Not due to math knowledge, but due to difficulty applying knowledge in real-world scenarios
accustomed to structured learning, struggle more with open-ended, problem-first approaches compared to those trained in Western-style
superficial engagement, reliance on structured guidance, avoidance of ambiguity, and resistance to open-ended problem-solving
Failed in abstraction (encoding) and application (decoding)

Since 2021, the Swiss Institute of Artificial Intelligence (SIAI) has refined its approach to teaching AI and data science (DS), learning valuable lessons from our early cohorts of students. One of the most significant insights we have gained is that students do not struggle due to a lack of mathematical knowledge. Instead, they find it difficult to engage with knowledge in a way that allows them to apply it effectively in real-world scenarios.

Many of these difficulties arise from differences in learning styles. Students from highly structured educational backgrounds, particularly those accustomed to traditional Asian learning methods, often face challenges adapting to our problem-first, exploratory approach. Western-style education, which emphasizes independent problem-solving and conceptual reasoning, has proven to be a significant shift for many of our students. While this transition can be difficult, we believe it is essential for real-world success.

Beyond Math: The Real Challenge

SIAI’s experience over the past few years confirms that success in AI and DS is not just about understanding formulas or solving equations but about knowing how to use this knowledge in practice. Students from various backgrounds have joined our programs, and we have found that their struggles are not necessarily correlated with their university’s prestige. Instead, the greatest challenge for many students has been moving from structured, well-defined problem-solving toward the type of open-ended, real-world thinking required in AI and DS.

Key Observations:

• Students struggle not with math, but with application. Many know the formulas but cannot use them in uncertain, real-world contexts.
• Textbook knowledge is an abstraction. Students must learn to reverse the abstraction process when applying theories in practice.
• Those accustomed to structured, test-based learning struggle the most. They are used to predefined solutions rather than exploratory problem-solving.

Our teaching philosophy is rooted in the belief that textbook knowledge alone is insufficient. Many students fail not because they do not understand theoretical concepts but because they cannot translate those concepts into real-world applications. This is where a significant cognitive gap exists. Textbooks present an abstracted version of reality, simplifying complex problems into models, theories, and equations. However, when students need to apply this knowledge in practice, they must learn how to reverse the abstraction process, translating theoretical models back into the messy, uncertain, and highly variable problems of the real world.

For many students, this transition is difficult because they have been trained to focus on structured problem sets with clear solutions rather than dealing with ambiguous, real-world challenges. Understanding AI and DS is not just about encoding knowledge—it requires decoding reality itself.

In short, a majority of Asian students failed to grasp the concept of encoding and decoding.

Asian vs. Western Learning Approaches

Asian educational systems are well-known for their strong emphasis on procedural mastery, structured problem-solving, and rigorous test-based evaluation. These methods produce students who are highly skilled at following established processes and excelling in standardized assessments. However, while this approach works well for structured learning, it does not always prepare students for fields like AI and DS, which require flexible, adaptive thinking.

Key Differences Between Asian and Western Approaches:

• Asian education emphasizes structure and memorization. Students excel at following predefined formulas but struggle with ambiguity.
• Western education emphasizes conceptual reasoning and exploration. Students are encouraged to justify their reasoning and navigate uncertainty.
• AI and DS require the Western approach. Success in AI depends on solving ill-defined problems and working with incomplete data.

Western education, on the other hand, emphasizes conceptual reasoning, exploratory problem-solving, and open-ended discussions. Students are encouraged to test different approaches, justify their reasoning, and work through uncertainty. Studies, such as a 2019 paper in Cognition and Instruction, have shown that while Western students may not always outperform their Asian counterparts in computational efficiency, they tend to excel in applying knowledge in real-world settings.

At SIAI, we have deliberately adopted a Western-style, problem-first teaching approach because we believe it is the most effective way to prepare students for the realities of AI and DS. Success in this field requires more than technical knowledge—it requires the ability to navigate complexity, adapt to new challenges, and derive solutions without predefined steps.

Key Challenges Faced by Students

From our experience, students who struggle the most at SIAI tend to face the following challenges:

• Superficial Engagement with Learning Materials – Some students read only the surface-level content and assume they have understood it. When asked to explain concepts in their own words or apply them in a different context, they realize they lack a deep understanding.
• Difficulty in Independent Research – Many students expect direct answers rather than seeking out information themselves. This reliance on structured guidance prevents them from developing the self-learning skills necessary for AI and DS careers.
• Avoidance of Struggle and Ambiguity – In AI and DS, many problems do not have clear-cut solutions. Some students become frustrated when they cannot immediately find the “right” answer, leading them to disengage rather than persist through trial and error.
• Lack of Open-Ended Thinking – AI and DS require working with incomplete information and making educated decisions based on limited data. Some students resist this uncertainty, preferring problems where a single correct answer exists.

Why We Focus on Western-Style Education

Over the past four years, we have refined our approach at SIAI to focus on what truly matters: bridging the gap between theory and real-world problem-solving. While some students initially struggle with this transition, those who push through emerge as independent thinkers capable of tackling complex AI and DS challenges.

Our Core Teaching Principles:

• Textbook knowledge is not enough. Students must learn how to apply theory to real-world, uncertain environments.
• AI and DS require adaptive thinking. Rigid, structured learning does not translate well to real-world challenges.
• Western-style education fosters independence. Our program forces students to solve problems autonomously, just as they will need to do in the workforce.

Our message to students is clear: success in AI and DS is not about memorizing more formulas or perfecting structured exercises. It is about developing the ability to think, adapt, and problem-solve in the face of uncertainty. Those who embrace this challenge will thrive. Those who remain dependent on structured, execution-based learning will find it difficult to transition into real-world applications.

At SIAI, we do not fail students. We provide the environment and challenges necessary for growth. It is up to students to make the transition from structured learners to adaptive problem-solvers. Those who succeed will find that this transformation is not only valuable for AI and DS but for any complex field where innovation and independent thinking are required.

What does SIAI take going forward

From this painful experience over the past four years, we have shifted our focus of admission from academic credentials to encoding/decoding flexibility. Our earlier assumption that outperformance in earlier schooling can be a persuasive indicator of academic and business success at and beyond SIAI has been disproven by 100+ students from Asia.

Although we do believe western schools run higher education with significantly different direction, it has come to our attention that siding with specific background may limit our potential to grow in network and more creative thinking.

From the understanding all together, going forward, the admission process will mainly focus on whether students can overcome hurdles each by each. More skillful,, versatile, and flexible students will have less trouble overcoming the hurdles, and those the key features we believe will be the very key of the academic success at SIAI as well as future success in the field. In the end, all students will be benefited by our alumni network.