Project Management Training | The Value of Training and Certification

The Value of Project Management Training and Certification in the Corporate Environment

Project management training and certification has been gaining a lot of popularity in various industries in the past several years (Project Management Institute, Inc., 2008). While that is a good thing for corporate trainers, there is still a question about its actual value. Is there any actual benefit to providing training (and subsequent certification) in the field of project management, or is project management experience enough to aid corporations with sustained profitability? This question could be the foundation of a comprehensive doctoral study.

Project management is a structured way in which projects (both small and large) can be taken from conception to implementation (Project Management Institute, Inc., 2008). Businesses have ostensibly been managing projects for years, yet the success of those projects has never been guaranteed. Training in project management has been seen as a corrective measure that would increase the success rate of current and future projects. By providing project managers with a comprehensive framework on how to best manage their projects, it could be argued that those project managers will be more successful. Moreover, by requiring certification upon the completion of a training program, businesses are ensuring that their project managers have been able to demonstrate that they can indeed successfully manage projects. Even so, that training and certification requires time and money, and businesses need to be certain that it is worth the investment.

The investment required for project management training becomes problematic because it can be difficult to measure the return on that investment. Several questions arise: Do certified project managers close more successful projects than non-certified project managers? Are businesses able to accurately recover the expenses of project management training and certification through ongoing project management work? Does training make a difference in the success or failure of the project? Can projects be managed without requiring trained (or certified) project managers, resulting in fewer training expenses? These questions form the foundation of an ever-present argument for training in the corporate environment.

The prevailing belief is that training and certification does indeed increase the chance of successful projects (Project Management Institute, Inc., 2008). A research study would be a great way in which to quantify this belief. Instead of merely relying on instinct (i.e., a belief that training is beneficial), a study can be conducted that could analyze both successful and failed projects in an effort to determine if the training of the project manager played a significant role. Once objective data have been gathered, the prevailing belief could be either confirmed or refuted. In addition, actual return on investment could be measured. That measurement, in turn, would provide businesses with valuable information that could help them decide how best to proceed in their project management endeavors in the future.

This would certainly not be an easy study. There are numerous factors that would need to be controlled. Nonetheless, this type of study would be a great way for businesses to choose whether to continue to fund project management training and certification in the future.

Reference
Project Management Institute, Inc. (2008). Value of a credential. Retrieved February 7, 2009, from http://www.pmi.org/CareerDevelopment/Pages/Certification-and-the-Job-Market.aspx

Corporate Training Programs | Intelligence and Education

Intelligence and Education

There are numerous ways to measure intelligence in education. Each methodology provides a glimpse into whether a student could be considered intelligent; however, it is only a glimpse. For each intelligence measurement, there are numerous arguments about what is NOT measured. This post discusses three intelligence measurements and attempts to show the relationship among them.

The first measurement is the Intelligence Quotient (IQ) and how it is distributed along a traditional bell curve. The next measurement is Emotional Intelligence (EI) and how it is complementary to IQ. Finally, Multiple Intelligences (MI) and how there is more than one way to measure intelligence are presented. According to Herrnstein and Murray, “In everyday language, people who are called very smart tend to have high IQs” (1994, p. 21). Because this is such a common way to determine intelligence, this post begins with IQ.

Finding a Place on the Bell Curve
When it comes to measuring intelligence, researchers are looking for a way to distinguish smart people from not-smart people. Herrnstein and Murray believe that “…high intelligence has earmarks that correspond to a first approximation of the commonly understood meaning of smart” (1994, p. 21). Based on this belief, IQ, as a measure of analytical intelligence, can be distributed among the general population along a traditional bell curve.

In Herrnstein and Murray’s book The Bell Curve (1994), the authors define cognitive classes of IQs along a normal distribution. Those who are in Category I are considered very bright and fall above +2 standard deviations. Those who are in Category II are considered bright and fall between +1 and +2 standard deviations. Those who are in Category III are considered normal and fall between -1 and +1 standard deviations. Those who are in Category IV are considered dull and fall between -1 and -2 standard deviations. Finally, those who are in Category V are considered very dull (a term preferred by the authors as being “less damning than the standard ‘retarded’” (p. 122)) and fall below -2 standard deviations. This would seem quite tidy if it were not for several glaring oversights.

