Chapter 1.1
Implications of the Information and Knowledge Society for Education
Ronald E. Anderson
University of Minnesota
Minnesota, USA
rea@umn.edu
Abstract: After an introduction to information and knowledge society concepts, their relevance
to education is elaborated. The principal value of these concepts is that they highlight the many
social changes happening concurrently with advances in information and communication
technology. A conceptual framework is proposed that illuminates the role that knowledge can
play in education’s attempt to apply technology to learning. In addition, the link between
knowledge and ICT literacy assessment is elaborated. The discussion also stresses the role that
knowledge can play in teaching within communities of practice and that technology can play in
enhancing the learning and teaching processes.
Keywords: information society, knowledge society, 21st century skills, information literacy,
knowledge –based models, knowledge management
1.1.1 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 &
Norman, 1970; Rothman & 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
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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 more obvious, the information society metaphor became even more
widely accepted (Webster, 2002).
1.1.2 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.
1.1.3 Information versus 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 & 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,
2
experience, insights, rules of thumb, 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.
1.1.4 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 co-existing [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
3
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.
1.1.5 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 need the skills to construct new knowledge, and
project-based learning offers opportunities for learning such skills.
Table 1
Implications of the demands of the global knowledge economy for youth in terms of required
skills and learning strategies
DEMANDS from SOCIETY
Knowledge as commodity
REQUIRED SKILLS
Knowledge construction
LEARNING STRATEGIES
Inquiry, project learning,
constructivism
Rapid change, renewal
Adaptability
Learning to re-learn, ondemand learning
Information explosion
Finding, organizing,
Multi-database browsing
4
retrieving info.; ICT usage
exercises
Poorly organized
Information management,
Database design and
information
ICT utilization
implementation
Incompletely evaluated
Critical thinking
Evaluation problem solving
Teamwork
Collaborative learning
information
Collectivization of
knowledge
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 s/he
knows already.
The explosion of information implies using systems that require new skills for accessing,
organizing, and retrieving information (Spitzer, Eisenberg & Lowe, 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 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 & Duguid, 2000).
Information and communication technology (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
5
organizations; constructivism; student centered learning; high performance learning; project
learning; digital divides; and so forth.
1.1.6 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" (IT) 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 five years to see whole new forms of ecommerce 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 they impact society and change
research priorities for research on ICT and education internationally.
1.1.7 The Twenty-First Century Skills Movement
6
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) Task Force
on Education for the Twenty-first Century and 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 21st Century Skills reports is summarized in Table 2 where key themes
are listed.
Table 2
Presence of Content Themes in 21st Century Skills Statements
Partnership for
Australian
NCREL &
Theme
21st Century
EDUTOPIA
Dept. of
Metiri Group
Skills
Education
Communication
*
*
*
Creativity
*
*
*
Collaboration
*
*
*
*
*
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Critical thinking
*
*
*
*
ICT Literacy
*
*
*
*
Information and Media
*
*
High Productivity
*
*
Life Long Learning
*
Life Skills
*
Literacy
*
*
*
*
Each report emphasizes different themes. The Partnership for 21st Century Skills
stresses critical thinking and life skills; the Eutopia 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 21st 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 initiatives are the WorldSkills project
(www.worldskills.org) and the e-Skills Certification Consortium (eSCC) (http://www.escc.org/default.aspx) organization.
As shown in Table 4 the 21st Century reports consistently emphasize the following
educational outcomes for students and workers of the 21st 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
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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 can not 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 21st Century, it
becomes clear that they coincide with requirements for knowledge societies. It would appear that
the 21st Century movement is predicated on knowledge and information society concepts and
concerns.
1.1.8 Parallels in Education and Management
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It is not accidental that the leading edge thinking about both education and organizational
management tend 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.
Table 3
Parallel Directions in Education and Management
Education:
Management:
Schools as learning
Organizations as learning
organizations
systems
Learning to learn
Renewal is integral
Knowledge constructing
Collaborative learning and
Knowledge as product
Knowledge is collective
teaching
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 & 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.
Table 4
Parallel Definitions of Knowledge in Education and Management
Education:
Management:
10
Factual knowledge: details,
Data, statistics
terminology
Conceptual knowledge:
Managing principles, theories,
principles, classes, theories
best practices
Procedural knowledge:
Procedural knowledge: rules
algorithms, application
and specifications
criteria
Metacognitive knowledge:
Integrative knowledge:
strategies, self-monitoring,
strategic plans, philosophies;
reflection
tacit knowledge
1.1.9 Some Knowledge-Based Models in Education
Scardamalia & 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.
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The influential “How People Learn” model argues that the last research in the cognitive
processes of learning provides a guide for instruction (Bransford, Brown, Cocking, & Pellegrino,
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.
1.1.10 The Emerging Pedagogical Practices Paradigm
Out of this diversity and terminological confusion the IEA (International Association for
the Evaluation of Educational Achievement) SITES project developed a conceptualization called
the "Emerging Pedagogical Practices Paradigm" (EPPP) (Pelgrum & 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
1.1.11 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
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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 21st
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.
