Self-adaptive Learning Algorithm as a Tool for the Development and Strengthening of the Dyslexic Student's Skills in the Study of Musical Composition

In this period, the topic of Artificial Intelligence (AI) is at the center of various discussions that mainly concern the teaching/learning system and the contribution that AI can make in the classroom. From a naturally inclusive perspective, technologies (based on AI) from the early stages of design and development must take into consideration the needs of all students, without neglecting dyslexic students. In that sense, the main problem is represented by the ability of these tools to support the dyslexic student in studying and not in carrying out the assigned tasks for him/her. This research paper presents an algorithm (which combines the Viterbi algorithm with the Markov process) designed and developed to enhance the learning process of a dyslexic student in the area of Music Composition, in particular, in the harmonization of a melodic line. The harmonization of a melodic line involves many cognitive processes and systems and a learning disability may lead to over-fatigue and to a psychological distress of the student, with the subsequent loss of confidence and personal motivation. The algorithm looks like a tutor able to support the student through suggestions during the harmonization of a musical melody (and not by providing the solution). The experimental results show that the algorithm, given a melodic line, is able to correctly generate a bass line as well as harmonize each sound of the melodic line. It is also demonstrated (through a case study) that the algorithm can have a positive impact on dyslexic students’ motivation and engagement in learning. Finally, educational implications and research suggestions are provided based on the research results.