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This systematic review investigates the significant role of ChatGPT in higher education, with a specific focus on its influence on academic writing. Utilizing insights from 17 peer-reviewed articles published between 2022 and 2024, it evaluates ChatGPT's features, advantages, and challenges in assisting both students and educators. ChatGPT enhances efficiency by automating repetitive tasks such as grammar correction, sentence restructuring, and formatting, allowing students to focus on critical thinking and content refinement. Its ability to enhance language, correct grammar, and maintain structural coherence proves especially valuable for non-native English speakers, fostering greater accessibility and fairness in academic writing. Moreover, ChatGPT fosters creativity through brainstorming support, simplifies technical explanations for diverse academic audiences, and enhances iterative learning by providing real-time feedback on coherence, language, and argumentation. The study underscores the risks of bias in AI-generated content and the possibility of worsening educational disparities due to unequal access to advanced AI technologies. Establishing clear institutional policies and ethical guidelines is essential to address these concerns and ensure responsible AI use. The review concludes that ChatGPT is a powerful tool for improving academic writing and learning in higher education. However, its success relies on a balanced integration of AI's capabilities with sound pedagogical practices to uphold academic integrity and encourage independent critical thinking.

This research aims to analyze errors in writing quotations in students' papers from the PGSD Study Program at Medan State University, especially in the paper entitled "Analysis of Teacher Difficulties in Implementing the Problem Based Learning Model in Elementary School Social Sciences Learning". This research uses a qualitative method with a design that prioritizes data collection through document analysis. The main data source comes from the text of the researched papers, with a focus on formatting errors, sources, and citation integrity. The data analysis technique uses the Miles and Huberman model which includes presenting data and drawing conclusions. The research results showed that there were inconsistencies in writing the author's name, the wrong writing order based on the year of publication, and the use of inappropriate punctuation in quotations. These findings emphasize the importance of understanding and applying correct citation writing rules to improve the quality of scientific literature.