While it is difficult for any researcher to exhaust a single topic, Herrnstein and Murray missed several important elements. Franz Samelson (1997) points out that at least three major historical references are not addressed in The Bell Curve. Those missing references would provide valuable supporting information for the reader. From these omissions (as well as from other oversights), Samelson believes that Herrnstein and Murray’s scientific objectivity “turns out to be an illusion” (1997, p. 132). Other researchers tend also to support this belief.

Robert J. Sternberg is one such researcher. Using a variety of references as evidence, Sternberg refutes seven of the book’s major claims (1996). One of his biggest arguments is that much of the study is merely an exercise in statistics. He writes, “Thus, the existence of a general factor [i.e., IQ] tells more about the statistical technique than it does about the mind” (p. 47). Sternberg is also correct in refuting many of the correlations in the book because correlation does not necessarily mean causation.

With as much controversy that surrounds the ideas presented in The Bell Curve, it is not surprising that other measurements of intelligence have emerged. One such measurement is Emotional Intelligence, which is presented in the next section.

A Curve Ball for the Bell Curve
If IQ measures cognitive intelligence, then Emotional Intelligence (EI) measures affective intelligence. Affective intelligence deals with feelings and sensations, both of an individual and of others. Emotional Intelligence is a way to determine if a person is smart about feelings.
Emotional Intelligence (EI) comprises five main domains (Goleman, 1995). The first is knowing one’s own emotions. The second is managing those emotions. Next is motivating oneself. The fourth domain is recognizing others’ emotions. Finally, the fifth domain is handling relationships. More recently, Goleman has split EI into two elements: Emotional Intelligence and Social Intelligence (2006). Goleman states, “…simply lumping social intelligence within the emotional sort stunts fresh thinking about the aptitude for relationship, ignoring what transpires as we interact”(p. 83). Both Emotional and Social Intelligence relate to the affective domain, and it is important to determine how to educate the affective domain.

There is value in educating the affective domain. Addressing the emotions of others is beneficial to society. According to Sherlock (2002), “The thinking-feeling-doing model is an educational process that would lead to greater understanding of others in the global community” (p. 146). Not everyone holds this same view. At the very least, not everyone believes that EI can be a predictor of success.

As a measure of intelligence, EI may not be able to predict an individual’s future success. Based on a study conducted by Barchard (2003), “The cognitive ability domain and the personality domain do a far better job at predicting academic success” (p. 856). Much like IQ, EI is a one-dimensional measurement. It cannot be used alone to determine if someone is smart or if that person can be successful. There are arguments against these findings as well.

One key argument for EI is that more recent research does indeed show a connection between EI and success. Much of the research has been done in the workplace environment instead of in the academic environment (Cherniss, Extein, Goleman, & Weissberg, 2006). In addition, there has been clarification about the relationship between IQ and EI: “Goleman proposes that EI abilities, rather than IQ or technical skills, will better discriminate those who will be most capable in top positions” (p. 242). Nevertheless, both intelligences are necessary.
In essence, IQ and EI are opposite sides of the same coin. By measuring both IQ and EI, a more accurate indicator of a person’s being smart could be obtained. Nevertheless, that still does not provide a complete picture. A person can be smart in still other ways. Gardner’s theory of Multiple Intelligences provides yet another way to measure intelligence.

Flattening the Curve with Multiple Intelligences
No one can deny that IQ and EI each provide a way to measure intelligence. Specifically, they measure analytical and affective intelligence. If someone is analytically intelligent, that person is considered smart. Does this mean that those who are not analytically intelligent are not-smart? That depends on the measurement and on the underlying meaning of the measurement. Because of this subjectivity, other measurements of intelligence, including Gardner’s theory of Multiple Intelligences, have emerged in an effort to flatten the curve.

