Category Archives: Financial Literacy

Understanding opportunity cost is pivotal to financial literacy

Opportunity cost, the trade-off of making a particular choice, is typically seen as more applicable to economics than personal finance. However, I believe understanding opportunity cost is central to being financially literate, and is sorely lacking among the general public. For example, most people are not aware of the magnitude of the “late-start” opportunity cost of obtaining a four-year degree. Many psychology doctoral graduates are overwhelmed by debt and wish they hadn’t stayed in school so long. While other factors are partly responsible, on the whole, college attendees do not recognize the sky-high value of their late teens and twenties, nor the opportunity cost of their decision. Moreover, delay discounting research shows that people frequently overvalue rewards now versus in the future, particularly if they have addictive dispositions. In part, this may be due to a lack of understanding or consideration for opportunity cost.

Research on consumer behavior shows that perceptions of value are often unduly influenced by coupons, promotions, and advertising. For example, an individual who knows that Tylenol and ibuprofen are the same might buy Tylenol with a coupon, even though the cost is still higher than the generic counterpart. The coupon is seen as a savings, when in fact it induced a purchase which was actually more expensive.

Retail gas prices are highly visible, and are given undue weight by consumers. The same consumer who purchased Tylenol might drive out of his/her way to save a few cents per gallon on gas, or might experience psychological distress at observing a lower price at another gas station subsequent to fueling up. However, the opportunity cost of the price difference is almost certainly inconsequential. In fact, the unhappy feelings themselves are more costly and are antithetical to rational choice theory, because they irrational and counterproductive. An understanding of opportunity cost can make this irrationality explicitly visible.

Human behavior when receiving a “windfall gain,” the unexpected acquisition of wealth that feels unearned, is a premier example of failure to understand opportunity cost. The opportunity cost of spending the windfall money is identical to the opportunity cost of spending any other money. However, the $3000 that is received as an IRS tax refund is spent more easily than the $3000 that is earned day-to-day, as if spending the former has less opportunity cost than the latter. Not so! Amazingly, many people will fail to understand opportunity cost even when it is merely their money that was withheld, interest-free, and is now being returned to them.

Money or items of value that are received for “free” are free only when received, but not when spent. Travel hackers who gain “free” vacations via credit card sign-up bonuses fail to recognize that only the acquisition of the rewards was trivial, but that the opportunity cost of using them for travel is what could have been received by cashing them in or selling them to mileage brokers (albeit, with varying levels of risk which should also be factored into one’s valuation). Gift card recipients spend lavishly, even when they would self-flagellate for making identical purchases with money they “earned.” However, the opportunity cost of spending money one received as a windfall or gift is usually no different from the opportunity cost of spending “earned” money.

Not only do purchasing decisions have opportunity costs, but also time-usage decisions. The opportunity cost of driving, for instance, is much greater than the cost of gas—it also encompasses maintenance, depreciation, and insurance on one’s vehicle, time spent driving, and risk of bodily harm. If one can earn $50 per hour in their area of expertise, the opportunity cost of doing one’s own secretarial or housekeeping work is quite substantial.

Investors who reject the risk of stocks for the “safety” of bonds or treasury bills do so at tremendous opportunity cost. In fact, over long time periods (e.g., over 20 years), the risk of stocks evaporates so much that one is over 99% more likely to lose money having picked the “safe” investments. Pandering to one’s psychological shortcomings comes at immense expense.

If an employer offers a 401(k) or IRA match, the opportunity cost of not taking advantage is staggering. Putting $50 per week into such an account at Age 25, which will immediately be doubled by your employer and feasibly may double every 10 years in the market even adjusting for inflation, can be equivalent to 1600 inflation-adjusted non-taxed dollars at Age 65! Even if we are conservative and halve this to $800, statistically as an American you are very likely to live past 65 and still need money at this age. Nevertheless, so many young people “need” this money to make ends meet, without even understanding the raw deal they have given themselves by not contributing.

Understanding and applying the principle of opportunity cost can literally be the difference between becoming a millionaire or pauper. In the Jump$tart Coalition’s National Standards in K–12 Personal Finance Education, 4th edition, it is mentioned only as “every investing decision has alternatives, consequences and opportunity costs” (4th grade knowledge statements; p. 24) and “every spending and saving decision has an opportunity cost” (8th grade additional knowledge statements; p. 8). Moreover, most K–12 teachers don’t even understand “technical” topics such as opportunity cost, let alone being able to teach them. What a pity.

