Gomory (2000) states that: “Interaction [in an online course] with the students is also different. Usually there is more interaction, and incautious professors who do not set rules for when they will answer e-mail find they have given themselves 24 hour/day jobs.” Noble (2001) complains that digital education, “entails an inevitable extension of working time and an intensification of work as faculty struggle at all hours of the day and night to stay on top of the technology and respond, via chat rooms, virtual office hours, and e-mail, to both students and administrators to whom they have now become instantly and continuously accessible.” (p. 32)
In support of Noble’s contention, Lee (2002) describes a survey of administrators and faculty involved in a large scale distance education cooperative that found that faculty did not perceive current rewards and incentives for distance teaching to be sufficient compensation for the heavier workloads such teaching required. However, few researchers have investigated the actual time demands of online teaching.
Behaviorism, cognitivism, and constructivism are the three broad learning theories most often utilized in the creation of instructional environments.
Behaviorism states that learning is largely unknowable, that is, we can’t possibly understand what goes on inside a person (the “black box theory”). Gredler (2001) expresses behaviorism as being comprised of several theories that make three assumptions about learning:
1: Observable behaviour is more important than understanding internal activities.
2: Behaviour should be focused on simple elements: specific stimuli and responses.
3: Learning is about behaviour change.
Cognitivism often takes a computer information processing model. Learning is viewed as a process of inputs, managed in short term memory, and coded for long-term recall. Cindy Buell details this process: “In cognitive theories, knowledge is viewed as symbolic mental constructs in the learner's mind, and the learning process is the means by which these symbolic representations are committed to memory.”
Constructivism suggests that learners create knowledge as they attempt to understand their experiences (Driscoll, 2000, p. 376). Behaviorism and cognitivism view knowledge as external to the learner and the learning process as the act of internalizing knowledge. Constructivism assumes that learners are not empty vessels to be filled with knowledge. Instead, learners are actively attempting to create meaning. Learners often select and pursue their own learning. Constructivist principles acknowledge that real-life learning is messy and complex. Classrooms which emulate the “fuzziness” of this learning will be more effective in preparing learners for life-long learning.
Limitations of Behaviourism, Cognitivism, and Constructivism.
A central tenet of most learning theories is that learning occurs inside a person. Even social constructivist views, which hold that learning is a socially enacted process, promotes the principality of the individual (and her/his physical presence – i.e. brain-based) in learning. These theories do not address learning that occurs outside of people (i.e. learning that is stored and manipulated by technology). They also fail to describe how learning happens within organizations.
Learning theories are concerned with the actual process of learning, not with the value of what is being learned. In a networked world, the very manner of information that we acquire is worth exploring. The need to evaluate the worthiness of learning something is a meta-skill that is applied before learning itself begins. When knowledge is subject to paucity, the process of assessing worthiness is assumed to be intrinsic to learning. When knowledge is abundant, the rapid evaluation of knowledge is important. Additional concerns arise from the rapid increase in information. In today’s environment, action is often needed without personal learning – that is, we need to act by drawing information outside of our primary knowledge. The ability to synthesize and recognize connections and patterns is a valuable skill.
Many important questions are raised when established learning theories are seen through technology. The natural attempt of theorists is to continue to revise and evolve theories as conditions change. At some point, however, the underlying conditions have altered so significantly, that further modification is no longer sensible. An entirely new approach is needed.
Some questions to explore in relation to learning theories and the impact of technology and new sciences (chaos and networks) on learning:
How are learning theories impacted, when knowledge is no longer acquired in the linear manner?
What adjustments need to be made with learning theories when technology performs many of the cognitive operations previously performed by learners (information storage and retrieval).
How can we continue to stay current in a rapidly evolving information ecology.
How do learning theories address moments where performance is needed in the absence of complete understanding?
What is the impact of networks and complexity theories on learning?
What is the impact of chaos as a complex pattern recognition process on learning?
With increased recognition of interconnections in differing fields of knowledge, how are systems and ecology theories perceived in the light of learning tasks?
