EDUC 6115-2 Course Reflection

I began this course with impatience. Although I typically enjoy deep theoretical

exploration, I doubted the immediate relevance of learning theory to my work, and I wondered if

this course was the best use of my limited time. Only later would I recognize myself in Merriam

& Cafarella’s (1999) description of adult-learners: “there is a change in time perspective as

people mature – from future application of knowledge to immediacy of application,” (Merriam &

Caffarella, 1999). Once I relaxed and embraced the gestalt, I found the intellectual stimulation I

crave and a seemingly limitless supply of new resources to expand my learning and enrich my

work.



I have been surprised by the diversity of thought among learning theorists, and

struck by the breadth and volume of empirical support for dissimilar theories. Atkinson

and Shiffrin (1971) proposed a two-store information processing model, which Baddeley

(1998) rejected as being too simplistic. The concept of levels of processing evolved in

response and with scientific support from Craik and Tulving (1975) among others.

However, it too was quickly determined to be incomplete (Morris, Bransford, and

Franks, 1977; Moscovitch and Craik, 1976). Anderson (1990) introduces activation

level, Nairne (2002) stresses the importance of rehearsal, and Gupta & Cohen (2002)

assert distinctions between declarative and procedural memory; all of this under the

umbrella of cognitive information processing theory. 



The science of learning theory is far less fixed than I previously thought, perhaps

because of what Gleick refers to as a “sensitive dependence on initial conditions” (1987,

p. 8); perhaps it is a function of differences between, or fluctuations within, learning

styles (Gilbert & Han, 2002) or multiple intelligences (Gardner, 2003); or something else

entirely. What I can say definitively is that there is no universal “on” or “off” switch, no

categorically “right” or “wrong” way for me to learn or design instruction.

Keller’s (1987) notion that “the outputs of effort, performance and consequences

are affected by the shared inputs of the person and the conditions of instructional environment,

which include design, media, strategies, delivery,” expands my understanding of the

interconnectedness of learning theories, learning styles, motivation, and the unique role

of educational technology in motivational design, delivery of instruction, and cultivating

collaboration among learners.



“The span of time between learning something new, being able to apply it, and

finding that it is outdated and no longer useful continues to decrease. This phenomenon

is what Gonzalez (2004) refers to as the "half-life" of knowledge - the time span from

when knowledge is gained until it becomes obsolete,” (Davis, Edmunds, & Kelly-

Bateman, 2008). Considering that, educational technology seems a necessity today, the

importance of which transgresses differences in learning style or circumstance. The

readings and discussions of this course have prepared me to enrich my instructional

design with interactivity, collaborative problem-solving activities, graphic organizers, and

other technological tools (O’Bannon, Puckett, & Rakes, 2006).



I now understand attention, motivation, and learning as a complex interplay of

individual learner characteristics, the environment, the instructional design, and the

learning community. I take with me from this course a deep appreciation for Cercone’s

(2008) discussion of the importance of considering learning styles when developing

online learning for adults, particularly: “Lifelong learning may be enhanced if students

are motivated to learn by understanding their learning style,” (Coffield, Moseley, Hall, &

Ecclestone, 2004). I cannot embed personal assessments of learning style in every

instructional design, but I can work from a blended foundation of Gardner’s (1999)

theory of multiple intelligences and Palloff and Pratt’s (1999) suggestion that “students

learn best when they approach knowledge in ways they trust,” to craft learner-centric

experiences that I hope will engage and change my learners as this course has

engaged and changed me.  


Sally Bacchetta

References

Anderson, J.R. (1990). Cognitive psychology and its implications (3^rd ed.). New York: Freeman.

Atkinson, R.C., & Shiffrin, R.M. (1971). The control of short-term memory. Scientific American,

225, 82-90.

Baddeley, A.D. (1998). Human memory: Theory and practice (Rev. ed.). Boston: Allyn and

Bacon.

Cercone, K. (2008). Characteristics of adult learners with implications for online learning design.

AACE Journal, 16(2), 137–159. Retrieved from

http://www.editlib.org/index.cfm?fuseaction=Reader.ViewAbstract&paper_id=24286

Coffield, F.J., Moseley, D.V., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in

post-16 learning: A systematic and critical review. London: Learning and Skills Research

Centre. Retrieved September 1, 2004, from http://www.lsda.org.uk/files/pdf/ 1543.pdf

Craik, F.I.M., & Tulving, E. (1975). Depth of processing and the retention of words in episodic

memory. Journal of Experimental Psychology: General, 104, 268-294.

