Publication Type

Journal Article

Publication Date

2-2017

Abstract

The applications of learning outcomes and competency frameworks have brought better clarity to engineering programs in many universities. Several frameworks have been proposed to integrate outcomes and competencies into course design, delivery and assessment. However, in many cases, competencies are course-specific and their overall impact on the curriculum design is unknown. Such impact analysis is important for analyzing, discovering gaps and improving the curriculum design. Unfortunately, manual analysis is a painstaking process due to large amounts of competencies across the curriculum. In this paper, we propose an automated method to analyze the competencies and discover their impact on the overall curriculum design. We provide a principled methodology for discovering the impact of courses’ competencies using Bloom’s Taxonomy, Dreyfus’ model and the learning outcomes framework. We developed the Curriculum Analytics Tool (CAT) which generates the competency scores for the entire curriculum across two dimensions; Cognitive levels and Progression levels. We use the CAT to analyze the competencies of an undergraduate Information Systems Management core curriculum program. Using 14 courses and the corresponding 578 competencies, this paper shows how our method enables us to perform in-depth analysis on the curriculum by discovering the cognition and progression statistics. We further apply the tool for recommending competencies when launching new courses.

Keywords

Competencies, Bloom’s taxonomy, Curriculum analysis, Competency cube, Undergraduate information systems program, Exploratory data analysis

Discipline

Programming Languages and Compilers | Software Engineering

Research Areas

Data Management and Analytics

Publication

Education and Information Technologies

First Page

1

Last Page

20

ISSN

1360-2357

Identifier

10.1007/s10639-017-9584-3

Publisher

Springer Verlag (Germany)

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org./10.1007/s10639-017-9584-3

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