BBC Documentary menelusuri keberuntungan Keluarga BUSH. Walau banyak para komentator mengatakan bahwa sebenarnya Bush tidak begitu spesial, tidak begitu smart, namun bagaimana Keluarga Bush bisa tetap memimpin Amerika. Dokumenter ini mengungka skandal-skandal keluarga Bush untuk mempertahankan kekuasaan mereka.
Shelina Janmohamed on BBC1 Heaven and Earth Show.
Shelina guests as a panelist and guest of Gloria Hunniford speaking about religous rights, the divine feminine and more…
Outfoxed examines how media empires, led by Rupert Murdoch’s Fox News, have been running a “race
panel of stem cell researchers from UCSF, two of UCSF’s Nobel laureates and visiting Nobel laureate Arvid Carlsson of Sweden discuss the future of stem cell research
As indicated in sociocultural literature that learning is embedded in social practice within a community. Students are active participants seeking help from peers, teachers and others who may share problems and interests. In a community they help each other and have access to resources to make sense of information and ideas. With the advance of the Internet technology and the availability of Virtual Learning Environments in particular, from sociocultural perspectives, students’ learning should have been transformed. This is, however, just an emerging field. It is important to investigate the evidence found in published research reports on how this advancement has contributed to and transformed learning processes. As Salomon (2000) points out, “millions of words have been written about the technology and its potential, but not much about the teachers and learners actually do online” (p. 11).This section is to provide an overview of the existing literature on learning in Virtual Learning Environments in higher education to articulate what is currently known about students’ participation in web-based learning environments both in formal like WebCT and Blackboard and broader environments, the access to the vast WWW. In particular, the review focuses on research about how students used the VLEs to facilitate and transform their learning. This review is to some extent a follow-up of Salmon’s claim above. As the time elapses this section is searching for the what-learners-actually-do-online from published research. The literature describing online learning, claims of benefits, advocacy, and success stories is huge in number but lack evidential research perspectives. Many articles appeared in research journals, conference proceedings, and book chapters are provocative and promotional. Such articles are not presented as a finding of research but rather as a belief or interpretation made by the authors, and thus they are excluded in this review. Materials like how-to books, institutional policy on online learning, and studies of online infrastructures are also excepted. In addition, studies that report comparative research between face-to-face and online format are not considered in this review as this study is not interested in separating between face-to-face and online environments; they are complimenting each other. This study argues that research separating face-to-face and virtual environments is misleading not only have the Web-based environments become parts of daily life, they are parts of most universities’ culture (Bayne, 2005; Bonk, 2004), observing only one environment and eliminating the other will result in incomplete picture of learning processes.To obtain more comprehensive coverage, this review includes both research traditions: quantitative and qualitative. Statistical research is helpful to survey the size of population (portion/quantity) that has (successfully) participated in Web-based environments. On the hand, a qualitative case study details what actually has happened when students use the Internet for their learning. Such study usually reports anecdotes from student’s perspectives that would be useful to depict what is currently known about students’ participation in web-based learning environments. The primary sources of literature were journals, proceedings and book chapters on educational technology. The starting point was the journals and proceedings that directly address ICT in education such as: Journal of Computer Assisted Learning, British Journal of Educational Technology, Internet and Higher Education, Interactive Learning Environments, Journal of Interactive Online Learning, Proceedings of Advances in Web-Based Learning, CSCL, and ASCILITE. The searches were expanded by following promising citations in bibliographies of key articles and in previous literature reviews.This is not, of course, a complete review. However, it represents a comprehensive search that covers most recent materials published from late 1990s; the research published earlier mostly covered stand-alone computers and therefore they are not relevant to review here. This review will be discussed in two broad categories: Communication and Content as shown in VLEs’ axis (Figure 3.5). The Communication category traces research investigating students’ interaction among them and with their teachers/instructors within a formal Community of Learners (CoLs) as well as their interaction with broader communities. The Content category searches for research investigating student’s uses of the Internet to locate information for their study.