Rebuttal to Northwestern Mutual’s 2017 Planning & Progress Financial Literacy Study

The 2017 Planning & Progress Study by the Northwestern Mutual Life Insurance Company (NWM) has a press release titled Americans Besieged by Debt: 4 in 10 Spend Up to 50% of Monthly Income on Debt Payments. The inaccuracy and uselessness of this statistic is astonishing, particularly for an in-house press release.

NWM Screenshot 01

Firstly, the statistic should be 4 in 10 among those who reported having debt. According to NWM’s 2017 Debt Dilemma presentation, they surveyed 2117 U.S. adults, plus an oversample of 632 Millennials, for a total of 2749 respondents. NWM’s slides are inconsistent—Slides 3 and 6 say “those with some debt” constituted 1086 respondents, while Slides 4–5 say 1597 respondents. I think the 1086 figure likely included the 2117 adults, while the 1597 figure likely included the 2749 adults (including the oversample), which would indicate that 511 of 632 oversampled Millennials (80.9%) reported having some debt, compared to 1086 of 2117 from the general sample (51.3%). This seems reasonable, given that Millenials are more likely to have student loan debts.

Even if we include the oversample, 1597 of 2749 respondents is only 58.1%. On Slide 4, NWM says that “more than 4 in 10 Americans with debt (45%) spend up to half of their monthly income on debt repayment.” Therefore, among all Americans, this figure should be .581 × .45 = .261 or 26.1%—only 2.6 in 10 Americans report spending up to half their monthly income on debt payments, not 4 in 10 as NWM incorrectly claims. Confusingly, the question asked respondents to exclude their primary home mortgage, yet includes a “mortgage is my only debt” choice, which 15% selected. Adding to the confusion, on Slide 3 it says the “amount of debt” question excluded mortgages, even though the question prompt is “how much do you estimate your debt to be?” without mentioning mortgages. Who knows what is going on here? Can such a survey even be cited when NWM keeps changing their story and refuses to provide the actual questions or raw data?

NWM Screenshot 02

Next, I turn to the elephant in the room—something that is blatantly obvious, at least to me. HOW is “up to half of their monthly income” in ANY way a useful statistic?! This only tells us they do not spend more than half their monthly income on debt payments, which is almost worthless. It would be like saying “4 in 10 Americans consume up to half their calories from donuts,” meaning that they consume anywhere from zero to 50% of their calories from donuts. The NWM statistic does not mean that 55% of Americans with debt spend more than half their monthly income on debt payments (which, if true, would be astonishing and much more meaningful). In fact, in addition to “mortgage is my only debt” (15%), “not sure” (21%) is also an option.

The egregious statistical illiteracy of NWM’s PR department is evident, as is their lack of consultation with whomever at NWM concocted this study, although NWM’s slides are also, at times, bewildering. An interesting and relevant statement would have been “among Americans with debts, 18% reported spending more than half their monthly income on debt payments.” But, “up to half” is sophomoric.

As a general trend, note also that NWM proffers only descriptive statistics rather than inferential statistics. My recent poster presentation, Relationships Between Financial Capability and Education Attainment: An Analysis of Survey Data From the 2015 National Financial Capability Study (NFCS), used inferential statistics to compare knowledge of personal finance with degree attainment. The FINRA Investor Education Foundation is government-funded and is tasked specifically with conducting surveys and statistical analyses, unlike NWM. Nevertheless, FINRA’s 2015 annual report, like NWM’s reports, is devoid of inferential statistics. This is sad. The NFCS provides detailed statistical files, so it’s tempting to argue that such analyses will come out on their own, from unaffiliated researchers. However, too often, this simply does not happen, even though there are many interesting relationships to be examined. In the NWM studies, for instance, running inferential procedures to compare the oversample of Millennials with the general population would empower us to say that Millennials are significantly different along dimensions such as debt burdens, student loans, et cetera, and provide effect sizes to boot. Surprisingly, NWM’s 2017 Planning and Progress Study provided only two reports (the Debt Dilemma and the Financial States of America), unlike past years (e.g., 2016) which had many more reports (eight in 2016), and neither of the 2017 reports include even descriptive statistics on the oversample of Millennials. Why bother collecting the data, then? Well, we know the reason. To market life insurance.

FINRA and NWM should both employ more statisticians, so they can provide insightful and detailed inferential analyses, among other useful statistics. This would greatly increase the value of their surveys to the public and to researchers, including researchers who are capable of performing the analyses but for whom it would only provide tangential value (e.g., supporting evidence for an argument in their manuscript).

