Financial Literacy

Like many others of my generation and younger, Millennials feel wholly unprepared when it comes to matters of personal finance. And the statistics, sadly, bear this out to be true.

We came together as a team of instructional designers to examine the issue more critically and try to find if perhaps the key to changing poor financial habits could be found through instruction. If you have the time and would like to read a much more detailed version of this project, click here.

While discussing which instructional design model would be best suited for this project, we ultimately decided to apply a Design Thinking Process first. Applying the Empathize stage allowed us to gather research data first so that we could see the problem(s) more clearly.

Conducting User Research

We benefited immensely from having people like Sung Jung, a former investment banker and our financial literacy subject matter expert, provide guidance throughout our project. With his encouragement, we designed a Qualitative user research plan and gathered 17 survey responses while conducting 3 interviews.

Our research allowed us to detect and make sense of various insights with which to inform the following series of Analyses we conducted, beginning with our Needs Analysis. At this point, we were confident that the Kemp model, with its non-linear and flexible approach, would serve as the ideal fit for this project - especially due to how well it was able to synchronize with the Design Thinking Process - and thus applied it to our design.

Needs Analysis

Our data not only helped us get to know our users better but we were able to isolate pain points and identify specific learning gaps, like:

• Knowledge Gap: Does the problem stem from a lack of knowing?
• Skills Gap: Would learners have to practice it in order to get better?
• Motivation Gap: Does lack of motivation prevent learners from solving this problem?

The problem, as we were able to define it, was rooted in the fact that these critical life skills were never taught as part of any school curriculum. In fact, even today, it is only mandated by just a handful of states.

Combined with the learning gaps identified above, the problem presented a clear need for an instructional intervention, although special attention would also need to be paid to addressing the additional Skills and Motivational Gaps as well.

Learner Analysis

We applied the Smaldino, Lowther, and Russell learner analysis method (2012) in order to focus our attention on the 3 following attributes of our learners:

• General Learner Characteristics: 70% of respondents had Master's degrees, and 75% were between 23-35. They were all busy students or working professionals but highly keen on improving their financial literacy.
• Specific Entry Competencies: 72% rated themselves as average or below in terms of their existing knowledge. The vast majority also said that whatever knowledge they did have was piece-mealed together through free online resources (like YouTube videos).
• Learning Styles: Learners already felt an inherent sense of stress when it came to financial matters, so they asked for a stress-free solution that was visual in nature (more graphics and videos than text) and did not feel very academic.

Content Analysis

As our SME helped us realize, the topic of financial literacy is so vast that even those who are highly literate would still admit it took years to learn. With the time constraints we were facing, therefore, we would realistically only have time to focus on just 1 aspect of it. So we let the data help us decide which to focus on, with our survey results revealing investing as the financial skill learners wanted to know most.

With the help of our SME as well through secondary desk research, we conducted a Content Analysis to determine what, exactly, learning about investing would entail. Through successive iterations of this analysis, we were able to narrow our scope down to 2 manageable categories:

• knowing "how" to invest - understanding the core concepts behind making sound investment decisions
• knowing "what" to invest in - understanding the various investment vehicles and options

Goal Analysis

With a clear idea of what the problem was (Needs Analysis), who our target audience was, what they already knew, and what they wanted (Learner Analysis), and a defined scope of instruction (Content Analysis), we concluded the Analysis phase of our project by setting instructional goals and objectives through our Goal Analysis.

Per our Content Analysis, we wanted to ensure that learners would be able to know both "how" to invest as well as "what" to invest in. Using the Morrison, Ross, & Kemp approach (2006), we organized these general ideas into the following 2 terminal goals for our instruction - that upon completing our instructional solution:

Terminal Goal 1

learners will be able to understand the rationale and core concepts of investing

Terminal Goal 2

learners will be able to create an investment portfolio that fits their budgets and risk tolerance

We applied a Divergent Thinking approach at the beginning of our Design phase in order to begin ideating some potential solutions.

Our Early Ideas

Based on what we learned during our Research and Analysis phases, we applied a Brainwriting ideation approach with the following parameters in mind:

• Highly Educated & Busy: The solution should assume that learners are college-educated and busy working professionals or grad students.
• Prior Knowledge: The solution should take into account the learners' pre-existing knowledge, which will differ between individuals.
• Stress-Free & Visual: The solution should be more visual than text-based and allow for high user freedom in its interactivity.

idea #1: competency through cognitive apprenticeships

The idea here is to offer pre-recorded video courses on the subject matter followed by chats with live advisors (experts). How does this fit in with our parameters?

• Credible Experts. Although there are plenty of free resources on financial literacy today, learners struggle to know who they can trust; whereas this solution brings in certified experts.
• Scaffolding. The live chats encourages learners to think aloud (externalize their thought processes), which allows experts to better personalize and scaffold their learning.
• Personalized. Due to the 1-on-1 nature of the interactions with experts, the learning is very personalized to the individual.

idea #2: engagement through interest-driven learning

With this idea, learners fill out an assessment on the app, which then assigns them to a learning track tailored to their specific goals and knowledge levels.

• Authentic. When the learning experience provides authentic challenges that learners know can be applied in the real world, it motivates them towards achieving a more robust understanding.
• Motivating. By placing the emphasis on making the experience fun and engaging, this solution helps to address the Motivation Gap that we identified in the Needs Analysis.
• Existing Knowledge. With this solution, the learner's prior knowledge is taken into account, so users who are more advanced wouldn't have to start from the basics (possibly causing them to become disengaged).

idea #3: motivation through rewards

Learning is encouraged through the use of a reward system (for completing modules or overcoming challenges). It might also be able to unlock real world prizes, depending on relevant factors.

