FROM :

INTERNATIONAL HANDBOOK OF INFORMATION
TECHNOLOGY IN PRIMARY AND SECONDARY EDUCATION


Ronald E. Anderson
University of Minnesota, Minnesota, MN, USA

The Information Society

The metaphor of “information society” was first used in Japan by Kohyama (1968) and it was in Japan that this metaphor was first used as a rationale for national policy (Masuda, 1981). In the 1970s, the authors of computer-related texts were not likely to refer to an “information society” but instead used words like “information age” and a “computerized society” (cf. Martin and Norman, 1970; Rothman and Mosmann, 1972). However by the late 1970s and early 1980s, the information society was mentioned so often around the world that many forgot that it was only a metaphor.
In fact by the late 1980s, “information society” had become a phrase that captured the essence of a culture inundated by information and dominated by information technology (IT). Daniel Bell’s “framework for the information society” spearheaded the movement to legitimize the information society concept (Bell, 1979). He confirmed that a majority of the jobs in the United States were information oriented in that they were structured to produce informational rather than material products. In subsequent years, as global networks became ubiquitous and a global information economy became more obvious, the information society metaphor became even more widely accepted (Webster, 2002).

The Knowledge Society

Ironically, the information society concept was undermined by the emergence of a new metaphor in the 1990s, the “knowledge society.” While the information society metaphor was associated with an “explosion” of information and information systems, the knowledge society metaphor primarily referred to economic systems where ideas or knowledge functioned as commodities. Many, if not most, people could not differentiate the two concepts because they tended to largely equate information and knowledge (Allee, 1997). Confusion about the nature of knowledge is still a problem, especially in the field of education. The educational community tends to define knowledge mostly in terms of facts or declarative knowledge, but the field of management defines it much more broadly encompassing insights, values, and other tacit cognitions (Tiwana, 2002). In this chapter, the broader definition of knowledge will be used.

Information vs. Knowledge

Increasingly, the definitional distinction of information from knowledge is that information consists of intentionally structured and formatted data, but knowledge consists of cognitive states needed to interpret and otherwise process information (cf. David and Foray, 2003). While information can generally be reproduced for minimal costs, knowledge reproduction requires training, apprenticeships, and other more costly forms of transmission. Knowledge that is difficult to codify and reproduce is called “tacit knowledge.” Tacit knowledge includes judgment, experience, insights, rules of thumb, and intuition and its retrieval depends upon motivation, attitudes, values, and the social context (cf. Polanyi, 1996; Tiwana, 2002).
A knowledge economy necessarily depends upon information as well as the intellectual capital of economic communities. Thus, a knowledge society necessarily presumes an information society, but not the other way around. In this chapter’s discussion of education, the rhetoric of the knowledge society will be used, but for the most part it will apply to the information society as well.

Knowledge Societies in Education

While economists tend to think of “knowledge society” as a global economy, other social scientists tend to think of it as a smaller level social collective. Thus, a knowledge society may exist on at least four levels: a global system, a national or cultural system, a social organization like a professional society, and a smaller community, e.g., the “Dead Poet’s Society.” A knowledge society is generally defined as an association of people with similar interests who try to make use of their combined knowledge. Of course, knowledge societies are not new, but what is new is that there has been a sharp rise in them and they are much more visible. Their rise follows digital networks that make them possible without members coexisting (do you mean residing?) in the same region and the technology makes accessing and sharing knowledge so much more feasible. On top of that is the pressure to exchange knowledge that emerges from the knowledge economy.
Loosely speaking, any educational system is a knowledge society, and that would include schools and classrooms. However, unless the educational unit devotes particular attention to knowledge-related activities, it is not particularly useful to call it a knowledge society. When an educational group invests considerable effort toward sharing and producing new knowledge, then it should be called a knowledge society. Communities of practice, typically groups of teachers that work with each other to improve their teaching, are good examples of knowledge societies, especially those that use all the tools, electronic and otherwise, to facilitate their goals (cf. Hargreaves, 2003).
“Knowledge society” in the next section refers to the (global) knowledge society.
Later sections of the chapter shift toward smaller scale knowledge societies.

