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Zoekresultaten (26)

HBO/WO

MBO

2025

Experimental Design and Technical Writing for Engineers

This text is intended for undergraduate engineering students completing a technical writing course. As engineers complete technical writing in conjunction with research activities, this work also includes a basic overview of experimental design and the implications of robust quantitative methodologies. Hallmarks of quantitative research, best practices in presentation of data and a brief description of the use of descriptive statistics in data analysis are also provided. Technical communications for engineers often include industry related documents like memos, executive summaries, case studies, quality and process documents, standard operating procedures and requests for proposals. These documents are discussed, in addition to formal technical reports. The text also includes best practices in engineering oral presentations and the impact of Artificial Intelligence on technical communications. Ethical implications of engineering communications are also discussed from a framework of professional integrity as defined by the National Society of Professional Engineers Code of Ethics. Students using this text should be capable of communicating, in both verbal and written formats, in a way that clearly, concisely and correctly conveys engineering principles, projects and concepts to both technical and nontechnical audiences. Table of Contents Introduction Chapter One: Basic Mechanics of Technical Writing Chapter Two: Digital Media and Technical Communications Chapter Three: About Experimental Design for Engineers Chapter Four: Data Analysis and Presentation of Data Chapter Five: Common Document Types in Engineering Chapter Six: Additional Brief Technical Documents Chapter Seven: Technical Reports and Other Large-Scale Documents Chapter Eight: Technical Presentations Chapter Nine: Ethical Engineering in Experimental Design and Technical Writing References

Open (Access) Tekst Boek

Susan Ly

23 januari 2026

Immersive Design Lab

Deze video laat zien wat het Immersive Design Lab is en hoe studenten hun ontwerpen tot leven kunnen brengen met immersive technologie. Je ziet hoe VR, projectie, licht, geluid, haptics en geur samen een volledige ruimtelijke beleving creëren. Het lab ondersteunt interieurdesignstudenten van experiment tot eindpresentatie om hun ontwerpen naar een hoger niveau te tillen.

Video

Hogeschool Saxion

7 februari 2024

Randomized Controlled Trials - variants in design

Compares a parallel and a cross-over trial. Introduces several non-randomized designs, such as quasi-experimental and pre-experimental studies. Describes limitations of a trial

Video

renate.winkels@wur.nl

2023

Maker Lab Assignment: Semi-structured_Experiments

Before the Maker Lab students begin the open inquiry phases, they first learn and practice some important skills, supported by small assignments. This assignment is a "structured", or "guided" inquiry, where students know ahead of time the result they should find, but have agency in their experimental design, within some prescribed limits. By assigning all teams different methods for addressing a single research question (currently: estimating the acceleration due to gravity), they are encouraged to reflect upon how experimental design and equipment limits the certainty of empirical findings. This assignment requires teams of four students (organized into two pairs, each performing the experiment separately, but analyzing data and reporting on conclusions together). In two weeks (wherein students' course workload is 10 hours per week), the teams must set up experiments, controlling sensors with self-programmed Arduinos, collect and analyze experimental data, and create a pre-recorded video presentation to be viewed in class and aimed at their peers, followed by a Q&A. Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the attached PDF will give an idea of its content and functionality. Note also: In order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is helpful to save the entire collection locally in a way that preserves the original directory structure. This is easiest to accomplish by downloading all files at once via the JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. This zip file of all Jupyter Notebook materials is located here: https://search.edusources.nl/materialen/d144774e-9705-489a-b3cd-28e3618f7324 Contents: partial experimental instructions (for students) in Jupyter Notebook: Semi-structured_Experiments.ipynb (and .pdf ) grading form for pre-recorded video presentation (both .docx and .pdf )

Document

Forrest Bradbury

2025

Randomized controlled trial

This e-learning module introduces the concept of a randomized controlled trial through interactive exercises, using the example of folic acid supplementation and its association with the cognitive performance. A randomized controlled trial is a scientific experiment that randomly assigns participants to a treatment group or control group to test the treatment’s effectiveness in improving health (outcomes). By the end of this module, you will be able to: Describe what a randomized controlled trial is Assess biases that can affect the validity of this epidemiological study design

