2022/23 Undergraduate Module Catalogue
XJCO3771 User Adaptive Intelligent Systems
10 creditsClass Size: 75
Module manager: Professor Vania Dimitrova
Email: V.G.Dimitrova@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2022/23
Pre-requisites
| XJCO2611 | Artificial Intelligence |
This module is not approved as a discovery module
Objectives
On completion of this module, students should be able to ...apply human-computer interaction methodology to identify user needs, draw requirements, design, and evaluate user-adaptive systems;
- identify most common techniques for user modelling and adaptation and apply them in practical areas;
- implement one or more recommender system techniques in a practical application;
- reason about the significance of user-adaptive systems and directions the field is going to develop.
Learning outcomes
On completion of this module, students should be able to:
-understand and demonstrate coherent and detailed subject knowledge and professional competencies some of which will be informed by recent research/scholarship in the discipline;
-deploy accurately standard techniques of analysis and enquiry within the discipline;
-demonstrate a conceptual understanding which enables the development and sustaining of an argument;
-describe and comment on particular aspects of recent research and/or scholarship;
-appreciate the uncertainty, ambiguity and limitations of knowledge in the discipline;
-make appropriate use of scholarly reviews and primary sources;
-apply their knowledge and understanding in order to initiate and carry out an extended piece of work or project;
Skills outcomes
Experience and understanding of techniques for user modelling and their application to build user adaptive intelligent systems
Syllabus
Adaptable and adaptive systems;
- General Schema of User-adaptive Systems;
- Basics for User Modelling;
- User Profiling (implicit and explicit methods);
- Stereotypes (construction and use);
- Modelling user knowledge and beliefs, affect and context;
- Adaptive Content Presentation - static and dynamic;
- Recommender Systems - item-item and user-user collaborative filtering, content-based approach, and hybrid approaches;
- Issues of scalability, diversity, potentials and drawbacks;
- Making prediction about the User;
- Evaluation of adaptive systems;
- Trends.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 20 | 1.00 | 20.00 |
| Private study hours | 80.00 | ||
| Total Contact hours | 20.00 | ||
| Total hours (100hr per 10 credits) | 100.00 | ||
Private study
Recommended 40 hrs of private study, to include 20 hrs working on summative coursework and 20 hrs private study following lectures. Remaining hours to read the articles issued in lectures and revision for examination.Opportunities for Formative Feedback
Progress is monitored through class exercises throughout the module and summative coursework.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| In-course Assessment | Coursework 1 | 30.00 |
| In-course Assessment | Coursework 2 | 10.00 |
| Total percentage (Assessment Coursework) | 40.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
| Exam type | Exam duration | % of formal assessment |
| Online Time-Limited assessment | 2 hr | 60.00 |
| Total percentage (Assessment Exams) | 60.00 | |
Resits will be assessed by online time-limited assessment only.
Reading list
There is no reading list for this moduleLast updated: 01/06/2022 16:59:02
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD