DrAnagi Gamachchi

T1 - 2026, T2 - 2026

A three-hour Agentic AI workshop delivered in collaboration with Google and Deloitte as the Week 11 learning activity for MIS780.

In 2026-T1, a redesigned assessment was introduced in MIS271 to strengthen students’ practical capabilities in data cleansing, analysis and reporting, key competencies required of business analysts. Moving beyond the traditional approach of providing a common dataset to all students, the initiative used a Python script to generate individualised Excel datasets for each student. This provided students with a unique data environment in which to apply and demonstrate their data preparation and analytical skills, promoting independent problem-solving, reducing opportunities for collusion and strengthening academic integrity. By exposing students to different datasets, the approach also better reflected the variability and challenges of real-world business data, enhancing the authenticity and relevance of the learning experience. The initiative was presented at the 2026 Deakin Teaching and Learning Conference under the title *“Unique by Design: Automated Individualised Datasets for Authentic Assessments”.

In MIS271, structured group-work progress checkpoints were introduced to strengthen teamwork, accountability and student engagement throughout the group assessment. As mandatory requirements, each team must submit a team contract and two sets of meeting minutes documenting their discussions, progress and agreed actions before gaining access to the final assessment submission folder. The staged submission process encourages teams to establish clear roles and responsibilities, maintain regular communication and monitor their progress throughout the assessment. It also provides opportunities to identify and address coordination issues early, rather than waiting until the final submission. This approach promotes more effective collaboration, shared responsibility and professional teamwork practices that reflect expectations in the workplace.

As Unit Chair of MIS271 – Business Intelligence and Data Warehousing in 2025, I proposed a comprehensive redesign of the unit's assessment structure, which was implemented for the first time in 2026. The redesign aimed to create a more balanced and progressive assessment experience, improve the timing and distribution of assessment tasks, and provide greater opportunities for feedback and feedforward throughout the trimester. Previously, the assessment structure comprised a group assignment worth 40% due in Week 9, an individual reflection worth 10%, and a 50% hurdle examination. The redesigned structure introduced three complementary assessment tasks. The first is an individual data cleansing assessment (30%) due in Week 4, enabling students to develop and demonstrate foundational data preparation and analytical skills. The second is a group-based dashboard design assessment (40%) due in Week 8, requiring students to develop stakeholder-focused dashboards based on a business case. The third requires students to develop a proposed Business Intelligence solution, including a report for a mid-level management audience addressing the BI lifecycle, data warehousing architecture and dimensional modelling, alongside a video presentation communicating the proposed solution to an executive audience.

Introduced in 2025-T2 and continued in 2026-T2 in MIS780 - Advanced AI in Business, this initiative incorporates a graded Generative AI (GenAI) reflection component into Assessment 2. Students develop Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) models using provided datasets. As part of the assessment, students document how they use GenAI tools to support model development, including brainstorming model-tuning strategies, troubleshooting coding errors and improving model performance.