Muukkonen Ha, Hakkarainen Ka, Lipponen La, Leinonen Tb

May 1999

aDepartment of Psychology, University of Helsinki, Finland
b Media Laboratory, University of Art and Design, Helsinki, Finland

[Paper presented at the Ninth European Congress on Work and Organizational Psychology, Innovations for Work, Organization and Well-being, 12-15 May 1999, Espoo-Helsinki, Finland. Session under the title Support Technology, May 15th.]


Several technology-based learning environments have been introduced in the last decade. However, very few of them depict, in their design, considerations for human learning and thinking processes. The design of a new-generation networked learning environment, called the Future Learning Environment (FLE) relies on recent achievements of cognitive research on educational practices and computer-supported collaborative learning (CSCL). The FLE has been developed in 1998 by the Media Laboratory, University of Art and Design, Helsinki, and the Department of Psychology, University of Helsinki.

The FLE environment consists of several modules that are designed to facilitate collaborative knowledge building in university and vocational education. In the design of FLE, special emphasis has been given to developing metacognitive tools for structuring users' activity. The environment provides each user "Virtual WebTop" for building his or her own knowledge objects. The Virtual WebTop has direct links to those of the other members of the study group, enabling all to share their process of inquiry. The "Discussion Environment" module facilitates between-user interaction and provides means for conducting multiple discussions simultaneously within a course. The "Jam Session" module encourages free flow of ideas and allows experimentation with different ways of representing knowledge. The "Library enables the user to share documents in various formats: text, graphics, audio, video, multimedia or WWW links. An important aspect of the Library is "Deep Principles", an environment for representing the conceptual foundations of each domain of knowledge.

Courses and seminars, that have adopted FLE as a tool for developing shared expertise, represent various academic domains (e.g., new media studies, psychology of thinking and learning, designing, language learning methodology, teacher education). Further, FLE has been used in developing teamwork and organizational planning (e.g., in the field of telecommunications and advertising). The preliminary results from academic domains indicate that the FLE environment has provided these groups means for structuring their efforts to produce new knowledge, and for collaborating without time constrains. More importantly, the environment has aided in mediating more developed practices of studying and discussing points of view, which were observed initially only in the products of the content experts and gradually adopted to the practices of others.

The study gives the theoretical grounding of FLE’s design and also examines the pedagogical constraints of successful implementation of the CSCL. It is concluded that in order to have some genuine pedagogical advantages, network-mediated learning should be fully integrated with the overall design of specific academic studies or vocational training, and not be a mere addition to a traditional program.


The literature in the field of knowledge management points to two immensely powerful and critical challenges for sharing knowledge in an organization. The process of transforming tacit knowledge to explicit knowledge on one hand, and the transfer of core skills and competencies on the other (e.g., Nonaka & Takeuchi, 1995; Davenport & Prusak, 1998). The use of networked technology has introduced new means for sharing knowledge, but, repeatedly, the advantages of using technology for shared learning appear controversial and difficult to measure (Davenport & Prusak, 1998). Indeed, cognitive research indicates that many applications of educational technology support only lower-level processing of information. However, environments designed following cognitive principles provide a noticeable exception (e.g., De Corte, 1993; Salomon, 1997; Salomon & Perkins, 1996).

During the last ten years, several technology-based environments of computer supported collaborative learning (CSCL) have been created (e.g., CSILE, CoVis, CoNotes, BELVEDERE, CLARE). Common to those environments is the provision of tools for the users for collaboratively producing and discussing knowledge. However, as such, the tools provide only means for collaboration. What appears to be a critical feature for developing a learning environment which supports higher level of processing, is to provide the users a pedagogical model embedded in the scaffolds for directing their efforts for knowledge advancement. Further, the entire structure of courses or training needs to be designed to support in-depth processing of information.