Students’ participation in VLEs can be traced from their communication with their communities. The availability of transcript and log files has mad it possible to study student behaviour when participating in discussions or social interaction. Goldman et al. (2005) argue that students who participate in online forum by reading or posting their ideas would lead them to the examination of their existing understanding which would lead to learning.Researchers in this field generally agree that mixed method multidimensional analysis is necessary to provide in depth understanding. To date, several researchers has attempted to develop systematic methodologies in analyzing students’ communication in online environments. This review found that there are four major methodologies researchers used to analyze online interaction: content analysis, social network analysis, survey, and interview.
Henri (1992) is a pioneer in the development of content analysis. She identified five key dimensions for analysis of online discussion, namely, (1) participation rate, (2) interaction, (3) social cues, (4) cognitive skills, (5) metacognitive skills and knowledge. Another model proposed by Gunawardena, Lowe, and Anderson (1997) was developed to measure social construction of knowledge in an online debate context. They developed the model as co-construction of knowledge within five progressive phases: sharing information, comparing information, discovery of dissonance, negotiation of meaning, modification of synthesis, and application of newly constructed meaning. The other seminal model is designed by Newman, Webb, and Cochrane (1995). They based their design on Garrison’s (Garrison (1992) cited in Newman et al., 1995) five-stage critical thinking with 40 indicators. Once a passage is coded, one can calculate the critical thinking index as “CT=(x+ – x-)/(x+ + x-)” (Newman et al., 1995, p. 70). Other typologies like Burnett (2000), Salmon, (2000), and van Dijk (as cited in Mazur 2004) all formulate how online conversation can be analized to find empirical evidence of higher-order and critical thinking in CMC messages.
Bayne, S. (2005). Deceit, desire and control: The identities of learners and teachers in cyberspace. In R. Land & S. Bayne (Eds.), Education in cyberspace (pp. 26-41). London: Routledge Falmer.
Bonk, C. J. (2004). The perfect e-storm: Emerging technology, enormous learner demand, enhanced pedagogy, and erased budgets. London: The Observatory on borderless higher education.
Burnett, G. (2000). Information exchange in virtual communities: A typology. Information Research, 5(4).
Goldman, R., Crosby, M., Swan, K., & Shea, P. (2005). Qualitative and Quisitive Research Methods for Describing Online Learning
In S. R. Hiltz & R. Goldman (Eds.), Learning Together Online Research on Asynchronous Learning Networks (pp. 103-120). New Jersey: Lawrence Erlbaum Associates.
Gunawardena, C. N., Lowe, C. A., & Anderson, T. (1997). Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing. Journal of Educational Computing Research, 17(4), 397-431.
Hara, N., Bonk, C. J., & Angeli, C. (2000). Content analysis of online discussion in an applied educational psychology. Instructional Science, 28(2), 115-152.
Henri, F. (1992). Computer conferencing and content analysis. In A. R. Kaye (Ed.), Collaborative learning through computer conferencing (pp. 117-136). Heidelberg: Springer.
Newman, D. R., Webb, B., & Cochrane, C. (1995). A Content Analysis Method to Measure Critical Thinking in Face-to-Face and Computer Supported Group Learning. Interpersonal Computing and Technology, 3(2), 56-77.
Ng, K. C., & Murphy, D. (2005). Evaluating interactivity and learning in computer conferencing using content analysis techniques. Distance Education, 26(1), 89-109.
Salmon, G. (2000). E-moderating: the key to teaching and learning online. London: Kogan Page.
Brown, J. S., & Gray, E. S. (2004). Introduction. In M. L. Conner & J. G. Clawson (Eds.), Creating a Learning Culture: Strategy, Technology, and Practice. Cambridge: Cambridge University Press.
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“learning is fundamentally social and, second, that learning about is quite different from learning to be, which is a process of enculturation”. “Building on observations in workplace, school, and craft settings, IRL researchers noted that successful learning happens with and through other people and that what we choose to learn depends on who we are, who we want to become, what we care about, and which communities we wish to join. In this frame, learning is also a matterof changing identity, not just acquiring knowledge. Learning of this nature occurs primarily through the process of gaining membership in a community of practice and is critically enabled by what Jean Lave and Etienne Wenger described as “legitimate peripheral participation”. In this sense the people is one of learning environments.
