in performance: bill frisell trio

bill frisell.

Following a keenly textured and wonderfully turbulent second set last night at Louisville’s Clifton Center where he weaved in and out of boppish swing, a neo-calypso groove and an improvisational segment that ran from the contemplative to the beautifully jagged, guitarist Bill Frisell opted for something a touch more familiar. He ended the performance, in quick succession (save for a very brief encore break) with a lovingly animated take on The Beatles’ In My Life, a reworking of the Hank Williams hit Lovesick Blues as a playful shuffle and a lullaby-like finale of Ol’ Man River that, indeed, kept rollin’ along.

Frisell is probably more versed than any contemporary instrumentalist – guitarist or otherwise – at weaving such an entrancing, vocal-less fabric out of pop, country, Americana and his own immensely literate jazz sensibility. Together with bassist Tony Scherr and drummer Kenny Wollesen (players that form the backbone of one of his longest running bands), Frisell constructed music based on roots-savvy simplicity.

The three would regularly affix themselves to a tune’s principal melody, repeat like a chant and watch it slowly melt and morph until their own improvisational handiwork could take over.

It was a continually fascinating process to watch. Sometimes, it allowed songs with inherently strident themes and melodic structures to sooth into something almost neighborly sounding, as in Frisell’s treatment of John Lennon’s Mother. Pulled from All We Are Saying…, the guitarist’s splendid 2011 tribute album to the late Beatle, the piece was delivered with an almost country-esque feel.

In other instances, the trio simply built upon the melodic core of a tune, enhancing or subtracting from it every time its chorus flew by. The winner in this category was Lucinda Williams’ Ventura, which floated along with rootsy solemnity until Frisell injected it with a flavorful power chord here or lush ensemble color there.

The ensemble spirit was high all evening long. Bassist Scherr hardly took his eyes off of Frisell, following the guitarist’s leads and solos while adding his own slo-mo blues swing to another (Hank) Williams staple, I’m So Lonesome I Could Cry. Drummer Wollesen, on the other hand, deftly navigated the extremes of Frisell’s interpretations, like the almost straight blues reading of Bob Dylan’s Masters of War that took several appealing, John Coltrane-ish turns.

Frisell, as always, beamed like the proverbial kid in the candy store throughout the performance. But it was tough to tell which excited him more – the discovery of new interpretive voices for such landmark compositions or the very immediate joy of crafting such music with his friends.

Effective Training Reader Q&A-What Are Adult Learning Principles?

Journal of GXP Compliance April 1, 2010 | Welty, Gordon “Effective GMP” discusses specific good manufacturing practice topics useful to practitioners in compliance and validation. We intend this column to be a useful resource for daily work applications. The primary objective for this column: Useful information.

Reader comments, questions, and suggestions are needed to help us fulfill our objective for this column. Please send your comments and suggestions to column coordinator Troy Fugate at or journal coordinating editor Susan Haigney at

KEY POINTS The following key points are discussed in this article:

* What are the principles of adult learning?

* Adults learn differently than children * It is important to determine whether employees have really learned * It is also important to determine whether employees remember the content of their training * Do adults learn differently as they age?

* A program logic model (PLM) provides a systematic way to manage training * Adult learning principles can be applied to an organization’s training programs.

INTRODUCTION A previous issue of “Effective GMP” (Journal of GXP Compliance, Summer 2009, Volume 13, Number 3) identifies and briefly discusses the following key points that should be considered in management of a GXP training program:

* Training policy, standards, and procedures documented * Training process strategy and approach defined * Principles of adult learning theory considered * Training needs analyzed and prioritized by risk analysis * Collaboration of affected groups with defined responsibilities and requirements for each group * Trainees and their organizations are “customers” of training * Training appropriate for task * Training materials and methods appropriate and effective * Qualified training personnel * Training performance * Training effectiveness monitoring and maintenance * Change training if needed * Training documentation * Efficient and cost-effective training * Senior management support training.

Reader Questions The editors of the Journal of GXP Compliance have received many positive comments regarding “Effective Training” including questions about the principles of adult learning. The comments and questions of readers have been consolidated in the following seven questions. Discussion of these questions follows. Each of the discussions contains information that has important implications for learning. These concepts should be considered in training programs to make organizational learning sessions as effective as possible. Questions discussed are as follows:

* What is adult learning theory?

* Do adults learn differently than children?

* How can we tell if employees have really learned?

* How can we tell if employees will remember the training?

