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Durham University

Faculty Handbook 2022-2023

Module Description

Please ensure you check the module availability box for each module outline, as not all modules will run each academic year.

Department: Computer Science

COMP3517: COMPUTATIONAL MODELLING IN THE HUMANITIES AND SOCIAL SCIENCES

Type Open Level 3 Credits 10 Availability Available in 2022/23 Module Cap None. Location Durham

Prerequisites

  • (COMP2271 Data Science OR COMP2231 Software Methodologies) AND COMP2261 Artificial Intelligence

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To enable students to understand and critically evaluate the application of computational modelling to problems in the humanities and social sciences.
  • To introduce students to algorithms and approaches relevant to the modelling of humanities and social science data.

Content

  • Computational models of text and language
  • Text and data mining
  • Critical evaluation of computational models

Learning Outcomes

Subject-specific Knowledge:
  • On completion of the module, students will be able to demonstrate:
  • an understanding of how computational modelling can be applied to humanities and social science research
  • an understanding of computational approaches to modelling text
  • an understanding of data mining techniques.
Subject-specific Skills:
  • On completion of the module, students will be able to demonstrate:
  • an ability to apply computational modelling to humanities and social science data
  • an ability to critically evaluate computational modelling approaches.
Key Skills:
  • On completion of the module, students will be able to demonstrate:
  • an ability to think critically
  • an ability to undertake general problem solving.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lectures introduce the principles and techniques covered in the module, and examples of their application to practical cases
  • Formative and summative assessments assess the understanding of core concepts and the application of methods and techniques.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
lectures 20 2 per week 1 hour 20
preparation and reading 80
total 100

Summative Assessment

Component: Coursework Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Summative Assignment 100% No

Formative Assessment:

Example formative exercises are given during the course.

â–  Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University


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