Journal•ISSN: 1050-8406
The Journal of the Learning Sciences
Routledge
About: The Journal of the Learning Sciences is an academic journal published by Routledge. The journal publishes majorly in the area(s): Learning sciences & Teaching method. It has an ISSN identifier of 1050-8406. Over the lifetime, 612 publications have been published receiving 80284 citations.
Topics: Learning sciences, Teaching method, Educational technology, Cooperative learning, Science education
Papers published on a yearly basis
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TL;DR: The lion's share of my current research program is devoted to the study of learning in the blooming, buzzing confusion of inner-city classrooms, and central to the enterprise is that the classroom must function smoothly as a learning environment before the authors can study anything other than the myriad possible ways that things can go wrong.
Abstract: (1992) Design Experiments: Theoretical and Methodological Challenges in Creating Complex Interventions in Classroom Settings Journal of the Learning Sciences: Vol 2, No 2, pp 141-178
3,738 citations
TL;DR: Video technology has been vital in establishing Interaction Analysis, which depends on the technology of audiovisual recording for its primary records and on playback capability for their analysis.
Abstract: (1995). Interaction Analysis: Foundations and Practice. Journal of the Learning Sciences: Vol. 4, No. 1, pp. 39-103.
2,343 citations
TL;DR: Barab et al. as discussed by the authors argue that learning, cognition, knowing, and context are irreducibly co-constituted and cannot be treated as isolated entities or processes.
Abstract: The emerging field of the learning sciences is one that is interdisciplinary, drawing on multiple theoretical perspectives and research paradigms so as to build understandings of the nature and conditions of learning, cognition, and development. Learning sciences researchers investigate cognition in context, at times emphasizing one more than the other but with the broad goal of developing evidence-based claims derived from both laboratory-based and naturalistic investigations that result in knowledge about how people learn. This work can involve the development of technological tools, curriculum, and especially theory that can be used to understand and support learning. A fundamental assumption of many learning scientists is that cognition is not a thing located within the individual thinker but is a process that is distributed across the knower, the environment in which knowing occurs, and the activity in which the learner participates. In other words, learning, cognition, knowing, and context are irreducibly co-constituted and cannot be treated as isolated entities or processes. If one believes that context matters in terms of learning and cognition, research paradigms that simply examine these processes as isolated variables within laboratory or other impoverished contexts of participation will necessarily lead to an incomplete understanding of their relevance in more naturalistic settings (Brown, 1992).1 Alternatively, simply observing learning and cognition as they naturally Correspondence and requests for reprints should be sent to Sasha A. Barab, School of Education,
2,233 citations
TL;DR: The conceptual bases of computer-supported intentional learning environments (CSILE) as mentioned in this paper come from research on intentional learning, process aspects of expertise, and discourse in knowledge-building communities, and combine to support the following propositions: schools need to be restructured as communities in which the construction of knowledge is supported as a collective goal, and the role of educational technology should be to replace classroom discourse patterns with those having more immediate and natural extensions to knowledge building communities outside school walls.
Abstract: In this article we focus on educational ideas and enabling technology for knowledge-building discourse. The conceptual bases of computer-supported intentional learning environments (CSILE) come from research on intentional learning, process aspects of expertise, and discourse in knowledge-building communities. These bases combine to support the following propositions: Schools need to be restructured as communities in which the construction of knowledge is supported as a collective goal, and the role of educational technology should be to replace classroom discourse patterns with those having more immediate and natural extensions to knowledge-building communities outside school walls. CSILE is described as a means for refraining classroom discourse to support knowledge building in ways extensible to out-of-school knowledgeadvancing enterprises. Some of the most fundamental problems are logistic, and it is in solving these logistic problems that we see the greatest potential for educational technology.
2,219 citations
TL;DR: The 10-year history of tutor development based on the advanced computer tutoring (ACT) theory is reviewed, finding that a new system for developing and deploying tutors is being built to achieve the National Council of Teachers of Mathematics (NCTM) standards for high-school mathematics in an urban setting.
Abstract: This paper review the 10-year history of tutor development based on the ACT theory (Anderson, 1983,1993). We developed production system models in ACT ofhow students solved problems in LISP, geometry, and algebra. Computer tutors were developed around these cognitive models. Construction ofthese tutors was guided by a set of eight principles loosely based on the ACT theory. Early evaluations of these tutors usually but not always showed significant achievement gains. Best-case evaluations showed that students could achieve at least the same level of proficiency as conventional instruction in one third the time. Empirical studies showed that students were learning skills in production-rule units and that the best tutorial interaction style was one in which the tutor provides immediate feedback, consisting of short and directed error messages. The tutors appear to work better if they present themselves to students as nonhuman tools to assist learning rather than as emulations of human tutors. Students working with these tutors display transfer to other environments to the degree that they can map the tutor environment into the test environment. These experiences have coalesced into a new system for developing and deploying tutors. This system involves first selecting a problem-solving interface, then constructing a curriculum under the guidance of a domain expert, then designing a cognitive model for solving problems in that environment, then building instruction around the productions in that model, and finally deploying the tutor in the classroom. New tutors are being built in this system to achieve the NCTM standards for high school mathematics in an urban setting. (http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA312246)
1,826 citations