* Do adults learn differently as they age – should an adult at age 25 be trained differently than an adult at age 55?

* Is there a single best learning style for training?

* How can adult learning principles be applied to an organization’s training programs?


Adult learning theory and practice became increasingly well known in the United States during the 20th century. There were a number of reasons for this. Industrialization resulted in substantial demands for training and continuing education of adults, those who had already completed their elementary and secondary education. These demands were increased by the development of the science-based industries such as the pharmaceutical and biopharm industries. Adult education became systematized and then professionalized, foregrounding a series of adult learning principles.

Eduard C. Lindeman (1885-1953) was a proponent of this development in the US (1). During the 1920s, Lindeman proposed a set of adult learning principles (see Table I).

Implications For Training Persons responsible for organizational training programs must evaluate the groups they are training to most effectively conduct training. Consider the following:

* Is this training for new hires or repeat training for people who have been doing the job for 20 years?

* Will the trainees be doing this work for one week and then be released, or will they be doing this work for an extended period – like one year?

* What are the perspectives of the individuals to be trained? Are they highly educated and experienced pharmaceutical scientists or newly hired workers without any background in the industry?

Each of these questions suggests differences in motivation, orientation to leam, experience, self-direction, and individuality – any of which may greatly impact the effectiveness of training. Training programs use the word “training.” Perhaps they should be termed ‘learning” to better focus on their true objective – learning.


It is a principle of adult learning theory that adults learn differently than children. Indeed, the term “pedagogy” derives from the Greek paidagog??s, meaning a (male) child’s tutor. Pedagogy literally means the teaching of children. Malcolm S. Knowles (1913-1997) became a prominent spokesperson for adult education and training after World War II, following the lead of Lindeman and others such as Carl R. Rogers (19021987) (2). Influenced by a Yugoslavian adult educator Dusan Savicevic, Knowles began to use the term “andragogy” to mean the teaching of adults (3).

Knowles stressed the difference between the education and training of children (pedagogy) and the education and training of adults (andragogy) (4). He argued that there are a number of dimensions along which adult learning differs from that of children (5). These include self-concept, experience, readiness to learn, orientation to learning, and motivation to learn (see Table II).

The similarities and differences between Lindeman’s adult learning principles and those of Knowles are clear. For instance, an important similarity of the two is the focus on the experiential base for adult learning. A point of major difference is Knowles’ stress on vocational learning, a focus that Lindeman did not share (6).

Implications For Training The implications of Knowles’ principles for training are also clear (7). There are two implications that should especially be stressed. The training process should recognize and utilize the independence of the trainee as a self-directed person (8) and the trainee’s experiential base.

The author of the training materials should develop the materials to engage the trainee as a self-directed person, as well as to utilize the experiential base that the trainee brings to the training situation. This means, for example, that a supervisor reading a procedure to an audience of trainees is a poor approach to training – it implies that the trainees are not adults and that they cannot read for themselves. Better the trainees to have the opportunity to read over the procedure a day or two in advance and then use the training session to discuss the implications of the procedure for the trainees’ workplace activities.

Likewise the author of the assessment materials should develop a pre-test to assess the trainee’s actual experiential base so that it can be brought into the training situation in a systematic fashion. Technical training is a response to some performance gap on the part of employees. No gap means no training is needed. Requiring employees to participate in unneeded training has a negative effect on the organization’s bottom line. Let the employee “test out” of a proposed training session. Testing out is a cheaper, better, and faster way for the organization to meet its training requirements. The organization can devote the training resources that would have otherwise been utilized to put this employee in this training session to a better purpose.

The trainer should facilitate the trainee’s engagement in the training session by utilizing the trainee’s experiential base whenever possible.


The best way to address this question is to begin by acknowledging the complexity of the issue. There are a number of dimensions of learning; there are several kinds of memory; there are multiple environmental and cultural factors; and there are methodological differences between various studies of learning across the lifecycle (9). All these bear on an answer to the question.

Dimensions Of Learning In the 1950s, in a series of publications called the Taxonomy of Educational Objectives, Benjamin Bloom (19131999) and his colleagues distinguished three domains of learning: cognitive, affective, and psychomotor (10). Within each domain are several categories. For instance, within the cognitive domain are the categories of knowledge, comprehension, application, analysis, synthesis, and evaluation (1 1). These categories are ordered: to know a fact (i.e., recall or recognition) precedes comprehending that fact, etc. Within the affective domain are the categories of receiving inputs, responding to inputs, valuing inputs, organizing values, and internalizing values. These categories are also ordered: to receive an input (phenomenon) precedes responding to that input, which in turn precedes valuing that input, etc.