Implications of the Knowledge Society for Learning Priorities

The contemporary currents of the knowledge society derive from two major forces: greater intercultural interaction made possible by global electronic networks and an economic system in which knowledge functions as a commodity. Underlying the new role of knowledge in society is, on the one hand, an explosion of information and knowledge, and on the other hand, a greatly increased value for knowledge that helps people get what they most want. Table 1 shows the major implications of the global knowledge economy for the skills and learning strategies of young people, particularly those entering the work force. For instance, making knowledge a commodity means that youth needs the skills to construct new knowledge, and project-based learning offers opportunities for learning such skills.

Another characteristic of the knowledge society is a much faster pace of change in what is known and what is institutionalized. The second row in the table suggests that young people need adaptation skills and access to on-demand information systems. They can expect that it may be necessary to be highly mobile occupationally, switching among jobs, if not careers. It is no longer possible to keep up with all the information and knowledge in a field, and employers are more preoccupied with how well a prospective worker is able to learn than how much he/she knows already. The explosion of information implies using systems that require new skills for accessing, organizing, and retrieving information (Spitzer et al., 1998). Generally, our information resources are poorly organized and poorly evaluated, which means that there is a premium on the ability to manage information and critically evaluate it, and on information and communication technology (ICT) skills, including basic utilization as well as database design and application. Furthermore, since knowledge is increasingly collective, it is necessary to learn collaboration skills and spend more time working in teams (Brown and Duguid, 2000).
ICT and the rapidly evolving knowledge society pose a difficult challenge to educators and policy makers. Ideological interest groups have formed around different proposals for addressing the future, and each group develops its own rhetoric. Examples include lifelong learning, distance education, schools as learning organizations, constructivism, student-centered learning, high-performance learning, project learning, digital divides, and so forth.

ICT

As noted already, ICT stands for information and communication technology and refers in principle to all technologies used for processing information and communicating. In most educational circles, it means computer technology, multimedia, and networking, especially the Internet. Educators in the United States and a few other countries use the term “technology” or “information technology” instead; however, this appears to be changing to include ICT. In business and industry, the most common label is IT, but sometimes the terms “new media” or “digital media” are used. This semantic diversity derives from the rapidly evolving integration of computers with communications, video, and audio technologies, where the separate technologies become nearly indistinguishable. In this discussion, the acronym ICT is used, recognizing that it means the same as IT or technology to many.
The scope of ICT is dynamic and continuously changes with the creation of new technologies. At one time, technology referred only to hardware, now it includes software techniques as well. Daily invention of new technologies provides a major challenge to implementation of ICT-based educational strategies. Given the skyrocketing pace of new ICT in the past decade, it would not be surprising in the next 5
years to see whole new forms of e-commerce such as Internet auctions or radically new ways to do homework using personal software agents that roam the Internet. It is imperative to track such developments because not only do they change the skill requirements for students, but also they impact society and change research priorities for research on ICT and education internationally.

The Twenty-First Century Skills Movement

The 1990s witnessed heightened attention to globalization, rapid change, and information economies. Policy decision makers in many countries began adopting the rhetoric of the information society, the knowledge society, and twenty-first century skill requirements. The United Nations Educational, Scientific, and Cultural Organization (UNESCO, 1999) on “Task Force on Education for the Twenty-First Century,” the European Union’s project, i2010, on “A European Information Society for Growth and Employment” (i2010, 2007), and the “Okinawa Charter on the Global Information Society” of the G8 world leaders (G8, 2000) all reflect the movement at all levels of policy making.
Now, the twenty-first century skills movement in the United States is led primarily by an organization called the Partnership for 21st Century Skills (2007). Many other organizations have written similar frameworks and position papers defining and promoting reform that moves education toward goals that specify what are called “twenty-first century skills.” They include the North Central Regional Educational Laboratory (NCREL, 2002), Edutopia (Pearlman, 2006), the 21st Century Literacy Conference (New Media Consortium, 2005), and the Australian Department of Education, Science, and Training (2005).
The content of the twenty-first century skills reports is summarized in Table 2
where key themes are listed.
Each report emphasizes different themes. The Partnership for 21st Century Skills stresses critical thinking and life skills, the Edutopia report emphasizes collaboration, the NCREL report puts heavy weight on high student productivity, and the Australian report emphasizes life skills, which it calls “enterprise skills.” In general, the reports reveal considerable consensus and consistency.

While the next century skills rhetoric now is predominantly used in the United States, support for this framework can be found in many countries including Australia, Thailand, and Oman. The majority of the twenty-first century reports address education in general; however, a few, which are not described here, are primarily oriented toward vocational education. The most notable examples of vocationally oriented initiativesare the WorldSkills project (http://www.worldskills.org) and the e-Skills Certification Consortium (eSCC) (http://www.e-scc.org/default.aspx) organization.

