Browse Public Designs
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Create your dream dynamic DNA nanostructure
Description:
The goal is to have the theoretical and practical basis to develop DNA nanostructures that can move in the nanoscale with high precision.
We will replace some of the literature reading by implementing tutorial videos on software use and related small activities/projects, to get hands on with the software. (e.g. use of CADNANO for designing a DNA nanostructure with an smiley face or NUPACK for designing molecular computers).
Intended Learning Outcomes:
- Understand the principles of DNA nanotechnology self-assembly and dynamic behavior
- Get hands-on experience with design software
- Create a DNA (dynamic) nanostructure
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Microbiome analysis using NGS technology
Description:
This activity is to introduce students to analyzing microbiomes using next generation sequencing technologies and bioinformatic analysis. Students will be introduced to next generation sequencing technologies, their uses and drawbacks for microbiome analysis and the biological questions you can answer using these techniques. Students will get hands on experience analyzing a real dataset, generating publication quality figures and interpreting the results.
The module will follow the STREAM model with before-class, in-class and out-of-class activities.Intended Learning Outcomes:
- Understand the terminology for describing ecological communities
- Explain the different sequencing technologies/'omics' and their uses
- Interpret biological meaning from sequencing data
- Understand and explain graphical interpretations of microbiome analysis
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Framing new knowledge
Description:
Context
This is the third lesson within the second part of a Master's course. Whereas the first part deals with well-established theory methodologies and practical application of integrated computational design, the second part tests their validity for the currently mostly research-oriented design of responsive structures.
The proposed lesson is the only one dealing with the interdisciplinary field of smart materials, whose possible impact on architectural engineering is yet to be clearly evaluated. The lesson shall balance between on one side, discuss and evaluate the role of smart materials in architectural engineering (theory), on the other side, support the students working on their final proposal for a responsive structure (exploratory research)
Lesson Aims
To introduce students to smart materials for architectural engineering;
to promote their critical thinking by foster their ability to focus on the role of a construction element within the design, behind its usual physical implementation;
to improve students’ soft skills;
to think ahead on how shall they structure their continuous learning during the profession
Intended Learning Outcomes:
- Identify the constraints and opportunities that smart materials can bring to architectural design
- Communicate effectively key aspects relevant to stakeholders
- Collaborative working: provide constructive feedback to peers
- Being able to search references
- Categorize a selected smart material within an existing framework
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Learn assembly (machine) language and compilation to assembly
Description:
This learning design pertains to a portion of the course "compilation" that I am co-teaching this semester. As part of this course students have to learn the assembly language (the machine language — it is essentially a human-readable version of the binary code that the machine executes). This activity is centered around the lecture. The students familiarize themselves with the topic before coming to the lecture. During the lecture the students are presented with the theory and the practical aspects of generating assembly code from higher-level code. After the lecture, students will implement the code-generation phase of the compiler that they have been developing throughout the semester as their course project.
As part of the lecture, the instructor poses questions to get students to think about different aspects of the problem at hand. Students are encouraged to talk to their peers and think together about the posed question. They will submit their answers online, e.g., on Mentimeter, or an image sharing platforms (in some cases, students have to produce code for a short code snippet (one line of code) which they will have to take a picture of and upload to share with the class).
The course's Birghtspace page plays a crucial role in this design. The students will find the material there, they will be able to participate in discussions with their peers, the TAs, and the instructor.
This learning design follows STREAM model. The Birghtspace discussions that students have with their peers, TAs, and the instructor informs the instructor as to what exactly to focus on during the lecture — this is why lecture slides are only made available to students shortly before the lecture starts as the instructor tries to adjust them to students' needs. Moreover, the discussions the students have regarding their project, and the progress they make on it gives feedbacks to the instructor on how to adapt the up-coming lectures.
Intended Learning Outcomes:
- Students will be able to describe and analyze the structure of programs in Intel X86-64 assembly
- Students will be obtain the skill to write programs in Intel X86-64 assembly
- Students will be able to identify and describe the process of generating assembly code from the high-level code
- Students will be able to implement the code generation phase of a realistic compiler
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Environmental Sampling and Analysis
Description:
I teach the course analytical chemistry. Here, the students are trained in operating analytical equipment for the analysis of pollutants in environmental samples (air, water, consumer products). In its current form, the students are provided with environmental samples to analyze for predetermined chemical compounds. Consequently, the course offers little insight into the many steps and considerations, and rationales preceeding the actual analytical analysis performed in the lab.
In this learning module I intent to give the students more complete learnings of the many processes that go into environmental analysis; from idea, protocol development, sampling, and analytical execution to presenting the final results.
The developed learning design will enable the students to both identity, develop and execute analytical studies of air pollution as well as deliver peer feedback to related reports and presentations
Intended Learning Outcomes:
- Understand the sources, composition and health effects of air pollution
- Identify environments important for our exposure to air pollution
- Develop and execute analytical protocols for the sampling and chemical analysis of air pollution
- Reporting and review of analytical results
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