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COMP3517: COMPUTATIONAL MODELLING IN THE HUMANITIES AND SOCIAL SCIENCES

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type Open
Level 3
Credits 10
Availability Available in 2023/24
Module Cap None.
Location Durham
Department Computer Science

Prerequisites

  • COMP2271 Data Science AND COMP2261 Artificial Intelligence

Corequisites

  • None

Excluded Combinations of Modules

  • None

Aims

  • To enable students to understand and critically evaluate the application of computational modellingto 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

ActivityNumberFrequencyDurationTotalMonitored
lectures202 per week1 hour20 
preparation and reading80 
total100 

Summative Assessment

Component: CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Summative Assignment100No

Formative Assessment

Example formative exercises are given during the course.

More information

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