Vibe Coding: AI-Assisted Software Development

Course ID

H810043201

ECTS value

Course Title

Number of lessons

4 hours per week

Course Responsible

Name	Email	Department
Edward Abel	abel@sdu.dk

Lecturer

Name	Email	Department	City
Edward Abel	abel@sdu.dk		Kolding

Mandatory prerequisites

The course is designed to be accessible to students from a range of academic backgrounds and does not assume any prior programming experience.

Recommended prerequisites

It is recommended that the student has basic interest in digital technologies and curiosity about how software and artificial intelligence systems work.

Overall description learning objectives

The described goals for knowledge, skills and competencies are supported by the specific teaching and working methods described below. At the same time, teaching and working methods are organized in accordance with the examination format described under Examination Regulations, which constitutes the most appropriate framework for testing the student’s achievement of the subject’s goals.The course combines theoretical perspectives on artificial intelligence–assisted software development with hands-on experimentation and practical project work. Students will engage with elements such as conceptual discussions, guided exercises, and collaborative activities designed to develop both practical competencies and critical reflection on emerging AI-supported development practices.

Learnings objectives - Knowledge

After completing the course, the student should be able to:

Explain concepts of AI-assisted software development and its relationship to traditional programming practices
Describe how contemporary AI systems can support software development workflows
Explain central concepts related to human–AI collaboration in programming and digital production
Demonstrate understanding of key programming concepts relevant for AI-assisted software development
Reflect on the broader technological, societal, and ethical implications of AI-assisted development practices

Learning objectives - Skills

After completing the course, the student should be able to:

Formulate programming tasks and development problems suitable for AI-assisted development approaches
Develop and adapt software solutions through constructive use of AI-assisted development tools and workflows
Identify limitations, errors, or inconsistencies in AI-assisted software artefacts and development outputs
Utilise fundamental programming concepts and knowledge to support the development and evaluation of AI-assisted software solutions
Critically assess the reliability, correctness, and usefulness of AI-assisted outputs and solutions

Learning objectives - Competences

After completing the course, the student should be able to:

Independently apply AI-assisted development approaches in practical digital development contexts
Critically reflect on the opportunities and limitations of artificial intelligence in software development and digital technologies
Integrate human judgment, domain knowledge, and computational reasoning when working with AI-assisted systems
Collaborate with others in exploratory and experimental digital development environments
Adapt to evolving technological environments and emerging AI-supported development practices

Content

The teaching explores a scientific introduction to AI-assisted software development with emphasis on emerging practices within human–AI collaboration in programming. The course explores how artificial intelligence systems can support different stages of software development, such as problem formulation, assisted code generation, debugging, documentation, and iterative refinement. Students are introduced to conceptual frameworks for understanding human–AI collaboration in programming, as well as practical techniques for working productively with AI-supported development environments. The subject also examines broader perspectives on reliability, accountability, authorship, and creativity in AI-assisted development. Through practical exercises and projects, students experiment with designing, building, and refining artefacts while critically reflecting on the evolving role of programming skills in an AI-augmented technological landscape.

The course is organized around a sequence of thematic elements exploring AI-assisted development practices. These may include:

- Introduction to AI-assisted programming and concepts such as “vibe coding”
- Human–AI collaboration and computational thinking in AI-supported environments
- Working with AI systems for assisting with generating, modifying, explaining, and evaluating code
- Core programming concepts relevant for supporting the development and evaluation of AI-assisted software solution
- Iterative development workflows within AI-assisted development
- Data-driven workflows and experimentation with AI-assisted data science analysis, modelling, and visualization
- Emerging developments in AI-supported software development
- Specific tools, technologies, and examples used in the course may vary in order to look to reflect current developments in the field.

Content of the current semester

Forms of instruction and work

The following teaching and working methods may be used in the course: lectures, group teaching, discussions, exercises, e-learning activities, workshops, practical coding activities, reflection exercises, and project-based work. Teaching is organized around a combination of conceptual lectures and hands-on exploration where students actively engage with AI-assisted development practices. Students will work both individually and collaboratively to develop artefacts, test ideas, and reflect on the strengths and limitations of AI-assisted solutions. Feedback may take the form of feedback provided by the teacher and peers in connection with exercises, discussions, and practical work.

The teaching is organized in such a way that it supports the humanities model for active learning and activating teaching, as described in the curriculum section Didactic, pedagogical basis and contact with the research environment. At the start of the course, the teacher informs students about how the study activities are organized.

