Browse Public Designs
Page: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
-
Pelagic Secondary Production Lab
Description:
This lab will introduce students to pelagic secondary producers and their role in the ecosystem. Students will get an introduction to theoretical topics in pelagic secondary production applying these theoretical concepts to create their own study resources through a series of e-tivities. We will then meet in person to discuss and question the ideas together, and fill out any missing information.
Intended Learning Outcomes:
- list and describe important secondary producers in marine ecosystems
- describe and compare the various roles of secondary producers in marine ecosystems
- describe and explain the causes behind temporal and spatial patterns of marine primary and secondary production
-
New learning design - testing template
Description:
Here I will include a description. This test is for Week 3 Activity 2
Intended Learning Outcomes:
- this is the first learning outcome
-
Learning metabolic concepts by Flipped Classroom
Description:
This learning design is implemented, as certain metabolic concepts pose a challenge to many of the students at this course.
The learning design includes Pre-class activities as preparation, In-class activities allowing students to work in groups on difficult concepts, and a post-class activity for assessment of learning.Intended Learning Outcomes:
- Describe central metabolism, including glycolysis, citric acid cycle and oxidative phosphorylation.
-
eLessons for Color in Data Visualization
Description:
-
Statistical Analysis of a dataset
Description:
The following module aims to introduce the basic principles and fundamental techniques of statistics and machine learning for data analysis. After the module they will have knowledge of probability theory, statistics to model uncertainties in engineering problems. The students will be able to do statistical analysis of datasets, and they will apply to their own chosen real-world dataset.
It will be used a blended learning approach including in-class and out-of-class activities, following the STREAM model. A 'feedback loop' will be used, shifting between 'out-of-class' content (self-study, preparatory activities, project assignment) and 'inThe 'out-of-class' activities will be used to provide feedback of the students' learning, and to adjust the 'in-class' activities (lectures, audience response systems, peer feedback).
Intended Learning Outcomes:
- understand the statistics theories for analyzing data
- apply statistical tools to a chosen dataset
- explain to the peers the project assignment
- improve the analyses after peers feedback
Page: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49