Version: 03/00
New Developments in Learning
Greg Kearsley
(http://home.sprynet.com/~gkearsley)
With the increasing prevalence of telelearning (especially web-based courses), there have been significant changes in our underlying assumptions about the nature of learning. Current pedagogy emphasizes collaboration, interactivity and authenticity in student learning activities. At the same time, the training world has undergone a major transformation in terms of its focus on organizational learning and knowledge management. There have also been important shifts in the way we assess learning and our views of its effectiveness. This chapter begins by discussing the past legacy of learning theories and their relevance to these new directions and concludes by speculating on the potential impact of emerging technologies on the nature of learning.
1. Background
Over the course of the 20th century, our views about
learning have changed considerably. In the early 1900s, the predominant
paradigm of learning was classical conditioning which evolved into the
behaviorism of Watson,
In addition to these general trends, there have been some important developments which have shaped learning theory and instructional applications. One of these is the emphasis on the social/cultural elements of learning (i.e., “situated cognition”) introduced by Jean Lave and John Seely Brown, drawing upon earlier work of Vygotsky and Bandura. This was a redirection from the preoccupation with individual learning (and individual differences) that dominated most of the research and practice in the 20th century. Another new direction was introduced by John Carroll in his minimalism framework – an alternative to the existing ideas about the development of instructional materials. Finally, a number of individuals, such as Schank (1997), Towne (1995), and Gibbons & Fairweather (1998), have advanced computer simulation as a major model for learning.
In parallel with these theoretical developments, technology came to be applied more frequently in education and training. Radio (audio), television (video), and eventually, computers, played major instructional roles in teaching and learning. However, the first two or three decades of educational computing (1960s-80s) were dominated by a rather narrow concept of how to use the technology (i.e., “Computer Based Instruction”) and it wasn’t until the Internet and World Wide Web came into widespread use that a better understanding of the real value of computers in education prevailed. By the end of the century, it had become clear that computer networks (and the Web in particular) were going to have a major impact on education at all levels (reflecting their effects on society in general).
2. TeleLearning
So now, at the beginning of the 21st century, we have a fairly different paradigm of learning from the previous century, one which is heavily influenced by computer technology. For simplicity, let’s call this paradigm, “telelearning” (aka “Online Learning”). Telelearning embraces a number of different elements from past learning theories, plus some new aspects – some of which are not yet understood very well.
First, it is important to understand that telelearning embraces a tremendous variety of online learning experiences, including conventional computer-based instruction (i.e., self-paced tutorials), simulations, MOOs/MUDs, and web-based courses (see Collis, 1996; Kearsley, 2000; Khan, 1997, Porter, 1997). The latter tend to be instructor-led and make use of tools such as email, discussion forums, and chat/conferencing for interaction.
Despite this diversity, telelearning approaches embrace most of the following characteristics:
Students often work together
2. Connectivity
Students are connected to everyone and everything
3. Student-Centered
Students choose what and how they learn
4. Unbounded
Classroom walls do not limit learning
5. Community
Groups are defined by common interests
6. Exploration
Students are encouraged to seek knowledge
7. Shared Knowledge
There is an easy way to share knowledge (on a global basis)
8. Multisensory
Information can involve sounds, graphics, audio, video and animation
9. Authenticity
Learning is real-world
These characteristics are enabled by network technology: email, discussion forums, conferencing, web sites, search engines, plug-ins, file uploading, etc. All of these characteristics have been associated with classroom instruction in the past, but not together. Collectively, they define a new form of learning.
The one domain that is relatively new is the community element. Classrooms represent a community of learning – but they are artificially constructed. Telelearning allows the creation of virtual communities based on genuine shared interests. People choose to interact with others online because they have common experiences or interests. These interactions may be fleeting or long-lasting, casual or structured. But they are a different kind of phenomenon than occurs in physical communities (e.g., Brown & Duguid, 2000; Rheingold, 1993; Turkle, 1997; Wenger, 1999).
