Abstract

This empirical study examines ChatGPT as an educational and learning tool. It investigates the opportunities and chal-lenges that ChatGPT provides to the students and instruc-tors of communication, business writing, and composition courses. It also strives to provide recommendations. After conducting 30 theory-based and application-based ChatGPT tests, it is found that ChatGPT has the potential of replacing search engines as it provides accurate and relia-ble input to students. For opportunities, the study found that ChatGPT provides a platform for students to seek an-swers to theory-based questions and generate ideas for ap-plication-based questions. It also provides a platform for in-structors to integrate technology in classrooms and conduct workshops to discuss and evaluate generated responses. For challenges, the study found that ChatGPT, if unethically used by students, may lead to human unintelligence and un-learning. This may also present a challenge to instructors as the use of ChatGPT negatively affects their ability to dif-ferentiate between meticulous and automaton-dependent students, on the one hand, and measure the achievement of learning outcomes, on the other hand. Based on the out-come of the analysis, this study recommends communica-tion, business writing, and composition instructors to (1) re-frain from making theory-based questions as take-home as-sessments, (2) provide communication and business writing students with detailed case-based and scenario-based as-sessment tasks that call for personalized answers utilizing critical, creative, and imaginative thinking incorporating lec-tures and textbook material, (3) enforce submitting all take-home assessments on plagiarism detection software, espe-cially for composition courses, and (4) integrate ChatGPT generated responses in classes as examples to be discussed in workshops. Remarkably, this study found that ChatGPT skillfully paraphrases regenerated responses in a way that is not detected by similarity detection software. To maintain their effectiveness, similarity detection software providers need to upgrade their software to avoid such incidents from slipping unnoticed.

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