Knowledge Related Skills:
a. Access, assemble, re-organize
knowledge
b. Interpret, analyze & evaluate
c. Collaborate on projects and
teamwork
d. Complex problem solving
e. Generate knowledge products;
f. Communicate, present, and
disseminate
g. Select appropriate tools & evaluate
impact
Knowledge Related
Task Phases:
are needed for
1. plan strategies and
procedures
2. choose appropriate ICT
tools
3. collect and organize
knowledge
4. analyze and synthesize
5. disseminate,
communicate
help develop
Figure 1
The Relationship between Knowledge Related Skills and Knowledge Related Task Processes,
with or without ICT
Skills and task phases, as illustrated in this 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.
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1.1.12 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.
A. Access, assemble, re-organize 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 is 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).
B. Critically interpret, analyze, and evaluate evidence. Integration involves evaluation of
the quality and relevance of knowledge in order 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.
C. 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
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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.
D. 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 more critical
for producing competitive products. Thus the stakes are higher and the importance of planning
strategies and higher-level thinking skills more critical. Not only are complex problems central to
school and the workplace but they are relevant to everyday living as well.
E. 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 21st century.
F. 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.
G. Select appropriate tools and evaluate their impact. This type of knowledge-based skill
encompasses not only awareness of these secondary effects but the ability to act according to
existing legal and ethical boundaries. These tasks coincide with technological literacy, also
called socio-technical literacy, which has been defined as balancing tool and application
potentials with practical constraints, especially social and ethical considerations. Rapidly
15
evolving information technology 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.
1.1 13 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 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
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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. None-the-less, 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.
1.1 14 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 Figure 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
17
given to illustrate the type of tool available.
Table 5
Illustrative Learning Activities for Knowledge Capabilities (rows) by ICT Tool Types (columns)
CommunicaKnowledge
Interpretation
tion,
construction
tools, e.g.
Collaboration
Knowledge
tool kits &
Semantic
Dynamic
visualization
and
Capabilities
database
organization
modeling
& search
Presentation
environment
tools
tools
tools
Tools

A. Access,
Making
Web
assemble, and
inferences
searching and
re-organize
using e.g.,
organizing
Knowledge
SIMCALC
using browser
using data
B. Critically
Scenario
interpret,
simulation
mining tools
to drill down
analyze, and
(see e.g. in
to highly
evaluate
Bennett,
knowledge
(2001))
granular
information
C. Collaborate
on projects and
Using
groupware
teamwork
18
Using
Using an
Interpreting
qualitative
optimization
data using
analysis
model for
visualization
software
decisions
tools
D. Solve
complex
problem
Constructing
reasoning
E. Generate
chains using
Knowledge
concept
maps
F.
Using
Communicate,
PowerPoint in
present, and
Net meetings
disseminate
G. Select
Selecting ICT
appropriate
tools for a
knowledge
medical
tools and
experiment
evaluate their
and evaluate
impact
tool impacts
Note: The table structure was substantially adapted from Anderson & Plomp (2002). The table
contains some changes to improve clarity.
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
(Information technology) literacy, and information literacy. The first large scale IT literacy
assessment was the 1979 Minnesota Computer Literacy Assessment (MCLA) the investigators
19
developed the first conceptual framework for the measurement of skills, knowledge, and
attitudes relevant to computer utilization by students (Johnson, Anderson, Hansen, & Klassen,
1980). Their framework consisted of three subdomains: knowing basic computer concepts;
knowing applications and their impact; and understanding and reading simple algorithms
(Anderson & 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 NAEP (National
Assessment of Educational Progress). Their framework was essentially the same as the earlier
study except that computer programming was the predominate emphasis (Martinez & Mead,
1988).
In 1992 the IEA CompEd (Computers in Education) study (Pelgrum & 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
FITT (Functional Information Technology Test). 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
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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 & Plomp, 2002) in an attempt to re-define 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 Educational Testing Service, 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, Nachimias & ForkoshBaruch, 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.
Figure 2
Venn Diagram of Applied ICT Literacy
21
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
22
tasks to very open problem solving tasks aimed at producing 'anything'.
1.1.15 Knowledge Societies and Cooperative Work
More than any other technology-oriented research strands, CSCW (Computer Supported
Cooperative Work) and CSCL (Computer Supported Cooperative Learning) have addressed the
growing importance of knowledge societies. The professional association of CSCW holds an
annual conference which is oriented to workplace research. ISLS (International Society for the
Learning Sciences) holds a bi-annual 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.
Knowledge
Inputs
Person
Understanding/
Communication/
Interaction
Person
Artifacts/
Knowledge
Products
Figure 3
23
Cooperative Work Framework
Tools that are used to facilitate interaction and networking are best represented on the
upper half of this diagram, where as 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 (cf. Scardamalia & 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 is it designed and oriented toward
instructors and directly improving instruction. When computer-based 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.
1.1.16 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
24
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 21st 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.”
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1.1.17 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 & Duguid (2000) argue that learning is the
acquisition of knowledge and it “presents knowledge management with its central challenge”
(p124). 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 don’t 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 & Snyder, 2000). As teachers learning to work together and
help each other, their productivity increases exponentially.
26
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 paper.
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