This study describes the cognitive-design rationale of a new-generation networked learning environment, called the Future Learning Environment (FLE) developed by the Media Laboratory, University of Art and Design, Helsinki, and the Department of Psychology, University of Helsinki. The environment is a groupware system designed for supporting collaborative knowledge building ( The primary users of FLE are university students and people in in-service training at various organizations. The users are able to access it from any internet-linked computer and make postings of knowledge productions to FLE-Tools database using their standard office applications and productivity tools producing documents in various formats, such as text, graphics or video.

FLE’s design relies on recent achievements of cognitive research on educational practices and CSCL (see, for example, Hall, Miyake, & Enyedy, 1997, Lipponen & Hakkarainen, 1997). In this paper, the pedagogical model of "progressive inquiry" embedded in the FLE design is discussed and, to demonstrate the use of FLE-Tools software, results from a course conducted using the FLE-Tools will be presented.

Process of Progressive Inquiry

In the present study, the sustained processes of advancing and building of knowledge characteristic of scientific inquiry are called progressive inquiry. Progressive inquiry entails that new knowledge is not simply assimilated but constructed through solving problems of understanding (Hakkarainen, Lipponen, & Muukkonen, 1998). Characteristic of this kind of inquiry, instead of direct assimilation, is that the student treats new information as something problematic that needs to be explained (Bereiter & Scardamalia, 1993; Chan, Burtis, & Bereiter, 1997). By imitating practices of scientific research communities, students can be guided to engage in extended processes of question- and explanation-driven inquiry. An essential aspect of this kind of inquiry is to engage collaboratively in improving of shared knowledge objects, i.e., hypotheses, theories, explanations or interpretations (Scardamalia & Bereiter, 1996). Through intensive collaboration and peer interaction, resources of the whole learning community may be used to facilitate advancement of inquiry.

By synthesizing results of the philosophy of science and cognitive research a framework can be constructed for analyzing essential elements of progressive inquiry (Figure 1). In the following, a conceptual framework of progressive inquiry is outlined and each aspect of inquiry shortly discussed.

Creating Context

A starting point of the process of inquiry is creating a context for a study project in order to anchor the problems being investigated to central conceptual principles of the domain of knowledge in question or complex real-world problems solved by experts. The purpose of context creating is to help the students to understand why the issues in question are important and worthwhile to investigate and personally commit to solve the problems being investigated. It is essential that the topic is sufficiently complex and multifaceted so that it can be approached from different viewpoints. It is very important to focus inquiry on a problem-area that is central for the students’ conceptual understanding and encourage them to take challenging learning tasks that facilitate in-depth conceptual understanding.

Figure 1. Elements of progressive inquiry

Engaging in Question-driven Inquiry

An essential aspect of progressive inquiry is to set up questions or problems that guide the process of inquiry. Without a research question there cannot be a genuine process of inquiry although information is frequently produced at different educational levels without any guiding questions. Cognitive goals determine what kinds of questions are generated, and, thereby, guide and regulate the process of inquiry. Questions that arise from students own wonderment or their need to understand, have a special value in the process of inquiry.

Generating Own Intuitive Theories

An important aspect of inquiry and a critical condition of developing conceptual understanding is generation of one’s own conjectures, hypotheses, theories or interpretations for the phenomena being investigated (Bruner, 1996; Carey & Smith, 1995; Dunbar & Klahr, 1988; Scardamalia & Bereiter, 1993). Construction of students’ own hypothesis and conjectures guides students to systematically use their background knowledge and make inferences to extend understanding.

Each student comes to instructional situations with a large body of preconceptions that diverge from generally accepted scientific ones. These affect considerably how he or she interprets new information. Progressive inquiry is aimed facilitating explication and externalization of these preconceptions (through guiding students, for instance, to write about their ideas) and taking them as the object of collaborative discussion. Generation of intuitive explanation before obtaining scientific information makes differences between one’s own conceptions and scientific conceptions salient and accessible to the student. If scientific conceptions are assimilated without explicating one’s own view, it is likely that potential differences or gaps of knowledge are not at all identified. As a consequence, the student is likely to assimilate scientific knowledge without any conceptual restructuring and reproduce misconceptions or wrong theories later on in the process of inquiry.

