Technology-Supported Learning Environments Research Paper

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The idea of learning environments refers to settings that are purposively designed and implemented to facilitate learning in students. The term ‘learning environments’ has only recently become current in the educational literature, and reflects an important shift in the basic conception of education, namely from a predominantly information transmission and absorption model toward a more constructivist view, and, consequently, a shift in perspective from teaching to learning (Collins et al. 1996). Technology-supported learning environments are, then, contexts for learning that involve technological devices that are assumed to foster students’ acquisition of the intended educational objectives. In this respect, the expression ‘technology supported ’ is also a relative newcomer in the educational vocabulary; in comparison to the frequently used term ‘technology-based,’ it attributes a less central role to the technology in the learning environment.

Using technological devices as teaching aids to facilitate learning has a relatively long history in education and educational research. A constant runs through this history as a continuous thread: initially there is great optimism and high expectations about the potential of the new technology for the improvement of the quality and the outcomes of learning and teaching, but this is afterwards followed by disappointment because the expectations are not met and the expected positive effects fail to appear. For instance, in an excellent historical overview of the classroom use of technology since 1920, Cuban (1986) quotes the following claims: ‘The central and dominant aim of education by radio is to bring the world to the classroom, to make universally available the services of the finest teachers, the inspiration of the greatest leaders’ (Darrow 1932, p. 79, quoted in Cuban 1986, p. 19); ‘The time may come when a portable radio receiver will be as common in the classroom as is the blackboard. Radio instruction will be integrated into school life as an acceptable educational medium’ (Levenson 1945, p. 457, quoted in Cuban 1986, p. 19). Obviously these predictions have remained unfulfilled. On the other hand, these statements echo many similar ones heard afterwards with respect to educational television, and more recently about the educational use of the computer. However, there is now robust evidence that in these cases too the euphoric, but naive expectations were not fulfilled (Hawkins 1996, Salomon and Gardner 1986); they were probably more based on wishful thinking than on well-grounded arguments. In sum, the history of educational technology has more or less repeated itself throughout the twentieth century, and apparently not much has been learned from it.

But paralleling the shift from an information transmission to a constructivist view of education, there has recently also been a trend toward a more productive application of educational technology that moves away from the romantic and naive technological optimism of the past, and is in accordance with the new perspective on education. Mainly focusing on the educational use of the new information and communication technology, this research paper will briefly document this trend, after first identifying major causes of the past failures.

1. From Adding-On Toward Embedding Computers In Learning Environments

A major cause of the relative failure of educational computing—as well as of previous ‘novelties’ in the instructional technology toolbox—is that since the early 1980s the computer has been mainly introduced in educational settings as an add-on to an existing and unchanged instructional setting (Salomon 1992). In other words, the typical application of computers could better be described as ‘computer-added instruction’ than as ‘computer-supported learning.’ In mathematics, for instance, the large majority of the available software fitted into the category of drill-and-practice programs, aiming mainly at exercising computational skills and replacing in this respect traditional worksheets (Kaput 1992). This means that the new information technology was implemented to reproduce and preserve the status quo.

The situation in other subject-matter domains of the school curriculum, but also in nonschool settings was largely similar. In language teaching, for example, programs focusing on practicing rules of spelling and grammar also prevailed, and much less software was available that supported the more essential aspects of reading and writing, namely comprehension and communication. It has now become obvious that this mere add-on strategy of educational computer use cannot produce the improvements in the quality and the outcomes of learning that were originally anticipated. A partial explanation of the inefficacy of this strategy is that the predominant drill-and-practice applications elicit only lower-level mental activity in learners, and do not at all exploit the specific potential of the computer such as its interactive possibilities and its tremendous capacity for data presentation and handling.

