Broader terms curriculum mapping: Using natural language processing and visual-supported communication to create representative program planning experiences

Rogério Duarte (1) , Ângela Lacerda-Nobre (1) , Fernando Pimentel (1) , Marc Jacquinet (2)

1 Instituto Politécnico de Setúbal
2 Universidade Aberta [Lisboa]

Accreditation bodies call for curriculum development processes open to all stakeholders, reflecting viewpoints of students, industry, university faculty and society. However, communication difficulties between faculty and non-faculty groups leave unexplored an immense collaboration potential. Using classification of learning objectives, natural language processing, and data visualization, this paper presents a method to deliver program plan representations that are universal, self-explanatory, and empowering. A simple example shows how the method contributes to representative program planning experiences and a case study is used to confirm the method's accuracy and utility.

Keywords: Curriculum mapping; Natural Language Processing (NLP); Network graphs; Learning objectives classification; Curriculum analytics; Curriculum design; Higher education

Domains: Engineering Sciences [physics]

Rogério Duarte, Ângela Lacerda-Nobre, Fernando Pimentel, Marc Jacquinet. Broader terms curriculum mapping: Using natural language processing and visual-supported communication to create representative program planning experiences. 2021. ⟨hal-03154022⟩