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An Overview of Learning

Learning is the manifestation of several components of the individual physiology and human essence.  Data collected via the five senses (sight, sound, taste, touch, and smell) is electrochemically processed, sorted, and stored in the brain.  In any given moment, those five senses are providing the brain with millions of individual bits of information that can create both conscious and unconscious reactions.  The key to conscious learning is memory.  Memory is a physical occurrence that is affected by environmental and physiological factors such as stress and functioning chemical receptors.  In simple terms we can consider the brain as the hard-drive of individual human existence (Schwartz, 2003).

Along with the five ever-present physical senses, multi-disciplinary research suggests that individuals possess a sixth sense.  If we define ”sense” as a data collections source that affects the function of the brain then our sixth sense would be the mind’s operation.  Just as the five senses provide data that alter the synaptic responses within varying sections of the interactive brain, the mind (thoughts, feelings, action) creates synaptic responses throughout the brain creating a constant bio-chemical loop or interface between the brain and mind (Dainton, 2006).  As the brain is the hard-drive of our existence, it is our mind that is the software that decodes the stored bits of data into symbolic representations we can manipulate to communicate, problem solve, and survive in general.

In many experiences and situations inside and outside of the classroom, the student’s internal mind-brain connection (software package) is not naturally compatible with the instructor’s mind-brain connection.  It is the goal of this project to research and develop original platforms that create synergy between information provider and information recipient by reformatting spoken language into linear, non-linear, and graphic representations without loss of data for the benefit of the recipient through information display options.  Recognition and application of how information is formatted, transferred, and processed is at the core of learning achievement as proposed in this project.   The section “Barriers to Student Learning” discusses the implications of student-professor compatibility on learning.  First, however, a theoretical framework for characterizing learners is presented.

A Learning Platform

The learning theoretical basis for this proposal encapsulates several models.  The Interactive Learning Model© (ILM) (Johnston, 1996) provides both a framework for understanding specific barriers to student learning and a theoretical rationale for why this platform has value.  The ILM purports that during the brain-mind interface data is processed using different degrees of four interactive patterns of operation and learning: sequence, precision, technical reasoning, and confluence.  These four observable patterns manifest themselves not only in our cognition (thinking), but our affectation (feelings) and conation (actions) as well.

The Learning Connections Inventory© is the instrument used to accurately measure the four inherent learning patterns (Dainton, 1996a and Johnston, 1998).  The Learning Connections Inventory (LCI) is a 28 item Likert-style instrument that contains three interactive short answer questions used to validate responses.  A numerical score from 7-35 is generated for each pattern.  The results of the LCI yield a profile of learning patterns in which the individual is characterized as ”avoids (7-17),” ”uses as needed (18-24)”, or ”uses first (25-35)” each of the four interactive learning patterns (Dainton, 1996b).

For example, typical attributes of learners who use Sequence at a Use-First level include:

-They want clear, step-by-step directions.

-They do not begin a task until they have a clear plan.

-They want time to do their work neatly and to double-check the work.

-They want to know if they are meeting expectations.

 

By contrast these are tendencies of those who use Sequence at an Avoid level:

-They tend not to read directions.

-They don’t plan or live by a rigid schedule.

-They rarely double-check their work.

-They find following directions confusing – and maybe even frustrating.

 

Typical attributes of learners with the Use-First level in Precision include:

-They want complete and thorough explanations.

-They ask a lot of questions and seek written documentation.

-They like to answer questions.

-They need to be accurate and correct.

 

While these are the tendencies of people who Avoid Precision:

-They rarely read for pleasure.

-They don’t attend to details; details are bothersome and boring.

-They find memorizing tedious and a waste of time.

-They tend to “tune-out” extemporaneous discussions.

 

Typical attributes of those who use Technical reasoning at a Use-First include:

-They like “hands-on” projects.

-They need to see the relevance and practicality of what they are doing.

-They like to work by themselves.

-They like to figure how things work.

-They don’t like to use a lot of words, and rarely write things down.

 

While learners who use the Technical pattern at the Avoid level have these tendencies:

-They don’t get involved with taking things apart to understand how they work.

-They don’t venture into the tool aisle if they can avoid it.

-They are intimidated by technology they don’t understand.

-They problem solve with others not alone.

 

Finally, regarding persons who use the Confluent pattern at a Use First level:

-They don’t like doing the same thing over and over.

-They have lots of ideas.

-They often see situations very differently than others do.

-They don’t like following the rules.

-They enjoy taking risks.

 

While these are the tendencies of learners who use Confluence at the Avoid level:

-They think taking risks is foolish and wasteful.

-They would rather not make mistakes than learn from mistakes.

-They are more careful and cautious in how they go about making decisions.

-They seek conventional approaches.

 

“Use as needed” patterns don’t tend to drive learning like ”Use First” and ”Avoid” patterns.  The “Use as needed” patterns tend to lay dormant until the specific task at hand requires their use: for example preparation of an outline for a report might be described as a task requiring sequential reasoning and repairing a leaky faucet might be described as a task requiring technical reasoning.  The individual who uses a pattern as needed feels no urgency either to seek out or to avoid such tasks.

