This systematic literature review explores the application of Generative Pre-trained Transformer (GPT) and Large Language Models (LLMs) in academic research, with a specific focus on data augmentation. The review examines 412 scholarly works, selecting 77 contributions that address three critical research questions: (1) GPT in generating research data, (2) GPT in data analysis, and (3) GPT in research design. The study highlights the central role of GPT in data augmentation, encapsulating 48 relevant contributions, and extends to its proactive role in critical data analysis and research design. A comprehensive classification framework is developed, categorizing existing literature into six main categories and 14 sub-categories, providing insights into the multifaceted applications of GPT in research data. The review also compares 54 existing studies, evaluating research domains, methodologies, and advantages and disadvantages, offering practical guidance for researchers integrating GPT into their scholarly pursuits. Despite the benefits, the review acknowledges limitations such as ethical concerns, biases, and hallucinations, emphasizing the need for careful scrutiny and responsible use of GPT in academic research.This systematic literature review explores the application of Generative Pre-trained Transformer (GPT) and Large Language Models (LLMs) in academic research, with a specific focus on data augmentation. The review examines 412 scholarly works, selecting 77 contributions that address three critical research questions: (1) GPT in generating research data, (2) GPT in data analysis, and (3) GPT in research design. The study highlights the central role of GPT in data augmentation, encapsulating 48 relevant contributions, and extends to its proactive role in critical data analysis and research design. A comprehensive classification framework is developed, categorizing existing literature into six main categories and 14 sub-categories, providing insights into the multifaceted applications of GPT in research data. The review also compares 54 existing studies, evaluating research domains, methodologies, and advantages and disadvantages, offering practical guidance for researchers integrating GPT into their scholarly pursuits. Despite the benefits, the review acknowledges limitations such as ethical concerns, biases, and hallucinations, emphasizing the need for careful scrutiny and responsible use of GPT in academic research.