Gardner’s theory of Multiple Intelligences includes seven ways in which intelligence can be measured. Those seven include musical intelligence, bodily-kinesthetic intelligence, logical-mathematical intelligence (similar to analytical intelligence), linguistic intelligence, spatial intelligence, interpersonal intelligence, and intrapersonal intelligence (1983). These last two are similar to affective intelligence. This is far more encompassing than IQ and EI combined. (It is interesting to note that Herrnstein and Murray called Gardner a “radical” (1994, p. 18).)

Since Gardner’s original theory was published, an eighth intelligence has been added. It is naturalist intelligence (Smith, 2008). While other intelligences have been proposed over the years, they have not been added to Gardner’s theory of Multiple Intelligences because of their flaws. Even the eight intelligences that Gardner supports have their own problems.

One of the biggest problems with the theory of Multiple Intelligences is assessment (Gardner & Hatch, 1989). In order to assess students who are taught using MI, it is not enough to construct yet another analytical test. Instead, a means for providing an “intelligence-fair” method for assessment is necessary (p. 6). Even with such assessments, it is unlikely that any one assessment could determine if someone is smart in any one intelligence. Instead, it is more likely that the assessments could show either strength or weakness in the intelligences (Gardner & Hatch, 1989). This problem of assessment has led to numerous critiques of MI.

One major critique of MI is that it is not based on empirical evidence. Gardner refutes this by writing, “This nonsensical view could not be held by anyone who has ever spent more than five minutes skimming through the book” (1996, p. 2). Another common critique of the theory is that it is attractive because of what it opposes, like standard psychometric tests. Instead, Gardner believes that the theory should not be attractive for what it is not, but for what it is: more than a “one-dimensional approach to students” (p. 2).

There are eight intelligences from which to choose. In addition, as these eight intelligences cannot measure if someone is smart, only if he or she has strength or weakness in any of the intelligences, it is conceivable that everyone has his or her own strengths and weaknesses. This is a notion that is far more compelling than simple smart and not-smart labels.

Conclusion
It is evident that there are numerous ways to measure intelligence. Each methodology presents only a small way in which intelligence can be measured, and not one of them can determine whether a person is smart. This post has presented three intelligence measurements and has shown the relationship among them.

First, the Intelligence Quotient (IQ), as plotted on a bell curve, was presented as a very narrowly focused, one-dimensional way to measure intelligence. Next, Emotional Intelligence (EI) was presented as the softer side of IQ, yet it was still one-dimensional. Finally, the theory of Multiple Intelligences (MI) was presented. It is this final theory that seems to encapsulate what should be most important when considering intelligence in education: everyone is smart in his or her own way.

References
Barchard, K. A. (2003, October). Does emotional intelligence assist in the prediction of academic success?. Educational and Psychological Measurement, 63(5), 840-858.
Cherniss, C., Extein, M., Goleman, D., & Weissberg, R. P. (2006). Emotional intelligence: What does the research really indicate?. Educational psychologist, 41(4), 239-245.
Gardner, H. & Hatch, T. (1989, November). Educational implications of the theory of multiple intelligences. Educational Researcher, 18, 4-9.
Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic Books, A Division of Harper Collins Publishers, Inc.
Gardner, H. (1996, November). Probing more deeply into the theory of multiple intelligences. NASSP Bulletin, 80(583), 1-7.
Goleman, D. (1995). Emotional intelligence. New York: Bantam Books.
Goleman, D. (2006). Social intelligence. New York: Bantam Books.
Herrnstein, R. J., & Murray, C. (1994). The bell curve: Intelligence and Class Structure in American Life. New York: The Free Press.
Samelson, F. (1997, Spring). On the uses of history: The case of the bell curve. Journal of the History of Behavioral Sciences, 33(2), 129-133.
Sherlock, P. (2002). Emotional intelligence in the international curriculum. Journal of Research in International Education. 1(2), 139-158.
Smith, M. K. (2008). Howard Gardner and multiple intelligences. The encyclopedia of informal education. Retrieved January 21, 2009, from http://www.infed.org/thinkers/gardner.htm
Sternberg, R. J. (1996, February). The school bell and the bell curve. Why they don’t mix. NASSP Bulletin, 80(577), 46-56.

