Analytical Report

Academic Report
An academic report requires students to develop a coherent analysis of a selected problem within a specific social, business, or academic context. Students formulate a research question, select relevant sources and data, make methodological decisions, and build an argument that leads to well-justified conclusions. The report follows a clear structure and makes the author’s line of reasoning explicit.

This task encourages students to combine data, interpretation, and argumentation into a logical whole. They give meaning to information, develop their own position, and justify it with evidence. The method strengthens students’ ability to work with different types of data, synthesise information, and communicate findings precisely. It also develops responsibility for analytical decisions and their consequences.

The academic report prepares students for expert work because it reflects the practices of analysts and specialists. In an AI-supported environment, it emphasises the importance of high-quality reasoning, coherent argumentation, and meaningful conclusions as core elements of academic and professional work.

An academic report should always include a clearly defined problem, references to the relevant literature or external sources, a description of the data or materials used, an analysis, conclusions, and recommendations. Depending on the learning objectives, however, different aspects of the analytical process may be emphasised more strongly, for example:
• An individual analytical report based on an independently defined problem.
• A team report with clearly divided roles and responsibilities.
• A report concluding with recommendations for an organisation or public institution.
• A critical report analysing existing studies or industry reports.
• A quantitative data-based report with elements of results visualisation.

Course: Sustainability Modelling
Topic: Quantifying the Progress of EU Countries Towards Achieving the 2030 Agenda
Students work in teams as analysts preparing a report for a public institution. Their task is to conduct a quantitative analysis of the progress made by EU countries towards selected Sustainable Development Goals (SDGs) and to prepare recommendations.

Problem Definition (15–20 min)
Teams select the Sustainable Development Goals (SDGs) they will focus on, define the scope of their analysis, and formulate research questions and hypotheses. A precise and well-justified problem definition is essential.

Variable Selection (20–30 min + independent study)
Students identify relevant variables, select those best suited to the analysis, and define how they will be measured. Each decision must be justified, as it may influence the final results.

Data Analysis and Indicator Construction (30–40 min + independent study)
Teams prepare data summaries, rankings, and visualisations. Methodological consistency and clear presentation of results are crucial.

Synthesis and Interpretation of Results (20–30 min + independent study)
Students link their findings to their initial assumptions, identify patterns and differences, and draw conclusions.

Academic Report Writing (independent study + 15–20-min consultation)
Teams prepare an academic report that includes a description of the problem, methodological assumptions, data analysis, interpretation of the findings, limitations, and recommendations. The teacher may provide feedback on a draft report structure or on selected aspects of the team’s argumentation during a consultation session.

Policy Brief and Presentation (15–20 min)
Teams prepare concise recommendations and present their key findings in a structured format.

• When the aim of the course is to develop in-depth analytical thinking.
• In situations where students must independently define a problem and make analytical decisions.
• When the course prepares students for research or expert-level work.

• When the primary aim is to deliver large amounts of factual knowledge in a short time.
• In very large groups where providing high-quality feedback is difficult.
• In situations where students tend to rely on AI tools uncritically.

• High student workload → clearly structure the project stages and divide the task into smaller, manageable milestones.
• Declining motivation during longer projects → introduce intermediate stages with visible outcomes and timely feedback to maintain engagement.
• Risk of overreliance on AI → focus assessment on students’ reasoning, analytical choices, and decision making processes.

Easier → Provide a ready-made report template with clearly defined requirements for each section.
More Challenging → Ask students to analyse alternative solutions and justify the options they rejected.

• Break the task into stages with clear checkpoints.
• Require students to distinguish between data, interpretation, and opinion.
• Ask “why” questions.

Formative Assessment
Assess the work at each stage, focusing on the quality of decisions, the coherence of assumptions, and the logic of the analysis. This enables you to guide and refine the work as it develops.

Summative Assessment
Use a rubric that covers problem formulation, methodological decisions, quality of analysis, and relevance of conclusions. The assessment should reflect the student’s reasoning process, not only the final outcome.