Practice is not merely the measure of learning but the medium of it.
Words, books, simulations, tool-kits, and the like are artifacts deliberately crafted to transfer knowledge byevoking practice in the participant; they are not the knowledge itself. Of course the current technology is crafted for learning culture
p.4
“Work Is Personal . . .Computing Is Social . . . Knowledge Is Power” blared the cover art. “Learning is about work, work is about learning, and both are social,”
p.6
approach to global knowledge sharing … Learning is clearly no longer synonymous with individual mastery
the culture being created by kids who grew up digital.
Due to a far-reaching diffusion of computers, networks and multimedia technologies throughout different sectors of society, issues of how information and communication technology (ICT) relate to learning, have become widely discussed during the last few decades. Moreover, the emergence of a global economy where material goods have ceased to be the most important product in favour of information and knowledge, have naturally resulted in a debate on what kind of educational practices that can prepare students for the future work place. A particularly important concern in research and development, relates to whether the insertion of technology into educational practices can enable students to learn better, faster or perhaps differently than before. A concern with the potential benefits of technology with respect to learning is understandable, among other things because considerable investments in technological equipment, support and maintenance of networks and computers along with the development of teachers’ skills and competences, are required. On the other hand, it is important to emphasize that these changes in technology, culture and society, bring with them a whole new set of opportunities for the development of thinking and learning processes. For example, the development of new artefacts such as portable and networked computers, can, potentially, transform the ways that personal and institutional tasks are carried out, the ways we communicate and coordinate our activities with other people, and the ways we engage with our material and cultural surroundings (Säljö, 1999). However, to introduce ICT into educational settings in order to facilitate the development of students’ thinking and learning skills, is not a straightforward matter. Thus, it is not likely that ICT in and by itself will bring about these changes. On the contrary, a whole range of personal, institutional and pedagogical concerns are made relevant when ICT is in place to enrich learning environments. The topic of this thesis is precisely how the technology-rich environment could transform educational practices in general and learning processes in particular. More specifically, this study seeks to examine the education students’ participation in their faculty virtual learning environments by uncovering the activities and online facilities they had and the way they appropriated them for their learning.To serve this topic, the outline of this chapter is as follows: First, in order to provide a certain background to the recent emergence of virtual learning environments, this section will give a historical survey of research on technologies (computers) for learning where the computer metaphors are evaluated. Given the declared interest in social dimension of learning processes of this study, the next section will conceptualize the social nature of computer experience. Then, in order to clarify the relationship between computer tools and the process of learning, the next section will offer a brief account of relevant research on learning in the VLEs contexts. This section should present the main research findings, focusing more specifically on research on higher education. Finally, and in order to specify and make explicit the theoretical and methodological approach, a more detailed discussion of one particularly relevant study is provided.
Educational technologists have offered modes for computer use in educational purposes. Taylor (1980) identified three principal modes for computer use: tutor, tutee, and tool. Higgins (1984) came up with a two-way classification of roles called magister and pedagogue, while Warschauer and Healey (1998) have based their classification on the use of computers in language learning: Behavioristic CALL, communicative CALL, and integrative CALL. In addition, Koschmann (1996) identify four different paradigms: (a) Computer Assisted Instruction (CAI), (b) Intelligent Tutoring Systems (ITS), (c) Logo as Latin and (d) Computer Supported Collaborative Learning (CSCL). All these classification are overlapped in many ways but render their discussion on the intertwined link between instructional technologies and theories of learning. Koschmann (1996) contends that ‘the shifts that have occurred in IT were in fact driven by shifts in underlying psychological theories of learning and instruction’ (1996, p. 3)[1]. According to Koschmann (1996) the paradigms should not be perceived as different stages in a developmental trajectory. Thus, all of the paradigms are, to a varying degree, still present in research and design. What is more, the boundaries separating the different perspectives are not clear cut, and even within the paradigms different theoretical and methodological approaches can be discerned. For the purpose of the study, Koschmann (1996) paradigms are the most relevant as he embrace the features of Virtual Learning Environments.