Searching New Scientific Information

The question-driven process of inquiry provides heuristic guidance in the search for new scientific information. Considerable advancement of inquiry cannot be made without obtaining new information. Further, large bodies of information cannot be managed without questions that guide and constrain the knowledge seeking process and help to structure information obtained (Bereiter, 1992). By examining one’s problem or intuitive theory with the help of new information, the student may become aware of his or her inadequate presuppositions or background assumptions. Monitoring progress of one’s conceptual understanding facilitates metacognitive awareness of the process of inquiry.

Engagement in Deepening Inquiry

In pragmatic problem-solving situations one has to start generating questions and tentative theories before all necessary information is available. As a consequence, the process of inquiry often has to start with initially very general, unspecified and "fuzzy" questions and tentative working theories (Sintonen, 1991). In spite of gaps, weaknesses, unclarities or other limitations, however, these kind of general questions and working theories may function as tools of inquiry and provide a basis for progressive inquiry.

A critical condition for progress is that a student focuses on improving his or her theory by generating more specific questions and searching for new information. The process of inquiry advances through transforming the initial big and unspecified questions into subordinate and, frequently, more specific questions. The student tries to solve the big question through using his or her existing knowledge and new information that provide answers to a series of subordinate questions. The dynamic nature of inquiry is, further, based on the fact generation of intuitive explanations and obtaining of new scientific information make new research questions accessible to the students that could not have been foreseen in the beginning of inquiry. By finding answers to subordinate questions, a student approaches step by step toward answering the big initial question.

Shared expertise

All aspects of inquiry, such as setting up research questions, searching for new scientific information, constructing of one’s own working theories or assessing the explanations generated, can be shared with other inquirers. Cognitive research indicates that advancement of inquiry can be substantially elicited by relying on socially distributed cognitive resources, emerging through social interaction between the learners, and collaborative efforts to advance shared understanding. Through social interaction, contradictions, inconsistencies and limitations of a student’s explanations become available because it forces him or her to perceive conceptualizations from different points of view. Hatano and Inakagi (1992) as well as Brown, Collins & Duguid (1989) argued, further, that deep conceptual understanding is also fostered through explaining a problem to other inquirers. In order to explain one’s view to his or her peers, an individual student has to commit his- or herself cognitively to some ideas, explicate his or her beliefs, as well as organize and reorganize his or her knowledge (Hatano & Inagaki, 1992). Through this kind of process, inadequacies of one’s understanding tend to become more salient.

Further, there is a growing body of evidence that cognitive diversity and distribution of expertise promote knowledge advancement and cognitive growth. Distribution of cognitive efforts allows the community to be more flexible and achieve better results than otherwise would be possible. Moreover, studies of Hutchins (1991) and Dunbar (1995) revealed that groups which consist of members having different but partially overlapping expertise were more effective and innovative than groups with homogeneous expertise. New pedagogical models as well as technology-based learning environments are emerging that are grounded on distributed expertise and which utilize cognitive diversity.

Description of the Design of FLE

General Design of the Environment

The Future Learning Environment (FLE) is based on a three-tier architecture in which the FLE-Tools software is distributed among three servers: the database server where most of the changing information (the database and search engine) resides, the application server that handles most of the logic in conjunction with the database server, and the www server that handles the backend www-processing and glues the other servers together. FLE software can be accessed through Internet (TCP/IP) with any HTML 3.2 compliant browser such as Netscape Navigator 3 (or later). Some non-critical features can only be accessed by browsers with a JavaScript implementation. The users are able to work with the common information processing programs that they use, producing for example, documents, graphics, video or WWW links. Because of the internet accessibility it follows that small groups working at different locations are able to coordinate their activities with the tools provided by FLE.

The main modules of the FLE-Tools that will be described include the Virtual Web-Top, the Discussion Module, the Jam Session Module and the Library.

