INFO123 - Business Information Systems & Technology Study Notes

Course Information

  • Course Code: INFO123 - 2026S1

  • Course Title: Business Information Systems & Technology

  • Location: University of Canterbury, Christchurch, New Zealand

Teaching Team

  • Richard Derham:

    • Email: richard.derham@canterbury.ac.nz

    • Location: Meremere Building, Room 520D

    • Availability: Weeks 1, 4-8, 12

  • Jean-Grégoire Bernard:

    • Email: jean-gregoire.bernard@canterbury.ac.nz

    • Location: Meremere Building, Room 510

    • Availability: Weeks 1-3, 9-12

  • Discussion Tutors: Angela Martin

  • Lab Tutors: Nicholas Poppelwell, Zizhuo Luo, Pouyan Jahanbin

Attendance and Support

  • Accountability: Regular attendance is crucial for staying on track with course material.

  • Study Support:

    • PALS (Peer Assisted Learning Support):

    • Regular group study sessions run by students who have a strong grasp of the material.

    • Starts Week 2, timetable available on MyTimetable.

    • Skill Development: Sessions designed to improve university skills such as:

    • Assignment structuring

    • Referencing

    • Exam preparation strategies

Course Overview

  • Learning Objectives:

    • IS Solution Implementation

    • Hardware and Software

    • Sustainable Infrastructures

    • Database Management

    • Database Design

    • Data Visualization

    • Business Information Systems

    • Fundamental Concepts

    • Strategic Initiatives

    • Digital Technologies in Business Processes

    • Collaboration Systems

    • Enterprise Resource Planning

    • Managing Information Systems

    • Digital Innovation and Business Models

    • Information Security

    • IS Governance

    • Business Productivity Tools

    • Emerging Technologies

    • Digital Ecosystems

Skills Related to Information Systems (IS) by Major

Financial Management IS

  • Digital Technologies:

    • Automated auditing systems

    • Blockchain for transactions

  • Business Productivity Tools:

    • Advanced Excel for financial modeling

  • Data Visualization:

    • Techniques for financial market analysis

HR and Management IS

  • Digital Technologies:

    • Focus on HR information systems and performance analytics

  • IS Governance:

    • Policies for the digital workplace

Marketing IS

  • Digital Business Models:

    • Exploration of e-commerce platforms and their impact

  • Data Analytics Tools:

    • Tools for analyzing customer behavior effectively

  • Collaboration Systems:

    • Tools for remote work management

Operations and SCM IS

  • Enterprise Resource Planning:

    • Optimizing supply chain processes

  • Digital Technologies:

    • Enhancing logistics operations

Semester Schedule

First Half of Semester

  • Week 1 (16-19 February): Introduction to IS & Digital Technologies in Business

  • Week 2 (23-26 February): Digital Strategy & Digital Innovation

    • Lab: Excel 1

    • Tutorial: Tut 1

  • Week 3 (2-5 March): Digital Business Models & Platforms

    • Lab: Excel 2

    • Tutorial: Tut 2

  • Week 4 (9-12 March): Business Process Management & Enterprise Systems

    • Lab: Excel 3

    • Tutorial: Tut 3

  • Week 5 (16-19 March): Data & Data Modelling

  • Week 6 (23-26 March): Databases in Business

    • Tutorial: Tut 4

    • Assignment Due: Excel assignment on 20 March, Database 1

Second Half of Semester

  • Week 7 (20-23 April): Business Intelligence & Big Data

    • Lab: Database 2

    • Tutorial: Tut 6

  • Week 8 (28-30 April): AI in Business Part 1

    • Assignment Due: Database assignment on 1 May

    • Tutorial: Tut 7

  • Week 9 (4-7 May): AI in Business Part 2

    • Lab: GenAI 1

    • Tutorial: Tut 8

  • Week 10 (11-14 May): IS Acquisition, Development & Implementation

    • Lab: GenAI 2

    • Tutorial: Tut 9

  • Week 11 (18-21 May): IS Security & Ethics

    • Lab: GenAI 3

    • Tutorial: Tut 10

  • Week 12 (25-28 May): Digital Technology & Future of Work

    • Assignment Due: Individual project and video presentation on 29 May

Discussion Tutorials

  • Start: Week 2

  • Format: Small group discussions to deepen understanding of topics; no assessment involved.