Corporate Training Programs | Educational Theory and Practice

Educational Theory and Practice

There is really no right theory or practice in education. Instead, education is contextual. The outcome of the educational endeavor often requires one theory over another. As such, it is rather difficult to compose a post that focuses on only one theory. Because of this difficulty, this post addresses three different practices that have found usefulness in my own teaching. The first that I will discuss is the theory of behaviorism. The second will be a response to a common educational scenario. Finally, I will also describe how Vygotsky’s Zone of Proximal Development has played a role in my classes.

Although there is a lot of criticism associated with behaviorism, I still find it to be an exceptional theory on which to base education. At its core, behaviorism is an educational theory that emphasizes repetition. This repetition continues until a particular behavior becomes automatic (Mergel, 1998). For many skill-based classes, repetition seems to be an excellent way to teach. For example, most students learn their multiplication tables through repetition. Foreign language acquisition also requires some deal of repetition. In nearly all sports, repetition is a key element of learning. While many of these things can eventually be learned through cognitive or constructivist approaches, when time is a constraint, a behaviorist approach seems to be the most effective. As a corporate trainer, I encounter this phenomenon often. Time and budget are always constraints, and training is limited to skills that can immediately be transferred to on-the-job performance. (It is also helpful to measure the return on investment (ROI) in the shortest amount of time.) As such, a behaviorist approach oftentimes is the best approach for corporate training.

In addition to using a behaviorist approach in corporate training, I also feel that an unusual scenario in schools today deserves to be addressed from a corporate training perspective. While I do not completely disagree with the prevailing approach of allowing multiple drafts from students until receiving a passing grade, I also do not believe that it is doing the students a great service. In the corporate world, more often than not, there are not unlimited chances to submit work. If a project is not done correctly, both time and money (sometimes a lot of money) are lost. By allowing students multiple chances to improve their grades, students are presented with an unrealistic expectation for the future. These students will not have that chance when they enter the workforce. Instead of being given unlimited chances to improve, they could be faced with unemployment. While this does not mean that students should not be given the chance to improve, I believe that the approach needs to be somewhat different. Allowing drafts to be submitted for feedback is excellent, and I allow that do be done in my class; however, when it is time for a student to submit an assignment for a grade, that grade should be final. I have found it to be far more effective to ask for exceptional performance than it is to allow for average performance that can be subsequently and incrementally improved.

Asking for exceptional performance can be beneficial when combined with Lev Vygotsky’s Zone of Proximal Development. This learning theory states that there is a gap between a student’s performance and potential (Vygotsky, 1978). A student’s performance can be greatly increased by providing guidance to the student. Continuing with the previous scenario, students could be given guidance on their assignments by the instructor or by more experienced students in order to reach a higher score. This approach could actually encourage more interaction and mentoring among students, which could provide more benefits than merely allowing students to resubmit assignments until they get a grade they like. In my own experience, I have found that partnering students who are weak in one area with students who are strong in that area benefits both students. The weaker student’s performance is improved: he or she moves into the zone of proximal development. The stronger student also gains an even greater understanding of what is being learned by sharing his or her experience with another student.

In the end, there are many approaches to education, and each approach depends on the student, the content, and the context. While I have listed several of my own theories and practices in this response, this is merely a sampling. Education is far more complex than any one theory can describe. Because of this complexity, my own theory is to use those theories that work best with the current combination of students, content, and context.

References
Mergel, B. (1998, May). Instructional design & learning theory. Retrieved March 8, 2009, from http://www.usask.ca/education/coursework/802papers/mergel/brenda.htm
Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.

