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The curriculum prerequisite network: Modeling the curriculum as a complex system.

Preston R Aldrich¹

¹Department of Biological Sciences, Benedictine University, Lisle, Illinois.

Biochemistry and Molecular Biology Education : a Bimonthly Publication of the International Union of Biochemistry and Molecular Biology

|February 25, 2015

Summary

This study visualizes academic curricula using prerequisite networks, revealing hidden structures and community organization within programs. These networks map course dependencies, aiding in curriculum reform and academic advising.

Keywords:

curriculum prerequisite network directed acyclic graph network systems biology

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Area of Science:

Educational research
Network science
Graph theory

Background:

Academic curricula are complex systems with inherent structures.
Previous research has utilized network analysis for various complex systems.
Course prerequisites define the flow of information within an academic program.

Purpose of the Study:

To visualize the hidden structure of academic curricula using prerequisite networks.
To analyze the structural properties of university and program-specific curricula.
To explore applications of curriculum network analysis for advising and reform.

Main Methods:

Representing academic curricula as directed acyclic graphs (DAGs).
Utilizing course catalogue data to build prerequisite networks.
Applying graph theory metrics to analyze network structures.

Main Results:

Curriculum data can be modeled as DAGs with analytical features.
The undergraduate curriculum is partitioned into isolated course groupings.
The Biochemistry and Molecular Biology program exhibits cross-disciplinary community structure.

Conclusions:

Prerequisite networks reveal intrinsic constraints on information flow in curricula.
Network analysis can identify hidden structures and roles of individual courses.
This approach offers valuable insights for curriculum development and student advising.