  • Content: Real business cases and hands-on problem solving.

  • Benefits:

    • Apply concepts to real-world scenarios.

    • Develop critical thinking skills desired by employers.

    • Improve networking with peers.

    • Regular attendance correlates with improved grades.

    • Practice for exams.

Labs Tutorials

  • Skills Development Schedule:

    • Weeks 2-4: Excel

    • Weeks 5-7: Databases

    • Weeks 9-11: GenAI

    • Week 12: Presentation with PowerPoint

  • Format: Flexible, drop-in sessions; pace set by students.

  • Goal: Prepare for assignments and future job market.

Assessments

  • Grading Breakdown:

    • Individual GenAI Project: 25%

    • Excel Assignment: 7.5%

    • Database Assignment: 7.5%

    • Mid-Semester Test: 30% (covers weeks 1-5)

    • Final Exam: 30% (covers weeks 6-12)

  • Assessment Details:

    • Excel Assignment (7.5%): Focus on conducting data analysis with Excel; no GenAI allowed.

    • Database Assignment (7.5%): Test ability to manipulate a database.

Individual Project Overview

  • Project Title: Build a Breakfast Products Business Using AI

  • Objective: Create a complete business using generative AI tools.

  • Tasks:

    • Analyze market data

    • Design product, brand, and marketing strategy

    • Model business processes and information systems

    • Build prototypes including a website and chatbot

    • Present business in a video

  • Project Timeline:

    • Weeks 7-12, due on 29 May 2026 at 5 PM

Project Deliverables

  1. Business Plan Document (PDF): Comprehensive plan integrating product design, market analysis, marketing, and operations.

  2. Advertisement Jingle (Audio): 15-30 seconds for podcast advertising.

  3. Company Website Demo: Functional landing page, product page, and shopping cart demo.

  4. Customer Support Chatbot: Functional AI agent for customer inquiries.

  5. Video Presentation: 2-3 minute pitch of the business and reflection on working with AI.

  6. Chat Log: Documentation of AI conversations.

Video Presentation Format

  • Type: "Talking Head" Screencast

  • Tools: PowerPoint will be used to record.

Tools & Support Needed

  • Required Subscriptions:

    • GitHub Copilot education account

    • Figma Studio education account

  • Recommended Plan: Pick one:

    • Google Gemini AI Plus

    • Mistral Le Chat Student Plan

    • ChatGPT Go

  • Support Offered:

    • Weekly labs for additional help

    • Detailed assignment briefs available on Learn

Assessment Criteria

  • Specification Grading Approach:

  • Evaluation Areas:

    • Technical competence with AI tools

    • Critical thinking regarding AI outputs

    • Business acumen in concept creation

    • Integration of AI outputs into deliverables

    • Reflection on AI's role and ethical implications

Mid-Semester Test & Final Exam

  • Mid-Semester Test (30%):

    • Date: March 24, 7-8:30 PM

    • Coverage: Weeks 1-5 including lectures and labs

    • Format: Closed book, multiple-choice questions (MCQs)

  • Final Exam (30%):

    • Date: To be determined during exam period

    • Coverage: Weeks 6-12 with materials from lectures, labs, and required readings

    • Format: Closed book, MCQs; practice questions provided.

Learning Resources

  • Mandatory Materials:

    • Lecture recordings, required readings, slide decks

    • Instructions and assignment briefs found on LEARN

    • Access to free tools like Office365 for Excel and PowerPoint

  • Counseling and Support Services: Available for academic skills improvement and personal wellbeing.