As shown in Table 4, the twenty-first century reports consistently emphasize the following educational outcomes for students, and workers of the twenty-first century will have expanded needs for skills in the following areas:
– Communication. Constructing logical arguments, reasoning from diverse evidence and sensitivity to audiences are essential to the outcomes of most projects. Using ICT tools when effective is critical as well.
– Creativity in knowledge generation. It is claimed that innovation is a critical need for the knowledge society. Creative, new knowledge solutions yield bottom line results and help solve problems with organizations of all kinds.
– Collaboration. Knowledge-intensive organizations require teamwork as well as coordination. Networks and network-based tools have become prerequisites to cooperative work.
– Critical thinking. Despite attempts to teach information literacy in schools, students often have not learned to critically evaluate knowledge and knowledge claims.
– ICT literacy. New literacies in the digital age lie at the foundation of preparing students for the next century. Technology may become obsolete but contemporary work cannot be efficient without standard productivity software and tools to augment the human intellect.
– Life skills. Life skills for the next century consist of those of the last century (e.g., ethics, leadership, accountability, and self-direction) as well as those which have become more relevant (e.g., personal productivity and personal responsibility).
In reviewing educational outcomes that are recognized as high priority for the twentyfirst century, it becomes clear that they coincide with requirements for knowledge societies. It would appear that the twenty-first century movement is predicated on knowledge and information society concepts and concerns.

Parallels in Education and Management

It is not accidental that the leading edge thinking about both education and organizational management tends to focus upon similar issues. Both attempt to anticipate the future where new forms of ICT are ubiquitous and knowledge is the dominant commodity. The contemporary reform rhetorics of education and management demonstrate some striking parallels as Table 3 illustrates.

Similar parallels can be found in the way each institution defines knowledge (Table 4). The four types of knowledge defined in the first column under education are adapted from Lorin Anderson’s taxonomy (Anderson and Krathwohl, 2000) and the categories of knowledge under management were extracted from Allee (1997).
Tacit knowledge was added to the cell containing “integrative knowledge”; it might be found in any of the cells; however, it is most likely to occur with integrative or metacognitive knowledge.

Some Knowledge-Based Models in Education

Scardamalia and Bereiter (1996) pioneered various strategies linking educational needs with ICT and knowledge concepts. One strategy is to use software that helps students build new knowledge using  scientifically guided experimentation and computer-based tools and resources. Another is to foster and guide knowledge-building communities (Bereiter, 2002). Learning tools are used that assist both with basic skills and with higher-level knowledge. The common element to these strategies is the goal of preparing learners for the knowledge society through exercises in ICT knowledge-based activities.
Using a very different rhetoric, Jonassen’s (1999) “mindtools” paradigm also seeks to optimize learning using software to augment higher-level knowledge-based functions. Mindtools, which are guided activities utilizing software tools, put the student in the role of designer or partner, as most activities require construction of some type of product, usually knowledge. Other activities facilitate collaborative conversations, cognitive amplification, and reflection aimed to enhance critical thinking skills. The influential “How People Learn” model argues that the last research in the cognitive processes of learning provides a guide for instruction (Bransford et al., 1999; National Research Council, 1999a). Taken as a whole, their synthesis of contemporary research identifies knowledge, assessment, and student-centeredness as major sources for optimizing learning.
These educational approaches also offer guidance in designing assessment strategies for measuring knowledge-based skills using ICT. A later section discusses how tasks using mindtools might be adapted for delivery as performance tests.

The Emerging Pedagogical Practices Paradigm

Out of this diversity and terminological confusion, the International Association for the Evaluation of Educational Achievement (IEA) SITES project developed a conceptualization called the “Emerging Pedagogical Practices Paradigm” (EPPP) (Pelgrum and Anderson, 1999; Kozma, 2003). It emerged primarily from three intellectual traditions (1) lifelong learning, emphasizing the need to learn to learn and autonomous learning; (2) constructivism, emphasizing collaborative learning, real-world projects, authentic assessments, and student responsibility for learning; and (3) information literacy, especially the gathering and analyzing of information. The EPPP addressed many requirements of the knowledge society but has not yet explicated the full range of ICT knowledge-based skills required. Essential skills like critical thinking, deep understanding, and high-performance learning have yet to be integrated into the paradigm. In this regard, the knowledge-based framework (below) points to some neglected but essential issues and directions.

