Digital Fluency in the Artificial Intelligence-Enabled Enterprise Course Descriptor

Course Summary

This course is delivered as a two-week, intensive, face-to-face bootcamp. Organisational leaders preparing for the future of digital advancement recognise the importance of accurately assessing the value of information resources, improving processes at all levels of the organisation, and preparing their workforce to make the most efficient and effective use of information systems deployed. Leaders faced with the challenge of preparing themselves and others for the next generation of human-computer interaction recognise that technology is a double-edged sword that presents opportunities and threats simultaneously. To meet this challenge, leaders must improve their digital fluency – the syntax knowledge, sociolinguistic sensibility, and strategic expertise that a person gains and demonstrates in their use of information resources. 

Course Aims

• Expose learners to critical thinking, design thinking and systems thinking.
• Introduce learners to the use of artificial intelligence within information systems.
• Train learners to use a case-based approach to understand the value, pitfalls and possibilities of AI.
• Allow learners to focus on design and deployment rather than development and coding.

Learning Outcomes

On successful completion of the course, learners will be able to:

Knowledge and Understanding

Subject Specific Skills

Transferable and Professional Skills

Teaching and Learning

This is an e learning course delivered throughout the year. 

This course can be offered as a standalone short course.

Teaching and learning strategies for this course will include: 

• Online Lectures
• Online informal discussion groups
• Online Assessment

Course information and supplementary materials will be available on the College’s Virtual Learning Environment (VLE).

Students are required to attend and participate in all the formal and timetabled sessions for this course. Students are also expected to manage their self-directed learning and independent study in support of the course.

The course learning and teaching hours will be structured as follows:

• Learning and teaching (5 days x 8 hours) = 40 hours
• Independent study = 110 hours 

Indicative total learning hours for this course: 150 hours

Assignments (see below) will be completed as part of private study.

Assessment

Formative

Students will be formatively assessed during the course by means of set assignments. These will not count towards the final degree but will provide students with developmental feedback. 

Summative

The summative assessment will be assessed in accordance with the assessment aims set out in the programme specification.

Feedback

Students will receive formal feedback in a variety of ways: written (via email correspondence); and indirectly through online group tutorials. Students will also attend a formal meeting with their Mentor. These reviews will monitor and evaluate the student’s progress.  

Feedback is provided on summative written assignments which will be handed back to the students

Indicative Reading

Note: Comprehensive and current reading lists for courses are produced annually in the Course Syllabus or other documentation provided to learners; the indicative reading list provided below is used as part of the approval/modification process only.

Books

• Briggs, C. and Makice, K., (2012), Digital Fluency: Building Success in the Digital Age, Digital Fluency
• Callan, R., (2003), Artificial Intelligence, Basingstoke: Palgrave Macmillan
• Van Emden, J. and Becker, L., (2016), Presentation Skills for Students, Basingstoke: Palgrave Macmillan

Journals

Learners are encouraged to read material from relevant journals on Digital Fluency and/or Artificial Intelligence as directed by their course trainer. 

Electronic Resources

Learners are encouraged to consult websites on Digital Fluency and/or Artificial Intelligence.

Indicative Topics

• Artificial Intelligence within Information Systems
• Recommendation Engines
• Voice-Activated Transaction Processing