Module FOUD0049: Concepts, Methods and Theories in Data Science

Department: Foundation Year (Durham)

FOUD0049: Concepts, Methods and Theories in Data Science

Prerequisites

Corequisites

• Mathematics 2 or Mathematics 3

Excluded Combination of Modules

• None

Aims

• The CMT modules are designed to introduce students to concepts, methods and theories within the student’s chosen discipline. The CMT modules provide a lens through which students engage with knowledge and knowledge creation in their chosen discipline; the Scholarship in Higher Education module provides the tool-kit for their engagement and communication of knowledge; and the Advanced Scholarship in Higher Education module provides an iterative experience of bringing toolkit and lens together to provide students with the opportunity to actively engage in the process of knowledge generation and communication by completing a research project within the student’s chosen discipline.
• To introduce a range of mathematics skills in operating with data sets applied in a range of degree progression routes.
• To introduce skills to solve statistics problems in real life contexts.
• To introduce the ability to communicate data effectively
• Skills and other attributes 
• This module also supports the overall programme aims to enable students to have:
• acquired the ability to work confidently with a range of academic materials and sources (as appropriate to progression subject area);
• acquired the ability to work confidently with numerical data and statistics (as appropriate to progression subject area);
• gained various skills for undergraduate study, including the ability to extract and summarise meaning from text, to read rapidly and accurately, to write and present clear and precise arguments using appropriate evidence;
• acquired a level of self-efficacy in relation to workload management, basic academic autonomy and a learner identity as an effective university student;
• gained skills in using libraries, online databases and other reference resources;

Content

• Descriptive statistical analyses.
• Probability
• Inferential statistics (including confidence intervals and hypothesis tests)
• Large data analysis using appropriate software

Learning Outcomes

• By the end of the module students will have demonstrated:
• 1. Knowledge of a range of relevant subject concepts and notations
• 2. Knowledge of a range of relevant statistics methods for problem solving
• 3. Knowledge of a range of relevant vocabulary

• By the end of the module students will be able to:
• 1. Demonstrate the appropriate use of a range of relevant statistics concepts in response to specific assessment tasks
• 2. Demonstrate the appropriate use of relevant statistics methods in response to specific assessment tasks
• 3. Demonstrate the appropriate use of a range of relevant vocabulary in response to specific assessment tasks

• By the end of the module students will be able to:
• 1. Demonstrate critical thinking
• 2. Demonstrate effective communication using appropriate academic styles
• 3. Demonstrate the use of appropriate sources of evidence

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

• This module will be delivered using seminars on a weekly basis. Students will be taught concepts and then challenged to apply them in a variety of contextual tasks that are designed to lead to achieving the module outcomes.
• The CMT assessments are designed to ascertain whether students have successfully engaged with concepts, methods, and theories in their chosen discipline, and are able to apply these in response to assessment tasks.
• In this module, the Test’s primary function is to allows students to demonstrate the range and sophistication of their engagement with the module’s Reference/Factual knowledge and Process knowledge, contextually and selectively applying this knowledge in response to specific test questions, with the secondary focus on the key skills of Academic communication under timed conditions (as they are likely to experience in their subsequent years of study).
• The Statistics Report primarily allows students to demonstrate the range and sophistication of their engagement with the module’s Procedural knowledge and how they apply these within the context of their discipline (e.g. statistical analysis), with the secondary focus on effective academic communication through the medium of a Statistical Report (as they are likely to experience in their subsequent years of study).

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

A range of formative tasks are used to help students work towards module outcomes and to iteratively build competency towards each respective summative assessment.

■ 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