Category Archives: Graduate Coursework

EME 6646 “Explain Brain Basics” Assignment

Assignment 1: Explain Brain Basics
For EDF 6646: Learning, Instructional Design, and Cognitive Neuroscience
By Richard Thripp
University of Central Florida
May 21, 2017

Magenetoencephalography

Magenetoencephalography (MEG) is a new type of non-invasive brain scan that detects brain activity via the associated magnetic fields (MEG Community, 2010b; PBS, n.d.). Although strictly speaking it is not an “imaging” technique, it nevertheless provides time-sensitive data about the activity of groups of neurons, and can be combined with functional magnetic-resonance imaging for spatial information (Rees, 2011). MEG is very expensive—not only does one MEG device costs millions of dollars and weigh approximately eight tons (PBS, n.d.), but it must be placed in a room with carefully designed, comprehensive magnetic shielding. Magnetic fields emitted by the brain are so faint that the earth’s magnetic field itself is 100 million times more powerful (MEG Community, 2010b). Consequently, it is unsurprising that few MEG machines exist—in the entire state of Florida, the only MEG machine is at the Florida Hospital for Children in Orlando (Florida Hospital, n.d.; MEG Community, 2010a).

An MEG device principally includes a helmet with about 300 sensors that use superconducting coils cooled with liquid helium to –452° F. This array is able to detect signals from the brain to an accuracy of less than 1/1000 of a second, which was unheard of with prior technologies (MEG Community, 2010b). Thus, it can detect, in real time, both spontaneous brain activity and activity from an evoked response such as visual or auditory stimuli. MEG is valuable for both medical treatments (e.g., epilepsy; Florida Hospital, n.d.) and research (e.g., cognition; Freeman, Ahlfors, & Menon, 2009). On its own, it may provide more accurate “source localization” than electroencephalography (EEG), meaning that the source of brain activity can be isolated to within a general region of the brain (MEG Community, 2010b). However, while EEG has a much higher latency, it also has specific uses that make it complementary to MEG (Sharon, Hämäläinen, Tootell, Halgren, & Belliveau, 2007), and in fact, MEG, EEG, and fMRI can be used in concert to give a more accurate spatial and temporal depiction of brain activity, and perhaps even to determine the antecedents of cognition (Freeman et al., 2009), albeit with significant challenges and costs.

Security, Lie Detection, and Privacy

Rees (2011) explains that the desire for neuroimaging to allow humans to “detect covert mental states or deception” (p. 17) is strong. Despite the many problems and limitations associated with current techniques, a prevailing assumption that these will be overcome via technical means is apparent. While the polygraph is an unreliable approach to lie detection that relies on skin conductance rather than neuroimaging, neuroimaging techniques themselves are also quite susceptible to countermeasures—individuals may deceive such attempts at detecting deception with practice or training. While present attempts to deploy neuroimaging and related techniques for lie detection, predicting recidivism, and determining criminal intent are lacking in rigor and validity (Rees, 2011), the privacy implications of deploying such technologies to improve human–computer interactions are plainly evident (Fairclough, 2009). Data about neurophysiological states can be used to make computers more responsive and useful, but can also be leveraged to spy on or manipulate individual users, as well as to analyze users in aggregate without their consent. Therefore, Fairclough (2009) suggests that users should be given a great deal of control over the information collected, and should also be required to opt-in to such data collection with written consent.

How Much of the Brain Can One Develop Without?