• Motivating. Winning points or prizes is always a great motivating factor for learners.
• Engaging. The gamification aspect has the potential to make what would otherwise be a traditional lecture into something fun and interactive.
• Immediate. Achieving true competency requires the ability to delay gratification. Reward systems make this process enjoyable, endurable, and, thus, sustainable.

idea #4: authenticity through scenario-based learning

eLearning modules put the learner as close to the real-live context as possible, which allows them to know how to respond appropriately to similar situations in the future.

• Authentic. Learners are able to prepare themselves for likely real-world scenarios.
• Interactive. Scenario-based modules allow learners to interact rather than passively absorb information.
• Engaging. Instead of having to read lengthy descriptions or technical explanations before interacting, eLearning scenarios allow learners to learn from the context by picking up clues as they go along.

Our Final Design Solution

Through the application of Convergent Thinking, we pulled together a final design solution, beginning with our design rationale to use Cognitivism as our guiding learning theory.

In particular, Cognitivism emphasizes factors that were highly relevant to our situation, such as the use of pre-existing knowledge, cognitive load, and self-regulated learning. Although it was not the only theory we ended up incorporating, it provided the overarching framework.

Logic Model

At this point, we constructed a logic model in order to illustrate how we hypothesized our solution would lead to the desired effects and changes.

Persona

One of the strengths of the Kemp model is its constant emphasis on the learner. By placing the learner at the center of the model, it allows the designers to always keep the learner's characteristics in mind as they design each stage of the process.

With that in mind, we decided to bring back one of 3 personas we had created during the Analysis phase, Bria, to be our first "test user" of this solution.

Learner Journey Map

By constructing a learner journey map using Bria's background, we were able to test out how a hypothetical interaction with our final design solution could play out (and possibly learn what worked well and what would need further revision).

As mentioned above, we faced some hard time and budget constraints, which forced us to push out a "bare bones" prototype that did not include all the features we were hoping for (at least not yet).

Building Prototype 1.0

Nonetheless, our first prototype, built on Articulate Rise 360, was able to serve its purpose by getting into the hands of potential users early on so that we could follow our own design strategy of "test early and test often."

Design in Action

Before we get to the actual prototype (which you can interact with below), how, specifically, did we end up incorporating elements of our guiding learning theory into our final design?

Applying our Learning Theory of Cognitivism:

• Pre-existing Schema. The module begins with a pre-assessment in order to gauge the learner's prior knowledge and assign an appropriate learning track for them.
• Self-Regulated Learning. We designed the module to provide maximum user flexibility and freedom by drawing from the Cognitivist theory of SRL that students independently and proactively select learning environments that are advantageous to them.
• Cognitive Load. George Miller's theory (7 +/-2) guided our decision to keep information chunked into cognitively-manageable portions.

Applying the Cognitive Theory of Multimedia Learning (CTML) to our Media Selection:

• Videos. We used videos to present the learning content wherever possible in observance of the dual-channels assumption (verbal + visual) of the CTML.
• Interactive Graphics. Humans learn better from words and graphics than from words alone, so we paired visuals with text, making sure that the visuals were actually doing the heavy lifting when it came to transferring the actual instructional content.

Applying a Behaviorist approach with Positive Reinforcement:

• Rewards System. As mentioned above, we borrowed elements of other theories where we saw fit. For instance, we gamified the experience by incorporating points and rewards for learners to unlock as they complete learning modules.

Rise 360 eLearning Module

Click here or on the image below to give our Rise 360 prototype a try.

The Kemp model works off the fundamental belief that design is a continuous cycle with revision being an ongoing process; this was how we approached the Development-Implement-Evaluate stages (aka iterative Prototype-Test-Refine cycle).

Building Prototype 2.0

The next iteration was built on Figma.

[coming soon]

How would we know if our solution actually worked the way we had designed it to? We formulated an Evaluation Plan and used the findings from it to compile an Evaluation Report. We concluded the report with our recommendations for whether to adopt our intervention.

The Evaluation Process

Evaluation Plan

We began by brainstorming a list of relevant formative and summative evaluation questions, including why we were asking those questions, and how we would go about collecting data from them.

We instituted the Dick et. al (2011) method for our evaluations (rather than the Kemp model) because it was much more in line with what we wanted to discover. In particular, this method recommends conducting usability tests with users of different expertise levels (low, middle, and high), which aligned with how we had designed our solution.

Usability Testing

We gathered 4 test users of varying prior knowledge levels to interact with our solution through a usability test. They were encouraged to verbalize their thoughts using the Think Aloud Protocol.

Data Analysis

Affinity diagramming allowed us to spot patterns and insights from the data. We made notes to help guide us in our second iteration of this solution, which we listed under "future modifications" below.

Findings

What did we learn from testing with users?

• Assess, not Stress. While it was a great idea to assess users' pre-knowledge at the beginning, the assessment itself should not be so difficult that it could end up demotivating them from continuing.
• Visual > Text. Users greatly appreciated the visual nature of the learning content. Instead of reading text, they highly preferred to learn things through multiple senses (in line with Richard Mayer's theory of Multimedia Learning).
• Test Early, Test Often. Frequent knowledge checks were not only fun and engaging for users, they helped them keep newly-learned facts fresh.
• Incentives Work. Users may be either intrinsically or extrinsically motivated to learn at the beginning, but what kept them coming back was the rewards system and gamification of the learning experience.