Student Knowledge Framework

In this section, a conceptual framework will be offered that flows from imperatives inherent in the information and knowledge society visions. The purpose of the framework is to explicate how societal knowledge demands suggest that learning activities and assessment strategies be structured. After a discussion of the framework, there will be discussion of the role of ICT in these learning activities. Ultimately, the argument is made that ICT and knowledge-related learning go hand in hand, helping to identify the desired direction of education in the twenty-first century.

Figure 1 shows how knowledge-related skills or capabilities go hand in hand with knowledge-related task phases. Skills are needed to carry out task phases of knowledge-related tasks. And completing these task phases helps develop knowledge-related skills. We call these tasks “task phases” because to work effectively on such tasks requires a systematic approach consisting of a number of steps within each task, and a sequence of processes or phases.
Skills and task phases as illustrated in figure are mutually supportive. Carrying out task phases is only possible with knowledge-based skills, but doing task phases helps to develop knowledge-based skills. Complex tasks tend to require all five of the task phases. A project consists of a collection of tasks or task phases organized to achieve a specific outcome.

Knowledge-Related Skills

The following taxonomy of knowledge-based skills reflects priorities implicit in assumptions of the knowledge society, especially as it applies to the changing nature of most jobs. It is intended to guide the design of curriculum, learning activities, and assessment activities, particularly when students have access to ICT tools. Each skill category pertains to a set of tasks and should be analyzed with respect to the type of knowledge predominating in these tasks. Each skill category may pertain to multiple types or levels of knowledge: facts, principles, procedures, metacognition, and subjective states; however, some require predominantly one type. Each of the seven types of knowledge-based skills will be described briefly:

Access, assemble, and reorganize knowledge.
It is generally recognized that in the age of databases and the Internet, the ability to effectively and quickly find and assemble information of all types is critical. Indeed, the concept of information literacy, which was invented about 35 years ago (cf. Spitzer et al., 1998), focuses upon this process. The skills required to search and organize information from the Web are what some have called new literacy or e-literacy. While the open Web is a great resource, there are numerous other sources of data and knowledge that are needed for many, if not most, knowledge questions. Considerable advances are being made in Internet-based systems that integrate browsing capabilities with additional tools that are pedagogically oriented (Soloway, 2000).

Critically interpret, analyze, and evaluate evidence.
Integration involves evaluation of the quality and relevance of knowledge to make appropriate conclusions. Critical evaluation is also called critical thinking and high-performance thinking. A variety of tools, both general and specialized, can be used for these tasks as appropriate.

Collaborate on projects and teamwork.
Sharing knowledge is an essential aspect of successful teamwork, as is the ability to consult with experts and others located at different levels of the hierarchy. Current options include e-mail, conferencing, and instant messaging, to name a few. Effective communication in most global organizations requires the skills associated with selecting communication tools as appropriate for various types of knowledge work. Intercultural communication, both with and without ICT, requires additional skills, which are in high demand.

Solve complex problems.

Problem solving has always been a major human challenge, but with new global technologies the problems are more complex and the solutions are more critical for producing competitive products. Thus, the stakes are higher and the importance of planning strategies and higher-level thinking skills are more critical. Not only are complex problems central to school and the workplace, but they are relevant to everyday living as well.

Generate knowledge products.
Knowledge products range from single ideas and tiny documents up to large, completed projects consisting of hundreds of documents and complex models. The skilled use of software tools is critical to effective completion of such tasks. Depending upon the goal of the task or subtasks, relevant software tools include word processors, spreadsheets, databases, concept mapping, and numerous other application software programs. Innovation and creativity should be considered both as a product and an outcome because of the importance of innovation and creativity to success in the twenty-first century.

Communicate, present, and disseminate.
Knowledge workers are expected to present their knowledge either to report factual data or to persuade an audience to accept particular positions. The use of audio, video, and computing media for such presentations has been called multimedia literacy.

Select appropriate tools and evaluate their impact.

This type of knowledge-based skill encompasses not only awareness of these secondary effects but also the ability to act according to existing legal and ethical boundaries. These tasks coincide with technological literacy, also called sociotechnical literacy, which has been defined as balancing tool and application potentials with practical constraints,
especially social and ethical considerations. Rapidly evolving IT yields new opportunities for cheating, plagiarism, access to private, personal information, and access to adult materials. The new global economy depends upon preparing youth to deal with ICT both technically and responsibly.


