SHE Level 1
SCQF Credit Points 20.00
ECTS Credit Points 10.00
Module Code M1I326726
Module Leader Richard Holden
School School of Computing, Engineering and Built Environment
Subject Computing
  • A (September start)

Summary of Content

The purpose of this module is to introduce students to core programming concepts and tools. A core language will facilitate the understanding of coding techniques common to all high-level languages. The aim is to equip students with the knowledge and skills to help them develop (and organise) code effectively. Basic programming structures, use of variables, statements and expressions, will be an early focus. As code becomes more complex, programming principles - e.g., modularity, the use of functions and classes - are introduced to support skills in code organisation. The importance of using libraries will be featured throughout the course, as will the use of real-word data sets. The percentage of Work Based Learning for this module, as represented by the proportion of the Activity Types which take place off campus, is 80%. The percentage of Work Based Assessment for this module is 10%.


Software and the machine, parallel vs serial execution. High-level programming language comparisons (such as Python, Java, C#, C, C++). Development environments (command-line, Desktop and Cloud IDEs, Notebooks). Numerical / non-numerical data types. Variables, operators (logical and arithmetic), statements and expressions Conditional structures Iteration Processing real-word data: files and data formats (CSV, JSON, XML, HTML) Object-Orientated Programming Program crashes, bugs and debugging Simple 2D graphics

Learning Outcomes

On successful completion of this module, the student should be able to:1. Demonstrate an understanding of data types and control structures2. Develop code, and exploit the software ecosystem, to solve problems3. Demonstrate an understanding of basic modular approaches to code organisation4. Understand that real-word data can be read, processed and exploited creatively5. Understand the role of software and different forms of execution

Teaching / Learning Strategy

Work based Education aims to maximise the direct and digitally mediated contact time with students by practicing teaching and learning strategies that use authentic work based scenarios and encourage action learning, enquiry based learning, problem based learning and peer learning. All these approaches aim to directly involve the students in the process of learning and to encourage sharing of learning between students. The module team will determine the level and accuracy of knowledge acquisition at key points in the delivery, inputting when necessary either directly or with the support of external experts who will add to the authenticity, the credibility and application of the education and learning in the workplace.? The University 'Strategy for Learning' documentation has informed the learning and teaching strategy for this module. Students will engage with practical and tutorial activities including during sessions on campus which will allow students to discuss key concepts and issues with peers and with instructors. Students will be expected to undertake a significant level of independent study within the workplace, including practical activities, and links will be provided to appropriate external material such as podcasts, MOOCs, videos and literature to supplement the module content. Students will also be encouraged to reflect upon the theoretical learning within the work place and the application of newly learned concepts to the work environment. Full use will be made of GCU Learn to provide Lecture-based and related study materials, along with sample solutions of Tutorial and Laboratory exercises, thus encouraging the development of independent learning and allowing self-reflective feedback on student performance. Staff-based feedback on student performance for submitted work will be provided in line with the University feedback policy, with summative feedback and grades on the coursework assessment utilising GCU Learn. The additional interactive discussion features of GCU Learn will be utilised, as appropriate to the module, to stimulate independent and flexible student learning outwith scheduled class time. Students registered on part-time programmes may use elements of work-related activity to underpin the learning on this module. To support part-time students in undertaking activities use will be made of GCULearn to provide study materials. Additionally, the interactive features of GCULearn will be utilised to support group learning outwith scheduled class time. GCULearn facilitates group interaction through discussion forum, file sharing, blogs, wikis and journals. Students will also be encouraged to make appropriate use of social media and collaboration tools.

Indicative Reading

Aaron, S and Barnes, R (2016) Code Music with Sonic Pi. Perfect Paperback. Create Commons. Downey, A (2016) Think Python: How to Think Like a Computer Scientist. O'Reilly. California. Galea, A (2018) Applied Data Science with Python and Jupyter. Packt Publishing. Birmingham. Petzold, C (1999) Code: The Hidden Language of Computer Hardware and Software. Microsoft Press. Washington. Sedgewick (2015) Introduction to Programming in Python. Person Education, Inc. Michigan. Severence, C (2016) Python for Everybody: Exploring Data in Python 3. Thomas, D. and Hunt, A (2019) The Pragmatic Programmer, Second Edition. Pearson Education, Inc. London.

Transferrable Skills

D2 Critical thinking and problem solving. D4 Communication skills, written, oral and listening. D6 Effective Information retrieval and research skills. D7 Computer literacy. D8 Self-confidence, self-discipline & self-reliance (independent working). D9 Awareness of strengths and weaknesses. D12 Appreciating and desiring the need for continuing professional development D13 Reliability, integrity, honesty and ethical awareness D15 Ability to prioritise tasks and time management (organising and planning work). D16 Interpersonal skills, team working and leadership. D17 Presentation skills. D18 Commercial awareness (Narrative)

Module Structure

Activity Total Hours
Practicals (FT) 36.00
Lectures (FT) 12.00
Independent Learning (FT) 122.00
Assessment (FT) 18.00
Tutorials (FT) 12.00

Assessment Methods

Component Duration Weighting Threshold Description
Course Work 01 n/a 100.00 40% Project code, documentation & report