Amazingly, anomalies in brain development can be compensated for by neuroplasticity, to the extent that such individuals may have a semblance of normalcy in adulthood. For example, Herkewitz (2014) summarizes the story of Michelle Mack, who was missing almost half of her brain at birth, yet graduated high school and is now in her 40s living a satisfying life. Another case described by Yu, Jiang, Sun, and Zhang (2015) involves a woman who has no cerebellum, and yet did not discover this until a hospital visit at Age 24. While according to her mother she could not speak intelligibly until Age 6 nor walk until Age 7, in her hospital visit she presented no signs of aphasia and only mild to moderately impaired speech, and she is married and gave birth to a daughter without incident. Finally, the case of Trevor Waltrip, a boy born with severe hydranencephaly whereby he developed with only a brainstem but no brain, is highly unusual because he lived to Age 12, although blind and unable to speak (Madden, 2014). Typically, children with this condition die shortly after birth. However, although there are many popular news articles with Waltrip’s story online (www.google.com/search?q=Trevor+Judge+Waltrip), it may be dubious because there appear to be no references to it in academic literature. Nevertheless, there are many other cases that demonstrate the brain’s plasticity particularly in childhood, but also to a less extreme degree in adulthood. Therefore, it has become clearly inaccurate to characterize the brain as a machine that can only deteriorate—the brain can also adapt to physical damage, and, of potentially greater importance, cognitive performance may be improved or regained through rehabilitation in a manner reminiscent of physical rehabilitation (Doidge, 2009).

References

Doidge, N. (2009). The brain: How it can change, develop and improve [Video file]. Retrieved from http://www.youtube.com/watch?v=tFbm3jL7CDI

Fairclough, S. H. (2009). Fundamentals of physiological computing. Interacting With Computers, 21, 133–145. http://doi.org/10.1016/j.intcom.2008.10.011

Florida Hospital. (n.d.). MEG: Advanced neuroimaging at Florida Hospital for Children. Retrieved from https://www.floridahospital.com/children/neuroscience/epilepsy/MEG

Freeman, W. J., Ahlfors, S. P., & Menon, V. (2009). Combining fMRI with EEG and MEG in order to relate patterns of brain activity to cognition. International Journal of Psychophysiology, 73, 43–52. http://doi.org/10.1016/j.ijpsycho.2008.12.019

Herkewitz, W. (2014). How much of the brain can a person do without? Retrieved from http://www.popularmechanics.com/science/health/a13017/how-much-of-the-brain-can-a-person-do-without-17223085/

Madden, N. (2014, September). Keithville boy born without brain dies at 12. Retrieved from http://www.ksla.com/story/26405843/keithville-boy-born-without-brain-dies-at-12

MEG Community. (2010a). Groups and jobs page. Retrieved from http://megcommunity.org/groups-jobs/groups

MEG Community. (2010b). What is MEG? Retrieved from http://megcommunity.org/what-is-meg

PBS. (n.d.). Scanning the brain: Magenetoencephalography. Retrieved from http://www.pbs.org/wnet/brain/scanning/meg.html

Rees, G. (2011, January). The scope and limits of neural imaging. In C. Blakemore et al. (Eds.), Brain Waves Module 1: Neuroscience, society, and policy (pp. 5–18).

Sharon, D., Hämäläinen, M. S., Tootell, R. B. H., Halgren, E., & Belliveau, J. W. (2007). The advantage of combining MEG and EEG: comparison to fMRI in focally stimulated visual cortex. NeuroImage, 36, 1225–1235. http://doi.org/10.1016/j.neuroimage.2007.03.066

Yu, F., Jiang, Q.-J., Sun., X.-Y., & Zhang, R.-W. (2015). Letter to the editor: A new case of complete primary cerebellar agenesis: Clinical and imaging findings in a living patient. Brain, 138(6), 1–5. http://doi.org/10.1093/brain/awu239

Thoughts on Cognitive Load and the Modality Effect; Self-Regulation and Mindsets

I wrote the following discussion replies for an assignment in IDS 6504: Adult Learning, instructed by Dr. Kay Allen. The first reply is about cognitive load theory and the modality effect; the second is about self-regulation and mindsets.

IDS 6504 Assignment 6: Replies to Others
Richard Thripp
University of Central Florida
March 17, 2017


FIRST REPLY

Richard Thripp, responding to [redacted]

Question: What are strategies that can be implemented to reduce cognitive load?

General Comment: Reducing extraneous cognitive load, that is, cognitive load unrelated to the instructional materials themselves, is a worthy goal. Two of your references might be characterized as the modality effect—that presenting information both visually and auditorily can reduce cognitive load as compared to using only one modality.