NWM Screenshot 03

To complete my rebuttal, I should analyze the rest of NWM’s 2017 Planning and Progress data. Their Financial States presentation is brief, and involves only perceptions. Unlike NFCS, there are no questions that actually measure content-knowledge. The usefulness of asking respondents questions such as “my long-term savings strategy has a mix of high and low risk investments” is dubious. This is the same sample of which 21% does not even know how much debt they have. How do we know whether they consider high-risk investments penny stocks and low-risk investments to be their Bank of America 0.03% APY savings account? Their “mix” of high- and low-risk “investments” could be totally stupid. Without explicitly defining our terminology, and ideally being able to correlate responses with questions measuring financial knowledge or competence, it is difficult to draw inferences from attitudinal questions like the preceding, or questions like “the ‘American dream’ is still attainable for most Americans.” How do you define the American dream? Does it involve emitting an ungodly amount of carbon dioxide and destroying the earth? Perhaps “the ‘human existential nightmare’ is still attainable for most Americans” might be a more accurate question.

NWM Screenshot 04

I found the above figure enlightening. These responses are among the 1086 respondents with “some” debt (evidently excluding the oversample of Millennials; see my discussion earlier). Granted, this question asks “which of the following best describes your strategy for managing your debt,” and much of what is listed are non-strategies. However, the option for “pay all bills monthly/on time” is present, and was selected by only 3% of those with debts. This is horrible. “I pay as much as I can on each of my debts each month” is not a strategy, yet 35% picked it. If you pay as much as you can, how do you know you will even be able to make the minimum payments next month? What do you do for unexpected expenses? Probably payday loans, given the deplorable state of American’s financial expertise. Where is the foresight? “I pay what I can when I can” is equally bad and also a non-strategy—at least 53% of respondents endorsed non-strategies. On the other hand, while not ideal, making minimum payments each month, or focusing on high-interest debts while making at least the minimum payments on others, are strategies. Doing so protects your credit from delinquency and allows you to avail of technical tricks like credit card balance transfers (BT) to mitigate high-interest debts. You can’t get a BT offer on a new credit card if you can’t get approved because of late payments or collections on your credit report.

In conclusion, while I agree with NWM’s conclusion that Americans are a financial basket case, their methodology is idiotic and their claims are blatant statistical misrepresentations. To cap it off, NWM’s infographic below claims that Americans spend 40% of their monthly income on leisure… without mentioning that the question asked respondents to exclude spending on “basic necessities” including housing, food, and transportation! Clearly, NWM is more interested in giving bombastic, just-plain-wrong talking points to the media, rather than an accurate representation of their survey data, which actually is not even in need of embellishment.

NWM Screenshot 05

Educational Attainment and Financial Literacy Questions from the National Financial Capability Study, 2009–2015

Here are my comments and an overview of the questions on the National Financial Capability Study (NFCS) about educational attainment and financial literacy, as they have changed during the three iterations (“waves”) of the survey (2009, 2012, and 2015). The NFCS is a survey that is administered nationally (by the FINRA Investor Education Foundation) to approximately 500 participants per U.S. state (about 27,000 per iteration total, due to large states or certain ethnicities being over-sampled) every three years. It began in 2009, so there have only been three iterations so far. While the raw data is not nationally representative—obviously, sampling 500 people from Alaska and 500 people from Florida grossly over-represents Alaska by proportion of population—the datasets include weighting variables to account for this at the national, state, and census-area levels. It is disappointing to see that the NFCS only began oversampling highly populous states in the latest iteration (2015), and only did so for New York, Texas, Illinois, and California (1000 respondents instead of 500), but this may be due to decisions about the NFCS being surprisingly political.

It is disappointing to see the lack of depth in the educational attainment question in the 2009 and 2012 surveys. Only in the latest version (2015) were options for Associate’s and Bachelor’s degrees added, while the vague “college graduate” was removed. However, now we have no option for trade school or certificate graduates. Moreover, making comparisons between the surveys is difficult. We can combine the two high-school graduate options in the 2012 and 2015 iterations to compare them to the single 2009 option, but it is somewhat tenuous to compare “some college” (2009 and 2012) to “some college, no degree” (2015), to consolidate “Associate’s degree” and “Bachelor’s degree” (2015) to compare them to “college graduate” (2009 and 2012), or to compare “post graduate education” (2009 to 2012) to “post graduate degree” (2015). These changes between survey iterations are not necessarily trivial. Indeed, the “tracking dataset” provided by FINRA, which includes respondents from all three survey iterations but only questions that are included in all three iterations, omits educational attainment due to the lack of consistency.

