Title: Apprentices Identifying Groups with Difficulties in Programming Education Using Data Mining

Issue Number: Vol. 2, No. 2
Year of Publication: Apr - 2016
Page Numbers: 59-72
Authors: Valter S. M. Neto, Rodrigo M. Feitosa, Dejailson N. Pinheiro, Milson L. Lima, Sofiane Labidi
Journal Name: The International Journal of E-Learning and Educational Technologies in the Digital Media (IJEETDM)
- Hong Kong
DOI:  http://dx.doi.org/10.17781/P002039


In the literature, one can find various research whose focus are the difficulties faced by students during the teaching and learning of programming. Among the proposals made to improve this situation called for the application of differentiated teaching, personalized since it is considered that the classrooms are formed by heterogeneous students with different ways of learning and who have needs and learning preferences specific. However, the customization of teaching in classroom mode is complicated to be made by the teacher. But the personalized attention to homogeneous groups of learners is a possibility to be considered. From this perspective, this article aims to describe an experience with the use of techniques of data mining along with a taxonomy of educational objectives, Bloom's Taxonomy, to identify similar groups of learners with learning difficulties in programming teaching with data obtained through assessments. With this, we hope to contribute to the construction of appropriate teaching strategies to student groups with the purpose of improving the learning process on the part of these students.