Supplement: When considering cognitive load and the modality effect, one should also look at whether the instruction at hand is system-paced or self-paced. Classroom lecturing, such as the Lewis (2016) article you cited, is a classic example of system-paced instruction, because the learner cannot decouple the auditory portion of the presentation from the visual portion—these two modalities are temporally linked. This is good. In fact, Ginnas’s (2005) meta-analysis found a strong presence of the modality effect for system-paced instruction, but a weaker presence when instruction is self-paced. In self-paced instruction, the learner consumes instructional materials in one modality while having the option of referring to materials in other modalities. An example is a textbook or learning modules with graphics and text, supplemented by an audio or video clip to be accessed separately. The modality effect may be so bad for self-paced instruction that it may even be worse than presenting instruction in one modality, at least according to a study by Tabbers, Martens, and van Merriënboer (2004). This implies that temporal contiguity is essential. Therefore, instructional designers may want to be cautious about providing text-based modules with multimedia supplements. In fact, if we accept the argument of Tabbers et al. (2004), it may be better to force students to watch a video where the temporal contiguity of multimodal information is preserved (i.e., learners hear the audio that accompanies relevant text at the right time, rather than minutes or hours after reading the text in the learning module or textbook), at least with respect to cognitive load theory and the modality effect.

While I have not mentioned the cueing effect, it may be important to the modality effect if cues are linked across modes (e.g., a narrator telling the learner to look at a particular portion of a diagram). However, the cueing effect, quite often, is seen purely in the visual modality, such as highlighting or otherwise visually drawing attention to an area of a figure, graph, table, diagram, or block of text.

As an added comment, what Dr. Allen does in this course with real-time learning sessions is a great example of using system-paced instruction to leverage the modality effect. She does not read from the slides, but auditorily elaborates on the points on the slides with different words. She does not offer the slides for download, nor a text transcript of the spoken portion of the presentation. Ironically, not offering these supplements may actually be preferable to offering them; even learners who miss the real-time session must review a video-recording of it, which ensures that temporal contiguity of the instructional modalities is preserved. If slides and transcripts were offered, learners availing themselves of them would become self-paced with respect to instructional modality, which can have deleterious, or at least sub-optimal, results (Tabbers et al., 2004).

References

Ginns, P. (2005). Meta-analysis of the modality effect. Learning and Instruction, 15, 313–331. http://doi.org/10.1016/j.learninstruc.2005.07.001

Tabbers, H. K., Martens, R. L., & van Merriënboer, J. J. G. (2004). Multimedia instructions and cognitive load theory: Effects of modality and cueing. British Journal of Educational Psychology, 74, 71–81. http://doi.org/10.1348/000709904322848824


SECOND REPLY

Richard Thripp, responding to [redacted]

Question: How can instructors of adult language-learners address the issue of learners’ self-regulation so they may better manage their learning?

General Comment: Self-regulation is multi-faceted. Explaining the research on self-regulation to learners may be beneficial. Influencing learners’ mindsets is another worthy avenue. The instruction or assessment goal at hand is a factor in whether self-regulation should be prioritized or deferred.

Supplement: In their blockbuster literature review and position piece, Muraven and Baumeister (2000) contend that self-regulation is like a muscle—it is finite, can be easily depleted, and yet may also be strengthened by being frequently exercised. Explaining this to learners may improve their understanding of self-regulation and perhaps reduce inappropriate self-blame. Moreover, learners’ personal situations and an educator’s present goals are important. During instruction and formative assessment, encouraging self-regulation among learners may be beneficial. However, allowing learners to exhibit self-regulation by making all assignments and assessments due on the last day of the semester may have profoundly negative results for learners who fail to self-regulate; instead, staggered deadlines can reduce learners’ self-regulatory burdens. Further, educators and institutions arguably should reduce the need for self-regulation among learners who are going through transitions or already have a lot of self-regulatory burdens. For instance, the self-regulation required of doctoral candidates may be foreign and overwhelming, which is a contributory factor toward the undesirable outcome of doctoral attrition (Bair & Haworth, 1999). In response, universities might mandate format reviews, committee meetings, and draft deadlines to reduce doctoral candidates’ reliance on self-regulation.

