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Belen Moncalvillo
Bloom's taxonomy is a learning model traditionally widely used by educators from various disciplines, including Computer Science. However, adapting the activities and evaluation methods typical of the computer field to this model presents serious difficulties. To analyze this problem, Professor Susana Masapanta Carrión from PUCE in Ecuador, who is writing her doctoral thesis in the Information and Communication Technologies Program at URJC, has carried out a systematic review of studies that use this methodology. The analysis of it has shed light on the use of Bloom's taxonomy in university teaching in computer science, the difficulties faced by educators and their possible reasons.
“The main use given to taxonomy in computer science is how it helps to evaluate students in programming subjects”, explains Ángel Velázquez Iturbide, professor in the area of Computer Languages and Systems at the URJC and director of the thesis. “The main difficulty is precisely to classify these evaluation activities in the different cognitive processes of the taxonomy”, adds the researcher.
The study has found that this difficulty is mainly due to insufficient knowledge of Bloom's taxonomy, possible deficiencies of the model and the lack of studies to adapt it to programming subjects. Based on their findings, the researchers are preparing a user guide aimed at teachers in the computer science field. Part of these efforts have recently been presented at the XXIV Conference on University Teaching of Informatics (JENUI'18), held in Barcelona.
The need to update the traditional model to the new times
The original version of Bloom's taxonomy dates back to 1956 and was primarily conceived to classify assessment exercises, establishing six levels of difficulty. In 2001, a revised version of this system was developed that instead of levels proposes two dimensions, cognitive and knowledge, with the aim of specifying and aligning the learning outcomes, teaching activities and evaluation activities of a subject. Nevertheless, computer science educators frequently find it difficult to equate their students' assessment activities with the classification of the taxonomy. Faced with this recurrent problem, the findings of the URJC researchers may be essential to improve current teaching models in programming subjects.
The research was originally published as communication in the minutes of 49th ACM Technical Symposium on Computing Science Education (SIGCSE'18), held in Baltimore (Maryland, USA), in February 2018. SIGCSE is one of the most prestigious conferences on computer science education and the largest by volume of attendees and diffusion.