This section concerns a form of computer software that reproduces a traditional model of teaching and learning. Cuban (1986) reminds us that the enterprise of marrying educational practice with contemporary technologies has a long history. Yet it was not until the 1950s that people began to entertain the concept of a “teaching machine” – in the sense of a mechanism that directly gives instruction. Such a computer would not be simply something that teachers employed to illustrate or elaborate their teaching. The computer takes the place of the teacher, in asking the question and giving feedback. To a significant degree it could take over, wholesale, what a teacher does. This mode of computer is called CAI, Computer Assisted Instruction, as the emphasis is put on that the technology gives the instruction.
CAI is founded on behaviourist learning principles, where knowledge is conceived as something transmitted to the learner through a step wise procedure with a corresponding management of different systems for reinforcing correct behaviour (Cooper, 1993). For this reason this mode of computer is called tutor computer by
Taylor (1980) and Behavioristic CALL by Warschauer and Healey (1998).
Koschmann (1996) traces the emergence of the CAI paradigm to the early 1960s. It should be noted that such software is popular despite criticisms from educational theorists. In fact, the appeal of CAI may, in part, be sustained by one particular perspective on the nature of teacher-pupil dialogue, a form of classroom interaction characterised as I-R-E sequences (Medina, 2001; Mehan, 1979), the form of a (teacher) Initiation, a (pupil) Response and a (teacher) Evaluation.
Ethnographers of classroom discourse report such sequences are commonplace (Cazden, 2001). It is, of course, a form of talk into which pupils become socialized and which we recognize as peculiarly characteristic of school experience. We accept its features, perhaps without much reflection: the ritualistic nature of the exchange, the idea of people asking questions to which they know the answer, the expectation of evaluative feedback, and so on. It is clearly something that happens when teaching is in progress (Cazden, 2001). It might also be something that could happen within a dialogue arranged between a pupil and a computer: “The computer initiates, the student replies, the computer evaluates, the computer initiates again, and so on” (Levin et al, 1990 p. 210). This mode is quite common within CAI.In this model, specific computer programs are designed in order to instruct a specific skill, such as multiplication or reading comprehension quizes. From behaviorism perspective, “development progresses from simple behaviors to more complex ones” (Salkind, 2004, p. 163). Therefore, the learning process is constituted as a stepwise procedure, where the user receives a response when he or she has accomplished a required step in the sequence. The design of such programs implies that a specific goal for the skills and knowledge that is to be learned has to be formulated and subsequently broken down into specific goals that correspond to certain forms of behavior (Salkind, 2004). A behavioral response is treated as the dependent variable, while the technological system or specific aspects of the system works as the independent variable. The main concern in research is to estimate the instructional efficacy of different computer applications.
The more advanced versions of such CAI are sometimes termed Intelligent Tutoring Systems (ITS). The “intelligence” of an ITS system would reside not merely in its programmed expertise for the domain of knowledge, but it would also be able intelligently to diagnose the learner’s needs and, then, intelligently to implement an individualized tutorial dialogue. In this regard, this kind of computer is still classified as computer as tutor by Taylot (1980).The design of Intelligent Tutoring Systems is founded on cognitive psychology (Koschmann, 1996), which is an approach where, to put it simple, the mind is conceived as an information processing device. Consequently, it is vital to design technologies that facilitate information processing, and, by the same instance, the construction of robust mental representations of problem spaces. A problem space consists of an initial state and a preconceived goal and a mental representation of the operations required reaching that goal. Instruction consists of arranging activities which facilitate the acquisition of such a correct mental representation. The system is relevant to one particular enthusiasm closely associated with computer-based education: namely, the goal of creating a strongly individualized curriculum. The preoccupation of ITS enthusiasts has been with the possibility of seriously individualizing the curriculum – a teaching technology sensitive to individual learners. Technologies are designed in order to provide appropriate feedback on students’ problem solving and reasoning. The tool responds when the student provides an answer which is wrong according to the scripted set of actions inscribed into the technology. These scripted sets are often modeled on how experts in a particular knowledge domain reason and solve problems. However, incorporating this kind of computer as a vehicle for practice has its own problem. In particular, marginalising certain activities in the way that can happen with computers, may serve to undermine their impact. Something of value may be lost where such activities are not fitted into a mainstream of class learning. The limit to computers functioning as tutors arises not just because tutorial dialogue is hard to simulate at the moment-to-moment level of conversation. This is due to the fact that effective tutorial dialogues are embedded in more extensive contexts of shared classroom experience. a richness of context, however, will be very hard to reproduce mechanically. This is the concern that this study has; learning is situated in the context.
