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EDI 3500 Low Code Software Development

EDI 3500 Low Code Software Development

Course code: 
EDI 3500
Department: 
Strategy and Entrepreneurship
Credits: 
7.5
Course coordinator: 
Ragnvald Sannes
Course name in Norwegian: 
Low Code Software Development
Product category: 
Bachelor
Portfolio: 
Bachelor of Digital Business - Programme course
Semester: 
2024 Autumn
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
English
Course type: 
One semester
Introduction

The essence of this course is to let students solve a business problem by creating a digital solution without witing code.

One key success factor in a digital transformation is how well an organization can mobilize its members to be part of the digitalization process. New technologies such as generative AI with chatbots and co-pilots enable end-users to create digital solutions such as apps, dashboard and automated workflows without the involvement of professional developers, or to co-create these with developers. There are many open-source and commercial tools available that help users build apps and other solutions without coding, and many of them includes digital assistants driven by artificial intelligence (AI) to support users in their development. 

The low code development tools have capabilities to automate tasks, workflows and processes and enable organizations to free employees from tasks that are boring, repetitive and labour intensive. The rapid development in new capabilities combined with reductions in price have made these tools affordable and practically available to the extent that we in many cases find an order of magnitude change in the cost/benefit-ratio of using technology compared to human labour.  

This course aims to train students in a problem-solving activity (a group project) where the team will create a digital solution with one or more components using the Microsoft Power Platform and other tools.

Learning outcomes - Knowledge

After completing the course, the candidate will have acquired knowledge about:

  • Problem-solving and problem-solving processes
  • Teamwork in problem solving processes
  • The mutuality of people, processes and technology in an organization
  • Low code software development compared to professional software development
  • Common platforms and tools for low code development
  • Data management
  • A framework for software sustainability assessment
Learning outcomes - Skills

After completing the course, the candidate is able to:

  • Work in a team to solve a business problem
  • Apply interdisciplinary knowledge to solve business problems
  • Apply tools that are feasible for the problem at hand
  • Develop and implement a digital solution 
  • Perform data management, including interacting with external data sources
  • Estimate and evaluate effects of the solution, including sustainability
General Competence

The candidates should be able to reflect on their own role in a problem-solving process, being part of a team and how one’s own behavior contributes to team success. They should also be able to reflect on ethical, legal and sustainability implications of softar development.

Course content
  • Problem-solving; methods and processes
    • Problem-solving techniques
    • Teamwork in problem solving
  • Data management in theory and practice
    • Manage and structure data sets
    • Using APIs to connect to data sources
  • Understanding business processes
    • Tasks, workflows and business processes
    • Process mapping and analysis
  • Low code development: concepts, tools and techniques
    • App creation from data
    • Build your own
    • Workflow automation - overview and introduction
    • Intelligent chatbots
  • People, processes and technology
    • Solution designs
    • Platform choices
Teaching and learning activities

The course includes a combination of lectures, case discussions, and "lab"-sessions with workshops and hands-on exercises.

Classes are designed to be interactive - small group activities, student-led discussions, and peer feedback exercises. Attendance and participation in class are expected.

Software tools

Students will have access to a variety of software tools in the course, including:

  • Virtual desktop (VDI) to run the software used in the course
  • Tools within the Microsoft 365 platform 
  • Online whiteboards with templates (e.g. Miro) and drawing applications (e.g. draw.io)
Software tools
Software defined under the section "Teaching and learning activities".
Qualifications

Higher Education Entrance Qualification

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

Students are expected to have a basic skills in coding and data management.

Mandatory courseworkCourseworks givenCourseworks requiredComment coursework
Mandatory53The course includes lab-sessions, workshops and other exercises to develop knowledge and skills in task automation. The coursework requirements is to hand in documentation on the result from five of these activities. More information will be given at the beginning of the course.
Mandatory coursework:
Mandatory coursework:Mandatory
Courseworks given:5
Courseworks required:3
Comment coursework:The course includes lab-sessions, workshops and other exercises to develop knowledge and skills in task automation. The coursework requirements is to hand in documentation on the result from five of these activities. More information will be given at the beginning of the course.
Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Submission other than PDF
Exam/hand-in semester: 
First Semester
Weight: 
100
Grouping: 
Group (4 - 6)
Duration: 
1 Semester(s)
Comment: 
The exam project is a group activity where students are expected to create a team to tackle a business problem. The group members should take on roles within the team and together develop a digital solution using low code tools.

The work should be documented in a written document that documents the problem-solving and development process, links for access to the solution and a multimedia production (e.g. video) that explains and demonstrates the solution.
Exam code: 
EDI 35001
Grading scale: 
ECTS
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
20 Hour(s)
Participation in lectures
Seminar groups
10 Hour(s)
Lab-seminars. Hands-on introductory training in tools and techniques
Seminar groups
15 Hour(s)
Participation in workshops
Prepare for teaching
20 Hour(s)
Reading and preparing for lectures and “lab”-sessions
Examination
90 Hour(s)
Work on the exam project, including preparing for workshops
Student's own work with learning resources
45 Hour(s)
Work with online content and assignments to develop skills in low code tools
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.