Building AI-Powered Responsible Workforce by Integrating Large Language Models into Computer Science Curriculum

Software development is undergoing a revolutionary transformation, fueled by remarkable advancements in Large Language Models (LLMs). This wave of innovation is reshaping the entire landscape and holds the promise of streamlining the development process, leading to increased productivity and efficiency. By providing text prompts, developers can now receive entirely generated code outputs, representing a fundamental shift in how software is built. This paradigm change can accelerate development cycles and unlock new levels of creativity and ingenuity, resulting in the realization of novel applications and business outcomes. However, this paradigm shift also brings new challenges and necessitates acquiring additional skills for software developers to fully harness the capabilities of LLM-powered tools. These skills include prompt engineering for software development, structural complexity management, debugging of AI errors, and compliance with ethical guidelines and principles.

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Publication Details

Published
2025-02-18
DOI
https://doi.org/10.1145/3641555.3704749
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Building AI-Powered Responsible Workforce by Integrating Large Language Models into Computer Science Curriculum

Brian K. Hare, Dianxiang Xu, Syed Jawad Hussain Shah, Joan Gladbach
Online Learning and Analytics
article

Building AI-Powered Responsible Workforce by Integrating Large Language Models into Computer Science Curriculum

Brian K. Hare, Dianxiang Xu, Syed Jawad Hussain Shah, Joan Gladbach
article en

Abstract

Software development is undergoing a revolutionary transformation, fueled by remarkable advancements in Large Language Models (LLMs). This wave of innovation is reshaping the entire landscape and holds the promise of streamlining the development process, leading to increased productivity and efficiency. By providing text prompts, developers can now receive entirely generated code outputs, representing a fundamental shift in how software is built. This paradigm change can accelerate development cycles and unlock new levels of creativity and ingenuity, resulting in the realization of novel applications and business outcomes. However, this paradigm shift also brings new challenges and necessitates acquiring additional skills for software developers to fully harness the capabilities of LLM-powered tools. These skills include prompt engineering for software development, structural complexity management, debugging of AI errors, and compliance with ethical guidelines and principles.

University of Missouri–Kansas City (US)
Quality Education
Openalex Percentile: Top 98%
Online Learning and Analytics
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