Knowledge-Related Task Phases


1. Plan strategies and procedures.

Planning is critical to knowledge-based tasks, although if the task is a familiar one, then the plans may be tacit, because the planning process may not be done consciously. Strategies involve larger sets of activities than do procedures and they take into account resources and power or control. For example, planning a new hospital should include several statistical subtasks to conduct a quality projection of future growth.

2. Choose appropriate tools.

The process of selecting tools is highly context driven in that both the task and the context may constrain the number and type of tools that can be used. A number of different tools could be used for projections, but if no data are available for the projection, then another type of tool may be needed.

3. Collect and organize knowledge and information.

Typically throughout the task process, information resources are needed for decisions of all types. For building a new hospital, not only would statistical data be needed, but also more subjective knowledge about building and staffing issues should be assembled and reviewed.

4. Analyze and synthesize information and knowledge.

After knowledge or data have been collected, it has to be analyzed, interpreted, and integrated in the context of the task. It is often useful to assemble the detail into a holistic summary or synthesis. Such a product may be the main intended outcome of a project.

5. Communicating and disseminating knowledge products.

Once the previous stages of a knowledge-related cycle have taken place, the sharing or dissemination of outcomes or products is necessary for impact. In fact, this is sometimes the most critical phase of the whole process. Dissemination and communication of information about such knowledge requires considerable analytic attention in its own right.

These five knowledge-based task phases constitute a model project cycle or sequence. However, in practice these processes will be implemented within many different cycles where earlier processes are repeated after subsequent ones have been started. For instance, after evaluating preliminary reports, it may be necessary to go back to collect more data and/or to select another set of tools. Nonetheless, these five processes occur in most knowledge-related projects and each process a distinct set skills.
The task phases are useful for thinking about the different types of software tools that are critical for knowledge-oriented projects. For instance, in the planning phase, it is particularly helpful to use project-based software for analysis of timelines, budgets, constraints, and priorities. For the collection and organization phase are browsers and database products. For the analysis phase are spreadsheet tools, modeling packages, and a variety of specialized software tools. And for dissemination, there are presentation and communication tools including writing enhancement aids.

Knowledge Capabilities and ICT Tools

The knowledge-related capabilities can be greatly expanded with ICT tools. Table 5 demonstrates this interrelationship by crossing knowledge capabilities with ICT tool types. The columns in Table 5 represent various categories of ICT tools, defined on the basis of what are considered the most useful ICT applications for teaching and learning. The taxonomy of tool types was adapted from Jonassen’s (1999) classification of mindtools.
The cell entries of this table consist of student outcomes that could be used as evidence for the associated knowledge-related capabilities. The outcomes specified in the cells presume that the student is using one or more ICT tools in the associated row. It should be evident that this framework is intended for a performance assessment where the student has specific software applications available. In some of the cells, a specific software application, e.g., SIMCALC, a Web-based simulation tool widely used in science and mathematics instruction, is given to illustrate the type of tool available. The concepts and categories for this framework were initially developed as an assessment framework. It emerged from dissatisfaction with traditional ways of defining computer literacy, IT literacy, and information literacy. The first largescale IT literacy assessment was the 1979 Minnesota computer literacy assessment (MCLA) the investigators developed the first conceptual framework for the measurement of skills, knowledge, and attitudes relevant to computer utilization by students (Johnson et al., 1980). Their framework consisted of three subdomains: knowing basic

