Robert “Rob” Haskell (1938-2010) was Professor of psychology and department chair at the University of New England. In writing Haskell’s obitiuary, Gresson (2010), his friend and colleague for more than forty years, wrote that he grew up on the coast of Maine and had mentioned reading his first book at the age of 19, when he entered the army.  He studied sociology, rhetoric and psychology and attended San Francisco State and Penn State University, where he earned his PhD. He taught at Harrisburg Area Community College in Pennsylvania for about ten years (roughly 1970-1980) and later at the University of New England.

       Among Haskell’s accomplishments are numerous publications, including Transfer of Learning: Cognition, Instruction, and Reasoning as well as Reengineering Corporate Training: Intellectual Capital and Transfer of Learning, Deep Listening: Hidden Meanings in Everyday Conversation, Between the Lines: Unconscious Meaning in Everyday Conversation (Amazon.com, n.d.) and over 65 research papers (University of New England, 2010). While at the University of New England, Haskell co-founded the Institute for Cognitive Science and was a charter member of the American Psychological Society. According to Gresson (2010, para. 5), Haskell was “fascinated with unconscious language and thought” and was passionate about “empirical theory-building”.  Haskell’s theory-building is evident in Transfer of Learning: Cognition, Instruction, and Reasoning (2001). In it he proposed a general theory of transfer of learning, which has relevance for all areas of knowledge and learning transfer settings. This paper will give a brief overview of his general theory of transfer of learning, review observations and recommendations in Transfer of Learning, and look at some applications of his general theory of transfer of learning.

 

Haskell’s General Theory of Transfer of Learning

    Haskell’s Transfer of Learning: Cognition, Instruction, and Reasoning (2001) was published after nearly a century of popular emphasis on learning strategies and instructional techniques aimed at improving transfer. The book outlines a general theory of transfer of learning in response to the ongoing problem of transfer, which he believed stemmed ultimately from faulty critical thinking.  In the Introduction, Haskell (para. 8) lists the eleven requirements of this general theory:

1. Acquire a large primary knowledge base in the area in which transfer is required.

2. Acquire some level of knowledge base in subjects outside the primary area.

3. Understand what transfer of learning is and how it works.

4. Understand the history in the area(s) that transfer is wanted.

5. Acquire motivation, or more specifically, a ‘spirit of transfer’.

6. Develop an orientation to think and encode learning in transfer terms.

7. Create cultures of transfer or support systems.

8. Understand the theory underlying the area(s) in which we want to see transfer.

9. Engage in hours of practice and drill.

10. Allow time for the learning to incubate.

11. Observe and read the works of people who are exemplars and masters of transfer thinking.

He supports and expands upon these in the book.  The implications of this foundational, general theory of transfer are broad and far-reaching.

Summary of Transfer of Learning: Cognition, Instruction, and Reasoning

    Haskell’s book is divided into two parts, defining what is meant by transfer and how it

works.  In the first part, consisting of chapters one through five, he traces the history of the discussion of transfer, contends that it is in critical condition, and argues its central and practical importance in nearly every sphere.  In the second part, chapters six through twelve and the Coda, he makes the case for a large knowledge base as the foundational principle for learning transfer.  He highlights key motivational, cultural, theoretical, and neurological aspects of learning transfer, in support of the stated eleven principles. Following are a few nuggets that seem particularly salient.

Knowledge Base

 

    For Haskell, knowledge base is essential for transfer.  It is almost like good soil, in which ideas and thoughts can grow. A solid, deep knowledge base enhances critical thinking and reasoning. It provides the necessary mental framework for asking relevant questions and determining where there are gaps in understanding.  The conceptual framework of a knowledge base creates order, so it is not simply a mass of fragmented data.  In chapter six, he identifies five kinds of knowledge: (a) declarative, (b) procedural, (c) strategic, (d) conditional, and (e) theoretical (Kinds of Knowledge, para. 1). He focuses on declarative knowledge, which he considers most critical for transfer for five reasons (para. 3):

-It provides the necessary “preconditions” for other kinds of knowledge.

-It often “includes or directly generates” the other kinds of knowledge.

-It provides a “general framework for assimilating” additional knowledge.

-It aids in the “elaboration of newly acquired knowledge”.

-It helps in providing “useful analogs (or mental models)” for understanding new knowledge.

In addition, Haskell proposes in chapter six that useless knowledge, or knowledge not deemed immediately relevant for the area of transfer, may have potential significance.  He cites inventors, scientists, and thinkers who have transformed useless knowledge into innovative work in their fields. One example is knot theory in mathematics, which was transferred over to biochemistry, as it became the lenses through which to see tangled strands of DNA (Usefulness, para. 3). It seems that transfer, both big and small, involves an open mind and a willingness to see connections between apparently disconnected information from a wide spectrum of knowledge.  

 

Learning With Transfer in Mind

    Haskell describes the fundamental basics of transfer as being able to make connections, to see one thing as similar to something else.  He contends that transfer is dependent on understanding what transfer is and how it occurs. In chapter two, Haskell outlines six levels of the taxonomy of transfer (General Scheme, para. 2):

-Nonspecific transfer, which essentially connects all learning to past learning

-Application transfer, or being able to apply or put into use what one has learned (such as learning to type and then typing)

-Context transfer, or the ability to transfer information learned in one context to a slightly different one (similar to seeing a pattern from one setting that is recognizable in another)

-Near transfer, which occurs with transfer of knowledge from one setting to a similar but different setting (such as someone who can ride a bicycle being able to easily learn to ride a motorcycle)

-Far transfer, which is relating learning from one setting to a vastly different one

-Displacement or creative transfer, which is, essentially, the creation of something new. It more than simply like something else, it is a new thing, idea, or concept.