In the late 1990s, two of Bloom’s colleagues, Lorin W Anderson and David R. Krathwohl, coordinated a revision of the taxonomy of the cognitive domain, analyzing the domain in terms of two dimensions. These are the knowledge dimension and the process dimension.

The knowledge dimension has four categories: factual knowledge, conceptual knowledge, procedural knowledge, and meta-cognitive knowledge (12). These are all nouns.

The process dimension has six categories: remembering, understanding, applying, analyzing, evaluating, and creating. These are all verbs. Like Bloom’s earlier categories, these categories are ordered (13).

This permits the development of a taxonomy table that facilitates the development of behavioral objectives (see Table III).

The appropriate cell in this table is identified for each training objective. For example, a behavioral objective for equipment cleaning might be “At the end of this training session, the trainee will be able to identify any visible residue that remains on the equipment.” Every behavioral objective situates its assessment of trainee proficiency with the phrase “At the end (i.e., time) of this training session (i.e., place) the trainee (i.e., the performer) will be able to. . .” The remainder of the sentence is specific to this particular behavioral objective. The term “identify” refers to the process category remembering, specifically to the sub-category recognizing. The phrase “visible residue that remains” refers to the knowledge category factual, specifically to the sub-category specific detail. The factual condition is a lack of cleanliness on the equipment. When the training has been successful, trainees will demonstrate that success by recognizing the factual condition that there is a visible residue on the equipment (should one exist) and identifying the residue as such to the trainer.

This analytical approach to the development of behavioral objectives ensures that they not only articulate with the operational process that is being trained to (in this case, the cleaning process), but the structure of adult learning theory as well.

Leaving aside for a moment the domains of affective learning and skills acquisition (psychomotor learning), it is clear that there is a complex set of dimensions of learning that must be considered if one tries to answer the question about variation in cognitive learning over time during adulthood. Which aspects of learning will be measured to determine if there is a change in learning over the adult lifecycle?


Even though we do a good job of presenting training, how can we know that the trainees will remember the training and use the training when they do their jobs? This leads to a discussion of the dimensions of memory.

Dimensions Of Memory Turning from the complexities of the learning domains, the processes of memory are just as complex (see Figure 1). The supposition that there exists a unitary memory has been abandoned decades ago in favor of the concept of the fractionation of memory (14). Different kinds of memory involve different systems within the brain (15).

Short-Term Memory. Alan D. Baddeley and his colleagues have proposed a multi-component system of short-term or working memory. This model proposes an attentional control element, supported by phonological and visuospatial perceptual systems (16). It has become the dominant conception in the field of short-term memory studies. This is clearly a complex construct made up of multiple dimensions.

Long-Term Memory. Turning then to long-term memory, it is comprised of two elements: the procedural and the declarative memory systems. As Eric R. Kandel has put it, “Procedural and declarative memory differ dramatically. They use a different logic (unconscious versus conscious recall) and they are stored in different areas of the brain” (17).

Procedural memory is an implicit form of memory, whereby performances can be elicited without conscious thought. The procedural memory system is related to a skill, such as motor or cognitive performance; an example would be operating a hi-lift pallet truck in a warehouse. Within procedural memory, the priming system involves increased sensitivity to stimuli due to previous experience, which occurs outside of conscious awareness. Classical conditioning involves two events, repeatedly occurring close together in time, producing the same response, again outside of awareness. Habituation involves a decrease in response to a stimulus when the stimulus is repeatedly presented.

Declarative (including episodic and semantic) memory, by contrast, is an explicit form of memory, where facts are stored and can be recalled and “declared.” Within declarative memory, the episodic memory system is related to the location or time of a personally experienced event; an example would be the content of a particular training event that this trainee attended. Within declarative memory, the semantic memory system is related to facts that are not based on any personal recollection of episodic memory. An example would be identifying a major pharmaceutical company mat has been subject to merger and acquisition within the past three years.

Hence, long-term memory is also a complex construct made up of multiple dimensions. It is not possible to do more here than sketch the implications of these complexities – of learning domains, of short-term and long-term memory – for the study of variation of learning across the lifecycle. adult learning theory


Should an adult at age 25 be trained differently than an adult at age 55? This leads to another question: do adults learn differently as they age – for example, an adult at age 25 vs. an adult at age 55?

