A framework to analyze argumentative knowledge construction in computer-supported collaborative learning

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)

From conditioning to learning communities: Implications of fifty years of research in e‐learning interaction design

This paper will consider e‐learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e‐learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné), cognitivist (Pask, Piaget and Papert), situated (Lave, Wenger and Seely‐Brown), socio‐constructivist (Vygotsky), socio‐cultural (Nardi and Engestrom) and community‐based (Wenger and Preece). Emerging from this review is the argument that effective e‐learning usually requires, or involves, high‐quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e‐learning

Support of the collaborative inquiry learning process: influence of support on task and team regulation

Regulation of the learning process is an important condition for efficient and effective learning. In collaborative learning, students have to regulate their collaborative activities (team regulation) next to the regulation of their own learning process focused on the task at hand (task regulation). In this study, we investigate how support of collaborative inquiry learning can influence the use of regulative activities of students. Furthermore, we explore the possible relations between task regulation, team regulation and learning results. This study involves tenth-grade students who worked in pairs in a collaborative inquiry learning environment that was based on a computer simulation, Collisions, developed in the program SimQuest. Students of the same team worked on two different computers and communicated through chat. Chat logs of students from three different conditions are compared. Students in the first condition did not receive any support at all (Control condition). In the second condition, students received an instruction in effective communication, the RIDE rules (RIDE condition). In the third condition, students were, in addition to receiving the RIDE rules instruction, supported by the Collaborative Hypothesis Tool (CHT), which helped the students with formulating hypotheses together (CHT condition). The results show that students overall used more team regulation than task regulation. In the RIDE condition and the CHT condition, students regulated their team activities most often. Moreover, in the CHT condition the regulation of team activities was positively related to the learning results. We can conclude that different measures of support can enhance the use of team regulative activities, which in turn can lead to better learning results

Impact of a Science Methods Course on Pre-Service Elementary Teachers\u27 Knowledge and Confidence of Teaching with Scientific Inquiry and Problem-Based Learning

The purpose of this study was to measure the impact of an elementary science methods course on pre-service teachers\u27 knowledge and confidence of teaching with inquiry and problem-based instructional strategies. Changes in pre-service teachers\u27 knowledge and confidence were measured before and after completing the course activities using a pilot survey entitled Science Pedagogical Content Knowledge & Confidence (PCKC) Survey. An integrated lecture/laboratory elementary science methods course engaged participants with hands-on activities designed to increase their pedagogical content knowledge: including theory, planning and implementation of inquiry, and problem-based learning. The results indicated that pre-service teachers\u27 knowledge and confidence improved as a result of enrollment in the elementary science methods course. This article validates reform movements to incorporate scientific inquiry and problem-based learning into coursework

Scripts and scaffolds In Problem-based computer supported collaborative learning environments: fostering participation and transfer

This study investigates collaborative learning of small groups via text-based com-puter-mediated communication. We analyzed how two approaches to pre-structure communication influence participation, individual knowledge transfer, the conver-gence of participation and the convergence of knowledge among learning partners. We varied the factor "scripted cooperation" and the factor "scaffolding" in a 2x2-design. 105 university students of Pedagogy participated. Results show that scrip-ted cooperation was most and scaffolding least beneficial to individual transfer, knowledge convergence and participation in comparison to open discourseDiese Studie befasst sich mit kooperativem Lernen in Kleingruppen über text-basierte computervermittelte Kommunikation. Es wurden zwei Ansätze der Vor-strukturierung von computervermittelter Kommunikation und ihre Auswirkungen auf Partizipation, individuellen Wissenstransfer, die Konvergenz der Partizipation und die Wissenskonvergenz innerhalb einer Lerngruppe untersucht. Dabei wurden die Faktoren "Kooperationsskript" und "Scaffolding" in einem 2x2-Design variiert. 105 Studierende der Pädagogik nahmen teil. Die Ergebnisse zeigen, dass sich das Ko-operationsskript am günstigsten und das Scaffolding am wenigsten günstig auf individuellen Wissenstransfer, Wissenskonvergenz und Partizipation im Vergleich zu einer Kontrollgruppe des 'Offenen Diskurses' ausgewirkt ha

Collaborative Epistemic Discourse in Classroom Information Seeking Tasks

We discuss the relationship between information seeking, and epistemic beliefs – beliefs about the source, structure, complexity, and stability of knowledge – in the context of collaborative information seeking discourses. We further suggest that both information seeking, and epistemic cognition research agendas have suffered from a lack of attention to how information seeking as a collaborative activity is mediated by talk between partners – an area we seek to address in this paper. A small-scale observational study using sociocultural discourse analysis was conducted with eight eleven year old pupils who carried out search engine tasks in small groups. Qualitative and quantitative analysis were performed on their discussions using sociocultural discourse analytic techniques. Extracts of the dialogue are reported, informed by concordance analysis and quantitative coding of dialogue duration. We find that 1) discourse which could be characterised as ‘epistemic’ is identifiable in student talk, 2) that it is possible to identify talk which is more or less productive, and 3) that epistemic talk is associated with positive learning outcomes

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Perspectives on Deepening Teachers’ Mathematics Content Knowledge: The Case of the Oregon Mathematics Leadership Institute

The Oregon Mathematics Leadership Institute (OMLI) project served 180 Oregon teachers, and 90 administrators, across the K-12 grades from ten partner districts. OMLI offered a residential, three-week summer institute. Over the course of three consecutive summers, teachers were immersed in a total of six mathematics content classes– Algebra, Data & Chance, Discrete Mathematics, Geometry, Measurement & Change, and Number & Operations—along with an annual collegial leadership course. Each content class was designed and taught by a team of expert faculty from universities, community colleges, and K-12 districts. Each team chose a few “big ideas” on which to focus the course. For example, the Algebra team focused on algebraic structure and properties of the concept of a group, while the Data & Chance team centered their activities on the exploration of ideas of central tendency and variation using statistics and data analysis software packages. The content in all of the courses was addressed through deep investigation of the mathematics of tasks that had been selected and adapted from resources for K-12 mathematics classrooms. In addition to mathematics content, the courses were designed with specific attention to socio-mathematical norms, issues of status differences among learners, and the selection and implementation of group-worthy tasks for group work. The faculty attended sessions grounded in the work of Elizabeth Cohen on strategies for working with heterogeneous groups of learners (Cohen, 1994; Cohen et al, 1999) which was central to the OMLI design and implementation. Institute faculty modeled these strategies in the Institute classrooms and made their moves as transparent as possible, so that the teachers would be able to grapple with these strategies during the Institute and plan for implementation in their own classrooms. The Data & Chance course also modeled uses of technology in instruction using Tinkerplots. Generalization and justification were emphasized as mathematical ways of learning and knowing, and institute faculty conducted classroom discussions that intentionally modeled pushing for generalization and justification