For the other questions about actual and perceived financial literacy, which is also known as financial capability (the two terms are fairly synonymous but “financial literacy” is the more popular term, despite FINRA and the post-2011 Obama administration relabeling it “financial capability”), the response options (not shown below but can be seen at the NFCS website or the Washington Post) remained identical between survey iterations. As someone interested in investigating the relationship between educational attainment and financial literacy (perceived and actual), it is disappointing to see “do you think financial education should be taught in schools?” being only included in the 2012 iteration, and to see “how strongly do you agree or disagree with the following statements? – I REGULARLY KEEP UP WITH ECONOMIC AND FINANCIAL NEWS” only included in the 2009 iteration. However, it is understandable that the survey cannot be overly long, and perhaps these questions were judged to be unimportant.

Special note on the question: “Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years, how much do you think you would have in the account if you left the money to grow?” —— The response options are “more than $102,” “exactly $102,” “less than $102,” and “don’t know.” This wording is very easy. In fact, it may have been more interesting to make the options centered around $110 rather than $102, in which case the question would be about understanding exponentiation (compound interest) rather than simple addition. Nevertheless, in every iteration, 25 to 27% of respondents got this question wrong! And, as with every question, those with higher educational attainment did better. However, for some questions, such as the one on interest rates and bond prices, even postgraduates did shockingly bad—only 46% of postgraduates in the 2015 iteration correctly answered “they will fall,” and overall, a mere 28% of respondents answered correctly, with 38% answering “don’t know.” Although some of the interpretations are spurious and I disagree with using pie charts to represent such data, this blog post by “the Weakonomist,” regarding the 2012 iteration, shows how terrible the public’s financial literacy is. Of course, on the question where respondents are asked to assess their financial knowledge on a 1–7 scale, most think they are geniuses… pretty sad.


EDUCATIONAL ATTAINMENT

 
What was the last year of education that you completed? [2009 codes]

  1. Did not complete high school
  2. High school graduate
  3. Some college
  4. College graduate
  5. Post graduate education

What was the last year of education that you completed? [2012 codes]

  1. Did not complete high school
  2. High school graduate – regular high school diploma
  3. High school graduate – GED or alternative credential
  4. Some college
  5. College graduate
  6. Post graduate education

What was the highest level of education that you completed? [2015 codes]

  1. Did not complete high school
  2. High school graduate – regular high school diploma
  3. High school graduate – GED or alternative credential
  4. Some college, no degree
  5. Associate’s degree
  6. Bachelor’s degree
  7. Post graduate degree

PERCEIVED FINANCIAL LITERACY

 
2009, 2012, 2015: How strongly do you agree or disagree with the following statements? – I AM GOOD AT DEALING WITH DAY-TO-DAY FINANCIAL MATTERS, SUCH AS CHECKING ACCOUNTS, CREDIT AND DEBIT CARDS, AND TRACKING EXPENSES.

2009, 2012, 2015: How strongly do you agree or disagree with the following statements? – I AM PRETTY GOOD AT MATH.

2009 only: How strongly do you agree or disagree with the following statements? – I REGULARLY KEEP UP WITH ECONOMIC AND FINANCIAL NEWS.

2009, 2012, 2015: On a scale from 1 to 7, where 1 means very low and 7 means very high, how would you assess your overall financial knowledge?


ACTUAL FINANCIAL LITERACY

 
2009, 2012, 2015: Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years, how much do you think you would have in the account if you left the money to grow?

2009, 2012, 2015: Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per year. After 1 year, how much would you be able to buy with the money in this account?

2009, 2012, 2015: If interest rates rise, what will typically happen to bond prices?

2015 only: Suppose you owe $1,000 on a loan and the interest rate you are charged is 20% per year compounded annually. If you didn’t pay anything off, at this interest rate, how many years would it take for the amount you owe to double?

2009, 2012, 2015: A 15-year mortgage typically requires higher monthly payments than a 30-year mortgage, but the total interest paid over the life of the loan will be less.

2009, 2012, 2015: Buying a single company’s stock usually provides a safer return than a stock mutual fund.


MISCELLANEOUS

 
2012 only: Do you think financial education should be taught in schools?

The College Graduate’s “Late Start” Earnings Disadvantage

The College Graduate’s “Late Start” Earnings Disadvantage

This is a simplified, contrived example for illustrative purposes.

Below, we have the 2017 IRS tax brackets for single individuals (for taxes filed in 2018). For this example, I’ll pretend income stays constant and the tax brackets remain the same over an entire working life.