One of the major research projects addressing the relationship between aging and learning is the Seattle Longitudinal Study. This study began in 1956, under the direction of Klaus Warner Schaie (18). It is a longitudinal study of five mental abilities: verbal meaning, spatial orientation, inductive reasoning, numeric ability, and word fluency (see Table IV). This study provides evidence that there is little or no significant decline in these abilities during normal aging until the mid-to-late sixties, and this decline is slow until the eighties (19).

There are further studies that bear on the question. Verhaeghen’s meta-analysis of the relationship between aging and vocabulary scores in 210 articles found substantial and positive age effect in vocabulary scores between younger adults (study level mean age 21 years) and older adults (study level mean age 70 years) (20).

In Michael R?¶nnlund and his colleagues’ Betula study, longitudinal and cross-sectional data from largescale representative samples revealed a decline in declarative memory performance after age 60, especially in episodic memory. However, no episodic decline was apparent before that age, and semantic memory tended to improve up to about age 60 (21).

Bopp and Verhaeghen’s meta-analysis of the relationship between aging and verbal memory span in 123 published studies found significant differences in memory span between younger adults (study level mean age 21 years) and older adults (study level mean age 70 years) (22).

Thus the question initially posed (whether adults learn differently as they age – between age 25 and age 55) could be answered with somewhat more confidence if it were rephrased to be between age 21 and age 70. Even if the question were rephrased, however, the complexities remain.

Implications For Training If there is little or no decline in mental abilities, then the training content and delivery does not need to be revised to accommodate employees of various ages. The trainer should be specifically aware of the difference between the trainability of a particular employee and the experiential base that employee is bringing to the training situation. The fact that the employee, of whatever age, does not find the training content compelling may mean that the trainer must attend more carefully to change management issues around this standard operating procedure (SOP) or the training being conducted.


This question leads to a discussion of learning styles and models of learning styles. A learning style is a habitual method a person tends to employ when acquiring knowledge, attitudes, or skills (23). There are numerous models of learning styles. These models are usually analyzed in terms of a continuum that ranges from a conception of fixed learning styles to a conception of flexible learning styles. An early example of such analysis is Lynn Curry’s “Onion Model” (Figure 2) that literally used the image of an onion to show the range of models of learning styles from models that highlight cognitive personality style (the most fixed), through those that highlight information processing style, to those that highlight instructional preferences (the most flexible) (24).

Another use of a continuum to analyze the range of models of learning styles is found in Learning Styles and Pedagogy in Post-16 Learning: A Systematic and Critical Review (25). This comprehensive review of the various models identified five “families of learning styles,” located along a continuum as follows (see Table V).

One of the major models of learning styles is the VAK modalities model of Rita Dunn and Kenneth Dunn, based on the visual, auditory, and kinesthetic (VAK) modalities of sense perception. Frank Coffield and his colleagues located this model in the “Constitutionallybased” family of learning styles. The Dunn model (see Table VI) employs more than 20 variables, including environmental variables (e.g., seating design), emotionality variables (e.g., motivation), social factors (e.g., group structure), as well as perceptual preferences (e.g., the VAK modalities) (26).

Thus learning styles cannot be reduced to the single dimension of modalities of sense perception. Moreover, the several modalities are not ordered – in particular, the kinesthetic modality does not dominate the other two.

Another model of learning styles that may prove particularly relevant to GXP training is the Felder-Silverman model, the Index of Learning Styles (ILS). The ILS model was specifically oriented to chemical engineering audiences. This model has four dimensions or continua: sensing and intuition, visual and verbal, active and reflective, and sequential and global (27). The development of this model was influenced by several other models (see Table VII).

The ILS has been the object of a number of validity and reliability studies (28). In the Felder-Silverman model, it is clear that sensory modalities are one dimension of learning styles, and active/reflective learning is another (presumably orthogonal) dimension. Thus seeing, hearing, and touching are sensory modalities with a trainee tending towards one or the other as learning style. Whether the trainee also tends toward a more active, engaged learning style, or remains with a more reflective style, is quite a different issue. Whether performance on either dimension relates to trainee proficiency is open to question. As Felder and Brent have put it “What is needed is solid evidence that either supports or refutes claims of the effectiveness of those methods in achieving the desired outcomes” (29).

Implications For Training It is possible to draw several implications for training from the ILS and the study of learning styles. The following paraphrase Felder and Spurlin (30):

* The ILS (or any other instrument) can provide guidance to trainers on the diversity of learning styles within their training sessions. They can orient the training accordingly.

