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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

XJCO2611Artificial 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 typeNumberLength hoursStudent hours
Lecture201.0020.00
Private study hours80.00
Total Contact hours20.00
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 typeNotes% of formal assessment
In-course AssessmentCoursework 130.00
In-course AssessmentCoursework 210.00
Total percentage (Assessment Coursework)40.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated


Exams
Exam typeExam duration% of formal assessment
Online Time-Limited assessment2 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 module

Last updated: 01/06/2022 16:59:02

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