2017 IRS Tax Brackets for Singles

Let’s pretend a high-school graduate earns $37,950 per year of taxable income for 47 years: Age 18 to 64. Let’s pretend a college graduate spends seven years in college, perhaps earning a graduate degree, earning no taxable income during this time, but then earns $69,591.25 per year of taxable income for 40 years: Age 25 to 64. This figure is contrived to result in the college graduate earning exactly $1 million more taxable income than the high-school graduate: $2,783,650 vs. $1,783,650. The college graduate’s $1 million earnings advantage is a common talking point among marketers and educators.

$37,950.00 × 47 years = $1,783,650 [High-school graduate]
$69,591.25 × 40 years = $2,783,650 [College graduate]

(Note: We are just considering taxable income in these examples. The standard personal deduction for 2017 is $6350, so in this example, the high-school graduate is actually earning $44,300 per year and the college graduate is actually earning $75,941.25 per year, assuming both do not itemize.)

Although the college graduate earns $1 million extra, $31,641.25 per year of the college graduate’s taxable income is in the 25% tax bracket, while all of the high school graduate’s taxable income is in the 15% tax bracket or below.

The high school graduate’s taxable income is taxed at 10% on the first $9325 and 15% on the next $28,625.

The college graduate’s first $37,950 of taxable income is taxed the same way as the high school graduate’s. However, the additional taxable income ($31,641.25) is taxed at 25%.

In each year, the high-school graduate pays $5226.25 of federal income taxes, or $245,633.75 over 47 years, which is 13.77% of his/her lifetime taxable income.

In each year, the college graduate pays $13,136.56 of federal income taxes, or $525,462.50 over 40 years, which is 18.88% of his/her lifetime taxable income.

This means that while the college graduate earned $1 million additional taxable income than the high-school graduate, after federal income taxes, the college graduate netted only $720,171.25 more. This is the college graduate’s “late start” earnings disadvantage. While it will usually be more subtle, it is usually there. There is a high cost for failing to saturate the 10% and 15% tax brackets in any calendar year. There is also a high cost for earning more.

Because the college graduate had no taxable income during his/her seven years of college, he/she was missing out on saturation of the lower tax brackets in these years. He/she could have been earning taxable income and enjoying a lower tax bracket on this income if his/her earnings were “spread out,” so to speak, rather than concentrated in a lesser number of lucrative years once the college education had been completed.

Moreover, the college graduate was prevented from contributing to tax-advantaged retirement accounts during Ages 18–24, because earned income is required to make such contributions. This is a tremendous loss. Just by itself, contributing the current maximum of $5500 to a Roth IRA during Ages 18–24 would total $38,500. If this Roth IRA is invested, rather aggressively, in a S&P 500 or total-market index fund, it will probably double every ten years, even adjusting for inflation. This is potentially a 16-fold increase at Age 65, to $616,000. The high-school graduate could contribute to the Roth IRA during Ages 18–24, paying only 15% federal income taxes in these years, which totals $5775 of taxes. Because Roth IRAs are tax-exempt, tax is paid when the money goes in, but not when it comes out. All $577,500 of inflation-adjusted gains would be tax-exempt. These earnings would be in addition to what both the high-school or college graduate could potentially earn from contributing to tax-advantaged retirement accounts at Age 25 and beyond.

Although the college graduate could have, while in college, just worked a few months each year to achieve $5500 of earned income and then contributed the maximum to a Roth IRA, this does not compensate for the previously discussed tax bracket differential. Also, college graduates typically accumulate student-loan debts and would have to take additional student loans to be able to contribute to a Roth IRA. (Taking student loans, if they are below perhaps 10% APR, to contribute the annual maximum to a Roth IRA in a whole-market index fund is actually a great idea, at least from a mathematical, non-psychological perspective. Tax-advantaged retirement contributions are so valuable that the APR of the loan required to make them can exceed the stock market’s average annual return-on-investment [ROI] and they can still be worthwhile. Debt hawks like Dave Ramsey totally eschew this point.)

Finally, there is a lot of collateral damage, so to speak, with achieving a higher income. Higher earners may become ineligible for healthcare subsidies such as the advance premium tax credit (APTC), ineligible for the earned income tax credit (EITC), ineligible for other need-based aid, and subjected to higher income taxes at the state and local level as well.

Due to the time required to acquire specialized knowledge and expertise (whether actual or perceived expertise), college graduates, financially, are late bloomers. This “late start” has substantial mathematical and tax-related costs. Therefore, a comparison of nominal dollars earned in one’s lifetime may present a rosy picture of college’s ROI.

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).

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