* The ILS (or any other instrument) can help instructional designers create courseware that addresses the learning needs of all of the trainees.

* The ILS (or any other instrument) can give individual trainees insights into their possible learning strengths and weaknesses. They can then strengthen weaker areas, if they so decide.

* Learning styles reflect the trainee’s preferences; they are not infallible indicators of a trainee’s strengths or weaknesses in either the preferred or the less preferred categories of a dimension.

* Learning styles (as measured with the ILS or any other instrument) should never be used to predict trainee performance, or to draw inferences about what trainees are and are not capable of doing.


The discussion has addressed the principles of adult learning and its ramifications to organization training programs. How are these principles of adult learning integrated into an organization’s training program?

Program Logic Model An adult learning program such as a GXP training program can be described in terms of a program logic model (31). Such a model includes the following:

* Input variables, a set of qualitative or quantitative variables that describe the initial state of the program (i.e., trainees and their level of task proficiency) * Program preconditions, relatively invariant program elements without which the program could not exist (e.g., training budget, facilities, etc.) * Program process, a set of program elements that act upon the variables and transform the initial program states into terminal program states * Output variables, the set of variables descriptive of intended program change as well as a record of the terminal state of the program * Program objectives, which represent the standards against which program performance is to be compared (see Table VIII).

For example, consider a training program for the sanitizing of controlled areas. The trainee measures could be proficiency in reducing the level of microbial contaminants in the controlled area. The input criteria for this measure would be trainee lack of proficiency in sanitizing activities and environmental monitoring (EM) data indicating unacceptably high levels of microbial contaminants. These criteria identify the “gap,” mentioned earlier, that is the trigger for technical training.

The preconditions include the trainee qualifications to participate in the sanitization training, the trainer’s qualifications, and the availability of the requisite time, place, and materials (e.g., sanitizing agent, yarn mops, personal protective equipment, etc.) Under process, the trainer activities would include conveying the training content to the trainees in the familiar steps of structured on-the-job training: describe, show, invite trainee’s practice, invite performance, and assess proficiency. Trainee activities could include using the double bucket method, preparing the sanitizing agent, using the appropriate personal protective equipment, etc. Process criteria, for example, include the specific sanitizing agent and solution, Nitrile gloves, etc. They also include criteria for trainer activities such as conformity with familiar adult learning principles as noted – recognizing the independence of the self-directed trainee as well as the trainee’s experiential base, and so forth. In particular, the trainer must not read the sanitization SOP to the trainees.

Finally, under outputs, the criteria include the assessment session wherein the trainee demonstrates proficiency in sanitizing activities and EM data that now fall within acceptable limits.

This illustrates how adult-learning principles can systematically fit into a GXP training program and serve to improve the delivery of the training content by directing the trainer’s activities during the session.

CONCLUSIONS Several points are clear from this discussion. Persons responsible for organizational training programs must assess the groups they are training to most effectively conduct training. There are many differences among employees that can impact the effectiveness of training, and they should be taken into account to make training be as effective as possible.

The training process should recognize and utilize the independence of the trainee as a self-directed person, and consider the trainee’s experiential base. The training materials should engage the trainee as a self-directed person, as well as utilize the experiential base that the trainee brings to the training situation. Likewise the assessment materials should include a pre-test to assess the trainee’s actual experiential base so that it can be brought into the training situation in a systematic fashion. The trainee should be engaged in the training session whenever possible by drawing upon the trainee’s experiential base.

The evidence regarding trainability of adults at various stages of the lifecycle is quite complex, but die argument can be made that there is little or no significant decline in ability during normal aging until the mid-to-late sixties, and this decline is slow until the eighties.

The study of learning styles has several implications for training. A measure of learning styles can provide evidence on the diversity of learning styles among employees, as follows:

* Instructional designers can develop courseware that addresses the learning needs of all of the trainees * Trainers can orient the training appropriately * Individual trainees can gain insight into their learning strengths and weaknesses, and they may strengthen weaker areas, if they so decide.

Learning styles are not infallible indicators of a trainee’s strengths or weaknesses in either the preferred or the less preferred categories of a dimension. Learning styles, however assessed, should never be used to predict trainee performance or to draw inferences about what trainees are and are not capable of doing.

Adult learning theory and practice can demonstrably improve an organization’s training activities and should be carefully reviewed by both training staff and line management to make training and learning as effective as possible.

[Sidebar] TABLE I: Lindeman’s principles of adult learning.

Motivation As adults experience needs and interests that can be satisfied through learning, they are motivated to learn Orientation to learn Adults have a life-centric orientation to learning Experiential base The richest source for adult learning is experience Self-direction Adults need to be self-directed Individual differences Individual differences increase with age [Sidebar] TABLE II: Dimensions of Andragogy vs. Pedagogy.

Self-concept The maturing person’s self concept moves from one of being a dependent personality toward one of being a self-directed human being Experience The maturing person accumulates a growing reservoir of experience that becomes an increasing resource for learning Readiness to learn The maturing person’s readiness to learn becomes oriented increasingly to the developmental tasks of his social roles Orientation to learning The maturing person’s time perspective changes from one of postponed application of knowledge to immediacy of application, and accordingly the orientation toward learning shifts from one of subject-centeredness to one of problem centeredness Motivation to learn As a person matures, the motivation to learn is internal [Sidebar] ARTICLE ACRONYM LISTING ILS Index of Learning Styles PLM Program Logic Model SOP Standard Operating Procedure VAK Visual, Auditory, Kinesthetic [Reference] REFERENCES 1. Eduard C. Lindeman, The Meaning of Adult Education, NY: New Republic, 1926. On Lindeman’s adult learning principles, see also Malcolm S. Knowles, Elwood F. Holton, III, and Richard A. Swanson, The Adult Learner: The Definitive Chssic in Adult Education and Human Resource Development, Burlington, MA: Elsevier, 2005, 6th ed., pp. 39-40. See also Jay Thornton and James C. Fisher “Eduard Lindeman’s Challenge to Adult Education,” Proceedings of the 13th Annual Midwest Research-to-Practice Conference in Adult, Continuing and Community Education, Larry Martin (ed.), Milwaukee, WI, October 13-15, 1994, pp. 198-203. go to website adult learning theory

2. On Lindeman, see Malcolm S. Knowles, The Making of an Adult Educator, San Francisco: Jossey-Bass, 1989, p. 8. On Rogers, see Dennis L. Boyer, “Malcolm Knowles and Carl Rogers,” Lifelong Learning,Vol. 7, No. 4, Jan 1984, pp. 17-20; Carl Rogers, “To Facilitate Learning,” Innovations for Time to Teach, Mal Provus (ed.),Washington, DC: National Education Association, 1966, pp. 4-19; and Carl Rogers, “The Interpersonal Relationship in the Facilitation of Learning,” Humanizing Education, Robert Leeper (ed), Alexandria, VA: Association for Supervision and Curriculum Development, 1967, pp. 1-18.

3. Malcolm S. Knowles, The Making of an Adult Educator, San Francisco: Jossey-Bass, 1989, p. 79. See also Dusan Savicevic, Adult Education, NY: Peter Lang, 1999.

4. Malcolm S. Knowles, The Modern Practice of Adult Education: Andragogy versus Pedagogy, Englewood Cliffs, NJ: Prentice Hall, 1970.

5. See Malcolm S. Knowles et al., Andragogy in Action. Applying Modern Principles of Adult Education, San Francisco: Jossey Bass, 1984, p. 12. The precise number has varying accounts; David M. Kaufman “Applying Educational Theory in Practice,” British Medical Journal, Vol. 25, No.326 (7382), Jan. 2003, pp. 213-216, holds that Knowles had seven principles. Sally S. Russell, “An Overview of Adult-Learning Processes,” Urologie Nursing, Vol. 26, No. 5, Oct. 2006, p. 349-350, indicates that Knowles had six.

6. See James C. Fisher and Ronald L. Podeschi, “From Lindeman to Knowles: A Change in Vision,” International Journal of Lifelong Education, Vol. 8, No.4, Oct.-Dec. 1989, pp. 345-353.

7. Knowles addressed the topic of training directly; see his “Where does Training Fit into the Adult Education Field,” Training and Development Journal, Vol. 33, No. 12, Dec. 1979, pp. 40-42; also Timothy G Hatcher, “An Interview with Malcolm Knowles,” Training & Development, Feb. 1997.

8. D. Randy Garrison, “Self-Directed Learning: Toward a Comprehensive Model,” Aduli Education Quarterly, Vol. 48, No. 1, Fall 1997, pp. 18-33.

9 Some of the methodological issues are reviewed in Christopher Hertzog and John R. Nesselroade, “Assessing Psychological Change in Adulthood: An Overview of Methodological Issues,” Psychology and Aging, Vol. 18, No. 4, 2003, pp. 639-657 10. See David R. Krathwohl and Lorin W. Anderson, “Bloom’s Taxonomy,” Psychology of Classroom Learning, Eric Anderman (ed.), NY: Macmillan, 2009, Vol. 1, pp. 107-110. See also Anita Harrow, A Taxonomy of Psychomotor Domain: A Guide for Developing Behavioral Objectives, NY: David McKay, 1972; E. J. Simpson, The Classification of Educational Objectives in the Psychomotor Domain, Washington, DC: Gryphon House, 1972; and David R. Krathwohl, B. S. Bloom, and Bertram B Masia, Taxonomy of Educational Objectives, the Classification of Educational Goals. Handbook II: Affective Domain, NY: David McKay, 1973.

11. See Benjamin S. Bloom (ed), Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain, NY: David McKay, 1956, pp. 62-200.

12. The category “metacognitive knowledge” refers to the knowledge involved in the selfs planning of task completion, especially learning tasks. This process is to be distinguished from the process of task completion itself. Metacognitive processes include the executive functions of the brain such as self-instruction for task completion and self-monitoring of performance. As Munby and his colleagues have put it, “metacognition refers to higher order thinking that involves knowledge of one’s cognitive functioning and active control over one’s cognitive processes while engaged in a learning task.” See Hugh Munby, Nancy L. Hutchinson, and Peter Chin, “Workplace Learning: Metacognitive Strategies for Learning in the Knowledge Economy,” International Handbook of Education for the Changing World of Work, R. Maclean and D. Wilson (eds.), Berlin: Springer (2009), p. 1765. See also Hugh Munby, Joan Versnel, Nancy Hutchinson, Peter Chin, and Derek Berg, “Workplace Learning and the Metacognitive Functions of Routines.” Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans, LA, April 1-5, 2002; and Hugh Munby, Joan Versnel, Nancy Hutchinson, Peter Chin, and Derek Berg, “Workplace Learning and the Functions of Routines,” Journal of Workplace Learning, Vol. 15, No. 3, 2003, pp. 94-104.

13. See Lorin W. Anderson and David R Krathwohl (eds.), A Taxonomy for Learning Teaching and Assessing, NY: Longman, 2001.

14. See Alan D. Baddeley, “The Psychology of Memory,” The Essential Handbook of Memory Disorders for Clinicians, A.D. Baddeley, M.D. Kopelman and B.A. Wilson (eds.), NY: John Wiley, 2004, Chap. I1 Also see Nelson Cowan, “What are the Differences between Long-term, Short-term, and Working Memory?” Progress in Brain Research, Vol. 169, 2008, pp. 323-338.

15. But see Charan Ranganath and Robert S. Blumenfeld, “Doubts about Double Dissociations Between Short- and Long-Term Memory,” Trends in Cognitive Sciences, Vol. 9, No. 8, August 2005; also Blumenfeld and Ranganath, “Prefrontal Cortex and Long-Term Memory Encoding: An Integrative Review of Findings from Neuropsychology and Neuroimaging,” Neuroscientist, Vol. 13, No. 3, 2007, pp. 280-291.

16. See Alan D. Baddeley, “Working Memory: Multiple Models, Multiple Mechanisms,” Science of Memory, Henry L. Roediger III, Yadin Dudai, and Susan M. Fitzpatrick (eds.), NY: Oxford University Press, 2007, pp. 151-154.

17. Eric R. Kandel, “The Biology of Memory,” The Journal of Neuroscience, Vol. 29, No. 41, October 14, 2009, p. 12750. See also Howard Eichenbaum, “How Does the Brain Organize Memories?” Science, Vol. 277, No. 5324, July 1997, pp. 330 – 332: “Cognitive neuroscientists agree that there are multiple forms of memory, each mediated by distinct brain pathways. There is not such ready agreement, however, as to the critical distinctions among types of memory and the contributions of specific anatomical structures to each.” 18. Klaus Warner Schaie, Sherry Willis, and Grace Caskie, “The Seattle Longitudinal Study: Relationship Between Personality and Cognition,” Neuropsychology, Development, and Cognition, Section B, Vol.11, Nos. 2-3 (June 2004), pp. 304-324; also Klaus Warner Schaie, Intellectual Development in Adulthood, Cambridge: Cambridge University Press, 1996. See Richard Seven, “Study on Aging Still Going Strong Some 50 Years Later,” Seattle Times, November 24, 2008.