A great deal of research in the latter part of the last century was devoted towards the development of intelligent tutoring systems (e.g., Burns, Parlett & Redfield, 1991; Farr & Psotka, 1992; Mandl & Lesgold, 1988). These systems were based upon the fusion of cognitive psychology and artificial intelligence work, and were intended to provide telelearning programs that were more responsive to individual student needs. Despite some impressive demonstrations [2], these systems never became widely implemented or available. This was partly due to the substantial computing resources needed to run them (not really a problem today) but mostly due to the enormous amount of time and effort required to create them. But this line of research did make some important contributions to instructional theory, namely the importance of misconceptions in learning, and the manner in which concepts and skills are acquired.
The challenge for educators is to figure out how to create telelearning environments and activities of greatest value to particular students. This is a difficult challenge because it requires that educators become very familiar with all the possibilities of online delivery. Knowledge of how to do this is accumulating (e.g., Bonk, 1998; Palloff & Pratt, 1999; White & Weight, 1999), but not widely disseminated in the teaching world yet. On the other hand, the commercial world is quickly figuring it out – see the emergence of “e-learning portals” such as about.com or hungryminds.com.
3. Engagement Theory
Engagement theory (Kearsley & Shneiderman, 1999) is intended to be a conceptual framework for telelearning. The fundamental idea underlying engagement theory is that students must be meaningfully engaged in learning activities through interaction with others and worthwhile tasks. By engaged learning, we mean that all student activities involve active cognitive processes such as creating, problem-solving, reasoning, decision-making, and evaluation. While in principle, such engagement could occur without the use of technology, we believe that technology can facilitate engagement in ways which are difficult to achieve otherwise.
Although not directly derived from other theoretical frameworks for learning, it has much in common with many such frameworks. For example, with its emphasis on meaningful learning, it is very consistent with constructivist approaches. Because it emphasizes collaboration among peers and a community of learners, it can be aligned with situated learning theories. Because its focuses on experiential and self-directed learning, it is similar in nature to theories of adult learning (i.e., androgogy).
Engagement theory is based upon the idea of creating successful collaborative teams that work on ambitious projects that are meaningful to someone outside the classroom. These three components, summarized by Relate-Create-Donate, imply that learning activities:
1.occur in a group context (i.e., collaborative teams)
2.are project-based
3.have an outside (authentic) focus
The first principle (the "Relate" component) emphasizes team efforts that involve communication, planning, management and social skills. The modern workplace demands proficiency in these skills, yet historically students have been taught to work and learn on their own. Research on collaborative learning suggests that in the process of collaboration, students are forced to clarify and verbalize their problems, thereby facilitating solutions. Collaboration also increases the motivation of students to learn, a significant consideration in settings with high drop-out rates (e.g., teen-agers, distance learners). Furthermore, when students work in teams, they often have the opportunity to work with others from quite different backgrounds and this facilitates an understanding of
diversity and multiple perspectives.
The second principle (the "Create" component) makes learning a creative, purposeful activity. Students have to define the project (problem domain) and focus their efforts on application of ideas to a specific context. Conducting their own projects is much more interesting to students that answering sterile textbook problems. And because they get to define the nature of the project (even if they don't choose the topic), they have a sense of control over their learning which is absent in traditional classroom instruction. Project orientation is the essence of Problem-Based Learning (PBL) approaches which are often used in medical and others types of professional education. [3]
The third principle (the "Donate" component) stresses the value of making a useful contribution while learning. Ideally each project has an outside "customer" that the project is being conducted for. The customer could be a campus group, community organization, school, church, library, museum, government agency, local business, or needy individual. In many cases, the projects can be work-related, i.e., an activity that fits into a team's occupational or career interests. The authentic learning context of the project increases student motivation and satisfaction. This principle is consistent with the emphasis on school-to-work programs in many schools systems and colleges, as well as the "service" philosophy of contemporary corporate training efforts.