Computer Software Training – Microsoft Project 2007 for Adult Learners

Microsoft Project 2007 for Adult Learners

In an effort to reduce costs while still providing value to its clients, Computer Aid, Inc. (CAI) is developing a training program that will provide new skills to adults who are re-entering the workforce. These adult learners have few computer skills; however, they are being hired to assist with data entry and tracking on CAI’s projects. The tool that they must use is Microsoft Project 2007. While some of the participants have limited computer skills, the participants are all new to this particular application. As such, this will be a transformative journey for the participants.

In order to address the needs of these adult learners, three learning theories will be combined. First, the entire program will rely heavily on the transformative learning theory that has been developed by Laurent Daloz (1999). In addition, the program will also focus on teaching the participants how to learn through the use of the cognitive learning theory—specifically Robert Gagné’s (1985) nine events of instruction. Finally, because this is a skills-based program, it will also rely on some aspects of the behaviorist learning theory as developed by B. F. Skinner (Merriam, Caffarella, & Baumgartner, 2007).

These three learning theories will all be encapsulated within Levinson’s Phase Theory of Development (Kegan, 1994). As adult learners, these participants are all at an age during which they may struggle with learning. Levinson’s Phase Theory will enable the students to feel more confident in their current phase. This post will present the how the learning theories will be used, how the developmental theory will be used, and what the actual curriculum will be.

Learning Theories
This program will focus on three learning theories. The overarching learning theory will be that of transformative learning. Within this learning theory, the cognitive learning theory will be addressed. Finally, some elements of the behaviorist learning theory will be included. Each of these is described next.

Laurent Daloz (1999) promotes the transformative learning theory as a journey. The learners will go through a process to make incremental steps toward change. In this sense, the course leader will act more as a mentor. In that role, the course leader will guide the participants in their transformation. The participants will need to transform from their previous lives to one of a professional project data analyst. This will be done through many examples, stories, and analogies in the form of guidance from the course leader. This will be done in conjunction with one aspect of the cognitive learning theory.

The purpose of the cognitive learning theory is to develop new capacities and skills to learn better (Merriam, Caffarella, & Baumgartner, 2007). Because many of the participants will have been away from the learning environment for some time, the course leader will need to help the participants learn how to learn. This will be done by following Robert M. Gagné’s nine events of instruction (Gagné, 1985). These nine events will be used each day for each lesson in an effort to structure the content in a way that will facilitate progress. While using these nine events, a behaviorist approach will also be used.

The behaviorist learning theory will be used to produce the actual behavioral change that the participants will need for their new job. Much of the work of B. F. Skinner (Merriam, Caffarella, & Baumgartner, 2007) will be used to ensure that the participants will actually make the required change. The participants will be required to demonstrate that change in behavior through the use of skills assessment and behavioral objectives.

Developmental Theory
In addition to three learning theories, this program will focus on Phase Theory of Development. While there are many phases to this theory, the focus on the middle phases aligns with the ages of the participants. Because of this, there are many advantages to relying on this developmental theory.

Levinson’s Phase Theory has is based on how people develop at different ages (Kegan, 1994). Levinson defines four phases: Childhood and adolescence, early adulthood, middle adulthood, and late adulthood. Levinson focuses primarily on early and middle adulthood. All of the participants in this training program fall in this range. Within these ranges, Levinson presents several key transitional moments that adults will go through.

This program will be a completely new environment for the participants, and they will be asked to make transitions in their lives. The course leader will need to understand how to help them move from one point to the next. Again, this will be done through the use of many stories, analogies, and structure while the course leader is providing guidance.

As adult learners, the participants will have already developed in some ways. They will have all passed the first phase. Many of them will be well into the second phase. Some will be transitioning into the third phase. And a few will already be in the third phase. The course facilitator will address the needs of these various phases throughout the course curriculum.

Course Curriculum
The course on Microsoft Project 2007 will use three learning theories and one developmental theory. The structure of the course will follow Robert Gagné’s nine events of instruction (Gagné, 1985). Those nine events are listed in the follow table, and each event will reflect these theories.