19. Klaus Warner Schaie, Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study, NY: Oxford University Press, 2005, p. 15, also pp. 416-423.

20. Paul Verhaeghen, “Aging and Vocabulary Scores: A MetaAnalysis,” Psychology and Aging, Vol. 18, No. 2, 2003, pp. 332-339.

21. Michael R?¶nnlund, Lars Nyberg, Lars B?¤ckman, and LarsG?¶ran Nilsson “Stability, Growth, and Decline in Adult Life Span Development of Declarative Memory: Cross-Sectional and Longitudinal Data From a Population-Based Study,” Psychology and Aging, Vol. 20, No. 1, 2005, pp. 3-18.

22. Kara L. Bopp and Paul Verhaeghen, “Aging and Verbal Memory Span: A Meta-Analysis,” Journal of Gerontology: Psychological Sciences, Vol. 6OB, No. 5, 2005, P223-P233.

23. See Alina M. Zapalska and Helen Dabb, “Learning Styles,” Journal of Teaching in International Business, Vol. 13 Issue3 and 4, 2002, pp. 77-97, esp. p. 79.

24. Lynn Curry, “An Organization of Learning Styles Theory and Constructs,” Paper presented at the Annual Meeting of the American Educational Research Association, Montreal, Quebec, 1983; see also Learning Styles in Continuing Medical Education, L. Curry (ed.), Ottawa: Canadian Medical Association, 1983, pp. 115-131. Curry has gone on Lo develop a more refined conception that includes three elements which, in taken together, define a learning style. These three are the method of motivational maintenance, the level of task engagement, and cognitive control functions; see L. Curry, “Patterns of Learning Style Across Selected Medical Specialties,” Educational Psychology, Vol. 11, Issues 3 and 4. 1991, pp. 247-278.

25. Frank Coffield, et al., Learning Styles and Pedagogy in Post-16 Learning. A Systematic and Critical Review, London: Learning and Skills Research Centre, 2004, p. 11. As they put it (p. 10): “Our continuum is based on the extent to which the developers of learning styles models and instruments appear to believe that learning styles are fixed.” 26. Kenneth Dunn, Rita Dunn, and G.E. Price, Learning Styles Inventory, Lawrence: Price Systems, 1997; also see Rita Dunn, “Multisensory Instructional Packages,” Insights on Learning Disabilities, Vol. 6, No. 2, 2009, pp. 17-19. The model “incorporates twenty to twenty-one elements dependent on the age-appropriate assessments administered;” see Rita Dunn et al., “Impact of Learning-Style Instructional Strategies on Students’ Achievement and Attitudes,” Clearing House, Vol. 82, Issue 3, Jan/Feb 2009, p. 136.

28. Richard M. Felder and Joni Spurlin “Applications, Reliability and Validity of the Index of Learning Styles,” International Journal of Engineering Education, Vol. 21, No. 1, 2005, pp. 103-112; also Thomas A. Litzinger et al., “A Psychometric Study of the Index of Learning Styles,” Journal of Engineering Education, Vol. 96, No. 4, 2007, pp. 309-319.

29. Richard M. Felder and Rebecca Brent, “Understanding Student Differences,” Journal of Engineering Education, Vol. 94, No. 1, January 2005, pp. 57-72, esp. p. 69.

30. Felder and Spurlin, op. cit., p. 110.

31. See Leslie J. Cooksy, Paige Gill, and PA. Kelly, “The Program Logic Model as an Integrative Framework for a Multimethod Evaluation,” Evaluation and Program Planning, Vol. 24, 2001 pp. 119-128; also Nancy L. Porteous, Barbara J. Sheldrick, and Paula J. Stewart, “Introducing Program Teams to Logic Models: Facilitating the Learning Process,” Canadian Journal of Program Evaluation, Vol. 17, No. 3, 2002, pp. 113-141. See also Robert L. Schalock and Gordon S. Bonham, “Measuring Outcomes and Managing for Results,” Evaluation and Program Planning, Vol. 26, 2003, pp. 229-235; and Knowlton Johnson, Carol Hays, Hayden Center, and Charlotte Daley, “Building Capacity and Sustainable Prevention Innovations: A Sustainability Planning Model,” Evaluation and Program Planning, Vol. 27, 2004, pp. 135-149.

[Author Affiliation] ABOUT THE AUTHOR Welty, Gordon

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