YTFWV100 New and Emerging Technologies (5 ECTS)

Course introduction: YouTube video, 8 minutes

Motivation

We are living in a constantly changing world. New technologies emerge so rapidly that everybody has a challenge how to learn new things. This course is for you if - you want to get familiar with a new technology and there is no dedicated course for that - you have a special interest towards new and emerging technologies a.k.a exponential technologies - you want to have proof of your special expertise in your portfolio

Orientation

This is a fully virtual course. By examining current and emerging developments in science and technology, you must choose a topic, with which you want to get familiar. In addition, you should think how to apply at least one new or emerging technology to your own field, e.g. how to apply artificial intelligence to marketing or to personal helth care.

This course suits very well for students who are exploring potential or current topic for their Master's thesis. The outcomes of this course are partly evaluated by using the same criteria as in the Master's thesis.

Learning outcomes taken from EUR-ACE Guidelines

The learning process should enable Master Degree graduates to demonstrate:

  1. Investigations * ability to identify, locate and obtain required data; * ability to conduct searches of literature, to consult and critically use databases and other sources of information, to carry out simulation in order to pursue detailed investigations and research of complex technical issues; * ability to investigate the application of new and emerging technologies at the forefront of their specialisation

  2. Lifelong Learning * ability to engage in independent life-long learning; * ability to undertake further study autonomously.

Course objectives etc., see the description in Asio.

Assignments:

  1. Listen presentations about state-of-the-art technology and its applications. You need to pick virtual lectures (webinars) or participate courses offered by your company or other organisations (e.g. through MOOCs such as Udemy or Coursera) so that the total amount of listening presentations is 32 hours.
  2. Report your main findings in a 16-32 pages long learning report. You can use any note taking app or tool. Following the reporting instructions are recommended.
  3. Summarise your findings in a 3-5 minute video presentation. For video recording, you can use e.g. Screencast-O-Matic. For storing, you can use e.g. YouTube or upload the video here in GitLab.

When you are ready, 1) return the document (learning report) and 2) link to the video presentation to the corresponding folder in our learning environment (Optima). After receiving feedback from the lecturer in charge, give suggestions how to improve this course (link to evaluation form is added here later).

Note: we are using anti-plagiarism system, so remember to refer original sources according to recommendations and follow either our reporting instructions or the ones of your own university. In addition, the ethical principles must be followed.

Assessment and grading:

Grading Scale: Pass/fail For passing you need to deliver the learning report which contains at least 16 pages (max 32 pages) of lessons learned and a short (3-5 minutes) summarising video. We evaluate the quality (clarity, correctness, readability, understandability) of your report and presentation. Presenting key findings and examining these in the context of previous work is important.

Other information

Communication during the course takes place in Slack

Course objectives etc., see the description in Asio.

Recognition of prior learning, see instructions at JAMK's web site.

Lecturer in Charge: Dr. Jouni Huotari (@huojo) Email: firstname.lastname@jamk.fi JAMK University of Applied Sciences, Institute of Information Technology