Virtual WebTop

The Virtual WebTop refers to a personal adjustable display window, which is automatically opened as the user logs into the system. It can be visited by other users in the same course, enabling them to share a process of inquiry and to get acquainted to their fellow students’ interests. The Virtual WebTop contains graphical links, represented by folders, that give information about the course attended, list the names of the other participants of the group, supply a private folder, and also provide direct access to different locations and tools, such as the Assessment Tools and the Thinking Tools. The Virtual WebTop is a place for the user to store his or her documents created by standard office applications in various formats. It is the main center for the user’s own knowledge production, and contains large documents such as research proposals, term papers, designs, or project reports that are related to one or several FLE projects. The Virtual WebTop also has a search engine build-in, enabling search into materials previously produced in other courses and also all materials in the Library. Through examining fellow students’ Virtual WebTop, a student is able to observe the topics and courses taken by them.

Within the FLE, primary attention has been given to developing metacognitive tools for structuring users’ activity. One way of achieving this is collecting evaluations from the courses and their outcomes by several assessment reports on the phases of the courses. These reports are given by a user on his or her work (self-assessment), and on the work of the group (group-assessment).

The Discussion Module

The Discussion Module provides a shared space for discussing topics and concepts generated by the users. All discussion messages within a course are posted to the shared space, visible as lists of messages. Each Discussion in accessible only by the users enlisted as participants of that specific course.

A user preparing a discussion message is routinely asked to label his or her message by choosing a Category of Inquiry label (e.g., problem, working theory, summary). These category labels are designed to enhance expert-like articulation and reflection on the contents of the discussion message. Further, they are designed to overcome the traditional question-answer -type discussion and introduce a higher-level explanation-driven paradigm to the discussion.

The Jam Session Module

In contrast to the Discussion module, the Jam Session encourages free flow of ideas and experimentation with different ways of representing knowledge. A prominent function of designing the Jam Session module is the presentation of ideas, thought or models under development. The environment provides tools for storing different versions of the object being developed, whether it is a design or a project report or something else. The users may take a version of the object and elaborate it further, and save it for the other users to be further elaborated. The Jam Session module assists in making thinking visible (Brown, Collins & Duquid, 1989; Scardamalia & Bereiter, 1989) by exposing contradictions and gaps in knowledge and also by allowing multiple sketching of ideas.

The Library

The Library allows the users to share the documents produced in various formats: text, graphics, audio, video, multimedia, or WWW links. The Library contains course materials chosen by the tutor as well as materials produced by the users. Materials from earlier courses may also be stored in the Library and made accessible to later users. The environment is intended to provide tools for helping teachers and students to create digitized study materials, to collect interesting link addresses to folders, and also gain access to other libraries linked to the internet.

Research questions

The study attempts to answer to two questions underlying any quests to measure or evaluate the use of any networked learning environment such as the FLE-Tools. First, what is the nature of messages produced by the participants in the discussion? Second, does the introduction of the model of progressive inquiry show itself in the database discussion? It is hypothesized that guided by the model the students would be posing many questions at the beginning of the course and would be offering explanations for the phenomena under study intensively throughout the course. In particular, we are investigating the condition that a tutor’s does not actively participate in the database discussion.


The data collection

The data was collected from a nine weeks course on "Perspectives of cognitive psychology on media education". The group had weekly face-to face seminar meetings and their course credit was obtained from reading the study materials, and actively participating in the seminar sessions and the FLE-database discussion. Thirteen students in a master’s program in educational technology took part in the database discussion in the FLE’s Discussion module. During the nine weeks course the students posted 125 messages. In addition, the tutor posted nine messages formulated collaboratively during the seminar meetings. These nine messages were initial inquiries into the general themes of the course, e.g. "How does the new information and communication technology support development of students’ expertise in different contexts?" or "Are there new kinds of pedagogical problems witnessed with networked learning?" Apart from these messages the tutor did not take part in the database discussion. The postings to the database constitute the data analyzed in this study.


