By Steven Krolak
(NEW ALBANY, Ind.)–Things you may know about Patrick Lach, assistant professor of finance: He is a financial advisor with his own financial services firm, a contributor to the Wall Street Journal, and the recipient of the 2021 Distinguished Research and Creativity Award (Junior).
What you may not know: He’s downright geeky about his field—in a good way.
In fact, it’s that hint of obsession that drives his attention to detail, which in turn helps him identify dangers and opportunities. Pretty important in finance. But also crucial in teaching, whether it’s finance or something else.
His willingness to go down a tech rabbit hole led him to a new way of preparing students to succeed in the classroom and in the world of business.
Frustration, the mother of invention
Lach’s classroom innovation is the creation of algorithmic problem sets that allow him to fine-tune problems to student performance in real time.
He piloted the use of this approach in his 300-level financial management course and then applied it in his 400-level investment course.
Ordinarily, problems that form homework assignments or quiz questions are taken from a textbook. They have an answer key to check their answers. Students either get it right or get it wrong. And that’s pretty much the end of the story.
For Lach, this was unsatisfying.
“I started to realize that students were not getting the right type of practice with the textbook homework because they were becoming too dependent on the homework solutions from the textbook,” Lach said.
He likened the textbook process to using rebalancing software that automatically return portfolios to their target level of asset allocation. It’s a time- and labor-saving replacement for the painstaking work of grinding through numerous intermediate steps to achieve the final number.
Yet those steps are important. They allow students to get their hands dirty, and they allow the instructor to identify flaws, and help the student work through them..
There were other reasons to be frustrated. The textbook-to-test journey started to feel rote. And from there, it’s a short step to student apathy.
“I knew that I needed to find a way to create unique, authentic problems so that the students could get hands-on practice without the crutch of textbook-provided solutions.”
Enter the algorithms, which enable Lach to manipulate the parameters of any given problem, essentially turning the static textbook question into a living field of endless possibilities. Any of the factors may be changed–interest, rate of return, and so forth. Lach can detect where students are, and help them progress at a reasonable pace.
Proof, pudding, etc.
The algorithmic problem sets manage to incorporate authentic assessment and scaffolding, two teaching best practices.
“Since there can be hundreds of trillions of different variations of a single problem, it is virtually impossible that the same question will be repeated,” Lach said.
That tailored-to-the-student approach is the essence of authentic assessment, which is defined by practices that encourage students to look at questions from a variety of perspectives and that incorporate real-world examples. Authentic assessment is usually involves qualitative measures, but Lach manages to generate one-of-a-kind questions in a quantitative context.
Through close observation, Lach also identified the need to provide an additional layer of scaffolding between homework derived from the textbook homework and problems appearing on exams.
Scaffolding is all about meeting students where they live, ie. adjusting instruction and expectation around current performance, and building from there. As students become more confident, they are more receptive to increasingly challenging problems.
According to Lach, the problem sets are more difficult than the textbook homework as there is no answer key. But because students can “rewind” the problems and check intermediate steps, or work with Lach to play out different scenarios with different inputs, students have a chance to improve, and know why they are improving, before a closed-book exam.
For Lach, the algorithmic problem sets are all about maintaining direct contact with student performance.
“This practice is unique because the algorithmic authentic assessments are instructor-created.” Lach said. “Although many textbooks in quantitative disciplines contain algorithmic problem sets created by the publisher, these often come at a cost to the student and they require the instructor to cede part of their pedagogy to the publisher.”
In that paradigm, the instructor is merely a transmitter. For Lach the unique value of a living, breathing instructor should be the more supple role of creator and guide, not only helping students arrive at the correct answer, but enabling them to come to a deeper understanding of how they got there.
“Instructor-created algorithmic problem sets allow the instructor to customize problems by adding tips such as where to find more information about a particular problem or how to round intermediate steps in a problem,” Lach said.
What emerges is, as Lach describes it, a consistent voice between lectures, homework, and exam questions.
And what about results?
According to Lach, in the first semester he used the problem sets, scores increased by 9.7%–essentially a full letter grade–compared to the previous semester. And students who earned at least a 70% on problem sets scored 23% higher than those who did not, on associated assessments.
Getting students outside the box
Lach’s innovation is a reflection of his teaching philosophy, which centers on inspiring students to want to learn about finance by connecting theory and practice, and providing tools they need to apply this desire to the work.
One of those tools is video tutorials. Lach had noticed that students often told him that they had trouble applying in their homework what had seemed so clear to them in class. Lach’s solution was to create step-by-step videos tutorials to help students review the steps necessary to solve the problems at home.
The key to this technological fix is somewhat old-fashioned.
“I always listen carefully to the way students talk through the questions they missed, so I can try and figure out where the student went wrong,” Lach said. “If I think many students are making the same mistake, I will try to come up with a way to correct the mistake by thinking outside the box.”
Lach’s willingness to step outside the box led him to start his own independent financial services firm in 2011. Much like the doctor in a monster movie who first tries his just-cooked-up antidote on himself to make sure it’s safe for others, Lach entered the financial services world to master every aspect of the business from the inside out, and most importantly, to understand the human consequences of financial decisions. As a result, his lectures are filled not merely with theory but with examples from his firm.
The use of algorithmic problem sets followed a familiar hands-on pattern of listening, comparing test and homework results, and designing an intervention to improve performance.
Growing student interest
Not coincidentally, Lach’s approach mirrors a growing reliance on algorithms and algorithmic thinking in the business world, as leaders begin to understand how these tools can make an entire enterprise more successful.
It’s about Big Data, which is the name given to the mountain of information captured from digital activity. Though impressive in its bulk, the data is useless unless one has a way to leverage it—or at least the most relevant part—to attain a company’s goals.
Algorithms can unleash that potential.
These mathematical formulae are the tools that, like overlays in a presentation, shape the raw data into usable information.
The more granular the information about a consumer, the more precisely a seller can tailor her product’s appeal, on the one hand taking the guesswork out of transactions, on another gathering information for further refinements of the product itself or the messaging used to sell it.
In his classroom, Lach brings this same mindset to students’ homework assignments, as a way to track their individual progress and to identify particular strengths and weaknesses.
In their improved performance, he sees his method validated, but more importantly, he sees the students’ interest grow.