import matplotlib.pyplot as plt
import matplotlib.patches as patches
Idea¶
Have you ever wondered why you enjoy doing some tasks more than others? Or why some people prefer to work independently, while others thrive in a group setting? Why some learn slowly and steadily, while others study in bursts — alternating between periods of intense effort and apparent inactivity?
As humans, we differ from one another — not just physically, but also in terms of our psychological makeup. We have different goals, desires, and motivations. One person may be drawn to the battlefield, another dreams of becoming an astronomer, and a third wants to start their own business and earn a lot of money. Psychologists have long asked whether — and how — we can study people in order to understand what motivates each of us and what we truly value in life.
If we could identify these driving forces, we’d be able to tell in advance, for example, which team member would be motivated by a promotion, who prefers a pay raise, and who values flexible working hours most. Who would stay late to work on an ambitious project, and who just wants to go home on time.
We could also determine who’s best suited to lead, who performs well under pressure, and who falls apart. Who needs detailed instructions, and who only requires a general direction. Who will complete a task faster, and who — while slower — will do it more thoroughly.
If only there were a tool that could assess us in this way: revealing our inner drives, aptitudes, and motivations...
Values¶
Each of us holds certain beliefs — often unconsciously. Yet whether we’re aware of them or not, they influence our lives. They’re connected to the emotions that drive us: pulling us toward some things and pushing us away from others. They are the underlying motivation behind our behavior.
# Ustawienia wykresu
fig, ax = plt.subplots(figsize=(8, 2))
# Rysowanie prostokątów
rect_values = patches.Rectangle((0.1, 0.4), 0.2, 0.2, edgecolor='black', facecolor='lightblue')
rect_motivations = patches.Rectangle((0.4, 0.4), 0.2, 0.2, edgecolor='black', facecolor='lightgreen')
rect_actions = patches.Rectangle((0.7, 0.4), 0.2, 0.2, edgecolor='black', facecolor='lightcoral')
# Dodawanie prostokątów do wykresu
ax.add_patch(rect_values)
ax.add_patch(rect_motivations)
ax.add_patch(rect_actions)
# Dodanie tekstu do prostokątów
ax.text(0.2, 0.5, 'WARTOŚCI', horizontalalignment='center', verticalalignment='center', fontsize=12)
ax.text(0.5, 0.5, 'MOTYWACJE', horizontalalignment='center', verticalalignment='center', fontsize=12)
ax.text(0.8, 0.5, 'DZIAŁANIE', horizontalalignment='center', verticalalignment='center', fontsize=12)
# Rysowanie strzałek poza prostokątami
plt.arrow(0.3, 0.5, 0.05, 0, head_width=0.05, head_length=0.05, fc='black', ec='black') # Strzałka z WARTOŚCI do MOTYWACJE
plt.arrow(0.6, 0.5, 0.05, 0, head_width=0.05, head_length=0.05, fc='black', ec='black') # Strzałka z MOTYWACJE do DZIAŁANIE
# Ustawienie granic wykresu
ax.set_xlim(0, 1)
ax.set_ylim(0.3, 0.7)
# Ukryj osie
ax.axis('off')
# Wyświetl wykres
plt.show()
But here's the catch: our beliefs aren’t fixed. They're not set in stone. They change over time. What’s important to us when we’re young may be irrelevant in old age. What motivates us when we’re single may differ entirely once we’re in a relationship. And sometimes a single life event — the birth of a child, the loss of a loved one, or surviving a serious accident — can shift our entire system of values.
That’s why it’s worth revisiting and examining our values from time to time — to understand how we’ve changed and how our motivations and life goals have evolved.
History¶
SoV – Study of Values
The first scientific attempt to categorize values and study them came in 1931, when Allport and Vernon classified people into six types:
- The theoretical type — driven by a search for truth and knowledge
- The economic type — practical and focused on utility
- The aesthetic type — who seeks beauty and harmony
- The social type — prioritizing love and altruism
- The political type — valuing power and influence
- And finally, the religious type
Now, let’s not laugh at what people believed a hundred years ago — psychology was just in its infancy. Just imagine what people in the 22nd century will think of us.
RVS – Rokeach Value Survey
Over 40 years and one world war later, in 1973, Milton Rokeach proposed that all humans, across the globe, share the same fundamental values. What differentiates us, he argued, is the hierarchy of those values. For some, religion or personal achievement may be of utmost importance. For others, it could be safety or family. But we all operate within the same set of core values — we just prioritize them differently.
PVQ – Portraits Value Questionare
A major leap forward came in 1987 when psychologist Shalom Schwartz discovered that human values form a closed, circular structure. If arranged in a circle, adjacent values are similar, while those on opposite sides are conflicting. Remarkably, the first value connects seamlessly with the last — no matter where you start — forming a beautiful, mathematically complete whole. This structure is illustrated in the graphic below.
The PVQ Questionnaire
Realizing that people often struggle to name or define their own values — but are quite good at comparing themselves to others — Schwartz developed a unique questionnaire. It consists of dozens of items, each describing a person making a particular life choice. Your task is to evaluate how much you identify (or don’t identify) with that person.
The questions are unbiased and realistic, describing scenarios and decisions that are sensible and common in everyday life. The brilliance of the method lies in this: by identifying more strongly with one type of choice, you simultaneously distance yourself from another.
This allows us to map your personal value structure on Schwartz’s circle as a kind of "amoeba-shaped" profile. The surface area is constant for every individual, because emphasizing some values inherently means de-emphasizing those on the opposite side of the circle. The result isn’t a jagged shape with sharp spikes — it’s smooth, with rounded "pseudopod-like" extensions, reflecting how valuing one area often overlaps with neighboring values. This shape also serves as a subtle check on the sincerity of the respondent.
Interestingly, when the results are averaged across the global population, the shape becomes a perfect circle. This suggests that humanity, as a whole, balances itself out: we seem to need both the assertive and the compassionate, both leaders and helpers. Philosophically speaking, for every Hitler, there’s a Saint Francis — maintaining a kind of dynamic equilibrium that improves our species’ chances of long-term survival. After all, societies driven solely by power, hedonism, or extreme altruism don’t tend to last long.
Schwartz refined his questionnaire for years. It has been used to study tens of thousands of people worldwide, and since 2012, it's been part of the European Social Survey. In Poland, Dr. Jan Ciechiuch spent two decades adapting and improving it, culminating in the PVQ-RR questionnaire in 2017 — and this is the tool we use in our study.
Our goal¶
Our three-person team — Adrian, Andrzej, and Rafał — set out to build an application and conduct a psychological survey among students of the “From Zero to AI” course.
We aim to identify what motivates people who sign up for this course — specifically, the underlying values driving their motivation. We hope to find that participants share a common set of dominant values. Of course, it may turn out we’re wrong — and that, on average, they form a perfect circle, just like the global population.
We also want to examine whether there is a correlation between personal values and course engagement — how quickly and thoroughly participants progress through the material. How far do they get? On the flip side, we want to understand what drives those who — unfortunately — drop out, lose motivation, or disengage along the way.
This would allow us to assess, right from the start, each participant’s likelihood of completing the course — and would help course creators design personalized motivational strategies for those who, through no fault of their own, face lower odds of completion (because their individual value profiles differ from those of typical graduates).
Until now, all motivational strategies used in the course have been uniform. Now we have a chance to change that — and make the system much more effective.