The proposed evolutionary learning model, EvoLearning, is aimed towards maximizing student mastery through effort and processing, scaffolding, and meaningfulness. The model was formed by inductive development of courses in software engineering and pervasive computing over two decades, inspired by agile and evolutionary software engineering principles. The model is built on the teacher being a guide on the side instead of a sage on the stage, with the aim to allow for maximum degrees of freedom for students to pursue interests and goals while providing scaffolding for the learning process.

The design of the model has been informed by theoretical frameworks from educational psychology and pedagogy. For example, course designs utilize taxonomies for defining objectives and to construct consecutive activities, that stepwise increase the cognitive and knowledge dimensions of learning. The steps are designed as incremental and interwoven, with increasingly challenging objectives and activities. The model emphasizes students’ feeling of ownership and purpose, through freedom of will, which leads to increased meaningfulness and motivation. The learning environments invite and require active participation, from the start of a course. The design benefit from student diversity that enhances the collaborative learning experience, while allowing for non-linear increments, that may cater for unexpected yet significant learning experiences for the students.

In practice, courses are composed by interwoven individual and group activities constructively linked to learning objectives, which the proposed model conceptualizes as 'heartbeats'. Weekly tutored meetings are of an utmost importance to guide the students towards taking incremental steps and for the teacher to qualitatively assess progress with the students, as well as to define, prioritize and plan the next activities. This illustrates the emphasis of consistent and scaffolded activation of students, keeping pace throughout a course, while allowing freedom of will and use of prior knowledge, that lead to high levels of processing and perceived meaningfulness in multiple contexts.