A failure to incorporate situatedness of learning within the computer-as-tutor strategy are apparently jeopardizing opportunities to do genuinely new things through the mediation of computers. The technology is believed to have capability of supporting distinctively challenging and innovative activities, as well as re-formatting more familiar tasks (Säljö, 1999; Wertsch, 1998) dan Cole (2002). This is an observation commonly deployed to justify and encourage implementations conceived according to the next paradigm, Logo as Latin.
The most widespread practical realization of computer-as-tutor like CAI and ITS is widely criticized by educationalist as constraining the learner’s experience. Papert (1980), in particular, argues that using CAI/ITS or computer as tutor, a student is controlled by the technology rather than vice versa. Papert’s vision of the computer in education offered possibility of shifting from more teaching-centered to more learning-centered practices. In his book Mindstroms (1980) Papert offered something of this potential. Papert not only denied the tradition of computers in control of students, he proposed an alternative in which that relation would be reversed: students would control the machines, for instance, in his LOGO program. The Logo as Latin paradigm is about how students can learn by constructing their own computer programs. Constructing means teaching the computer or programming it to do something. As in the Logo as Latin paradigm a computer is used by teaching it, Taylor (1980) classifies this computer use as tutee or pupil by Cozens (2001). Why this computer is called pupil or tutee will be clearer later.Grabe (1985) argues that the use of a computer in this sense can provide a rich and positive learning environment in which the student can engage in the active cognition processing necessary to develop particular learning skills. In other words, the ways in which a student teaches the computer would entail especially potent learning experiences. The idea is captured well in Papert’s notion of a microworld (1980). Papert refers to a microworld as a growing place for a specific species of powerful ideas in intellectual structure. The Logo environment has allowed Papert to provide a concrete example of geometry microworld. Within this environment, students are free to explore and created their own understanding of geometric concepts. In microworld, students construct new understanding through their exploratory activity. It suggests an important theoretical influence, namely, constructivist epistemology, implying that students learn best when they themselves construct knowledge and discover solutions to problems(Koschmann, 1996). First, the notion of the learner as necessarily active is strongly endorsed. A microworld is a place where things are getting done: in Papert’s realizations, such action means to teach computers to do something interesting – the computer is thus the “pupil” in this role. Another important principle defining the microworld environment is that it should be somewhere that maximizes the experience of discovery. Some writers like Maddux and Johnson (1988) claim that to put a child in a Logo environment is to provide the child with a constructivist experience. Advocates of discovery learning concur with Piaget’s assertion that “each time we prematurely teach a child something he would have discovered for himself, the child is kept from inventing it and consequently from understanding it completely” (Piaget, 1970, p. 715).For Papert, Logo exemplifies ‘powerful ideas’: ideas that can be mobilized very generally for problem solving. He supposes that the opportunity to exercise them in some concrete (computer-based) activity allows them to surface sufficiently clearly that the learner can directly contemplate them. Such reflection will help these skills become more readily available in other problem solving domains. Treating the computer as a “pupil” in Papert’s sense (programming it) is, thus, taking an opportunity to cultivate general problem solving skills.It is assumed that the construction of computer programs, when a child teaches the computer, will result in the development of generic cognitive skills, which are transferable to other knowledge domains. To examine what kind of problem solving strategies that affords certain solutions as well as the characteristics of strategies that enable transfer to other domains, are important objectives in research on Logo. It is from here this paradigm is being criticized.Several researchers and theorists investigated Papert’s claims and found them lacking (Sloan 1985; Pea and Sheingold 1987; Hughes 1990). A large scale research project evaluating the claims of Logo in classrooms was undertaken by Roy Pea and his colleagues in the mid-1980s (Pea and Kurland 1987; Pea, Kurland, and Hawkins 1987), concluding that no significant effects on children’s cognitive development could be confirmed, and calling for much more extensive and rigorous research