Engagement theory is different from many older models of computer-based learning in which the emphasis was on individualized instruction and interactivity. Engagement theory does promote interaction, but human interaction in the context of group activities, not individual interaction with an instructional program. The latter form of interaction tended to be measured by single responses (e.g., key presses or mouse clicks) whereas engagement requires assessment of larger units of work (e.g., reports, programs, user satisfaction). The difference between engagement and interactivity reflects the shift in thinking about computers in education as communication tools rather than some form of media delivery devices. Furthermore, engagement theory places a great deal of emphasis on providing an authentic (i.e., meaningful) setting for learning, something not present in previous models.
4. Organizational Learning and Knowledge Management
Perhaps the most significant development in learning theory in the last couple of decades has been the concept of organizational learning (Arygris & Schon, 1996; Debella & Nevis, 1997). Most simply defined, organizational learning refers to the capability of an organization to improve its effectiveness based upon its experience. Other definitions embrace the cultural or human capital element: Senge (1990) defines a learning organization as one "where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free and where people are continually learning how to learn together."
Organization learning theory recognizes that another level of learning beyond the individual has become important in modern society. Since most human endeavors are now conducted in the context of organizations ranging from corporations to government agencies and educational institutions, how these entities take advantage of their experience (i.e., the accumulated knowledge and skills of their staff) is a fundamental issue. Indeed, how a given business, school, hospital, or service provider learns, affects the well-being of their constituents and employees. Historically, organizations provided training to employees to improve their individual performance. Organizational learning theory suggests that this is not sufficient; attention needs to be paid to collective knowledge and experience.
The detailed mechanism of how an organization learns has come to be called knowledge management. Knowledge management involves the processes of acquiring, storing, evaluating, and distributing the accumulated experience of an organization (Davenport & Prusak,,1997; Liebowitz, 1999). Obviously, this can take place at many levels from refining operational procedures to better management decisions. Documenting how to do things well (i.e., best practices) and making those results available to all is a major task. Collecting data on what works and what doesn’t (i.e., quality control) is part of this process.
Technology plays an important role in enabling knowledge management within any organization (Applehans, Globe & Laugero, 1998; Marquardt & Kearsley, 1999). Computer networks make it possible to collect and disseminate information easily (especially via the internet or intranets). Database systems with powerful sorting and search capabilities make it possible to organize and find items very selectively, despite enormous amounts of information. Expert systems can make connections and inferences based upon patterns in the data.
But it is the way technology can enhance communication within organizations that may be its most important contribution to organizational learning. As we discussed earlier with telelearning, there are many ways for people to interact online such as email, discussion forums, and conferencing. People are using these capabilities to interact with colleagues and clients more, increasing the overall connectivity of organizations and their constituency. So networks are changing how organizations behave (see Sproull & Kiesler, 1991; Lipnack & Stamps, 1997).
Incidentally, it is worth noting that universities could represent the most potent forms of learning organizations given their content and research expertise; yet educational institutions have so far been very slow to address organizational learning. This is probably because interest in organizational learning is driven by the desire to become more effective/efficient – something not particularly salient to most institutions of higher education (but see Daniels, 1998).
5. Measurement of Learning
Another aspect of learning that has changed over the past century is our ideas about how to measure learning. For the first half of the century, the emphasis was on quantitative measures such as achievement, ability, or intelligence tests. But in subsequent decades, there was a shift towards competency-based, qualitative assessment methods, particularly due to the influence of Bloom, Block, and Mager. In schools, portfolios have become increasingly popular as a way to assess student learning in lieu of exams or tests. In the workplace, performance-based methods of evaluation tied to job tasks have become common.