Table 1

Course Curriculum

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Conclusion
In order to meet the needs of its clients, CAI is developing a course to teach Microsoft Project 2007. The approach includes three learning theories: first, transformative learning theory will enable the participants to make the journey to a new career; second, cognitive learning theory will help the participants learn how to learn; and third, behaviorist learning theory will ensure that the participants actually learn a new skill. These three learning theories will also be closely connected to phase theory of development, which will ensure that the transitions necessary for adult learners are met. The combination of these four theories creates a strong program to ensure the success of its participants.

References
Daloz, L. A. (1999). Mentor: Guiding the Journey of Adult Learners. San Francisco: Jossey-Bass.
Gagne, R. (1985). The conditions of learning (4th ed.). New York: Holt, Rinehart & Winston.
Kegan, R. (1994). In over our heads: The mental demands of modern life. Cambridge, MA: Harvard University Press.
Merriam, S. B., Caffarella, R. S., & Baumgartner, L. M. (2007). Learning in adulthood: A comprehensive guide. San Francisco: Jossey-Bass.

Corporate Training Programs | CAI – Computer Aid, Inc.

Who Is CAI?

CAI is a global IT services firm that is currently managing active engagements with over 100 Fortune 1000 companies and government agencies around the world. Specific CAI offerings include balanced outsourcing solutions, legacy Support, application development, knowledge capture, desktop services, and managed staffing services. Our ability to provide on-time and on-budget results has been critical to our success for over 25 years, and our unique methodologies and tools enable us to provide our clients with real techniques for increasing productivity, profitability, and competitiveness.

Headquartered in Pennsylvania, with offices and staff throughout the United States, Canada, Europe, and the Asia Pacific region, CAI offers a variety of delivery options including on-site, off-site, and blended solutions. Our Solution Delivery Centers are successfully leveraged to enable our global staff of 3,000 technical and managerial professionals to quickly and effectively respond to client requirements.

CAI operates on the principle that IT solutions should be delivered at a fixed price, on time, and within budget. To this end, CAI has been focused for 25 years on the development of service models that leverage defined processes and performance metrics in order to maximize visibility, control, and productivity. Each of CAI’s offerings enables customers to concentrate on their core competencies while preserving customer control over the IT function.

High Productivity

Defined processes and performance metrics allow CAI to increase the productivity of IT development and support functions by up to 30%. Increased productivity leads to reduced costs, higher levels of end-user satisfaction, and increased shareholder value.

Fixed Price

More than 90% of all IT projects in our industry are completed on a Time and Materials (T&M) basis. With T&M, it is difficult to manage the project’s scope and expended time. In contrast, CAI provides a fixed-price, shared-risk approach to IT development and support. At CAI, all projects contracted on a fixed price provide customers with a guarantee that the agreed upon scope of work will be completed at the agreed upon price. CAI is not selling hours; we are selling results.

On Time

Fixed price and on-time delivery go hand in hand. Field-proven estimating techniques and performance metrics enable CAI to provide customers with a known delivery date and price. Over the past 10 years, 94% of our projects have been completed on time or early.

In Budget

With fixed price, the budget is known. No surprises – ever! CAI delivers the results customers expect at an agreed upon price. When possible, CAI works to reduce the annual price on multiyear maintenance engagements by increasing productivity and effectiveness.

Defined Processes

CAI’s field-proven methodologies, metrics, and tools improve management control of the IT function and provide the foundation for continuous process and quality improvement in all IT environments. CAI’s methodologies were developed using standard industry approved models and enhanced overtime using a best practices approach. Commitment to process enables CAI to guarantee quality deliverables time after time.

Performance Metrics

Productivity improvement and performance management requires detailed, accurate reporting of all resources. CAI’s proven methodologies, standard estimating techniques, and proprietary tools eliminate subjectivity and help customers make better IT decisions.