Barriers to Student Learning

A longitudinal analysis of instructor versus student learning patterns across institutions and grade levels suggests potential disconnects unless both parties can articulate their differences and develop strategies to negotiate, connect, and meet the needs as both instructor and learner.  The LCI is the tool that can be used for learning analytics and communication as it provides a vocabulary for both the instructor and student to use to explain learning tasks, accomplishments and frustrations.

Even when there is no fundamental incompatibility between instructor and student learning pattern, there exists the potential for student misunderstanding of the role of lectures and lecture notes.  Institutions of higher education intend to promote and design experiences that require deductive/inductive reasoning, enhance problem solving skills, and enable self discovery.  However, single-loop learning continues to be the norm in K-12 education and in many university courses, particularly in general education courses.  Single-loop learning is characterized by information dissemination, passage of time, and then information collection.  In this case assessments are not based on reasoning, problem-solving, and self-discovery, but rather on note-taking skills and memory.

Double-loop learning is the concept that most resembles the goals of adult and higher education. Double-loop learning is characterized by an opportunity for students to actively engage information, apply the information, and reflect upon the outcomes of that intentional engagement and application of said information (Bernold, 2000).  One commonly-used tool in engineering education is Bloom’s Taxonomy (Anderson, 2001), which describes six levels of student ability.  The distinction between single- and double-loop learning is well illustrated in the context of Bloom’s Taxonomy.  Single-loop learning is best viewed as a vehicle for attaining “Remember,” the lowest level of Bloom’s Taxonomy, while the key learning objectives for higher education courses are essentially always at higher levels of mastery (understand, apply, analyze, evaluate, create).

Active learning is a fundamental component of double-loop learning (Osterman, 2004).  In recent years many educators and instructors have developed and published active learning techniques, problem-based learning methods, and other innovations consistent with the paradigm of double-loop learning (Felder, 2003).  However, even instructors who do all these things well must contend with the fact that students often enter a course with the prejudice that accurate note-taking and data regurgitation is what’s expected.  Internal conflict can arise within students as some feel the need to scribe accurate and organized notes at the exact time they are expected to connect theories and concepts.  If single-loop learning continues as a norm in adults and higher education it is self evident as to which task students will focus their mental force (Schwartz, 2003).

When a person understands the way that their mind translates data collected by their brain (learning patterns) they can identify and decode the challenges that confront them, then balance and apply their learning patterns to overcome that challenge.  In order to be successful in any endeavor we need to understand our individual learning, the system we are working in, the learning patterns of the people we work with and the task at hand.

The LCI is neither a skills assessment nor determinant of achievement or success.  It is designed to help people recognize and understand the ways in which they interpret and operationalize information .  The vocabulary provided by the LCI helps each person explain who they are as an individual learner, and also provides strategies for how to use your personal learning processes with intention.  The importance of completing the LCI lies in the fact that the LCI provides an inward look at learning processes, an outward analysis of an individual’s actions, and a vocabulary for explaining the specific actions the person takes that result in productive or unproductive outcomes.

The vocabulary provided by the LCI helps each person explain and talk about who s/he is as an individual, and also provides strategies for how to use your personal learning processes with intention. When there is an understanding and awareness of each other’s learning patterns, planning and action takes on an innovative, calculated approach to task completion and achievement.

The LCI can form a basis for dialogue between student & teacher, student & student, and associate & supervisor resulting in the development of a universal vocabulary, improvement in the working dynamics, and intentional effort creating partnerships between workers and learners.

Literature Cited

Anderson, L.W. and Krathwohl, A Taxonomy for Learning, Teaching and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. Longman, New York, 2001. 

Bernold, L.E., Bingham, W.L., McDonald, P.H., and Attia, T.M., “Impact of Holistic and Learning-Oriented Teaching on Academic Success,” Journal of Engineering Education, 89, 2 (2000).

Dainton, G, and Johnston, C, “Learning Connections Inventory”, Learning Connections Resources, LLC, Turnersville, NJ, 1996-a.

Dainton, G, and Johnston, C, “Learning Connections Inventory User’s Manual”, Learning Connections Resources, LLC, Turnersville, NJ, 1996-b.

Dainton, G, and Johnston, C, “Learning to use my potential”, Learning Connections Resources, LLC, Turnersville, NJ, 2006.

Felder, R, M, and Brent, R, “Learning by doing”, Chemical Engineering Education, 37(4), pages 282-283, 2003.

Felder, R. M. and Brendt, R.  “Understanding Student Differences,” Journal of Engineering Education, 94, 1 (2005).

Johnston, C, Unlocking the will to learn, Corwin Press, Thousand Oaks, CA, 1996.

Johnston, C.A., Let Me Learn, Corwin Press Inc., London, 1998.

Osterman, K, and Kottkamp, R, “Reflective Practice for Educators: Professional Development to Improve Student Learning”, Corwin Press, Thousand Oaks, CA, 2004.

Rusu, A. and Dainton, G., “Automatic Generation of Sequence-Style Notes from Live Lecture,” Proceedings of the Ninth International Conference on Engineering Education, San Juan, Puerto Rico, 2006.  

Rusu, A., Dainton, G., Dahm, K. and Metting, J., “Automatic Generation of Discreet Data Formats from Live Lecture,” Proceedings of the 2008 Frontiers in Engineering conference, Saratoga Springs, NY, October 2008.

Schwartz, J, M, and Begley, S, “The mind and the brain: Neuroplasticity and the power of mental force”, HarperCollins, New York, NY, 2003.