Given our discussion earlier in this chapter about the characteristics of telelearning and engagement theory, it should be clear that qualitative assessment methods are much more appropriate for technology-based learning environments. If the outcomes of learning involve the completion of projects rather than the acquisition of simple skills or information, multiple-choice tests won’t work. Instead, the results must be gauged in terms of competencies or criteria related to subject matter or the utility of the effort. Simulation also has an important role to play as a new form of assessment, especially in technology-based training. Simulations involve performance-based activities, whether they require hands-on skills in equipment operation or decision skills in scenario choices.
Ironically, telelearning provides us with very detailed data on student learning. Almost every online system is capable of recording and reporting the entire sequence of user behavior in a learning session. But this data is seldom used because it is too minute – what is an instructor to conclude about individual keypresses made by a student? On the other hand, when this data is aggregated into meaningful units, such as how much time students spend on a given lesson, how many mistakes they make trying to solve a particular problem, or which elements of a course they used most often, it starts to become useful in assessing student learning.
New methods for assessment must also take into account the sociocultural elements of learning that have been introduced earlier in this article. To the extent that course assignments are the collaborative efforts of teams, grading schemes must be sensitive to the group effort. When discussion forums and conferencing are a central part of online courses, the quality of the interaction should be an important measurement. Peer evaluation becomes quite important because students need to judge the value of each other’s work in relative terms. And language/literacy limitations need to be taken into account when participation in courses spans a global audience.
Finally, almost our current methods of evaluation are based upon performance in a learning unit of brief duration (e.g., single exam, seminar, semester). But with life-long learning, we need more longitudinal measures that can be used to integrate diverse data over a long time period. But where would such records reside, when the learning activities transcend many institutions? Perhaps we need a personal learning record, like today’s credit agency or driving records.
6. Discussion and Conclusions
When considering the changes that have taken place in learning theory over the past century, it is important to realize that the nature of knowledge and expertise has changed dramatically in this timeframe. Knowledge used to be something acquired on the basis of experience over time. Experts knew a lot about a particular subject matter. But in today’s world, there is too much information and it changes too fast for either of these traditional forms of knowledge or expertise to be valid. Today, experts are people who know where to find information of immediate use and only the most up-to-date information is useful. Experts are more likely to be young than old. Knowledge has a half-life which gets shorter all the time.
Clearly, the old model of learning that emphasizes the orderly accumulation of knowledge or the practice of well-worn skills is no longer appropriate. Instead we need models that focus on how to acquire, evaluate and synthesize information. And, how to learn in collaboration with others, not as a solitary endeavor. We want people who are good at the learning process itself and can easily replace old knowledge with new.
While it is beyond the scope of this article, these changes in learning have major implications for the design and delivery of instruction. Classic instructional design is based upon the old paradigms for learning and knowledge: creating a self-contained course, taught by a content expert. But new learning paradigms call for learning environments in which students are given access to relevant resources/tools and helped by facilitators/mentors. The latter are not content experts, but good guides or coaches.
New developments in technology will surely shape the evolution of learning. Developments in areas such as virtual reality and multimedia affect the kind of information available online and how we interact with each other. Sound and motion certainly make information more interesting. And being able to use more sensory modalities (i.e., speech, touch, gestures) and see three-dimensional images affects what and how much we learn. Most learning theory is concerned with learning from printed text – not highly interactive and multi-sensory learning environments.
There is much discussion about the increasing prevalence of technology in everyday circumstances – socalled “pervasive or ubiquitous” computer environments. We can see the distinction between formal (i.e., classroom) and informal learning being removed through the use of technology: for a student, there isn’t much difference between learning on a computer at home, work, library or school. As technology becomes more and more portable and embedded in everyday devices, this trend will continue. However, most past learning theory has been conceptualized in the context of formal learning environments. So we need guidelines for learning in “real-world” contexts.
Learning theory has changed quite a lot over the past century and it is likely to change even more in the 21st. While the neurochemical mechanisms that underlie learning may be the same, the behavior evolves. Learning is what allows living organisms to adapt to a changing world. And that means that learning itself must be adaptive.
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