among the excitement of Logo. Much of the criticism, however, has come from the ‘outsider’ perspective: the cognitive psychology. In general, the criticism aims to identify and account for the cognitive “effects of” (Pea and Kurland 1987) and the “effects with” (Salomon, Perkins, and Globerson 1991) computers and computer programming, and the possibility of cognitive or instructional “transfer” (Koschmann, 1996, p. 10). But these attempts tend to instrumentalize the technology and practices surrounding it. Papert’s plea was for the recognition of the generative and cultural possibilities from within, rather than looking to evaluate a technology by external criteria. Perhaps the biggest flaw of Papert’s Logo paradigm is the least attention to the social nature of learning. All attention when a student is working on a Logo program is paid to the computer programming.If learning is social in nature, the attention to the ‘learning environments must be important. One such perspective on learning environments, and an innovation within educational theory attracting many people nowadays, is the concept of “community of learners.” The common characteristic of this concept is that people are learning resources for each other. The objection toward the concept of learning environments starts only when it is not taken into account how people are learning resources for each other, and how artifacts are involved in the interactional play of instruction-and-learning.Very close to the concept of it is the idea of “community of practice” (Lave and Wenger 1991). In the opening of their book, Lave and Wenger claim that “the meaning of learning is configured through the process of becoming a full participant in a community of practice.” They stress that they choose the concept of legitimate peripheral participation specifically “to draw attention to the point that learners inevitably participate in communities of practitioners.”(1991, p. 29) Later (in Chapter 4) they explain that “structuring resources for learning come from a variety of sources, not only from pedagogical activity.” Therefore, they focus their attention on “the structure of social practice rather than privileging the structure of pedagogy as a source of learning.” This structure of social practice encompasses access to different resources, e.g. technological artifacts, human resources as well as access to practice. Proponents of constructionism have also recently underlined the importance of communities of practice. In the introduction of the book Constructionism in practice.Designing, thinking, and learning in a digital world Kafai and Resnick (the students of Papert) write: “The idea of community has always been present in the constructionist vision. In Mindstorms, written in 1980, Papert discussed the Brazilian samba school as an example of a community of learners. But many of the early constructionist studies focused primarily on the development of the individual learner. It is only in recent years that idea of community has emerged as a major theme in constructionist research.” (1996, p. 6)In his conception of constructionism Papert attaches special importance to the learning environment. “The construction that takes place ‘in the head’ often happens especially felicitously when it is supported by construction of a more public sort ‘in the world’ – a sand castle, a Lego house or a corporation, a computer program, a poem, or a theory of the universe. Part of what I mean by ‘in the world’ is that the product can be shown, discussed, examined, probed, and admired. It is out there.” (1993, p. 142)Gregory Gargarian, also a constructionist, has pointed out that the notion of microworlds was invented by Papert as an “answer to critics of Logo’s discovery learning. The main arguments of the critics were this: ‘Discovery learning is fine: it may even be the best way to learn. However, it takes too much time. If it took the whole of human history to bring us to our present knowledge, how can we expect children to ‘discover’ this knowledge on their own?’ Microworlds provide the means to control what is discoverable without giving up discovery learning.” (Gargarian, 1996, p 151)The challenge is to discover how this computer use is to be redefined, that in turn, may require incorporating collaboration that Logo-as-latin affords.This section on computers-as-pupils has reached one conclusion very similar to that reached in the discussion computers-as-tutors above. In each case, the implementation of the computer activity may too easily encourage a distancing of social involvement of the students; or, more generally, a dislocation from the normally rich context of class-based activity and discussion. This is a threat to the social quality of learning experiences: one to which this study gives more attention.Conceptions of computers as tutors and as pupils have been important in determining the most common patterns of use. However, there is another metaphor with wide appeal to social nature of learning.