A more fundamental reason, however, for the failure of the add-on strategy is that it is based on the erroneous assumption that computers will evoke productive learning by themselves (Hawkins 1996). A representative illustration in this respect relates to the way Logo was often used referring to Papert (1980): it was expected that ‘mindstorms’ resulting in improved thinking and problem-solving skills, would arise of themselves in children’s heads due to the unique characteristics of the Logo environment. Contradicted convincingly by well-designed studies, as well as by practical experience, this viewpoint has been abandoned. The point of view has rapidly gained ground that effective computer support for learning requires that it is embedded in powerful teaching–learning environments, i.e., instructional settings that elicit in students and trainees the acquisition processes necessary to attain worthwhile and desirable educational objectives. Embedding means here that the computer is not just an add-on, but is judiciously integrated in the environment capitalizing on its specific strengths and potential to present, represent, and transform information (e.g., visualization and simulation of phenomena and processes), and to induce effective forms of communication, interaction, and cooperation (e.g., through exchanging data, information, and problems via a network). But, there is also a physical aspect to the embedding; indeed, as argued by Collins (1996), the spatial design of the classroom and the design of the computer are currently incompatible with the appropriate and widespread use of computers in schools.

2. From Computer-Controlled Tutoring To Student-Controlled Collaborative Learning

Paralleling the large-scale introduction of computers in education and training, the cognitive science community interested in learning and teaching has invested a lot of work and effort in the design of intelligent tutoring systems (ITS), which can be characterized as computer-supported learning environments based on artificial intelligence (AI) (for an overview see Seidel and Park 1994, Wenger 1987). It is interesting to ask whether this interdisciplinary research endeavor has contributed to overcome the flaws of educational computing discussed above. The question arises because a major incentive for designing ITS derived from dissatisfaction with traditional computer assisted instruction (CAI). In fact, educational software involving AI was originally called ‘intelligent’ computer-assisted instruction (ICAI). The critical distinction between CAI and ITS is that CAI involves static systems that embody the decisions of expert teachers, whereas ITS contain the expertise itself and can use it as a basis for taking decisions about instructional interventions.

The domain of AI and education is an interdisciplinary crossroad and, consequently, the development of intelligent tutors is guided by a substantial and varied body of inquiry-based knowledge. Nevertheless the field is strewn with pitfalls. For instance, one very robust result of research on learning and instruction is that learners’ prior knowledge is a very strong determinant of their future learning. Therefore, instruction should explicitly be linked up to prior knowledge, and the ITS community has taken this principle seriously. Indeed, a major component of an intelligent tutor is the student model which, as Wenger (1987, p.16) states : ‘… should include all the aspects of the student’s behavior and knowledge that have repercussions for his performance and learning.’ But the same author adds immediately that building such a student model is a very difficult task for computer-based systems. Moreover, it is not clear how far one should go in the construction of student models, and how flexible and diagnostic a system should be in view of providing the most appropriate guidance.

An even more fundamental issue concerns the nature of the guidance that an ITS should provide, taking into account the now well-documented conception that learning is an active and constructive process: Learners are not passive receptacles of information, but they actively construct their knowledge and skills through interaction with the environment and through reorganization of their prior mental structures. Consequently, as argued by Scardamalia et al. (1989), computer-based learning environments should support the constructive acquisition processes in students. The question arises whether the existing ITS are in accordance with this constructivist view of learning. Indeed, intelligent tutors that base their instructional decisions on a detailed diagnosis of student’s knowledge can easily lead to a preponderance of highly structured and directive learning situations lacking sufficient opportunities for active learner involvement and participation (Kaput 1992). More recent new approaches in ITS have taken such criticisms into account, and imply a more active participation of the learner in the learning process, especially by involving (learner-controlled) interaction and cooperation between the learner and the system using a kind of built in colearner or learning companion (Frasson and Aimeur 1996).

