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Summary (17/20) ENGINEERING & DESIGN SCIENCE: SOLVED EXAM QUESTIONS €8,49   In winkelwagen

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Summary (17/20) ENGINEERING & DESIGN SCIENCE: SOLVED EXAM QUESTIONS

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2023/24: This document features detailed answers to past exam questions for the course 'Engineering & Design Science'. This is a compulsory course in the first year of masters for students pursuing "Digital Business Engineering". Please refer to the preface for additional important information!

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  • 19 februari 2024
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  • 2023/2024
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giorgibala
Academic Year: 2023 – 2024

University of Antwerp




EXAM QUESTIONS
ENGINEERING & DESIGN SCIENCE
prof. H. Mannaert

,Preface
This preface is designed to guide students who use this document in their preparation for a successful
exam outcome.

We assure users that the questions listed and thoroughly answered herein closely reflect what will
likely be asked on the exam. In fact, many of these questions have appeared on previous exams. The
course professor tends to maintain consistency in the exam questions, which means there's a high
probability that some questions from the previous academic year might reappear, possibly with
minor modifications. The author of this document confirms that the exam questions for the academic
year 2023-2024 are included within. The responses provided here were utilized in the exam,
contributing to a commendable score of 17/20. This document encompasses a significant portion of
the course material, offering an excellent review opportunity for students.

, A1

QUESTION 1: EXPLAIN THE SCIENTIFIC METHOD.

The scientific method is a systematic way of learning about the world through observation,
experimentation, and analysis to form and test hypotheses. It relies on empirical evidence and
reproducibility rather than on trust or authority. Hence why, trust is the antithesis of the empirical
method. Reliance on trust or belief without evidence is fundamentally opposed to the principles of
the scientific method. The scientific method is grounded in five fundamental steps:

1. Observe a phenomenon: This is the first step where scientists notice something in the
natural world that piques their curiosity or poses a question. It involves careful and detailed
observation to gather data.

2. Find patterns in observations: After collecting data, scientists look for patterns or
regularities. This could involve categorizing, measuring, and comparing different aspects of
the data.

3. Develop fitting descriptions and/or equations (models or hypotheses): Using the patterns
observed, scientists create models or hypotheses. These are tentative explanations for the
patterns and regularities they have observed. A hypothesis is a testable prediction that
explains the observations.

4. Conduct experiments to verify to what extent the models can predict future observations:
Scientists design and conduct experiments to test their hypotheses. These experiments are
controlled and repeatable and are intended to determine whether the hypothesis can
accurately predict new observations.

5. If the model/hypothesis predicts multiple observations successfully, it will become a law or
scientific theory: When a hypothesis has been repeatedly tested and confirmed, it may
develop into a scientific theory. A theory is a well-substantiated explanation of some aspect
of the natural world that can incorporate facts, laws, inferences, and tested hypotheses.
Scientific laws are statements based on repeated experiments or observations that describe
some aspect of the world. A law simply tells what happens; a theory explains why it happens.

It's important to note that the scientific method is iterative. If a hypothesis is not supported by
experimental evidence, it must be modified or abandoned, and the process begins again. Even
theories and laws can be revised or discarded if new evidence emerges that does not fit.


QUESTION 2: EXPLAIN THE MODEL’S CHARACTERISTICS.

- Are a description, a simplification of reality: Models are tools that represent complex real-world
phenomena in a more simplified way.

- Fundamental laws describe, do not explain reality: With a model, you show what happens, but
they often do not explain the underlying reasons for why these things happen.


- Appeal preferably to intuition: Good models are intuitive, meaning they should be
understandable and resonate with common sense.

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