The database material was analyzed with qualitative and quantitative methods in order to identify central themes of discussion and evaluate the process of knowledge advancement. The methods applied to analyzing the date aim at providing a richer view on the content and the progression of the discussion (cref. Chi, 1997). The messages were segmented into propositions which were considered to address one idea in form of an explanation, a question, a metacognitive evaluation, or a quote from prior discussion. To analyze the reliability of segmentation, an independent coder classified approximately 15 percent of the messages. The inter-coder reliability was .91, indicating that the reliability of segmentation was satisfactory.

Coding categories

To explore the nature of knowledge presented in the messages, each segment or idea was coded to manifest the properties of one of the four core "categories of ideas" identified in the coding process: Questions, own knowledge, metastatements, and reference to prior discussion in form of quotes. All of the units of analysis fitted in one of these four core categories, which were mutually exclusive. For each category subcategories were identified and they will be introduced in the following paragraphs.

Five subcategories for the Question category were identified in the analysis process: Inquiry question, inference question, discussion-prompt question, alternatives question, and unspecified or mixed question. The inquiry question was a central subcategory in our analysis. The presentation of inquiry questions was cognitively modeled during the first seminar meeting with the collaborative construction of research question for the course.

Six subcategories of Explanation category were constructed: Expert-source explanation, own explanation, suggesting approach for inquiry, summary or conclusion, reflecting own experience, and unspecified or mixed explanation. For research purposes, the category of explanations was divided into two. The first, "expert-source explanations", represented the explanations that contained explicit reference to an article, book or other study material that the student had read and based the explanation on. The second, "own knowledge" product, referred to all the other subcategories combined, own explanation, suggesting approach for inquiry, summary or conclusion, reflecting own experience, and unspecified or mixed explanation. This division was based on the need to investigate the role of searching scientific information and introducing it to the database discussion, apart from other types of explanations.

Metastatements consisted of evaluation of own learning, evaluation of the discourse, evaluation of the course progression, evaluation of the FLE-Tools and other metacognitive statements. Ideas were judged metacognitive when they contained an explicit expression of a generalization from own or group’s experience, an evaluation of own thinking process (e.g., confusion) or a reflection on the learning process.

Quotes from prior discussion presented excerpts form messages posted prior to the message where it was reprinted. A quote contained the verbalizations of someone other than the author of the analyzed massage. Therefore, it contained ideas the author had chosen to highlight from previous discussion.


The students took most actively part in the discussion during the first and the last quarter of the course, producing during that time 67 percent of all ideas. The analysis of the proportions of ideas generated indicated that 25.5 % (n = 126) of ideas were questions, 45 % (n = 225) were explanations, 13.3 % (n = 66) were metastatements, and 16.2 % (n = 80) were references to prior discussion. The distribution of the different categories of ideas is presented in Figure 1.

The results indicated that the frequency of Questions was the highest during the first quarter of the discussion and gradually decreased. This result seems to show the construction of initial research questions in accord with the model of progressive inquiry. However, a second impulse expected from developing deepening questions is less evident, although the data revealed that inquiry questions (aimed at reaching a better understanding of the phenomena under discussion) were produced at a reasonable level throughout the course. During the 1st quarter 23, and 12, 6, and 2 on the following quarters respectively.

Figure 1. Frequencies of different categories of ideas produced.
(Click the picture to view the figure at full size)

The amount of Own knowledge products was highest during the first and the last quarter. On the contrary, the subcategory of Expert-source explanations did not produce similar increases, and remained at a strikingly low level throughout the course. However, the frequency of metastatements was observed to increase as the course proceeded, particularly during the last quarter, presumably influenced by explicit instructions from the tutor to summarize own learning. Encouragingly, the students formulated these summaries in a fashion that showed explicit metacognitive efforts, e.g., evaluation of own knowledge advancement efforts, aspects of own studying and writing that should be improved and ways for improving them. One reoccurring object of evaluation discussed by the students in the database during the last quarter was the low amount of scientific explanations compared to own intuitive explanations, suggesting that the students did come to understand their value even though they did not change their own practices accordingly.

