ACADEMIC AND PROFESSIONAL SKILLS DEVELOPMENT IN COMPUTER SCIENCE - 2026/7

Module Overview

This module supports students develop essentials skills and thinking approaches needed to succeed at university and in the computer science discipline. Students will actively engage in problem-solving tasks, collaborative activities, and real-world challenges. Students will explore career pathways, work with industry-led case studies, and develop communication skills through a poster and presentation project.

Module provider

Computer Science

Module Leader

LAM Joey (CS & EE)

Number of Credits: 0

ECTS Credits: 0

Framework: FHEQ Level 4

Module cap (Maximum number of students): N/A

Module Availability

Year long

Prerequisites / Co-requisites

n/a

Module content

The module introduces core academic and professional practices required for success in Computer Science. 

Topics include: 

• Transition to university-level Computer Science study and independent learning strategies 
• Use of digital tools to support learning, including responsible and critical use of generative AI 
• Understanding assessment, feedback, and approaches to improving academic work 
• Collaborative working practices, including communication, teamwork, and version control workflows 
• Introduction to professional skills and employability in Computer Science, including career pathways and skill development 
• Application of problem-solving skills to real-world and industry-led challenges

Assessment pattern

Alternative Assessment

Individual report

Assessment Strategy

The assessment strategy is designed to: 

develop essential skills for the academic and professional expectations in the Computer Science discipline. 

The summative assessment for this module consists of: 

• A group poster and presentation (addresses learning outcomes 3, 4); 
• Attendance - students are required to attend 80% of sessions (addresses all learning outcomes). 

Formative assessment: 

In class quizzes, using polling software assess progress as well as level of understanding of the module content. 

Feedback: 

• Summative feedback will be provided for the posters and presentation. 
• Formative feedback is given throughout the module where students have the opportunity to engage in a variety of activities to receive both peer and tutor feedback.

Module aims

• To support the transition to university-level study through effective learning strategies
• To introduce collaborative working practices and the efficient use of digital and AI tools
• To increase awareness of employability skills, career pathways, and professional expectations in the computer science discipline
• To apply knowledge to real-world problems and communicating solutions to different audiences

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to: 

• Develop confidence in use of digital tools and independent study strategies
• Enhance professional skills in problem solving through real-world scenarios 
• Integrate academic and employability skills within an industry-inspired context 

The learning and teaching methods include: 

• Interactive sessions and activities focused on problem solving 
• Group work activities to build collaboration skills 
• Poster development and presentation practice sessions 
• Opportunities to engage with external speakers such as alumni, employers and other students.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: COM1036

Other information

The School of Computer Science and Electronic Engineering is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, Resourcefulness and Resilience. 

This module is designed to allow students to develop knowledge, skills and capabilities in the following areas:

• Digital Capabilities: Developing digital literacy and responsible use of AI tools.
• Employability: Understanding industry expectations and developing relevant transferrable skills. Building confidence in job searches, applications and interviews. 
• Global and cultural capabilities: Developing cultural literacy and confidence by collaborating in group work activities. 
• Resourcefulness and Resilience: Developing self-awareness and self-regulation and proactive wellbeing approaches.

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2026/7 academic year.