computer concepts, knowing applications and their impact, and understanding and reading simple algorithms (Anderson and Klassen, 1981).
The next such assessment was the ETS Computer Competence Study in 1986 by the Educational Testing Service (ETS). The study was done under the auspices of National Assessment of Educational Progress (NAEP). Their framework was essentially the same as the earlier study except that computer programming was the predominate emphasis (Martinez and Mead, 1988).
In 1992, the IEA CompEd (Computers in Education) study (Pelgrum and Plomp, 1991) conducted the first international, technology-related large-scale survey and assessment. Nearly 20 different countries were involved in one or more segments of the study which developed the functional information technology test (FITT). Again, the subdomains were defined similarly to the earlier studies.
The IT fluency project was sponsored and administered by the National Research Council (NRC) of the United States, and the report was published by the National Academy Press (NRC, 1999b). A panel of mostly computer scientists was convened as the starting point for the conceptualization. Their framework consisted of a number of categories of IT fluencies within each of three major domains: IT concepts, IT skills, and intellectual capabilities. The first two domains were quite similar to the concepts and applications dimensions of earlier studies. But, the “intellectual capabilities” domain contained some rather complex and challenging topics expressed as behavioral objectives, specifically, “manage complexity” and “think about IT abstractly.” Although this was never translated into a large-scale assessment, it marked an important advance. Specifically, it defined the prerequisites for literacy or fluency in terms of non-IT knowledge and how that related to IT.
A few years later, the IEA SITES project developed a knowledge management framework for assessing ICT-related skills (Anderson and Plomp, 2002) in an attempt to redefine IT or ICT literacy in terms of knowledge-related skills. It was from this work that the model in the previous section emerged. The framework had a similar flavor as that developed by the ICT Literacy Project at the ETS, which has been renamed the iSKILLS assessment (ETS, 2007). The core part of their framework defined it in terms of five capacities: the capacities to access, manage, integrate, evaluate, and create information. Many more models of ICT literacy are discussed in the next chapter in this section (Mioduser et al., 2008).
ICT literacy has traditionally been defined in terms of technical skills related to IT, whereas information literacy is usually defined in terms of information functions. If we view the intersection of these two domains with a third, a particular subject or knowledge domain, then we can define the intersection as ICT literacy. This is represented by the accompanying Venn diagram below (Figure 2). However, it is more
appropriate to label it as “applied” ICT literacy because it consists of using IT and information manipulation toward the purpose of carrying out a particular knowledge-related purpose.
For an assessment framework, this model implies that to be ICT literate means that one has essential knowledge and skills from three domains: a technical one, a knowledge domain, and an information skill area, making it possible to use ICT appropriately with information in specific content areas. This implies that ICT literacy by definition is necessarily limited to tasks that require skills from all three domains.
The traditional approach to defining ICT literacy would not require that ICT skills intersect with knowledge- and information-related skills. The knowledge-oriented model is more consistent with the integration of ICT into curricula and into more advanced applications of ICT.
Many publications about education in a knowledge society emphasize that for students to acquire knowledge-based skills, a “student-centered” didactical or pedagogical approach is needed (cf. Jonassen, 1999). The student-centered approach advocated by Jonassen is to let students develop or build new knowledge and he suggests putting the student into the role of designer. Both of these approaches illustrate

how learning activities that require ICT can facilitate skills in ICT as well as in more knowledge-based areas such as self-regulation, creativity, and project management. This learning process can occur for well-defined learning tasks to very open problem-solving tasks aimed at producing “anything.”

Knowledge Societies and Cooperative Work

More than any other technology-oriented research strands, computer supported cooperative work (CSCW) and computer supported cooperative learning (CSCL) have addressed the growing importance of knowledge societies. The professional association of CSCW holds an annual conference which is oriented to workplace research. International Society for the Learning Sciences (ISLS) holds a biannual research conference on CSCL. Software tools called groupware, which assist teamwork, are among the products from these communities. Software tools for interaction and exchange of knowledge are also investigated by researchers in these communities. Figure 3 shows a general model for cooperative work, which takes knowledge, works on it, and produces various knowledge products.
Tools that are used to facilitate interaction and networking are best represented on the upper half of this diagram, whereas tools that are designed to facilitate joint production are best represented by the lower half. Tools of the former kind would be threaded discussions and chat rooms. Joint reviewing/editing tools would be an example of the second type. Tools that help with knowledge mapping, note structuring,

and so forth, should be seen as overlaying over the entire diagram. Examples of knowledge community projects in education can be found in the work of Bereiter (2002) and Scardamalia and Bereiter (1996). The most extensive review of CSCL can be found in Stahl (2006). His research investigations concentrate on mechanisms to support group formation, multiple interpretive perspectives, and the negotiation of group knowledge in applications as varied as collaborative curriculum development.
Stahl discovered processes involved in the emergence of group meaning and outlines a theory of collaborative knowing. His work has yielded designs of optimal software environments for knowledge-based learning utilizing collaboration.
Assessment tools can be considered knowledge-based tools, but assessment is not very interesting in the context of knowledge development unless it is designed and oriented toward instructors and directly improving instruction. When computerbased content grading procedures become more refined, that will also help to integrate assessment and knowledge society functions. One thing that both groupware and assessment yield is input to improving instruction using scaffolding guides. That is, the teacher can be helped to design the best strategies for balancing between being too explicit and too vague in defining and assisting students.