Another important factor is mindset—whether the learner has a growth mindset (incremental theory of intelligence), meaning they believe they can improve their abilities with effort, or a fixed mindset (entity theory of intelligence), meaning they believe their abilities in a particular domain, or in general, cannot be increased through effort (Thripp, 2016). In an extensive meta-analysis, Burnette, O’Boyle, VanEpps, Pollack, and Finkel (2013) found that having a growth mindset predicted superior self-regulation. Growth mindset can be easily taught through brief instructional modules advocating the brain’s plasticity and potential for growth (Paunesku et al., 2015). Such interventions may have collateral benefits to self-regulation. Efforts should be made by educators to demystify important concepts, such as mindsets and self-regulation, among their learners. Then, learners may achieve metacognitive awareness, becoming empowered to recognize and adjust for their human limitations as a step toward truly taking control of their educations.

References

Bair, C. R., & Haworth, J. G. (1999, November). Doctoral student attrition and persistence: A meta-synthesis of research. Paper presented at the meeting of the Association for the Study of Higher Education, San Antonio, TX.

Burnette, J. L., O’Boyle, E. H., VanEpps, E. M., Pollack, J. M., & Finkel, E. J. (2013). Mindsets matter: A meta-analytic review of implicit theories and self-regulation. Psychological Bulletin, 139, 655–701. http://doi.org/10.1037/a0029531

Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion of limited resources: Does self-control resemble a muscle? Psychological Bulletin, 126, 247–259. http://doi.org/10.1037/0033-2909.126.2.247

Paunesku, D., Walton, G. M., Romero, C., Smith, E. N., Yeager, D. S., & Dweck, C. S. (2015). Mind-set interventions are a scalable treatment for academic underachievement. Psychological Science, 26, 784–793. http://doi.org/10.1177/0956797615571017

Thripp, R. X. (2016, April 21). The implications of mindsets for learning and instruction. Retrieved from http://thripp.com/2016/05/mindsets-education-lit-review/

Pedagogical Implications of the Testing Effect, Working Memory

I wrote the following for an assignment in IDS 6504: Adult Learning, instructed by Dr. Kay Allen. I chose the testing effect and cognitive load theory because of my interest in these constructs and their pedagogical importance.

IDS 6504 Assignment 6
Richard Thripp
University of Central Florida
March 8, 2017

1. Theory and Construct – Cognitive Information Processing – The Testing Effect

2. First Implication for Instruction – Testing learners’ ability to recall (“retrieval practice”) improves learning and assessment outcomes by strengthening both retrieval ability and knowledge encoding.

3. Question – When should teachers and trainers implement retrieval practice to engage the testing effect?

4. Answer – My claim that the testing effect may even improve knowledge encoding sounds audacious to the uninitiated, but is being borne out by recent research—Karpicke and Blunt (2011), in a statement that sounds more like synaptic pruning than an educational phenomenon, propose that “retrieval practice may improve cue diagnosticity by restricting the set of candidates specified by a cue to be included in the search set” (p. 774). That is to say, the testing effect is not so much increasing the number of encoded features, but rather improving the lucidity of the existing encoded features, somewhat like tracing over a pencil sketch in pen. For closed-book assessments, retrieval practice has been shown to be much more effective than repeated study of learning materials, if the exam is given some time after the last study session (in Roediger & Karpicke, 2006, the testing effect was apparent two days and a week later, but not five minutes later). Teachers and trainers should augment their lessons with retrieval practice activities early and often, even for complex materials (Karpicke & Aue, 2015). Simply re-reading a textbook is not enough. Even teachers who implement elaborative learning activities are leaving a great deal of potential learning gains on the table if they do not engage the testing effect through retrieval practice (Karpicke & Blunt, 2011). One of the few times where retrieval practice may not be useful is immediately before an exam (i.e., the five-minute condition in Roediger & Karpicke, 2006). Giving yourself flashcard quizzes while waiting for the exams to be passed out is probably not very useful, perhaps because there simply is not enough time for the testing effect to incubate at this point.

