Abstract:

Higher education institutions are currently facing significant changes in the academic preparation, learning habits and competencies of incoming students. This situation is influenced by the intensive use of social networks, the growing integration of artificial intelligence tools in learning processes and a digital culture characterised by immediate access to information. While these environments favour certain digital skills, they also introduce challenges related to sustained attention, analytical reasoning, deep understanding of complex concepts and perseverance when addressing demanding problems.

Chemical Engineering education aims to develop competencies required to design, scale up and operate industrial processes that transform matter and energy, based on principles such as mass and energy balances, transport phenomena, separation processes and reactor design. This knowledge areas correspond to the competencies defined for the degree in the Spanish Order CIN/351/2009, which establishes the requirements for academic programmes that qualify graduates for professional practice in Chemical Engineering.

To analyse the current student profile and associated educational challenges, a departmental seminar was organised in the Chemical Engineering programme at the Universidad de Castilla-La Mancha. The seminar included short presentations addressing the profile of first-year students, the perspective of secondary school teachers, feedback from recent graduates, the institutional framework for competency-based assessment and the potential impact of artificial intelligence on engineering education. These presentations were followed by structured debates on student profiles, curriculum adaptation and teaching methodologies.

A structured questionnaire consisting of 17 questions was implemented using the interactive tool Mentimeter and answered by approximately 20 lecturers from the Department of Chemical Engineering. Results indicate that, although students show greater familiarity with digital tools, weaknesses appear in analytical reasoning, reading comprehension, sustained attention and tolerance to frustration when facing complex engineering problems.

Based on these findings, several priority strategies were identified, including problem-based learning, integrative projects and reinforcement of critical thinking skills. Activities developed in small groups allowing direct interaction between lecturers and students were highlighted as particularly valuable for diagnosing learning difficulties and adapting teaching methodologies to students’ real level of understanding.

Acknowledgement:
The support of the University of Castilla-La Mancha through the project “Development of Audiovisual Resources and Simulation Models for Biological Process Laboratory Practices in the Faculty of Chemical Sciences and Technologies” is gratefully acknowledged.

Keywords:

Chemical Engineering, Student competencies, Artificial intelligence.