3. Toward A New Generation Of Computer-Supported Learning Environments

Identification of the deficits of the past approaches to educational computing, together with a better theoretical understanding of the characteristics of effective learning processes, have fostered the emergence of the view that technology-supported learning environments should not so much involve knowledge and intelligence to guide and structure learning processes, but that they should rather create situations and offer tools that stimulate learners to make maximum use of their own cognitive potential (Scardamalia et al. 1989). In this connection Kintsch (1991, p. 245) has launched the idea of ‘unintelligent tutoring’:

A tutor should not provide the intelligence to guide learning, it should not do the planning and monitoring of the student’s progress, because those are the very activities the students must perform themselves in order to learn. What a tutor should do is to provide a temporary support for learners that allows them to perform at a level just beyond their current ability level.

The major characteristics of productive learning processes that have resulted from research on learning and instruction during the past decades can be summarized in the following definition: Learning is an active, constructive, cumulative, self-regulated, goaldirected, situated, collaborative, and individually different process of knowledge building and meaning construction (for a more elaborated discussion see Instructional Psychology). In line with this conception of learning a new generation of technology-supported learning environments has emerged, characterized by a clear shift toward supportive systems that are less structured and less directive, that are more focused on coaching and scaffolding than on tutoring, that involve student-controlled tools for the acquisition of knowledge, and that attempt to integrate both tools and coaching strategies in interactive and collaborative learning environments (Cognition and Technology Group at Vanderbilt 1996). In those environments the technological tools and scaffolds are embedded in the sense as defined above. Different groups of researchers have designed and implemented computer and/or multimedia programs around which novel, powerful learning environments were built that are in accordance with the characteristics of effective learning processes and thus embody the new conception of technology-supported learning (see e.g., Lehtinen et al. 1999, Vosniadou et al. 1996). By way of illustration a few representative cases are briefly described.

A major example is the ‘Jasper project’ of the Cognition and Technology Group at Vanderbilt (CTGV 1997), focusing on learning and teaching mathematical problem solving in the upper primary school. The CTGV introduced the notion of anchored instruction representing one approach to implementing technology-supported learning: Instruction is anchored in videodisk-based complex problem-solving spaces that provide a richer, more realistic, and more dynamic presentation of information than textual material; the videodisk (such as ‘Adventures of Jasper Woodbury’ relating to trip planning) creates an environment for active, cooperative learning and discussion in small groups, as well as for individual and whole-class problem solving.

CSILE (Computer-Supported Intentional Learning Environment) is a domain-independent hypermedia environment that can be used as an educational medium throughout the curriculum (Scardamalia et al. 1994). The system allows students to build and elaborate their own common database consisting of text and graphical material relating to problems and topics under study. All students have access to the database and they can comment on each others’ notes. This latter feature of the environment aims at inducing collaborative problem solving and knowledge construction in the classroom. A software tool derived from CSILE called ‘Knowledge Forum’ (Scardamalia and Bereiter 1998) is available on the World Wide Web.

Since 1993 the two previous projects (‘Adventures of Jasper Woodbury’ and CSILE) have collaborated closely with Brown and Campione’s (1996) ‘Fostering Communities of Learners’ (FCL) program in the framework of the overarching ‘Schools for Thought’ (SFT) project (Lamon et al. 1996). Important in this respect is that—in line with the view of technology supported learning put forward above—the SFT project aims at restructuring and transforming the entire learning environment in schools founded on present-day theory of learning from instruction, and integrating the new technologies (Cognition and Technology Group at Vanderbilt 1996).

A last example, Cabri Geometre, developed in Grenoble, France (Baulac et al. 1988), consists of a series of computer programs that create a powerful learning environment in which students become active learners and explorers of Euclidean geometry guided by their teacher. The underlying ideas are that students can make their own mathematics, and that formulating and testing conjectures constitute the main activities of doing mathematics. The program elicits and facilitates such activities by offering a tool for constructing, manipulating, and exploring geometric shapes.

