Transfer of learning

Transfer of learning is the dependency of human conduct, learning, or performance on prior experience. The notion was originally introduced as transfer of practice by Edward Thorndike and Robert S. Woodworth.^[1] They explored how individuals would transfer learning in one context to another, similar context – or how "improvement in one mental function" could influence a related one. Their theory implied that transfer of learning depends on how similar the learning task and transfer tasks are, or where "identical elements are concerned in the influencing and influenced function", now known as the identical element theory.

Today, transfer of learning is usually described as the process and the effective extent to which past experiences (also referred to as the transfer source) affect learning and performance in a new situation (the transfer target).^[2] However, there remains controversy as to how transfer of learning should be conceptualized and explained, what its prevalence is, what its relation is to learning in general, and whether it exists at all.^[3] There are a wide variety of viewpoints and theoretical frameworks apparent in the literature, which can be categorized as:

• a taxonomical approach that categorizes transfer into different types;
• an application domain-driven approach that focuses on developments and contributions of different disciplines;
• the examination of the psychological functions or faculties transfer models invoke; and
• a concept-driven evaluation, which reveals compares and contrasts theoretical and empirical traditions.

Transfer taxonomies

The following table presents different types of transfer, as adapted from Schunk (2004).^[4]

Positive Transfer: Transfer of learning or training is said to be positive when the learning or training carried out in one situation proves helpful to learning in another situation. Examples of such transfer are:

• The knowledge and skills related to school mathematics help in the learning of statistical computation;
• The knowledge and skills acquired in terms of addition and subtraction in mathematics in school may help a child in the acquisition of knowledge and skills regarding multiplication and division;
• Learning to play badminton may help an individual to play ping pong (Table Tennis) and lawn tennis.

Traditional fields of transfer research

Learning and transfer: implications for educational practice

A modern view of transfer in the context of educational practice shows little need to distinguish between the general and specific paradigms, recognizing the role of both identical elements and metacognition. In this view, the work of Bransford,^[7] Brown and Cocking (1999) identified four key characteristics of learning as applied to transfer. They are:

1. The necessity of initial learning;
2. The importance of abstract and contextual knowledge;
3. The conception of learning as an active and dynamic process; and
4. The notion that all learning is transfer.

First, the necessity of initial learning for transfer specifies that mere exposure or memorization is not learning; there must be understanding. Learning as understanding takes time, such that expertise with deep, organized knowledge improves transfer. Teaching that emphasizes how to use knowledge or that improves motivation should enhance transfer.

Second, while knowledge anchored in context is important for initial learning, it is also inflexible without some level of abstraction that goes beyond the context. Practices to improve transfer include having students specify connections across multiple contexts or having them develop general solutions and strategies that would apply beyond a single-context case.

Third, learning should be considered an active and dynamic process, not a static product. Instead of one-shot tests that follow learning tasks, students can improve transfer by engaging in assessments that extend beyond current abilities. Improving transfer in this way requires instructor prompts to assist students – such as dynamic assessments – or student development of metacognitive skills without prompting.

Finally, the fourth characteristic defines all learning as transfer. New learning builds on previous learning, which implies that teachers can facilitate transfer by activating what students know and by making their thinking visible. This includes addressing student misconceptions and recognizing cultural behaviors that students bring to learning situations.

A student-learning centered view of transfer embodies these four characteristics. With this conception, teachers can help students transfer learning not just between contexts in academics, but also to common home, work, or community environments.

Human-Computer Interaction: designing for transfer with technology

Technology has been successfully used to increase the degree with which learners effectively utilize skills and knowledge gained through class in the real world. This interaction of learners with computers and other technology has altered the landscape of education by reducing the need for paper based educational artifacts, altering curriculum, and introducing a plethora of innovations that allow for key simulations and virtual experiences in the learning environment. Examples of curriculum shifts related to HCI include the change from penmanship towards word processing and computer languages being allowed to be substituted as foreign language requirements.

Instructors that properly implement HCI simulations and animation in the learning environment create a learning state that reflects actual situations in which the knowledge or skill will likely be used in. This transfer using HCI techniques has been shown to effectively increase transmission for both scientific and technology knowledge. HCI also allows for group based learning as opposed to teacher based learning through interactive and individualized technologies including: blogs, wikis, social networks, video casts, and virtual worlds such as Second Life. These various aspects of HCI allow for unique learning experiences to be undertaken that highlight different learning styles and cultural perspectives helping to increase transfer (Erikson 2012; Choi 2007).

Transfer is increased when learners see the potential transfer implications of what they are learning. Properly designed HCI interfaces promote visual thinking that leads to more successful transfer as well. The field of Instructional Design will be an area primarily focused on design principles and the implications on successful blending of HCI to optimize transfer. The learner base that benefits the most from transfer enhanced HCI implementations consists of digital natives to these concepts and expertise. The instructors however are often first generation computer users with limited prior knowledge. Often this makes it difficult to incorporate HCI into improved conditions for transfer within the new world learning environments. While these “digital immigrants” struggle to successfully incorporate technology into areas such as transfer, it is possible to overcome with proper goal setting, assessments, peer support, and instructor support (Joo 2011; Rosen 2009; Rodgers 2007; Eriksson 2012; Choi 2007).

Motivation

In a review of research on motivation and transfer, Pugh and Bergin (2006)^[8] concluded that motivational factors can influence transfer, although the research is limited and not wholly consistent. They found that mastery goals were more consistently linked to transfer success than were performance goals. They also found that interest was related to transfer success when this interest was associated with the learning content. However, when the interest was related to peripheral things, such as seductive details in text, it inhibited transfer success. In addition, they found evidence that transfer success was positively related to self-efficacy. Finally, the reviewers proposed that the transfer process is affected by the presence of an explicit goal of achieving transfer. Pugh and Bergin (2006)^[8] predicted that motivational factors influence transfer in three ways. First, they can influence the quality of initial learning in ways that support transfer. Second, they can influence the initiation of transfer attempts, particularly in situations where individuals have an opportunity to apply learning but are not required to. Third, motivational factors can influence individuals’ persistence when engaged in transfer tasks.

See also

Wikiversity has learning materials about Transfer of learning

• Metaphor
• Analogy, Analogical reasoning
• Priming (psychology)
• Affordance
• Learning
• Problem solving
• Classical conditioning
• Gavriel Salomon

References

Further reading

• Corder, S. P. (1967). The significance of learners' errors. International Review of Applied Linguistics in Language Teaching, 5, 161–170.
• Perkins, D. N., & Salomon, G. (1992). Transfer of learning. International Encyclopedia of Education (2nd ed.). Oxford, UK: Pergamon Press.