Considerations on Interdisciplinary Instruction and Design Influenced by Adaptive Learning. A Case Study Involving Biology, Computer Science, Mathematics, and Statistics

TL;DR

This paper discusses the implementation of ALICE, an adaptive learning system, in interdisciplinary education to personalize learning and improve knowledge acquisition across diverse academic backgrounds.

Contribution

It presents a detailed case study on integrating ALICE into a graduate Systems Biology course, highlighting instructional design considerations for interdisciplinary adaptive learning.

Findings

ALICE enables personalized learning paths based on students' prior knowledge.

Implementation of ALICE improves engagement and understanding in interdisciplinary courses.

The case study provides practical guidelines for instructional design in adaptive interdisciplinary education.

Abstract

ALICE (Adaptive Learning for Interdisciplinary Collaborative Environments) is an open-source web based adaptive learning system designed for interdisciplinary instruction. ALICE has the potential to transform education by empowering transdisciplinary knowledge acquisition. This is particularly important in fields that accept newcomers with diverse scholastic backgrounds, e.g. Systems Biology. With traditional interdisciplinary instruction, the instructor must cover pre-requisite information from multiple disciplines to ensure all students begin at a common baseline - slowing the learning process. With ALICE, students follow a personalized syllabus based on their previous knowledge and work towards individual goals. Implementing an adaptive learning system in an interdisciplinary course requires careful considerations of the instructional design. Structuring material, formulating assessments, and other instructional design aspects must be carefully considered. These considerations are detailed through the exploration of a case study implementing ALICE in a graduate level Systems Biology course.