Case studies

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The process of analysing real-world scenarios to identify problems, propose solutions, and/or justify decisions (e.g. business cases, patient scenarios, engineering problems, etc).

Type = Case studies

Category: Inquiry or investigation – Open

Description

Case Studies are open inquiry and investigation assessments that challenge students to analyse real-world scenarios, identify problems, propose solutions, and justify decisions based on evidence and critical reasoning. Case studies are a great opportunity for students to authentically apply and demonstrate their learning in relation to real-world scenarios.

Students engage with authentic, discipline-specific contexts, such as business cases, patient scenarios, engineering failures, legal disputes, or environmental challenges, requiring them to interpret data, evaluate sources, and draw informed conclusions. The emphasis is on applying theoretical knowledge to practical, often complex, situations, thereby preparing students for professional decision-making and problem-solving.

Generative AI tools can be integrated into the task design to enhance learning. Students might use AI to conduct literature searches, summarise research, analyse datasets, or explore alternative solutions, with a focus on critically interpreting AI outputs and justifying their final recommendations. This encourages students to balance AI support with human judgment, strengthening their digital literacy alongside disciplinary expertise.

Educators can assess how well students navigate and evaluate information, synthesise evidence, and communicate their findings, ensuring that the learning focus remains on higher-order thinking, not just the final answer.

Meaningful engagement with AI

Students might engage with AI to support various stages in the case study analysis.

• Data analysis and visualisation: Students use AI tools to analyse data, identify trends, and suggest visualisations for their reports.
• Brainstorming strategic options: AI tools can help brainstorm potential strategies based on the identified challenges.
• Summarising research: Students could use AI tools that access literature to help with finding sources and summarising relevant information to justify their solutions.
• Feedback on writing: AI tools can provide feedback on the clarity and persuasiveness of their written recommendations.
• Role-playing simulations: Students might use AI to simulate conversations with virtual stakeholders (e.g., clients or board members) to practice presenting and defending their recommendations.
• Simulated peer feedback: AI could simulate a discussion with a colleague, offering feedback on the analysis or allowing practice for communication skills.

Examples

• Business students might analyse a case study about a company's declining market share. They identify key challenges, evaluate potential strategies, and recommend a solution based on market data and financial projections. The final product is a written report, supported by a presentation of their findings to the class.
• Engineering students could work on a case study about the structural failure of a bridge. They analyse the causes of the failure, propose alternative designs, and justify their recommendations using engineering principles and calculations. The final product is a technical report accompanied by design schematics.
• Health sciences students might examine a patient scenario involving the diagnosis and management of a chronic condition. They evaluate the patient’s history, recommend a treatment plan, and justify their decisions based on evidence-based practices. The final product is a detailed care plan, supported by a brief oral presentation to peers.