## 5 Conclusions  
Addressing the curriculum development process is of paramount importance. This process has profound consequences, being responsible for the preparation of future professionals and for laying the foundations for dynamic knowledge transfer systems affecting local and global realities. At the heart of curriculum development lies program planning. Program planning is of immense strategic value. The effort put into program planning propagates through all levels and subprocesses of teaching and learning, imprinting the values, intentions, and expectations that will guide stakeholders; shaping HEI educational outcomes. To improve program planning, more participatory touchpoints to non-faculty groups (i.e., students, industry, society) are needed. Creating these touchpoints and contributing to representative program planning was the motivation behind this paper. An important impediment to representative program planning lies in the communication gap between faculty and non-faculty groups. Curriculum mapping has been used to promote better communication between faculty and shape program planning. This paper collected practices available from different types of curriculum mapping and, using information and data science techniques, tailored a curriculum mapping method for non-faculty groups' participation in program planning discussions. The resulting method--the broader terms CM (curriculum mapping) method--was illustrated with the help of a simple example--the five courses example. The following conclusions were found:  
* (Section 3.1) Classification replaces the head-on discussion of subjective course LO-statements with the much more objective task of selecting broader terms from a control vocabulary. * (Section 3.2) Natural language processing allows the quantitative analysis of the program plan, providing a way to cut across disciplinary and scientific boundaries, hierarchical and functional differences, and atomized discourses. * (Section 3.3) Mappings render quantitative results' interpretation universal and self-explanatory, empowering stakeholders with evidence-based details on weaknesses (and strengths) in the program plan. * (Section 3.4) The discussion of visual outputs with non-faculty groups allows representative program planning, with these groups' voices being heard on reclassification and review of course LO-statements. * (Figure 1) The iterative nature of the method ensures program planning using quantitative elements and stronger links between courses' LO-statements, allowing a holistic approach to curriculum development. Despite the relevance of the above conclusions--related to the participatory involvement of non-faculty stakeholders--the simple five courses example was unable to answer the question of the broader terms CM method's accuracy and, therefore, of the method's utility. To evaluate the method's accuracy, a case study--the T&IM bachelor degree--was used. Mappings for the case study were obtained and compared with observations from an independent panel of experts. From this comparison, the following was concluded (Section 4.4):  
* Mappings provide evidence supporting the observations, and the broader terms CM method provides an accurate depiction of T&IM program plan weaknesses. * Key concepts obtained from course LO-statements--and the broader terms CM method--are useful in program planning. Considering the benefit of non-faculty groups' participation in curriculum development processes, and considering the progress made in information systems and relational databases [50; 51; 52], the merger of techniques used in the broader terms CM method and HEI information systems would help bring the method's benefits into HEIs' everyday reality; for example, with the inclusion of mappings in information systems' summary dashboards. This merger is just one potential topic for further explorations in this rich and challenging research area that joins education, information, and data sciences. Conceptualization, R.D. and A.L.N. ; methodology, R.D. and A.L.N.