Learning curves and the corporate environment

In their seminal 2001 white paper Powering the leap to maturity: The eLearning ecosystem, Pat Dillon and Chas Hallet suggest a useful interpretation and use for the traditional learning curve, and introduce their concept of the e-learning curve. They assert that emerging technology has changed the focus of corporate learning systems from task-based, procedural training to knowledge-intensive performance enhancement where learning interventions are broader-based, flexible, and more adaptable to meet the needs the needs of knowledge workers.

In their white paper, they apply the concept of the conventional learning curve to the context of the corporate learning environment in order to supply an appropriate structure for understanding when and how different modalities of learning are used. Within their framework, the conceptualisation of the learning environment consists of systems to manage and support:

1. instructor-led training
2. cohesive team management
3. knowledge generation and sharing
4. performance support
5. content storage and retrieval
6. on-demand learning

In a similar fashion, I have suggested that we can apply Bloom's Taxonomy of Educational Objectives to a conceptual model of a learning curve (see Figure 1) and begin to investigate how an "e-learning curve" based upon the modalities of that domain would align with the phases of learning in the traditional model.

Figure 1 Bloom's Taxonomy applied to a learning curve

In my view, a constructivist approach provides the most effective means of enabling adults to learn, particularly in the workplace. In the context of Bruner's principles of constructivism (see Table 1) technologies like the Internet, websites, and virtual learning environments, applying collaborative learning, problem-based learning and goal-based mechanisms, making Open Source Software and Course- and Content Management Systems accessible to learners, and using e-learning applications like online conferencing and collaboration tools could be the foundation for these multiple constructivist conditions for learning. (Duffy & Jonassen 1992, Driscoll 1994; Schank 1994)


Table 1. Principles of constructivism (Toward a Theory of Instruction, p.225)

Principle		Definition
Readiness		Instruction must be concerned with the experiences and contexts that make the student willing and able to learn
Spiral organisation	Structure.	The content must be structured so that it can be grasped by the learner.
	Sequence.	Material must be presented in the most effective sequences.
Generation		“Going beyond the information given” - Instruction should be designed to facilitate extrapolation and or fill in the gaps

These characteristics provide an appropriate framework for knowledge workers to learn (and for the learning intervention), given that their ongoing development is based in the context of already-established cognitive schemata (from the learners’ perspective), the knowledge and skills are applied to solve real-world problems, and their expertise (behaviours) are typically used in collaboration with their peers to enhance the performance of organisations.

More tomorrow, when we apply e-learning modalities to the learning curve.

FÓGRA: Somebody asked me what does "fógra" mean.
Fógra (pron. fowgrah. equal emphasis on both syllables) is the Gaelic Irish word for "Notice."
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References:

Bruner, J. S. (1966) Toward a Theory of Instruction. Cambridge, MA: Harvard University Press.

Dillon, P. & Hallett, C. (2001, October). Powering the leap to maturity: The eLearning ecosystem. Cisco Systems white paper.

Driscoll, M. P. (1994). Psychology of learning for instruction. Boston, MA. Allyn & Bacon.

Duffy, T. M. & Cunningham, D. J. (1996) Constructivism: Implications for the design and delivery of instruction. IN: Jonassen D. H. (Ed) Handbook of Research for Educational Communications and Technology (pp.170- 198). New York: Simon & Shuster Macmillan.

Schank, R. (1994) Active Learning Through Multimedia. IEEE Multimedia, 1(1), pp.69-78.
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Fundamentals of learning curves

In the introduction to yesterday's blog post, I alluded to the axiom that 'practise makes perfect' - the concept that the acquisition and improvement of new skills, knowledge or expertise are broadly predicated upon the learner's facility to rehearse and become more proficient in the tasks or activities being practised. This is not news - we have all experienced this process - and behaviorists would assert that perhaps we know it intuitively.

What is surprising is that the rate and shape of improvement is fairly common across learning.

The concept of the learning curve illustrates a simplified model of learning in which knowledge of a given subject is acquired through a progression of steps. Figure 1 shows a model of an idealized (and simplified, and in no way scientifically accurate) learning curve applied to Bloom's Taxonomy. At the lowest levels of the curve, the learner is a novice who then progresses through the various stages of cognitive development, where at each stage they increase in competency until (perhaps up to 10 years later) they reach an expert level of competency in the subject matter being tracked.

Figure 1. Bloom's Taxonomy charted on a learning curve

The learning curve has substantial implications for e-learning: it suggests that practice always helps improve performance, but that the most dramatic improvements happen first, with smaller and smaller incremental improvements being accrued over time. Another implication is that with sufficient practice people can achieve comparable levels of performance. For example, extensive practice on mental arithmetic (Staszewski reported in Delaney et al., 1998) and on digit memorization have turned average individuals into high performers.

The learning curve was devised from the historical observation that individuals who perform repetitive tasks demonstrate an improvement in performance as the task is repeated over time. First studied empirically in the 1930's by T. P. Wright's Factors Affecting the Cost of Airplanes, three conclusions were drawn upon which the current theory and practice surrounding learning curves are based:

1. The time required to perform a task decreases as the task is repeated
2. The amount of improvement decreases as more units are produced, and
3. The rate of improvement has sufficient consistency to allow its use as a prediction tool

In this study, Wright concluded

that consistency in improvement has been found to exist in the form of a constant percentage reduction in time required over successively doubled quantities of units produced. The constant percentage by which the costs of doubled quantities decrease is called the Rate of Learning.