The last category, Quotes from prior discussion, showed a steady level during the first three quarters and decreased only during the last quarter. An interesting discussion culture was developed, which used quotes from previous messages to set a context for own knowledge productions. The students very selectively maintained only the parts of a prior massage that they were elaborating on. The design of FLE supports this contextualization process by including the original message the person is responding to in the writing field of the new message.

Use of scaffolds

The Discussion module of FLE-Tools has seven build-in scaffolds: Problem, Working Theory, Deepening knowledge, Comment, Metacomment, Summary and Help (not used during this discussion). It is mandatory for a user to choose one of these scaffolds called "categories of inquiry" to describe the message before it is posted to the database. The use of these scaffolds was investigated in terms of how often they were applied in each of the four periods. For each quarter the relative proportion of messages with a given category of inquiry are displayed in Table 1. In the table, the relative proportions of the four categories of ideas are also shown.

Table 1. The relative proportions of different categories of inquiry and categories of ideas within the four quarters of the course.












Working theory





Deepening knowledge





















100 %

100 %

100 %

100 %







Own knowledge





Expert-source explanation










Referencing prior discussion






100 %

100 %

100 %

100 %

The relative proportion of Comments within the array of other scaffolds was rather high 56 % (n = 78). This result can be interpreted to reflect the tendency to choose a Category of Inquiry that is perceived neutral or responding to an earlier message. This is problematized also in the database discussion, as one student explains in a message labeled Problem (in parenthesis is the "category of idea" it obtained in the analysis):

"The choice between the Categories of Inquiry is puzzling: what does it mean, and more importantly, how possible is it to separate them during a practical task (Inquiry question)? A comment may contain equally much information as deepening knowledge type (Own Explanation). Or is it a problem because I’m not used to this new environment (Inference question)?"

Despite the obvious uncertainties the student had about using the scaffolds, the scaffolds appear to have reached at least some of the cognitive goals set forth for them. This student as well as others were deliberating on their knowledge and the ways to present it in the discussion.


A model of progressive inquiry was introduced to a master’s program course in Educational technology. The analysis of discussion held in the FLE-Tools database with 13 participants revealed that the relative proportion different categories of ideas provided a good match with the progressive process of inquiry model. The amount of questions produced was the highest during the first two quarters of course. The amount of own knowledge expressed in form of explanations remained relatively high. The proportion of metacognitive evaluations showed an encouraging increase as the weeks passed on.

The information obtained from books, articles and study materials introduced as course material played a minor role in the explanations produced by the students. It is questioned whether active participation by a tutor would enhance the integration of scientific information into such a discussion with adult participants. However, the explanations produced by the students did provide valuable shared knowledge on how the students perceived working with an online environment and the opportunities they saw for its use in education. Together with externalization of own knowledge and the increase of metacognitive evaluations produced by the students, the course provided positive evidence for an integration of progressive inquiry and online discussion to compliment a face-to-face seminar.

In terms of the use of the scaffolds provided by the FLE-Tools interface, the students showed a bias for selecting a Category of Inquiry that was very neutral, mostly a comment. A thematic analysis of the discussion revealed that a tutor’s "just-in-time" participation could have significantly changed this pattern, judging from the evaluations and reflections on own experience produced by the students. An implication for further courses is that the participation of a tutor into the discussion is recommended, at least for course with new users, until a pattern of interaction is established which explores all scaffolds provided by the environment.


Bereiter, C. (1992) Problem-centered and referent-centered knowledge: Elements of educational epistemology. Interchange, 23/4,337-361.

Bereiter, C. & Scardamalia, M (1993) Surpassing ourselves. An inquiry into the nature and implications of expertise. Chicago, IL: Open Court.