 

The “Spirit of Transfer”

    In chapter seven, Haskell discusses his concept of a spirit of transfer, which is more than simply motivation. It is meaningful encoding.  He refers to tagging, which suggests intentionally marking information to aid in its recall and retrieval (Personality, Meaning). He also cites the role of feeling, or affect, in the encoding process, which historically has been minimized.  There is evidence to suggest that the brain experiencing positive (or negative) emotions and feelings will be doubly recording information for richer, more complex encoding (Feeling and Transfer).

 

Reflective Practice

     Haskell argues that drill and practice are critical for transfer, citing the benefits of ten or more years of practice in any field and the correlation between expertise and practice (chap. 6, What Do We Mean by Practice?).  He distinguishes good practice from bad practice as reflective rather than “mindless drill” (Good Practice, para. 1).  Good practice makes the action or process automatic and frees up the brain to be thoughtful and deliberate in analysis and performance.

 

Neurological and Cognitive Processes in Transfer

    Haskell rightly concludes that any theory of the transfer of learning should not contradict what we continue to learn about the brain and how it works. He notes in chapter eleven the evolutionary processes in the brain that distill incoming information to avoid taxing the central nervous system (chap. 11, Evolutionary Origins). He suggests that these processes that support learning transfer are actually “hard-wired” in the brain into our brain” (para. 3).  In the book’s Coda titled “Deep-Context Teaching for Transfer”, Haskell addresses the cognitive barriers of beliefs, worldviews, and frames of reference that inhibit receptivity to the learning material.  He describes deep context teaching as proactive engagement on the part of the instructor that is meant to encourage awareness in learners.  For example, if a student (whether a man or woman) believes that women are categorically less intelligent than men, that student will likely have some reservation or a barrier to learning from a female professor or a curriculum dominant in female scholarship. While the student may learn and perform well in the class, there may be a significant mental block to encoding or receiving the information in a deep way. As such, deep-context teaching seeks to uncover and address guarded beliefs that hinder the transfer of learning.

 

Current Applications of Haskell’s Work

    Haskell’s general theory of the transfer of learning in Transfer of Learning has been applied in a number of contexts, including businesses, organizations, and education.  Two examples of the application of his work are found in materials written for educational and instructional practitioners. First, in their article titled “Training vs. Learning: Transfer of Learning in a Peer Tutoring Course and Beyond”, Driscoll and Harcourt (2012, para. 2) cite Haskell’s work on the transfer of learning and his assessment that the transfer of learning is “the very foundation of learning, thinking, and problem solving”. They are transfer-focused in their approach to teaching peer tutoring. They draw from different pedagogical approaches to encourage the transfer of learning, but the design is framed and supported by Haskell’s emphasis on designing learning with transfer in mind.  

Another example of Haskell’s influence is found in the journal New Directions for Adult and Continuing Education (2013) in its “Learning Transfer for Adult Education” issue. He is cited in two articles. Foley and Kaiser, in their article “Learning Transfer and Its Intentionality in Adult and Continuing Education”, reference Calais’s use of Haskell’s taxonomies for transfer of learning (p. 7-8). In their article “Leveraging Experiential Learning Techniques for Transfer”, Furman and Sibthorp describe active learning as an example of the “deeper interaction with content” prescribed by Haskell. (p. 20). These are just recent examples of how Haskell’s thought and work is being applied in the area of transfer development.

     In conclusion, Haskell’s work on learning transfer is a synthesis of his years of experience in teaching and research.  At the time it was published, this spanned about thirty years. It is as much a summation of his observations of college students over the years as it is of his reflection on everyday interactions with people and his research and findings in his work in social psychology. His work is a significant contribution to the discussion of the challenge of learning transfer.

 

References

Amazon.com. (n.d.). Robert E. Haskell author page. Retrieved from http://www.amazon.com/Robert-E.-Haskell/e/B001H6U5II

 

Clark Training & Consulting. (n.d.). Book review: Transfer of learning. Retrieved from http://web.archive.org/web/20031228091306/http:/www.clarktraining.com/research/haskell.html

 

Driscoll, D. L., & Harcourt, S. (2012). Training vs. learning; Transfer of learning in a peer tutoring course and beyond. The Writing Lab Newsletter, 36(7-8), 1-6. Retrieved from https://writinglabnewsletter.org/archives/v36/36.7-8.pdf

 

Foley, J. M., & Kaiser, L. M. (2013). Learning transfer and its intentionality in adult and continuing education. In Learning transfer in adult education (pp. 5-15). San Francisco: Jossey-Bass

 

Furman, N., & Sibthorp, J. (2013). Leveraging experimental learning techniques for transfer. In Learning transfer in adult education (pp. 17-26). San Francisco: Jossey-Bass

 

Gresson, A. D. (2010, December). Rob Haskell obituary. Retrieved from http://manwithoutqualities.com/2011/02/23/rob-haskell-obituary

 

Haskell, R. E. (2001). Transfer of learning: Cognition, instruction, and reasoning. [Kindle Touch version]. Retrieved from Amazon.com

 

University of New England. (2010). Robert Eugene Haskell. Retrieved from http://www.une.edu/people/robert-eugene-haskell