AI-Enabled Early Innovation (3cr)

Evaluation scale

Approved/Rejected

Content scheduling

Instructional videos (3)
Completing and submitting the Innovation Template with the help of AI, examples, and guidelines
Preparing for and taking the exam

Location and time

Self-paced online course (INVEST Moodle). Register for the exam after your Innovation Template meets the success criteria. Detailed instructions and dates are communicated on the course platform.

Materials

- 3 short videos (course intro; process intro; using AI)
- Innovation process instruction & success criteria (PDF)
- Blank Innovation Template and an example template
- Exam questions for self-study

All materials are provided on the platform.

Teaching methods

A fully online, self-paced course where you use AI and a clear 10-step innovation process to turn early ideas into draft products or services. You will first watch three short videos, then follow step-by-step instructions and success criteria while completing an Innovation Template. When your template meets all criteria, you submit it and register for the exam. AI is used throughout as a learning partner and a tool for implementing the studied innovation skills.

By the end of the course, you will be able to
1. look at your own skills, values and resources and use them to spark business ideas;
2. work with others (and with AI) to generate, compare and improve early-stage ideas;
3. follow a simple 10-step method to move an idea toward a first prototype;
4. explain the unique value of your solution in a short Innovation Template ready for pitching.

Employer connections

The course materials were created by professionals in business idea development. Ideally, the student can continue developing the business idea they worked on during the course by making use of the university’s services.

Exam schedules

The exam will be held at the end of the period. The exact time and location are posted on the course’s INVEST Moodle platform.

International connections

The course has been developed in collaboration with the European University alliance INVEST, of which Karelia University of Applied Sciences is a member.

Student workload

3 ECTS credits correspond to approximately 81 hours of student workload. This includes familiarizing yourself with the learning materials, the use of AI tools, refining your own business idea, preparing for the exam, and taking the exam.

Assessment criteria, approved/failed

This course is graded on a pass/fail basis. To pass, the student must:
- answer at least 50% of the 30 multiple-choice exam questions correctly;
- submit an Innovation Template that meets at least 50% of the assessment criteria