The Active Role of Students in Solving Real-World Problems in Animal Nutrition
Vida Rezar is an associate professor at the Faculty of Biotechnology who systematically incorporates digital tools and active learning approaches into her teaching. She pays special attention to linking theory with practice and to fostering students’ independence and critical thinking. She regularly uses online learning environments to structure course content, assess student knowledge in real time, and facilitate collaborative student work. She shares her experiences with colleagues at workshops, conferences, and through mentoring. As a multiplier at the faculty, she aims to share examples of best practices and concrete pedagogical solutions, provide professional support in planning innovative learning activities and the meaningful use of ICT, participate in presentations and workshops, and foster a culture of reflection, collaboration, and the adoption of new, innovative approaches to teaching.
The challenge – students’ passive role and weak links with the world of work
In courses where the lecturer is planning to modernise the teaching, she faces several challenges:
- the student group is diverse – there are differences in prior knowledge, experience and digital skills,
- students often remain in a passive role as listeners,
- and students find it more difficult to link theoretical knowledge to practical situations.
This leads to a superficial understanding and a reduced willingness to apply knowledge in a real-world context.
The solution – learning by solving real-world professional problems
The multiplier aims to develop and introduce a digitally supported problem-based learning model. The proposed upgrade introduces a shift:
- from passive listening to active exploration,
- from the transmission of knowledge to solving real-world problems,
- from single-answer solutions to the analysis of complex situations.
Students will tackle practical case studies in the field of animal nutrition, in which they will:
- work in small groups,
- use digital tools for analysis, collaboration and reflection,
- meaningfully incorporating artificial intelligence to support their research, the development of draft solutions and self-assessment,
- and developing critical judgement of the information obtained.
How will work on the updated subjects be organised?
The learning process incorporates theoretical content and practical or problem-based work.
Introduction to a real-world problem: presentation of a real-world professional challenge
Group work: students analyse the problem and devise solutions in small groups
Use of digital tools: during group work, students will use digital tools for collaborative work, data analysis and reflection on learning
Supported use of AI: students will utilise generative artificial intelligence tools to assist them in their activities, including researching sources, drafting and self-assessment.
Reflection: students will critically evaluate solutions and the learning process
Link to theory: students will contextualise practical solutions within a professional framework as they go along.
This approach enables the gradual development of knowledge through experience and active participation.
The role of digital technologies
Digital technologies play an important supporting role. Students will use collaborative digital tools for group work; they will also use technology to analyse data and reflect on the learning process. Generative artificial intelligence tools will be used in certain parts of the activities for searching, researching sources, creating initial drafts of solutions and self-assessment. The emphasis will be on the critical and thoughtful use of technology, not on automation.
Why is this approach of interest to other educators as well?
The approach is transferable to numerous fields, as:
- it encourages students to take an active role and fosters greater engagement,
- it enables the effective integration of theory and practice,
- it develops critical thinking and the ability to solve complex problems,
- it offers a concrete model for the meaningful integration of artificial intelligence into teaching,
- and it is suitable for heterogeneous groups of students.