Brown, J.S., Collins, A., & Duguid, P. (1989) Situated cognition and culture of learning. Educational Researcher 18, 32-42.

Bruner, J. (1996) Culture and Education. Cambridge, MA: Harvard University Press.

Carey, S. & Smith, C. (1995) On understanding scientific knowledge. In D. N. Perkins, J. L. Schwartz, M. M. West, & M. S. Wiske. (Eds.) Software goes to school. (pp. 39-55). Oxford: Oxford University Press.

Chan, C., Burtis, J., & Bereiter, C. (1997) Knowledge building as a mediator of conflict in conceptual change. Cognition and Instruction, 15, 1-40.

Chi, M., (1997) Quantifying Qualitative Analyses of Verbal Data: A Practical Guide. The Journal of the Learning Sciences, 6, 271-315.

Davenport, T. & Prusak, L. (1998) Working Knowledge: How organizations Manage What They Know. Harvard Business School Press.

De Corte, E. (1993) Psychological aspects of changes in learning supported by informatics. In Johnson, D. C., & Samways, B. (Eds.). Informatics and changes in learning. (A-34). Proceedings of the IFIP TC3.1/WG3.5 Open Conference on Informatics and Changes in Learning. Gmunden, Austria 7-11 June, 1993. Amsterdam: North-Holland.

Dunbar, K. (1995) How scientists really reason: Scientific reasoning in real-world laboratories. R. J. Sternberg. & J. Davidson. (Eds.) Mechanisms of insight. (pp. 365-395). Cambridge, MA: MIT Press.

Dunbar, K. & Klahr, D. (1988) Developmental differences in scientific discovery process. In K. Klahr & K. Kotovsky (Eds.) Complex Information Processing (pp. 109-143) Hillsdale, NJ: Lawrence Erlbaum.

Hakkarainen, K., Lipponen, L. & Muukkonen, H, (1998) Facilitating progressive inquiry through computer-supported collaborative learning: A guide to teachers. Unpublished manuscript.

Hall, R., Miyake, N. & Enyedy N. (1997) Proceedings of CSCL, The Second International Conference on Computer Support for Collaborative Learning, December 10-14, 1997 University of Toronto, Canada.

Hatano, G. & Inagaki, K. (1992) Desituating cognition through the construction of conceptual knowledge. In P. Light & G. Butterworth (Eds.) Context and cognition. Ways of knowing and learning. (pp. 115-133). New York: Harvester.

Hutchins, E. (1991) The social organization of distributed cognition. In L. B. Resnick, J. M. Levine & S. D. Teasley (Eds.). Perspectives on socially shared cognition. (pp. 283-307). Washington, DC.: American Psychological Association.

Lipponen, L. & Hakkarainen, K. (1997). Developing culture of inquiry in computer-supported collaborative learning. Proceedings of the Computer-supported Collaborative Learning 1997 (CSCL97) conference, University of Toronto, 10-14 December, 1997.

Nonaka, I. & Takeuchi, H., (1995) The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press.

Salomon, G. (1997) Novel constructivist learning environments and novel technologies: Some issues to be concerned with. An invited key note address presented at the 8th conference of the European Association for Research on Learning and Instruction, Athens, August 1997.

Salomon, G. & Perkins, D. 1996. Learning in wonderland. What do computers really offer education? In S. Kerr (Ed.), Technology and the future of schooling in America. The ninety-fifth yearbook of the national society for the study of education, part II. The University Press of Chicago.

Scardamalia, M., & Bereiter, C. (1993) Technologies for knowledge-building discourse. Communications of the ACM, 36, 37-41.

Scardamalia, M., & Bereiter, C. (1996) Adaptation and understanding: A case for new cultures of schooling. In Vosniadou, S., De Corte, E., Glaser, R., & Mandl, H. (Eds.) International perspectives on the psychological foundations of technology-based learning environments.

Sintonen, M. (1991) How evolutionary theory faces the reality. Synthese, 89, 163-183.