More...

References:

Delaney, P. F., Reder, L. M., Staszewski, J. J., & Ritter, F. E. (1998). The strategy specific nature of improvement: The power law applies by strategy within task. Psychological Science, 9(1), 1-8.

Wright, T.P. (1936). Factors Affecting the Cost of Airplanes. Journal of Aeronautical Sciences, 3.4 : 122 -128.
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Definition of an E-Learning Curve

A colleague recently asked me "What is an e-learning curve?"

Well, when I originally started The E-Learning Curve Blog, my primary concern was to create a witty electronic learning-related title that hopefully caught my potential audiences' eye, and the name implied that the content of the blog would be a learning journey - for me as much as anyone. I can't deny that it's also a nice pun, or humourous play on words.

While undertaking some research on a different topic recently (learning objects - more to come about this in a few weeks), the term 'e-learning curve' cropped up with a certain regularity. Those occurrences, as well as my colleague's query have prompted me to write a short series on Curves (not the geometric kind).

Now read on.

We're all familiar with the old joke about the lost tourist in New York asking a cop how to get to Carnegie Hall. To which the cop replies "Lady, you gotta practice real hard."

Going back to the fundamentals, when we talk about learning, we're discussing ways to acquire new skills, knowledge or expertise. When we use learning curves, we're looking at approaches to measuring the growth or development of these abilities in the individual or group. As learning professionals working, we are perhaps most familiar with Bloom's Taxonomy of Educational Objectives are a means of evaluating a learner's current knowledge- or skill assets, and creating content accordingly to enhance and develop their current cognitive abilities(see Table 1). As is traditional, I will now mention the lesser-known domains, only to ignore them from this point forward...

Bloom identified three domains of educational activities:

• Cognitive: mental skills (Knowledge)
• Affective: growth in feelings or emotional areas (Attitude)
• Psychomotor: manual or physical skills (Skills)

Table 1. Bloom's Taxonomy

Competence Level	Skills Demonstrated
Knowledge Recall data or information.	observation and recall of information knowledge of dates, events, places knowledge of major ideas mastery of subject matter Associated verbs: list, define, tell, describe, identify, show, label, collect, examine, tabulate, quote, name, who, when, where, etc.
Comprehension Understand the meaning, translation, interpolation, and interpretation of instructions and problems. State a problem in one's own words.	understanding information grasp meaning translate knowledge into new context interpret facts, compare, contrast order, group, infer causes predict consequences Associated verbs: summarize, describe, interpret, contrast, predict, associate, distinguish, estimate, differentiate, discuss, extend
Application Use a concept in a new situation or unprompted use of an abstraction. Applies what was learned in the classroom into novel situations in the work place.	Use information use methods, concepts, theories in new situations solve problems using required skills or knowledge Associated verbs: apply, demonstrate, calculate, complete, illustrate, show, solve, examine, modify, relate, change, classify, experiment, discover
Analysis Separates material or concepts into component parts so that its organizational structure may be understood. Distinguishes between facts and inferences.	Seeing patterns organization of parts recognition of hidden meanings identification of components Associated verbs: analyze, separate, order, explain, connect, classify, arrange, divide, compare, select, explain, infer
Synthesis Builds a structure or pattern from diverse elements. Put parts together to form a whole, with emphasis on creating a new meaning or structure.	Seeing patterns organization of parts recognition of hidden meanings identification of components Associated verbs: analyze, separate, order, explain, connect, classify, arrange, divide, compare, select, explain, infer
Evaluation Make judgments about the value of ideas or materials.	compare and discriminate between ideas assess value of theories, presentations make choices based on reasoned argument verify value of evidence recognize subjectivity Associated verbs: assess, decide, rank, grade, test, measure, recommend, convince, select, judge, explain, discriminate, support, conclude, compare, summarize

When designing content, the taxonomy can be used as part of a holistic approach learning and development, rather than as a linear model (see Figure 1).

Figure 1. Bloom's Rose. [Source: John Manuel Kennedy Traverso]

Bloom's taxonomy is hierarchical - learning at the higher levels is dependent on the learner attaining prerequisite knowledge and skills at lower levels (Orlich, et al. 2004). Similarly, the verbs associated with Bloom's taxonomy must enable the learning professional to elicit a measurable result from the learner. From this perspective, we can say that learning can be quantitatively assessed and tracked, and these assessments can be represented on a graph, which leads us neatly to learning curves.

More tomorrow.

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References:

Bloom B. S. (1956). Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain. New York: David McKay Co. Inc.

Orlich, C., Harder, R., Callahan, R., Trevisian, M., & Brown, A. (2004). Teaching strategies: A guide to effective instruction. (7th ed.). Boston: Houghton Mifflin Company.

St. Edward’s University Center for Teaching Excellence. (2004) Task Oriented Question Construction Wheel Based on Bloom’s Taxonomy.
[Internet] Available from:
http://www.stedwards.edu/cte/media/BloomPolygon.pdf [Accessed 15th May 2008]

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