5. References

Karpicke, J. D., & Aue, W. R. (2015). The testing effect is alive and well with complex materials. Educational Psychology Review, 27, 317–326. http://doi.org/10.1007/s10648-015-9309-3

Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331, 772–775. http://doi.org/10.1126/science.1199327

Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17, 249–255. http://doi.org/10.1111/j.1467-9280.2006.01693.x

6. Specific Application – One specific application, employed by Dr. Kay Allen at the University of Central Florida in such courses as EDF 6259: Learning Theories Applied to Instruction and Classroom Management, and IDS 6504: Adult Learning, is to give learners multiple-choice quizzes during lectures. This retrieval practice may aid long-term retention and retrieval ability, particularly for learners who read the textbook, modules, or other supporting materials prior to attending the lecture or web conference.


7. Theory and Construct – Cognitive Load Theory – Working Memory and Cognitive Efficiency

8. Second Implication for Instruction – Instruction should be designed to accommodate the learner’s working memory capacity by reducing or eliminating the need to hold information in working memory unnecessarily. This is just one step toward designing instruction with cognitive efficiency in mind.

9. Question – How should instructional designers account for working memory capacity in multimedia learning?

10. Answer – Multimedia learning activities should be designed to avoid cognitive overload for the target audience (Mayer & Moreno, 2003). If the target audience is learners who are already experts in the field of study at hand, obviously, learning activities that produce substantial cognitive overload for novices might become viable. Cognitive efficiency, or “qualitative increases in knowledge gained in relation to the time and effort invested in knowledge acquisition” (Hoffman, 2012, p., 133), is arguably a worthy consideration—the time and resources available to learners and instructors are perennially constrained. Instruction that exceeds the learner’s working memory capacity most commonly results in cognitive inefficiency, not unlike a computer running out of random-access memory and being forced to “swap” information to the hard disk which is one one-thousandth as efficient. Therefore, instructional designers should not only consider their target audience(s), but develop their multimedia materials with good pedagogy that transcends the target audience. For example, expecting learners to memorize a lengthy number or sentence and then enter this information on a different screen is neither appropriate for novices nor experts (except, in the rare case that the instructional goal is short-term retrieval practice). Instead, the learning activity should be designed so the learner can simultaneously view this information while entering it into a different area or application. In a similar vein, multimedia learning should employ techniques such as segmenting, pretraining, signaling, and weeding to avoid extraneous cognitive load and optimize learning-relevant cognitive load (Mayer & Moreno, 2003), thereby avoiding cognitive or working-memory overload and improving cognitive efficiency.

11. References

Hoffman, B. (2012). Cognitive efficiency: A conceptual and methodological comparison. Learning and Instruction, 22, 133–144. http://doi.org/10.1016/j.learninstruc.2011.09.001

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52. http://doi.org/10.1207/S15326985EP3801_6

12. Specific Application – If you are designing multimedia training that requires interacting with external computer programs, it is not appropriate for this training to take up the entire computer monitor. The training window should be capable of being resized to a smaller size by the learner, so that he or she can avoid unnecessary working memory usage and avoid the split-attention effect by being able to position other computer program windows next to the training window (Mayer & Moreno, 2003). Similarly, within the multimedia training, such situations should be avoided. For a specific application, in IBM’s Statistical Package for the Social Sciences (SPSS), there are many instances where it is impossible to access certain information about the data-set at hand without closing a statistical options menu or dialog box. This phenomenon occurs even when accessing certain information about the data-set is essential to the task at hand in an options menu or dialog box. This is a prime example of poor design that fails to consider cognitive load theory, working memory, or efficiency of any kind besides the convenience of the programmers and developers of the software or training at hand.