Knowledge Societies and Learning to Learn

While this knowledge framework may appear to preclude other approaches to defining major skill requirements, it is not as narrow as it may seem. We illustrate this implication by describing some areas of overlap of the knowledge management framework with other approaches, most notably “learning to learn” and informatics.
A major tenant of the lifelong learning (also called “continuous learning”) movement is that “learning to learn” is a critical skill for the twenty-first century.
ICT implicitly supports this by making possible new ways of obtaining “knowledge on demand” or “just in time” learning. There is a large literature on study skills, but contemporary advocates of “learning to learn” tend to argue that contemporary learning requires much more than study skills. Effective “learning to learn” requires attitudes and motivations such as motivation to learn and motivation to take selfresponsibility
to learn. Now, there is little consensus on how to define and measure the skills of learning to learn.
Many educational systems have a national informatics curriculum consisting of one or more courses at the elementary and/or secondary level that teach ICT skills. Traditionally, the content of informatics courses has emphasized beginning computer science principles along with some general principles of information management.
In many instances, students taking informatics also receive hands-on instruction in the use of productivity tools such as word processors, Internet browsers, spreadsheets or databases, and other such technology. Some educational systems offer courses in ICT concepts and applications but do not call it informatics.
The knowledge may be useful in evaluating both curricula where ICT instruction is integrated into existing courses as well as traditional informatics curricula. A course on the use of productive tools teaches skills in constructing knowledge products such as document production, and retrieving and organizing knowledge with a database system or browser, and solving problems with spreadsheet or other software tools.
A curriculum that includes instruction in computer programming typically may teach students these same information management skills but with different tools. Programming instruction usually puts a major emphasis upon the knowledge-oriented task phase that we have called “analyzing and synthesizing.”

Implications for Education in the Era of Knowledge Societies

One should infer from this chapter that progress harnessing of technology for education requires progress in understanding the tools and their context, both educational and social. For that understanding to go forward effectively requires increments in theory and research. The theory part includes refining the concepts and specifying the underlying influences within the overall system. The concepts of the information and knowledge society are central to that understanding. In particular, we need to know much more about knowledge: how best to define it, how to utilize students’ prior knowledge in the learning process, how to manage knowledge in organizational environments, how to let it guide the construction of assessments, and so on.
In support of this emphasis upon knowledge, Brown and Duguid (2000) argue that learning is the acquisition of knowledge and it “presents knowledge management with its central challenge” (p. 124). Furthermore, they state that learning is social and “it requires developing the disposition, demeanor, and outlook of the practitioners.”
While this very well captures the process of apprenticeship, professional, and most workplace learning, it also applies to general education. The point is not so much that the student is being socialized by the teacher, but that effective learning involves learning attitudes and values associated with any new knowledge. In other words, without the tacit dimension of knowledge, people do not learn when and how to apply the explicit part.
Looking beyond information to knowledge of various types gives us a much richer picture of learning. It also helps to clarify the ways in which learning and practice are interrelated. First and foremost, the link between learning and practice is a social one. And if we embed learning in a social context, then subsequent practice is much more assured.
Learning is not just about students. It is also an essential dimension of teaching and schooling. Teachers are not likely to be very effective on there own, hence the power of communities of practice (Wenger and Snyder, 2000). As teachers learning to work together and help each other, their productivity increases exponentially.
Finally, schools must learn to adapt, not just to change, but to new knowledge that helps them run more effectively (cf. Hargreaves, 2003). Hence, we see the power of schools as learning communities (Senge, 2000). School reform has a much higher chance of success when its leaders nurture the learning processes of the school community. Reform is not just a matter of vision, but it is a matter of vision, resources, community participation, and taking full advantage of social mechanisms for making learning maximally effective.

Acknowledgment The author wishes to acknowledge and thank Tjeerd Plomp, Professor Emeritus at the University of Twente, for his major help with several sections of this chapter.

References

Ronald E. Anderson (2008) , Implications of Handbook of Information and Knowledge Society For education, International Handbook of Information Technology in Primary and Secondary Education, Part One, University of Minnesota, Minnesota, MN, USA, Section Editor:, Editors, Joke Voogt University of Twente, the Netherlands, Gerald Knezek, University of North Texas, USA, Springer Publisher