As the use of multiple learning styles can improve the students’ performance, computer aided instruction is expected to explicitly support them. Searching for their correspondences within software engineering, we identified three concerns that may be applied within learning systems: modeling – for adding symbolic representations; knowledge engineering – for a semantic characterization of the domain of study; and tools – for giving a figural form to learning objects. The article regards the students’ practical work that uses instrumentation and measurement, generally present in engineering education. The proposed Web-based solutions targeted the learning improvement based on a combination of learning styles; they lean on: creating visual models of instruments; domain ontology for structuring practical work guidelines specific to engineering; model driven tools for integrating data and generating learning content. An experiment was conducted on a group of engineering students, validating that, under time pressure conditions, the proposed models, knowledge and tools, allow a better comprehension in respect with the traditional text guidelines. This brings into discussion whether the design of learning systems could better support multiple learning styles by introducing more models and knowledge representations specific to the domain of study

Keywords: Engineering education, Modeling, Knowledge engineering, Computer aided instruction, Instrumentation and measurement