These technology applications are excellent examples of what Kaput (1992, p. 548) has called ‘implementing technology toward reformed objectives.’ Indeed, these programs embody major principles for the design of good technology-supported learning environments discussed above: They stimulate active learning oriented toward higher-order cognitive skills in a collaborative and teacher-guided context, and they exploit optimally the computer’s interactive potential as well as its capacity to present and manipulate graphic and symbolic information. While a number of educational software projects, of which the three mentioned cases are representative examples, show promising results in small-scale studies, they do not get widely disseminated. A major obstacle in this respect is that most of the available products are expensive, incompatible, and inflexible. Solving this problem is a main challenge for software research and development in the near future. A promising avenue is the ‘component’ approach to educational software, the gist of which consists in the construction of a digital library of reusable (i.e., adaptable to new needs without the help of the original developers) software modules that can be easily mixed and matched. The further elaboration of this strategy should make it possible to reduce the cost, to increase the reuse, to decrease incompatibilities, and to enhance the flexibility of educational software (Roschelle and Kaput 1996).

4. The Potential Of The World Wide Web For Designing Powerful Learning Environments

The end of the twentieth century saw schools rapidly acquiring access to the Internet. For instance, according to a recent survey in the USA over 90 percent of the public schools have some kind of access to the Internet, and 39 percent of the teachers (grades 4–12) have some sort of connection in their classroom (Becker 1999). This new technological tour de force again fuels great enthusiasm and high expectations about the potential of the World Wide Web for enhancing learning and teaching. There is no doubt that the WWW has such a potential; however, a critical approach is indicated in order to avoid once again replicating the naivety and errors from the past with respect to other media.

Obviously the Web is a tremendously rich information source, but this is accompanied by the danger of information overload; also the Web can be used as a channel for communication, but its value as a tool for collaboration should not be overestimated (Roschelle and Pea 1999). Furthermore, making information available and facilitating communication does not yet imply that the Web will foster the quality and the outcomes of student learning; in this respect it is useful to remember that the Web was developed at first as a tool for sharing research information in the community of high energy physics scholars, and not as an educational medium. The following important issues have recently been raised from an educational perspective: the lack of integration of today’s Web with the structure and content of K-12 education; the difficulty of using the Web as a medium for constructive learning (because receiving information on the Web is much easier than creating information); the inability of the Web by itself to foster higher-order skills such as problem solving, creative and critical thinking, and teamwork (Roschelle and Pea 1999). All this implies that in view of exploiting the educational potential of the WWW there is a need for thorough research on the impact of its application in classrooms on the quality and the results of students’ learning and teachers’ instruction, as well as for innovative development aiming at overcoming the educational weaknesses of today’s Web.

Bibliography:

  1. Baulac Y, Bellemain F, Laborde J M 1988 Cabri Geometre. Cedic-Nathan, Paris
  2. Becker H J 1999 Internet Use by Teachers: Conditions of Professional Use and Teacher-directed Student Use (Teaching, learning, and computing: 1998 National survey, Report 1). Center for Research on Information Technology and Organizations. University of California, Irvine, CA and University of Minnesota, MN
  3. Brown A L, Campione J C 1996 Psychological theory and the design of innovative learning environments: On procedures, principles, and systems. In: Schauble L, Glaser R (eds.) Innovations in Learning: New Environments for Education. Erlbaum, Mahwah, NJ, pp. 289–325
  4. Cognition and Technology Group at Vanderbilt 1996 Looking at technology in context: A framework for understanding technology and education research. In: Berliner D C, Calfee, R C (eds.) Handbook of Educational Psychology. Macmillan, New York, pp. 807–40
  5. Cognition and Technology Group at Vanderbilt 1997 The Jasper Project: Lessons in Curriculum, Instruction, Assessment, and Professional Development. Erlbaum, Mahwah, NJ
  6. Collins A 1996 Whither technology and schools? Collected thoughts on the last and next quarter century. In: Fisher C, Dwyer D C, Yocam K (eds.) Education and Technology: Reflections on Computing in Classrooms. Jossey-Bass, San Francisco, pp. 51–65
  7. Collins A, Greeno J G, Resnick L B 1996 Environments for learning. In: De Corte E, Weinert F E (eds.) International Encyclopedia of Developmental and Instructional Psychology. Elsevier Science, Oxford, UK, pp. 687–91
  8. Cuban L 1986 Teachers and Machines: The Classroom Use of Technology Since 1920. Teachers College Press, New York
  9. Darrow B H 1932 Radio: The Assistant Teacher. R.G. Adams, Columbus, OH
  10. Frasson C, Aimeur E 1996 A comparison of three learning strategies in intelligent tutoring systems. Journal of Educational Computing Research 14: 371–83
  11. Hawkins J 1996 Dilemmas. In: Fisher C, Dwyer D C, Yocam K (eds.) Education and Technology: Reflections on Computing Classrooms. Jossey-Bass, San Francisco, pp. 35–50
  12. Kaput J J 1992 Technology and mathematics education. In: Grouws D A (ed.) Handbook of Research on Mathematics Teaching and Learning. Macmillan, New York, pp. 515–56
  13. Kintsch W 1991 A theory of discourse comprehension: Implications for a tutor for word algebra problems. In: Carretero M, Pope M, Simons R J, Pozo J J (eds.) Learning and Instruction: European Research in an International Context. Pergamon, Oxford, UK, Vol. 3, pp. 235–53
  14. Lamon M, Secules T, Petrosino A J, Hacket R, Bransford J D, Goldman S R 1996 Schools for Thought: Overview of the project and lessons learned from one of the sites. In: Schauble L, Glaser R (eds.) Innovations in Learning: New Environments for Education. Erlbaum, Mahwah, NJ, pp. 243–88
  15. Lehtinen E, Hakkarainen K, Lipponen L, Rahikainen M, Muukkonen H 1999 Computer-supported Collaborative Learning: A Review (The J.H.G.I. Giesbers Reports on Education, Number 10). University of Nijmegen, Department of Educational Sciences, Nijmegen, The Netherlands
  16. Levenson W B 1945 Teaching Through Radio. Farrar and Rinehart, New York
  17. Papert S 1980 Mindstorms, Children, Computers, and Powerful Ideas. Basic Books, New York
  18. Roschelle J, Kaput J 1996 Educational software architecture and systemic impact: The promise of component software. Journal of Educational Computing Research 14: 217–28
  19. Roschelle J, Pea R D 1999 Trajectories from today’s WWW to a powerful educational infrastructure. Educational Researcher 28(5): 22–5
  20. Salomon G 1992 Effects with and of computers and the study of computer-based learning environments. In: De Corte E, Linn M C, Mandl H, Verschaffel L (eds.) Computer-based Learning Environments and Problem Solving (NATO ASI-Series F: Computer and System Sciences Vol 84). Springer-Verlag, Berlin, pp. 249–63
  21. Salomon G, Gardner H 1986 The computer as educator: Lessons from television research. Educational Researcher 15(1): 13–19
  22. Scardamalia M, Bereiter C 1998 Web Knowledge Forum. User Guide. Learning in Motion, Santa Cruz, CA
  23. Scardamalia M, Bereiter K, Lamon M 1994 The CSILE Project: Trying to bring the classroom into world 3. In: McGilly K (ed.) Classroom Lessons: Integrating Cognitive Theory and Classroom Practice. Bradford Books MIT Press, Cambridge, MA, pp. 201–28
  24. Scardamalia M, Bereiter C, McLean R S, Swallow J, Woodruff E 1989 Computer-supported intentional learning environments. Journal of Educational Computing Research 5: 51–68
  25. Seidel R J, Park O C 1994 An historical perspective and a model for evaluation of intelligent tutoring systems. Journal of Educational Computing Research 10: 103–28
  26. Vosniadou S, De Corte E, Glaser R, Mandl H (eds.) 1996 International Perspectives on the Design of Technology-sup-ported Learning Environments. Erlbaum, Mahwah, NJ
  27. Wenger E 1987 Artificial Intelligence and Tutoring Systems. Computational and Cognitive Approaches to the Communication of Knowledge. Morgan Kaufmann, Los Altos, CA
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