Lifelong Learning Ñ More Than Training
Lifelong Learning Ñ More Than Training
Lifelong Learning Ñ More Than Training
Gerhard Fischer
Center for LifeLong Learning & Design (L3D)
Department of Computer Science and Institute of Cognitive Science
University of Colorado, Boulder
1. INTRODUCTION 3
3.1. Training 6
4.1. Requirements 9
4.4. Critiquing 13
5. ASSESSMENT 17
7. REFERENCES 20
1. Introduction
Learning needs to be examined across the lifespan because previous notions of a divided
lifetimeÑeducation followed by workÑare no longer tenable [Gardner, 1991]. Professional
activity has become so knowledge-intensive and fluid in content that learning has become an
integral and irremovable part of adult work activities. Learning is a new form of labor [Zuboff,
1988], and working is often (and needs to be) a collaborative effort among colleagues and peers.
In the emerging knowledge society, an educated person will be someone who is willing to
consider learning as a lifelong process. More and more knowledge, especially advanced
knowledge, is acquired well past the age of formal schooling, and in many situations through
educational processes that do not center on the traditional school [Illich, 1971].
Information overload, the advent of high-functionality systems, and a climate of rapid
technological change have created new problems and challenges for education and training.
New instructional approaches are needed to circumvent the difficult problems of coverage (i.e.,
trying to teach people everything that they may need to know in the future) and obsolescence
(i.e., trying to predict what specific knowledge someone will need or not need in the future).
Learning should be part of living, a natural consequence of being alive and in touch with the
world, and not a process separate from the rest of life [Rogoff & Lave, 1984]. What learners
need, therefore, is not only instruction but access to the world (in order to connect the knowledge
in their head with the knowledge in the world [Norman, 1993]) and a chance to play a
meaningful part in it. Education should be a distributed lifelong process by which one learns
material as one needs it. School learning and workplace learning need to be integrated.
In training, learning is often restricted to the solution of well-defined problems. Lifelong
learning includes training approaches and also transcends them by supporting learning in the
context of realistic, open-ended, ill-defined problems. In our environments, learners explore
information spaces relevant to a self-chosen task at hand; for example: learning on demand
3.1. Training
Learning new skills and acquiring new knowledge cannot be restricted to formal educational
settings. Effective learning needs to be integrated into the work process. Current teaching
programs train people to use what is effectively a snapshot of an evolving technology. Training
is often considered as a variable plugged into an economic model. This short-sighted cycle of
training and retraining cannot be broken unless we recognize that learning is a lifelong process
that cannot be separated from working [Sachs, 1995].
By integrating working and learning, people learn within the context of their work on real-
world problems. Learning does not take place in a separate phase and in a separate place, but is
integrated into the work process. People construct solutions to their own problems, and the
system advises them when they are getting into trouble and provides directly relevant
information. The direct usefulness of new knowledge for actual problem situations greatly
improves the motivation to learn the new material because the time and effort invested in
learning are immediately worthwhile for the task at hand Ñ not merely for some putative
long-term gain.
Many conventional frameworks of training (programmed instruction, computer-based training)
and working (a best scientific way) are grounded in the behaviorist learning theory of B.F.
Skinner and the models of industrial work of F.W. Taylor. Figure 2 contrasts these approaches
with the lifelong and self-directed approaches to learning.
¥ learning should take place in the context of authentic, complex problems (because
learners will refuse to quietly listen to someone elseÕs answers to someone elseÕs
questions);
¥ skills and processes that support learning as a lifetime habit must be developed.
Learning taking place outside of an (instructionist) classroom can often be characterized as
follows: humans are engaged in some activity (some action such as working, collaboratively
solving a problem, or playing); they experience a breakdown; and they reflect about the
breakdown (i.e., the piece of lacking knowledge, the misunderstanding about the consequences
of some of their assumptions, etc.). Schšn [Schšn, 1983] calls this reflection-in-action. Because
self-reflection is difficult, a human coach, a design critic, or a teacher can help the learner to
identify the breakdown situation and to provide task-relevant information for reflection. In our
own work, we have explored the possibility using computational critics [Fischer et al., 1993] to
provide some of this support when humans are not present. Critics make argumentation serve
design, that is, they support learners in their own activities.
Engagement and support for self-directed learning is critical when learning becomes an integral
part of life Ñ driven by our desire and need to understand something, or to get something done
instead of solving a problem given in a classroom setting. A lifelong learning perspective
implies that schools and universities need to prepare learners to engage in self-directed
learning processes because this is what they will have to do in their professional and private
lives outside of the classroom.
It is advantageous for both motivation and the ability to acquire new knowledge that students
be able to direct their own learning [Fischer, 1991]. Self-directed learning [Fischer, 1998b] de-
emphasizes teaching as a process in which a teacher tells something to a passive learner, but
focuses instead on mutual dialogs and joint knowledge construction, which are enhanced by the
creation, discussion and evolution of artifacts.
4.1. Requirements
One of the major roles for new media and new technology is not to deliver predigested
information to individuals but to provide the opportunity and resources for engaging in
meaningful activity, for social debate and discussion, for creating shared understanding among
stakeholders, and for framing and solving authentic problems. This global perspective leads to
the following requirements for lifelong learning:
¥ The vocabulary, tools, functions, and practices supported by the system come from
the working environment, where they are natural and appropriate.
¥ The mode of operation emphasizes learning from breakdowns and from fulfilling
commitments.
¥ Tools must appear directly relevant to help with the problem at hand; they must
not generate further breakdowns.
¥ Although learning environments may have some built-in expertise, users will
find most expert knowledge by locating other people who have the knowledge.