13. Specific Application – Supplement – If the prior application is difficult to understand, here is an easy example: you have received a voicemail on your smartphone where the caller has spoken a call-back number that is different from his or her caller ID number. However, without some external tool such as a pen and paper, it is impossible to record this phone number in your phone while listening to it. Consequently, you are forced to hold the number in working memory if an external recording device such as a pen and paper is unavailable, and then enter it into your contacts or dialing app. If you are familiar with the area code, remembering seven numbers is an easy task, but if the area code is unfamiliar, attempting to hold 10 numbers in working memory may easily exceed your working memory capacity. Regardless, from a design standpoint, this is a poorly designed and needlessly inefficient situation.

Task Analysis Comparison for Calculation of Net Worth

I wrote the following paper for my coursework in EME 7634: Advanced Instructional Design, instructed by Dr. Atsusi Hirumi. Net-worth calculation was my chosen topic, due to my persistent interest in financial education.

I am also making this paper and companion slides available for download. The companion slides are not included in the paper. They were made two weeks before I wrote this paper, prior to conducting the actual task analyses.

Download paper as Microsoft Word 2016 document
Download paper as PDF
Download companion slides as Microsoft PowerPoint 2016 file
Download companion slides as PDF

My work should only be used appropriately and I should be credited.


Task Analysis Comparison for Calculation of Net Worth
Richard Thripp
University of Central Florida
March 1, 2017

Calculating one’s net worth is a vital part of financial literacy (French & McKillop, 2016). Tallying the value of one’s assets and debts improves understanding of one’s financial situation. Although at first, this process may seem simple, appraising one’s assets is a complex issue, and even remembering all of one’s possessions and liabilities may be difficult. Therefore, net-worth calculation seems a suitable instructional situation to analyze. For this portfolio analysis, I am applying three alternative analysis techniques that were included in Jonassen, Tessmer, and Hannum’s (1999) handbook—procedural analysis, critical-incident analysis, and case-based reasoning (CBR). The former two are differentiated by their focus on overt elements and underlying methods, respectively, while CBR’s status as a task-analysis method is tenuous and its utility in this situation is marginal—it is included here for demonstration purposes.

Procedural Analysis

This type of analysis is geared toward assembly lines and other easily observable tasks. However, it can be used to describe cognitive activities if they are overtly observable, and when extended with flowcharting, can even describe relatively complex decision-making processes.

The following analysis is for the net-worth calculation task, based on the steps described by Jonassen et al. (1999, pp. 47–49):

  1. Determine if the task is amenable to a procedural analysis. Listing assets and liabilities, looking up their values, and sometimes, appraising values are overt actions and can be conceived as a series of steps. However, recalling all relevant items and appraising values can require covert cognitive processes in some cases, so procedural analysis does not capture everything required for this task.
  2. Write down the terminal objective of the task. “Calculates their net worth by estimating and tallying the values of their real assets and liabilities.” Note that this task excludes analyses of liquidity, cash flow, monthly expenses, and interest rates on debts, which are also important components of one’s financial situation.
  3. Choose a task performer. I am the performer for this task. I achieved competence in this task three years ago. If the training is for novices, Jonassen et al. (1999) say the flowchart should be based on someone who has only achieved expertise recently, to avoid “an idiosyncratic sequence” (p. 47). For this task, Investopedia’s Net Worth Calculator (www.investopedia.com/net-worth) was examined to help guide the analysis. Additionally, based on my knowledge of personal finance, I accounted for a variety of common financial situations (e.g., marriage, retirement funds, etc.).
  4. Choose a data-gathering procedure. I took notes as a silently executed the task.
  5. Observe and record the procedure. I made a text-based list of tasks before starting, and opted to construct a flowchart while executing the net-worth task.
  6. Review and revise outline. This step was skipped, because I did not do an outline.
  7. Sketch out a flowchart of the task operations and decisions. See Figure 1. In constructing this flowchart, is was readily apparent that a complete flowchart would be “cumbersome in detail” (Jonassen et al., 1999, p. 53). Consequently, I constructed the flowchart at an abstracted level that condenses or generalizes many steps. For example, Item 210: “Cash equivalent asset or debt?” actually applies to a host of items including bank accounts, taxable investment accounts, mortgages, student and auto loans, and credit card debts. Item 120: “Recall and list real assets and liabilities …” implies the learner will list assets and debts as separate line items (e.g., house and mortgage would be listed separately). These details and others are omitted from the flowchart to prevent it from becoming overwhelming and unwieldy. At Item 200, a foreach loop is used to iterate over the array (list) of assets and debts, similar to the foreach construct in PHP, a popular web scripting language.
  8. Review the procedural flowchart. This was done during its construction.
  9. Field-test the flowchart. I compared the flowchart to the Investopedia’s Net Worth Calculator (www.investopedia.com/net-worth) to see if it could fit the same situations. The categories of assets and liabilities on this calculator all fit into items on the flowchart. A net-worth spreadsheet is more versatile than Investopedia’s calculator because it can be saved, amended, and reused.