In the CSCL paradigm, which started to emerge in the late 1980s and early 1990s, the locus of study is on how technologies work as a mutual point of reference in collaborative activities (Koschmann, 1996; O’Malley, 1995). Collaboration can go on both through and around computers and different kinds of texts, models, video, animations, micro worlds and so forth, can work as resources for collaborative inspection and deliberation. Regarding technological design, CSCL applications enable users to collaborate in computer mediated environments where different resources scaffolding students’ joint construction of knowledge are made available. According to Koschmann (1996, p. 11), CSCL is founded on disciplines such as anthropology, sociology, language sciences and communication studies, disciplines which are all concerned with understanding the role of language and culture. Consequently, learning is conceived as interconnected with language, culture and the social and material ordering of the settings in which people learn.18 Consequently, cognition emerges in situations where people use artefacts to accomplish certain goals. Regarding design, it is therefore just as pertinent to focus on how learning situations are designed as on how specific artefacts are put together. According to Koschmann (1996), research questions in the CSCL paradigm may be about how competence, skills and learning are reflected or constituted in the language of learners, how cognitive processes interact with social factors in learning activities, and how technology is used as part of collaborative activities. As Koschmann puts it: ‘the central focus for research in CSCL is on instruction as enacted practice’ (1996, p. 14, Italics in original). A whole range of qualitative techniques are employed in order to examine these questions, such as interviews, observations, texts and records of interaction. However, also quantitative techniques involving measures of participation structures, frequency of certain speech acts, or the relation between certain forms of participation and various outcome measures, are employed. Cazden, C. B. (2001). Classroom discourse: The language of teaching and learning (2nd ed.). Portsmouth, NH: Heinemann.
Cooper, P. A. (1993). Paradigm shifts in designed instruction: From behaviorism to cognitivism to constructivism. Educational Technology, 33, 12-19.
Cozens, P. (2001). But I’m a teacher, not a programmer. Paper presented at the Technology in Language Education: Meeting the Challenges of Research and Practice, Hongkong and Nanjing.
Cuban, L. (1986). Teachers and Matchines: The classroom use of technology since 1920. New York: Teachers College Press.
Grabe, M. (1985). Evaluating the educational value of microworld. In S. Harlow (Ed.), Humanistic perspectives on computers in the schools (pp. 35-44). New York: The Haworth Press.
Koschmann, T. (1996). Paradigm shifts and instructional technology: An introduction. In T. Koschmann (Ed.), CSCL: Theory and Practice of an Emerging Paradigm. Mahwah, New Jersey: Lawrence Erlbaum Associates Inc.
Maddux, C. D., & Johnson, D. L. (1988). Logo: Methods and curriculum for teachers. New York: The Howthorn Press.
Medina, P. (2001). The intricacies of Initiate-Response-Evaluate in edult literacy education. Paper presented at the 2001 AERC ( the Adult Education Research Conference), Michigan State University.
Mehan, H. (1979). Learning lesson social organization in the classroom. Cambridge, MA: Harvard University Press.
Papert, S. (1980). Mindstroms: Children, computers, and powerful ideas. Sussex: The Harvester Press.
Piaget, J. (1970). Piaget’s theory. In P. Mussen (Ed.), Carmichael’s manual of child psychology (Vol. 1, pp. 703-772). New York: John Wiley & Sons.
Säljö, R. (1999). Learning as the use of tools: A sociocultural perspective on the human-technology link. In K. Littleton & P. Light (Eds.), Learning with computers: Analysing productive interaction (pp. 144-161). London: Routledge.
Salkind, N. J. (2004). An introduction to theories of human development. Thousand Oaks: SAGE Publications.
Taylor, R. (1980). The computer in the school. New York: Teachers College Press.
Wertsch, J. V. (1998). Mind As Action. Oxford: Oxford University Press.
[1] IT in this quotation refers to instructional technology.