Davis, C., Edmunds, E., & Kelly-Bateman, V. (2008). Connectivism. In M. Orey (Ed.),

Emerging perspectives on learning, teaching, and technology. Retrieved from

http://projects.coe.uga.edu/epltt/index.php?title=Connectivism

Gardner, H. (2003, April 21). Multiple intelligences after 20 years. Paper presented to the

American Educational Research Association, Chicago, IL. Retrieved from

http://www.pz.harvard.edu/Pls/HG_MI_after_20_years.pdf.

Gilbert, J.E. & Han, C.Y. (2002). Arthur: A personalized instructional system. Journal of

Network and Computing Applications, 22(3), 149-160.

Gleick, J. (1987). Chaos: The making of a new science. New York, NY: Penguin Books.

Gupta, P. & Cohen, N.J. (2002). Theoretical and computational analysis of skill learning,

repetition priming, and procedural memory. Psychological Review, 109, 401-448. 

Keller, J.M. (1987a). Development and use of the ARCS model of instructional design. Journal

of Instructional Development, 10(3), 2-10.

Merriam, S.B., & Caffarella, R.S. (1999). Learning in adulthood (2^nd ed.). San Francisco:

Jossey-Bass.

O’Bannon, B., Puckett, K., & Rakes, G. (2006, March). Using technology to support visual

learning strategies. Computers in the Schools, 23(1/2), 125-137.

Morris, C.D., Bransford, J.D., & Franks, J.J. (1977). Levels of processing versus transfer-

appropriate processing. Journal of Verbal Learning and Verbal Behavior, 16, 519-533.

Moscovitch, M., & Craik, F.I.M. (1976). Depth of processing, retrieval cues, and uniqueness of

encoding as factors in recall. Journal of Verbal Learning and Verbal Behavior, 15, 447-

458. 

Nairne, J.S. (2002). Remembering over the short-term: The case against the standard model.

Annual Review of Psychology, 53, 53-81. 

Palloff, R.M., & Pratt, K. (1999). Building learning communities in cyber-space. San Francisco:

Jossey-Bass.

Putting the Pieces Together

Several weeks ago I was asked, "Through what methods, either conventional or unconventional, do you seem to learn most productively?" I responded, "I learn best through experience and most through failure. Success confirms what I believe to be true; failure reveals new truths," and “My thinking and experience are most closely aligned with Constructivism.” Now, several weeks more learned and well-read, my answer is the same.

Do I know more now than I did when I began this course? Have I, in fact, gained knowledge from the assigned readings, group discussions, and professor’s feedback? If “learners create their own meaning of knowledge,” (Jung and Orey, 2008), then indeed, I do, and I have.

Today the question before me is, “Now that you have a deeper understanding of the different learning theories and learning styles, how has your view on how you learn changed?” Although still Constructivist, my view is less arrogant, somewhat less self-centric, and it feels less solitary. I have tended to embrace some tenets of Constructivism more than others, grooving with the notion of individual interpretation and getting tripped up by the importance of the environment.

That changed when I was introduced to Connectivism in this course: “Knowledge is literally the set of connections between entities. Learning is the creation and removal of connections between the entities, or the adjustment of the strengths of those connections,” (Downes, 2012), and for some reason or reasons, that really jives for me. I am very comfortable apart, but I now more deeply appreciate the value of being part of. “Experiences with the environment are critical to learning,” (Ertmer & Newby, 1993). 

Technology is instrumental in my learning. Without it, I wouldn’t be a student of an online university. I wouldn’t have met and challenged and been challenged by my virtual classmates, each of whom has changed me distinctly by our presence in each other’s lives. Technology enables me to enter and exit environments largely at will, and to create and remove my connections between entities, which means that I can learn and grow with and from more diversity than a non-technology me could ever imagine.

Sally Bacchetta

References

Bednar, A.K., Cunningham, D., Duffy, T.M., and Perry, J.D. (1991). Theory into practice: How do we link? In G. Anglin (Ed.), Instructional Technology: Past, Present and Future. Englewood, CO: Libraries Unlimited, Inc.

Downes, S. (2012). Connectivism and Connective Knowledge: Essays on meaning and learning networks.

Ertmer, P. and Newby, T. (1993). Behaviorism, Cognitivism, Constructivism: Comparing Critical Features from an Instructional Design Perspective. Performance Improvement Quarterly, 6(4), pp. 50-72.

Jung, E. J. and Orey, M. (2008). EDIT 6100 Introduction to Instructional Technology. Comparison of Major Learning Paradigms.