Procedural-analysis flowchart for net-worth calculation task

Figure 1. Procedural-analysis flowchart for net-worth calculation task.

Critical-Incident Analysis

This type of analysis involves interviewing subject-matter experts (SMEs) to gain a realistic understanding of the task at hand, including the important elements (Jonassen et al., 1999). Interview or survey data from SMEs must be culled to remove noncritical elements, focus on the required behavior, and to arrange tasks by importance (Flanagan, 1954). You can also ask your SMEs to arrange tasks by importance (Jonassen et al., 1999).

Continue reading Task Analysis Comparison for Calculation of Net Worth

On the Purported Essentiality of Higher Education for the Adult Learner

Written on January 29, 2017 for an assignment in my Spring 2017 course, IDS 6504: Adult Learning, at University of Central Florida.

1. StatementQuote: The transformation of the world economy over the past several decades has put a premium on an educated workforce. A more fluid and volatile global economy is characterized by more frequent job and career change, which is an important factor in the growing demand for continual learning and skill enhancement. Because of these changes, it is clear that current and future generations of adult workers seeking employment and better quality of life will require more education credentials. Thus 2- and 4-year degrees, certificate programs, and workforce educational and training opportunities are becoming increasingly essential for all workers. (Hansman & Mott, 2010, pp. 19–20)

2. Explanation – There is a lot to unpack in this statement. First, we have to take Hansman and Mott’s arguments with a grain of salt—they are university professors and administrators, who are obviously not a neutral source to ask about the necessity of their practice. It is difficult to imagine them saying that higher education is becoming increasing irrelevant, even if it were true.

Next, we can contrast this 2010 book chapter, having been published after the 2008 financial crisis, with the Reach Higher, America report (National Commission on Adult Literacy, 2008), which was published just three months before the worst part of the financial crisis. The Reach Higher report complains that American adults are less educated than the generation before, unlike every other OECD free-market country. While it is unfair and inaccurate to blame the financial crisis primarily on Americans’ lack of education, in a time of economic recession, high-value skills are essential to obtaining a living wage. I would contend that Hansman and Mott (2010) would not have worded their arguments as strongly had they been writing a few years earlier, when times were good.

However, according to the U.S. Census Bureau (2009), in 2009, of adults aged 25 and older, 85% reported having a high school diploma or equivalent and 28% reported having a bachelor’s degree or higher. These statistics are higher than ever before. To say that Americans are less educated is a misnomer, at least with respect to formal attainment. Nonetheless, it is possible they are completing secondary and post-secondary education yet coming away poorly educated or educated in subjects that do not provide value to employers. If so, educators, administrators, and policymakers share much of the blame.

Economically, globalization is characterized as a foregone conclusion, except perhaps by nationalists like President Trump. However, in lieu of protectionist policies, it becomes necessary for adult learners to develop increasingly specialized and high-value skills to merit a living wage in the open market. Under globalization-friendly policies, coupled with mechanical and technological advancements, jobs can be outsourced to foreigners at a small fraction of the cost of an American worker. First, this applied to durable goods, and now, in the Internet age, it applies even to U.S.-based technical positions, and certainly any jobs that can be performed remotely (e.g., customer service). For example, Americans working in information technology (I.T.) frequently complain about reduced wages or unemployment due to skilled foreigners with H-1B visas flooding the American workforce. These foreign workers are willing to work for far lower wages than Americans were previously accustomed to.

