making. Experiments show that, compared with a face-to-face meeting, a computer-mediated discussion leads to delays; more explicit and outspoken advocacy; “flaming;” more equal participation among group members; and more extreme, unconventional, or risky decisions. Technological and social psychological variables that cause these effects in laboratory groups do not scale at equal rates. Technological change in organizational group decision making can lead to outcomes not seen in the laboratory, which makes it essential to do field research. Three phenomena observed in field studies are redistributions of work time, relative advantages in participation for peripheral workers, and increases in complexity of group organization. Experimental and field studies on these technology effects are useful not just as an “impact statement” for those considering technological change; this research also can put a new light on basic processes in which we have always had an interest.

Epistemic cooperation scripts in online learning environments: Fostering learning by reducing uncertainty in discourse?

Article

Jul 2005
COMPUT HUM BEHAV

Using online learning environments in higher education offers innovative possibilities to support collaborative learning. However, online learning creates new kinds of problems for participants who have not previously worked with each other. One of these problems is uncertainty which occurs when participants do not know each other. According to the uncertainty reduction theory, low uncertainty level increases the amount of discourse and decreases the amount of information seeking. Therefore, uncertainty may influence online discourse and learning. This study investigates the effects of an epistemic cooperation script with respect to the amount of discourse, information seeking and learning outcomes in collaborative learning as compared to unscripted collaborative learning. The aim was also to explore how and what kind of information learners seek and receive and how learning partners react to such information exchange. The participants were 48 students who were randomly assigned to groups of three in two conditions, one with and one without an epistemic script. The results indicate that the epistemic script increased the amount of discourse and decreased the amount of information seeking activities. Without an epistemic script, however, learners achieved better learning outcomes. The results of two qualitative case-based analyses on information seeking will also be discussed.

Eliciting Self-Explanations Improves Understanding

Article

Jul 1994

Learning involves the integration of new information into existing knowledge. Generating explanations to oneself (self-explaining) facilitates that integration process. Previously, self-explanation has been shown to improve the acquisition of problem-solving skills when studying worked-out examples. This study extends that finding, showing that self-explanation can also be facilitative when it is explicitly promoted, in the context of learning declarative knowledge from an expository text. Without any extensive training, 14 eighth-grade students were merely asked to self-explain after reading each line of a passage on the human circulatory system. Ten students in the control group read the same text twice, but were not prompted to self-explain. All of the students were tested for their circulatory system knowledge before and after reading the text. The prompted group had a greater gain from the pretest to the posttest. Moreover, prompted students who generated a large number of self-explanations (the high explainers) learned with greater understanding than low explainers. Understanding was assessed by answering very complex questions and inducing the function of a component when it was only implicitly stated. Understanding was further captured by a mental model analysis of the self-explanation protocols. High explainers all achieved the correct mental model of the circulatory system, whereas many of the unprompted students as well as the low explainers did not. Three processing characteristics of self-explaining are considered as reasons for the gains in deeper understanding.

Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems

Article

Apr 1989
COGNITIVE SCI

The present paper analyzes the self-generated explanations (from talk-aloud protocols) that “Good” and “Poor” students produce while studying worked-out examples of mechanics problems, and their subsequent reliance on examples during problem solving. We find that “Good” students learn with understanding: They generate many explanations which refine and expand the conditions for the action parts of the example solutions, and relate these actions to principles in the text. These self-explanations are guided by accurate monitoring of their own understanding and misunderstanding. Such learning results in example-independent knowledge and in a better understanding of the principles presented in the text. “Poor” students do not generate sufficient self-explanations, monitor their learning inaccurately, and subsequently rely heavily on examples. We then discuss the role of self-explanations in facilitating problem solving, as well as the adequacy of current AI models of explanation-based learning to account for these psychological findings.

A Framework to Analyze Argumentative Knowledge Construction in Computer-Supported Collaborative Learning

Abstract

No full-text available

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