Demystifying Artificial Intelligence (AI)

Track : Online Design
Delivery Mode : Asynchronous Workshop
Levels : Intermediate,Advanced
Eligible for Online Teaching Certificate elective : Yes

Throughout higher education, we see a great deal of excitement around the potential of AI, though we’ve yet to develop a common vocabulary around it to more clearly communicate to institutional leaders the potential value. Nearly all of our stakeholders, from senior administrators to newly-admitted students, want to be consumers of AI-driven insights (mention “AI-driven dashboards” to an administrator, and you get almost immediate buy-in), but few people outside of the computer and data science fields have an accurate understanding of what it takes to create and/or deploy AI software in different contexts.  

AI is an umbrella term, much like data science, and encompasses a wide range of approaches and techniques. If we want to examine how AI can impact education, we first need to build a shared understanding of the things that fall under AI, allowing us to have more knowledgeable conversations. While AI as a field is decades old, the advent of machine learning coupled with greater computational power and the availability of big data has led to rapid advancements in the field over the last decade. 

This workshop will serve as a bridge for those individuals who seek to engage in AI-driven initiatives by helping to develop a common vocabulary and understanding of popular AI methodologies. In order to build our common understanding, we will focus our attention on specific applications of AI, and provide examples of these applications used for educational purposes. 

 

Learning Objectives:

 

  • Define common AI methodologies, such as machine learning and natural language processing

  •  Describe applications, limitations, and privacy/ethical concerns of common AI methodologies in different scenarios. 

  • Describe the different components of the AI pipeline/workflow, as well as associated tools and environments that are used in AI projects and how this relates to vendor or homegrown initiatives.

 

Prerequisite: None

 

Format:

This is an asynchronous, week-long workshop which will begin on a Monday and end on the following Sunday. The workshop will require approximately 6-8 hours of work, including reading research-based articles, viewing presentations, engaging in online discussion forums, and submitting assignments. There is one live synchronous session that will be recorded. Total length of time to completion: 7 days.

 

Who should attend?

  • Administrators

  • Instructors

  • Instructional designers

  • Education technologists

  • IT Staff

 

What are the key takeaways from this workshop?

 

  • An understanding of the major AI methodologies in use today, and how they might be used in educational contexts.

  • The ability to help plan for various IT requirements associated with AI projects.

  • Leveraging various “AI Readiness” tools to better understand your institution’s readiness for implementing AI projects designed to impact education.

  • An AI readiness assessment for your institution. 

Members can take our workshops at a discounted price. Not a member? Learn more about membership and join here.

Refund Policy
If you register and pay for a OLC workshop and are unable to enroll (due to personal schedule conflicts, illness, etc), we will be happy to apply your payment to another OLC workshop in the same calendar year upon your written request to workshop@onlinelearning-c.org. No refunds will be given.