Fundamentally, however, a significant component of the “growing demand for continual learning” (Hansman & Mott, 2010, p. 19) is induced demand. If not for Pell grants, student loans, tax money, and government guarantees, it is unlikely that many of the faculty and staff—even those employed at University of Central Florida (UCF)—would be able to sustain their tenure, salaries, or quality of life. Moreover, the federal government offers student loans at unnaturally low interest rates even to non-creditworthy borrowers pursuing unsalable degrees, further incentivizing perverse educational choices among Americans. Ironically, this may be even more destructive with respect to private institutions. For example, private universities like Keiser University and University of Phoenix are over-priced and fairly pointless compared to public institutions like UCF, and yet ill-advised Americans can be suckered into ridiculous and unnecessary debt burdens due to the illogical availability of student loans for private institutions with low return-on-investment (ROI).

The burgeoning sector of the American economy that operates with relative independence from market forces—government and government-sponsored or government-like enterprises (healthcare, education, large corporations, etc.)—is now the ticket to the American dream. Yes, advanced degrees are usually required. However, I contend that in many cases, the day-to-day duties in a surprising proportion of these positions could be performed by high-functioning high school dropouts with a few months of well-executed training.


3. Statement – “Nearly half of new job growth in the first decade of the 21st century required college or other postsecondary education” (Hansman & Mott, 2010, p. 19).

4. Explanation – Once again, the temptation to conflate formal education with real education is strong. What may really be happening here is that employers are requiring a 4-year degree as a weed-out. My Psychology B.S. does not make me any better an office worker, but in an employer’s market, employers are flooded with desperate applicants. Thus, they use shortcuts to thin the herd. This may be one of the antecedents of the bizarre credential-inflation phenomenon we have seen over the past 50 years. Even quite recently, new advanced degrees like the Doctor of Nursing Practice (DNP) have emerged, arguably to pander to this phenomenon. The cost to the adult learner is staggering. If a job that required 12 years education (Grades 1–12) in my grandfather’s time now requires 17 (Grades K–12 + Bachelor’s), the costs are huge, even to young adults who push straight through. (In truth, completing a 4-year degree in 4 years or less has actually become somewhat unusual.) Entering the workforce at Age 22 with $50,000 in debt versus Age 18 with no debt is a massive handicap, and this is a fairly conservative debt estimate. The 18-year-old can invest in retirement funds and brokerage accounts perhaps 10 years ahead of his/her college-educated counterpart, which can consistently produce a 7% inflation-adjusted annual return. Obviously, a 10-year head start yields an increase of 1.07^10 = 1.97× in retirement, which is almost double.

Consequently, the full-time adult learner pursues education at a massive opportunity cost. It is important for learners and educators to internalize this knowledge and act accordingly. If Americans desire the overwhelming, comprehensive advantages that high socioeconomic status (SES) delivers for themselves and their progeny, then as adult learners, it may be necessary to curate their programs of study with actuarial ruthlessness.


References (Note: Certain references are only included in the narrative as hyperlinks)

United States Census Bureau (2009). Educational attainment in the United States: 2009. Retrieved from http://www.census.gov/prod/2012pubs/p20-566.pdf

Hansman, C. A., & Mott, V. W. (2010). Adult learners. In C. E. Kasworm, A. D. Rose, & J. M. Ross-Gordon (Eds.), Handbook of Adult and Continuing Education (2010 ed.; pp. 13–23). Thousand Oaks, CA: SAGE Publications. Retrieved from http://www.sagepub.com/sites/default/files/upm-binaries/34503_Chapter1.pdf

National Commission on Adult Literacy. (2008, June). Reach higher, America: Overcoming crisis in the U.S. workforce. Retrieved from http://files.eric.ed.gov/fulltext/ED506605.pdf