The activities in the course are primarily aimed at achieving the learning objectives and preparing the student for the examination form, which consists of a portfolio, but may also include written reflections, practical exercises, and collaborative exploration

Teaching in the subject may involve students participating in the following teaching and study formats:

Teaching room where the teacher has planning responsibility and is present
Study rooms where the teacher has planning responsibility but is not present
Teaching room where the teacher is present, but students have planning responsibility for specific sub-activities
Study rooms where students have planning responsibility and the teacher is not present

Workload

10 ECTS is equivalent to 280 working hours. The working hours are distributed between the activities described in the humanities model and listed under Forms of instruction and work as well as the exam including the preparation of this. The university teacher will provide an indicative distribution of the workload at the beginning of the course.

Teaching language

English

Examination regulations

Final examination

Name

Final examination

Timing

The examination is portfolio of work explored and worked on during the semester.

The examination will take place as follows:

- Final examination (1st examination attempt): Winter exam 2026/2027
- Reexamination (2nd examination attempt): Winter exam 2026/2027
- Reexamination (3rd examination attempt): Summer exam 2027

Tests

Final examination

EKA

H810043202

Name

Final examination

Form of examination

Portfolio

Assessment

Second examiner: None

Grading

Pass/Fail

Identification

Full name and SDU username

Language

English

Length

The teacher will in writing via SDU’s digital e-learning platform inform about the number and extent of assignments that make up the portfolio assessment at the commencement of teaching.

Examination aids

Information about aids and use of generative AI can be found on the program's study pages

Assignment Submission

Submission on SDU´s digital platform required.

ECTS value

Additional information

Assessment criteria:

Considering the method of assessment and the current study level, specific emphasis will be put on the extent to which the student´s performance meets the learning objectives as well as to what extent the student masters the general competence objectives mentioned in the currciulum, section Aim of Programme, including any professional profile and specialisations, particularly no.

3. be able to systematize complex knowledge and data and select and prioritize issues that are relevant to the subject
4. be able to critically apply the different theories and methods of the discipline
5. demonstrate a precise and consistent application of concepts
8. be able to focus and establish coherence in resolution of tasks
10. employ language - in writing and/or verbally - that is subject-oriented, precise and correct
13. be able to work independently, disciplined, structured, and targeted, including complying with deadlines and formal requirements
14. employ IT as a tool for both information retrieval as well as verbal and written communication

that the course pays special attention to.

The Pass/Fail assessment reflects it the student properly understands the general and discipline specific competencies.

Several students may contribute to the assignment: No

Re-examination takes place in the same way as the ordinary examination.

Interim provisions

No interim provisions.

Timetable for the course

Kolding

Show full time table

Deviation from the General Rules for Withdrawal

Withdrawal from this course is not permitted from the start of the semester and 21 days onwards, where withdrawal is generally allowed. Therefore, registration for the course is binding. Reference is made to the Collection of Rules for University of Southern Denmark regarding registration for course elements and exams paragraph 5, section 3-5.

Further information

See timetable for the course either above or in the calendar function in Itslearning.

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Please notice: There are limited seats in this course. Seats are assigned in order of registration.

Courses offered

Offer period	Offer type	Profile	Education
Fall 2026	Optional	Bacheloruddannelse i Digital design med interaktionsstudier og IT, 180 ECTS, start 2024	BA Digital design med interaktionsstudier og IT \| Bachelor of Arts (BA) in Digital Design, Interaction Studies and IT \| Kolding
Fall 2026	Optional	Bacheloruddannelse i international virksomhedskommunikation i engelsk, it og digital kommunikation, 180 ECTS, start 2024	Bachelor of Arts (BA) in International Business Communication in English \| Kolding
Fall 2026	Optional	Bacheloruddannelse i Biblioteksvidenskab, it og kommunikation, 180 ECTS, start 2025	Bachelor of Arts (BA) in Library Science, IT and Communication \| Kolding
Fall 2026	Optional	Bacheloruddannelse i Biblioteksvidenskab, it og kommunikation, 180 ECTS, start 2024	Bachelor of Arts (BA) in Library Science, IT and Communication \| Kolding
Fall 2026	Optional	TOMPLADS Medievidenskab, It og web	Samdrift (BA), Samdrift (KA) \| Odense
Fall 2026	Optional	TOMPLADS Humanistisk informations- og kommunikationsvidenskab	Samdrift (BA), Samdrift (KA) \| Odense

Programmes the course description is part of

Profile	Education	Semester	Offer period