When your Uber driver drops you off at the back entrance, you don't really know what to expect. You see everything in the reverse order you're supposed too, but you get the first crack at the pastries everyone else is drooling over. Then, when you finally get to the front, you turn around and see the banner for the Open edX 2019 Conference and realize you're actually here.
Open edX is an open-source, collaborative, online-learning platform that allows you to build online courses for online campuses, instructor-led courses, or self-paced learning. It's likely that if you've taken any of the increasingly popular online courses, it was built on Open edX. Which brings us to our participation in this week-long conference. Data Science Dojo offers a top-rated Data Science Bootcamp. Our bootcamps are a blended learning experience which couple the hands-on, in-person training with online learning. Students will gain access to all of their bootcamp materials (pre and post as well) which include recorded videos, slides, quizzes, labs, homework, and can even go back and refresh the material once the training is complete.
This post is a breakdown of the sessions the Data Science Dojo team participated in, what we learned, and how we are going to use that knowledge towards our ongoing projects.
Day 1 - Instructional Design (ID) Summit
On Tuesday, we participated in the ID Summit. The summit focused on how to create an online course from scratch. This was a great talk for the marketing team and other non-technical folk as it discussed the approach to creating a course on Open edX by keeping the learner in mind.
One of the learner-centered design concepts focused on backward course design.
A question you should start with everytime you create an online course is, "What do you want the learner be able to accomplish by the end of the course?" You need to work with a backwards approach starting with the learning objectives and outcomes, creating tests and assessments to make sure that students can garner an understanding of the concepts, and then cultivate an engaging curriculum that encompasses a variety of activities from reading, to quick videos, to short quizzes.
Another item that was discussed was to have clear messaging on your online platform. When creating a learning objective in your course, you want to use action verbs to describe the outcome the students should expect once the course is complete. It's easy for people to "know" things, but do they "understand" them?
Here are some examples of a clear learning objective:
- Students will be able to draw the body of a cell.
- Students will be able to establish the difference between type I and type II errors.
In our online platform, we state very clearly that students will be able to:
- Learn the theory and practice of data science and engineering using state of the art tools
- Explore, visualize, and cluster data
- Build and evaluate predictive models for classification and regression
- What did we do during the ID Summit?
- what did we learn at ID Summit?
- how will we use what we learned?
- Learn-Centered Design: Who are your learners (background, experience)
Some side questions were brought up during the class that, unfortunately, we didn't get to cover, such as:
- How do you measure confidence in a student?
- How do you know if your learning assessments are actually helping the student to understand the concepts taught in the class?
Other thing on Tuesday
This is a companion discussion topic for the original entry at https://blog.datasciencedojo.com/p/aa39e59c-232c-49dc-b101-def05df69339/