module specification

This module offers a fundamental understanding of data science and computer software, specifically focusing on how they facilitate the collection, analysis, and presentation of accounting data. Designed to prepare you for careers in accounting, economics, finance, and related fields, this module emphasises developing crucial academic and practical skills, particularly in research and the application of AI. Students will gain proficiency in analysing data, interpreting, and effectively communicating both qualitative and quantitative results.

A key aspect of this module is its focus on the collection, analysis, interpretation, and presentation of accounting and financial data through measuring variable changes and associations. Learners will acquire essential skills in gathering and comprehending financial and non-financial information, building a comprehensive understanding of client businesses and their operating environments. This knowledge will be vital for preparing robust business plans and advising on their implementation. Ultimately, this module hones students' data science and research abilities to provide innovative solutions to challenges within the accounting and finance sectors, with a strong emphasis on leveraging AI.

Part 1: Data Science, AI, and Analytics Fundamentals
This section introduces students to the core concepts of data science, artificial intelligence (AI), and their application in business.
• Data Science, Digital & Technology: Big Data and Data Analytics We'll explore what data science and AI are, looking at current trends and how they add value to businesses and organisations. You'll learn about the basic role of AI in processing and understanding data. You'll gain practical skills in using digital technologies, including some simple AI-powered tools, to visualise data clearly. We'll cover different sources and types of data, including an introduction to "big data," and how to organise it for business use. [Maps to LO1]
• Data Analysis and Statistical Techniques: Analysing Data with Appropriate Technologies and Tools This part teaches you fundamental mathematical and statistical techniques. You'll learn about basic sampling methods, simple forecasting, and how to summarise and analyse data using tools like spreadsheets. [Maps to LO2]
• Basic Numeracy Skills We'll help you build foundational numeracy skills necessary for understanding and working with data. [Maps to LO2]
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Part 2: Research Skills and Ethical Data Use
This section focuses on developing foundational research skills and an awareness of ethical considerations in data handling, including research bias.
• Research Skills: Identifying Current Issues and Methodologies You'll learn how to approach basic research questions in fields like accounting, economics, finance, and banking. This includes finding information and using digital tools to help gather data. We'll introduce common research methodologies (e.g., surveys, case studies, basic quantitative analysis) and discuss the concept of research bias and its potential impact on findings. [Maps to LO3]
• Research Skills and Conducting Basic Research We'll guide you in using research-related databases to locate relevant information and data for your studies. [Maps to LO3]
• Ethical Judgement in Data and Technology Use This part introduces the basic ethical considerations involved when using data and digital technologies, especially concerning AI, in a professional context. We'll discuss how to recognise and mitigate different types of research bias. [Maps to LO4]

Learning Activities: Lectures, Seminars and Digital Resources

The module will employ a blended learning approach, combining interactive lectures and seminars with comprehensive digital support.

Seminars: These sessions will serve to introduce new topics and themes pertinent to accounting, finance, and other related disciplines. Dedicated time will provide students with practical opportunities to apply concepts introduced, both with and without the aid of specialist computer software. This hands-on practice is designed to deepen students' understanding of the applied aspects of each topic, with particular emphasis on quantitative analysis relevant to the subject areas.

Digital Resources: Learning will be significantly supported by a dedicated Weblearn site. Students will be expected to access this platform frequently as a primary resource for preparing for workshops and for independent study.

Upon successful completion of this module, students will be able to:
• LO1: Explain fundamental concepts of data science and Artificial Intelligence (AI), identifying how information technology supports basic organisational processes and decision-making. (FHEQ Level 4 - Knowledge, Understanding; Bloom's Taxonomy - Understanding)
• LO2: Apply basic mathematical and statistical techniques to analyse data, using appropriate software tools to support simple planning and decision-making scenarios. (FHEQ Level 4 - Application; Bloom's Taxonomy - Application)
• LO3: Undertake basic research by locating and gathering relevant data related to current issues in accounting, economics, finance, and banking, utilising digital technologies. (FHEQ Level 4 - Application, Knowledge; Bloom's Taxonomy - Application, Remembering)
• LO4: Present simple data analyses and research findings clearly, while recognising basic ethical considerations associated with the use of data and technology. (FHEQ Level 4 - Communication, Understanding; Bloom's Taxonomy - Understanding, Application)

Reading List Talis Link:
https://rl.talis.com/3/londonmet/lists/DC5615D2-97BE-D35E-86BE-B9D220130A07.html

Core Text:

Quinlan, C., Babin, B., Carr, J., Griffin, M. and Zikmund, W. (2024) Business Research Methods. 3rd edn. Andover: Cengage Learning EMEA.

Additional Texts:

Oakshott, L. (2020) Essential Quantitative Methods for Business, Management and Finance, 978-1137518552, Bloomsbury Publishing Plc, 7th edition.

Saunders, M. N. K., Lewis, P. and Thornhill, A. (2023) Research Methods for Business Students, Pearson 9th edition. ISBN-10: ‎1292402725; ISBN-13:‎ 978-1292402727

Swift, L. and Piff, S. (2014) Quantitative methods for business, management and finance, 978-1137376558, Basingstoke: Palgrave MacMillan, 4th edition

Other Texts:

Boddy, D. (2019) Management: Using Practice and Theory to Develop Skill Pearson Education, Limited 8 Edition PRINT ISBN 9781292271811; EBOOK ISBN
9781292271804

Cottrell, S. (2019) The Study Skills Handbook, London: Red Globe Press; Macmillan International

Useful Websites:
These websites offer valuable resources and supplementary learning materials:
• Accounting Today: http://www.accountingtoday.com
• Restore SRME: http://www.restore.ac.uk/srme/www/fac/soc/wie/research-new/srme/modules/videos/index.html
• BBC Bitesize Maths: http://www.bbc.co.uk/learning/subjects/maths.shtml
Journals and Periodicals
To keep up-to-date with current developments and research, we recommend the following:
• Financial Times
• The Wall Street Journal Europe
• Journal of Information Systems
• The Accounting Review
• Issues in Accounting Education
Electronic Databases
You'll use the following electronic databases to access academic articles and company information:
• ScienceDirect
• FAME (UK Companies)
Education Research Complete