Website

Lenie Rossem, van, Cora Busstra, Luc Heerkens

8 mei 2018

04-05: Research designs - micro lecture THE EXPERIMENT

In this micro lecture the following items will be explained regarding this lecture: Introducing the classical experiment: A research design fo testing bivariate causal relationship (a.k.a. randomized experiment)

Website

Henk van der Kolk

10 juni 2025

Designing a Research Experiment

Main Concepts Design (in research): The art or process of deciding how something will look and work by creating a plan or making models. Design thinking: A human-centered, iterative process used to solve complex problems by prioritizing the user's needs. Cross-innovation: Looking at other industries or fields for ideas to improve your experiment design. User stories: Short descriptions of what a user needs and why, written from their perspective (“As a…, I want…, so that…”). Measurements: The data collected during an experiment (e.g., time, heart rate, reactions). Outcomes: The results you expect or aim to learn from your experiment. Learning Goals Understand how design applies to research experiments Transform research questions into designed, testable experiences Apply creative design strategies, including inspiration, problem–solution approaches, and cross-industry innovation Use user stories to clearly express research requirements Integrate measurement and data goals into experiment planning Key Takeaways Design is not only about aesthetics — it’s an active planning process. Designing your experiment means defining what participants will experience and what you will measure. Inspiration can come from other fields like gaming, engineering, or education. User stories help communicate needs and goals between researchers and developers. Always connect your design choices to your research variables, hypotheses, and data collection goals. Further Exploration Search for “Agile user stories examples for research projects” Search for “Design thinking in scientific research” Search for “Cross-innovation examples in VR education” Search for “How to design experiments in virtual reality”

Video

Lucia M Rabago Mayer, Jordi Weldink, Amanda Poulin

8 mei 2018

08-10: Data collection methods- micro lecture THE EXPERIMENT

In this micro lecture the following items will be explained regarding this micro lecture: Introducing the classical experiment: a research design for testing bivariate causal relationship. Also known as “Randomized experiment”.

Website

Henk van der Kolk

10 juni 2022

From Idea to Study — Research Questions, Hypotheses, and Variables

Main Concepts The pathway: Idea → Research Question → Hypothesis → Variables → Design Hypothesis: a testable prediction Variables: elements of your study that can change or vary Independent variable: the factor that you manipulate in your study to investigate its effects Dependent variable: the outcome in your study which might be influenced by the independent variable Control variable: the factor in your study that you keep constant Causation vs. correlation and how design affects claims Learning Goals Formulate a specific research question from a broad idea Write a testable hypothesis aligned with measurable outcomes Identify independent, dependent and control variables for a study Distinguish between experimental and observational designs Key Takeaways Clarity grows step by step: idea → question → hypothesis → variables Keep the IV manageable and the DV aligned to the hypothesis Control what you can; state what you can’t Avoid causal language when the design doesn’t support it Variables become the backbone for design, development, and testing Further Exploration Search: “operationalizing constructs in behavioral research” Search: “experimental vs. quasi-experimental vs. observational” Search: “writing testable hypotheses examples” Search: “construct validity and measurement reliability”

Video

Lucia M Rabago Mayer, Jordi Weldink, Amanda Poulin

2024

How to design open inquiry labs

In this article we show how student “open inquiries” in undergraduate labs can be powerful teaching and assessment methods. In such open inquiries it is the students who define the question they want to answer, formulate the hypothesis, search for information, design and carry out experiments to reach their goal, and share their ideas, needs, and results with others. This student agency afforded by open inquiry trains critical thinking, teaches students to learn from failure, and requires effective science communication in authentic contexts. Adapting open inquiry methods for the first time can be especially daunting for instructors who have no examples to draw upon. To address this challenge we explain the findings of a diverse group of five lab instructors and an educational researcher who have compared open inquiry practices in different contexts. As a group, we formed a Community of Practice dedicated to “Supporting students’ scientific Open Inquiries in Labs” (aka SssOIL). The commonalities across our diverse project team suggest some defining features and best practices. By sharing our findings and example course designs and materials, we hope to aid instructors in adapting more open inquiry teaching methods in their own lab courses. Any questions about this article can be addressed to Forrest via: forrestbradbury@gmail.com or to our team via: S3OIL@outlook.com

Document

Forrest Bradbury, Simone Mesman, Morten Stromme, Paul Logman