¥ The systems should aid users in two kinds of reflection Ñ immediate, to deal
with the problem and to organize a solution; and post-mortem, to see if the
problem is recurrent and can be avoided by restructuring work processes.
¥ Systems should feature many interactions among people, because these are the
sources of most breakdowns.
¥ Systems should support not only the individual's solo performance, but work in
cooperation with others and while belonging to different groups at the same
time: systems should support the improvement of collective knowledge as well as
individual knowledge.
Open Systems. The needs of people engaged in lifelong learning will transcend the boundaries of
any closed system, making mechanisms such as end-user modifiability and end-user
programming a necessity rather than a luxury. One of the biggest challenges facing systems in
support of lifelong learning is to allow end-users to become co-developers of systems. Figure 4
differentiates between two stages in the design and use of an artifact. At design time, system
developers create environments and tools including help systems, guided tours, forms, and so on,
and they have to make decisions for users (who may want to be consumers or designers), for
situational contexts, and for tasks that they can only anticipate. For print media, a fixed
context is decided at design time, whereas for computational media, the behavior of a system
at use time can take advantage of contextual factors (such as the background knowledge of a
user, the specific goals and objectives of a user, the work context) known only at use time. The
fundamental difference is that computational media have interpretive power Ñ they can
analyze and critique the artifacts created by users [Fischer et al., 1993] Ñ and users acting as
designers will create artifacts of all kinds. The challenge is to build new innovative systems
that allow the users to articulate contextual factors (e.g., in using a specification component
[Nakakoji, 1993] and/or infer this information from the environment), which will serve as
objects for interpretation.
Figure 5 characterizes the duality and the distributed nature of knowledge: a specific user can
learn (specifically learn in context and on demand) from a computational environment (which
contains knowledge and tools contributed by many members of the community of practice), but if
this user considers her/himself a designer, she/he will also contribute to the environment
(assuming mechanisms are available that allow her/him to do so with a reasonable effort).
This perspective illustrates the concepts and need for co-adaptive systems: (1) users learn from
key
time
design use
time time
Figure 4: Design and Use Time
End-User Modifiability,
End-User Programming
Learning on Demand
Collaborative Systems. Even though we face too much information in the abstract, in most
specific problem situations we do not have enough knowledge. Learning cannot be restricted to
finding knowledge that is Òout thereÓ. If nobody in a group knows the answer, we have to create
new knowledge and new environments that stimulate innovation and creativity by exploiting
breakdowns, symmetry of ignorance, experimentation, and external objects serving as objects-to-
think-with and objects-to-talk-about. The individual, unaided human mind is limited: there is
only so much we can remember and there is only so much we can learn. Talented people require
approximately a decade to reach top professional proficiency. This general observation
provides the rationale that when a domain reaches a point where the knowledge for skillful
professional practice cannot be acquired in a decade, specialization will increase, teamwork
will become a necessity, and practitioners will make increasing use of external reference aids
(such as printed and computational media). With powerful technologies becoming widely
available, people take on more jobs that are more complex or more comprehensive. Therefore,
they need help accomplishing unfamiliar tasks that are part of an expanded job. Beyond the
need for new and changing domain knowledge, there is also a large demand for new tool
knowledge.
Intelligent Tutoring
Systems
Self-Directed Learning
Contextualized Tutoring
Domain-Oriented
Design Environments
End-User Modifiability
Learning on Demand
Interactive Learning
Environments
Learner Control
4.4. Critiquing
In many lifelong learning situations, human understanding evolves through a process of
critiquing existing knowledge and consequently expanding the store of knowledge. Critiquing is
a dialog in which the interjection of a reasoned opinion about a product or action triggers
further reflection on or changes to the artifact being designed. Our work has focused on applying
this successful human critiquing paradigm to human- computer interaction. Computer-based
critiquing systems are most effective when they are embedded in domain-oriented design
environments. Embedded critics [Fischer et al., 1993] play a number of important roles in such
design environments: (1) they increase the designer's understanding of design situations by
pointing out problematic situations early in the design process, (2) they support the integration
of problem framing and problem solving by providing a linkage between the design
specification and the design construction, and (3) they help designers access relevant
information in the large information spaces provided by the design environment.
Critiquing is ubiquitous. It is, for example, at the heart of the scientific method. Popper
[Popper, 1965] theorized that science advances through a cycle of conjectures and refutations.
5. Assessment
6. Conclusions
Training and lifelong learning are essential problems for our current and future information
societies. Unfortunately (as is probably the case with all important questions and challenges)
there are no simple answers and no simple facts that would allow enumerating briefly failures
and successes. To acknowledge the complexity of these issues implies that we rethink, reinvent
and redesign the way how we think, work, learn, and collaborate in the future. A lifelong
learning perspective is more than training and continuing education: it forces us to rethink and
reinvent our schools and universities [Brown & Duguid, 1995; Noam, 1995].
We have to understand the co-evolutionary processes between fundamental human activities
and their relationships and interdependencies with new media. We need progress and a deeper
understanding of new theories, innovative systems, practices, and assessment. We have to
create new intellectual spaces, new physical spaces, new organizational forms, and new reward
structures to make lifelong learning an important part of human life. We need individuals,
Acknowledgments
The author would like to thank the members of the Center for LifeLong Learning & Design
(L3D) at the University of Colorado, who have made major contributions to the conceptual
framework and systems described in this paper. The research was supported by (1) the
National Science Foundation, Grants REC-9631396 and IRI-9711951; (2) Software Research
Associates, Tokyo, Japan; and (3) PFU, Tokyo, Japan.
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