1. Introduction
AIeD (Artificial Intelligence in eDucation) has become a hot topic currently with the launch of an online chatbot tool called ChatGPT [1]. As per [2], “Chatbots incorporate generic language models extracted from large parts of the Internet and enable feedback by limiting themselves to text or voice interfaces”. ChatGPT is based on a pre-trained Large Language Model (LLM) called GPT-3.5 [3]. AIeD is not new and has been around for more than a decade now. However, the new advancement in the field of Artificial Intelligence has made it possible to create tools like ChatGPT, which can convincingly imitate humans when it comes to writing skills [4]. ChatGPT hit 1 million users across the globe within a week [5]. The strengths of ChatGPT include language understanding, human-like conversations, flexibility to tune to a specific language task, speedy responses, and cost-effectiveness [6]. Particularly, for a student in higher education, LLM can assist in writing tasks, and help promote critical thinking and problem-solving skills [7]. The use of AI is inevitable in academia, so we also need to ensure that the students have a good understanding of how the tool can be used such that the students remain competitive when it comes to employability. Particularly, for the student in computer science, it is expected of them that they are aware of recent technology developments and are expected by employers to have a good understanding of their use. More importantly, for computer science students, ChatGPT can generate algorithms and translate them into any programming language of their choice. It can also help with debugging the code. However, it cannot provide code to obtain output for a given input, as it is not a compiler [8]. Furthermore, its performance on natural language-type questions is far superior to questions containing code snippets. It can assist in completing partially written code blocks, but lacks the execution capabilities required to produce the correct output; after all, it is a language model [8]. Likewise, ChatGPT is unable to evaluate a complex math function for a given input [9]. Thus, it is important that the user is aware of its limitations and does not entirely trust the generated output for all types of quarries.
ChatGPT is developed by OpenAI, a non-profit AI research and development organization dedicated to benefiting humanity through advancement in digital intelligence
[10]. OpenAI is striving to create safe Artificial General Intelligence (AGI) that can benefit all of humanity and wants to ensure responsible development, deployment, and use of their models
[11]. Along with ChatGPT, OpenAI also offers a state-of-the-art artificial image generator model named Dall.E 2, which takes a text prompt and turns it into photo-realistic images that have never existed before
[12]. Dall.E 2 can assist users to imitate any artist by creating original, realistic art or can combine concepts, attributes, and styles in the generated images. Since the company is free from financial obligations, it can better focus on a positive impact by developing highly autonomous systems that outperform humans at the most economically valuable work
[13].
ChatGPT is trained to provide detailed responses to instructions in a prompt. ChatGPT is based on the GPT-3.5 series and is regularly updated as more users interact with the tool and provide the system with their feedback
[1]. The capabilities of ChatGPT are showcased in
[14], a paper co-authored by ChatGPT itself, which has outlined the two important benefits of using this tool from the perspective of journalism. First, it helps in creating personalized content for readers based on their interests and preferences, and second, it summarizes a long news article to quickly grasp the key points. Later, a detailed survey is performed by
[4] around the capabilities of ChatGPT in content generation, which is reported to be indistinguishable from the contents produced by humans. As discussed by the writers, the tool can aid the writers to tackle writer’s block and save them time on repetitive tasks. A good example of these capabilities is in the two recent papers published by the same author, in which the author has used the tool to write the paper, and where the author prompts ChatGPT with questions around the topic and presents the responses as part of the publication
[15][16]. Although ChatGPT is capable of producing acceptable research articles in a short time, the originality in the arguments is lacking in these papers. But, the writing structure of a typical research article is well-captured and arguments are presented in an articulated manner, which makes it very convincing for academic writing.
The capabilities of the tool in generating texts have now alarmed research journals. The editorial board of a journal published in Knee Surgery, Sports Traumatology, Arthroscopy (KSSTA), which is a peer-reviewed medical journal, mentions in their guidelines that the authors should not use ChatGPT in their articles submitted to KSSTA. Their guidelines specify that it is currently a preliminary decision but state that if ChatGPT is used in writing a manuscript submitted to a journal then it should be acknowledged
[17]. This certainly has opened a conversation around the use of AI chatbots in research, which needs to be defined while considering good scientific and ethical practices. The International Journal of Research in Marketing (IJRM) has taken a clear stand that they will not accept any submission with ChatGPT or any Generative Artificial Intelligence (GenAI) tools as a co-author
[18] on the grounds of lack of accountability, and will interpret ChatGPT 1:1 response in any manuscript as plagiarism. It is emphasized in
[18] that researchers should be more transparent regarding the use of AI tools in their study.
2. Effect of ChatGPT on Higher Education
2.1. ChatGPT Utilization in Academia
In academia, ChatGPT can be utilized for a diverse range of applications beyond what has been mentioned here. To begin with, it provides valuable support for writing reports, essays, and scientific articles. It can also proofread the provided text for structural, punctuation, and grammatical errors
[19]. Another useful application is acting as a virtual tutor; it can break down a complex concept into an easier-to-understand language
[20][21]. For research projects, ChatGPT can not only aid in literature review but can also generate innovative ideas in brainstorming sessions
[22][23]. In computer science, it can aid students by debugging their code and suggesting programming solutions
[24]. Despite this, if fine-tuned within a specific field, it has the potential to revolutionize automated grading and immediate feedback for essay questions. This is a challenging and time-consuming task, particularly in large modules where grading is handled by multiple markers
[25]. Lastly, if trained on University UPRs (University Policies and Regulations), ChatGPT could thoroughly address student inquiries without human intervention
[26].
2.1.1. Promoting Student Learning
ChatGPT can be useful for students in higher education in several key aspects of their learning. A study performed by
[4] found that ChatGPT can increase student engagement, collaboration, and accessibility, along with facilitating asynchronous communication, feedback, and remote learning. According to
[7], tools like ChatGPT can assist in various subjects by simplifying and contextualizing content, promoting problem-solving skills, and developing analytical and critical thinking. They can also facilitate group and remote learning, empowering learners with disability and assisting in professional training
[6].
All of these applications lean towards the use of ChatGPT for helping students in their learning and it is important for educators to consider how to include ChatGPT in the university curriculum in a way that does not harm and, at the same time, improves learning. The discussion around how to optimally use ChatGPT is an ongoing question and, according to
[6], “the technology behind ChatGPT could potentially be utilized to improve the performance of personalized adaptive learning”. The authors
[6] argue that it is ironic that a tool which can facilitate innovative teaching and learning has caused anxiety among academics.
2.1.2. Enhancing Teaching Strategies
ChatGPT can not only aid students in their learning, but it can also assist tutors and educators in various ways. In
[7], various ways in which educators can leverage this tool in teaching have been outlined. For example, the tool can be positively used in personalized learning, lesson planning, language learning, assessment, and evaluation. It can also assist the student in aspects like professional development, research, writing for seminars, papers, etc.
[6].
Apart from several advantages of employing ChatGPT in teaching, the tool also has various shortcomings. For example, ChatGPT is not as competent in producing text in low-resource languages. As documented in
[27], when they are asked to write about medical problems in the Korean language, the texts that are produced by ChatGPT essays are not comparable to the ones produced by medical students. Another example of the problem that ChatGPT faces in generating the texts is referencing. In these texts, the source of the references is not accurate; in some cases it is made up
[3], or sometimes missing. Because referencing is very important in academic writing, the students still have to find original references to support their arguments
[4]. Another problem with using ChatGPT is, as argued in
[7], that the learners sometimes heavily rely on the AI models to do their tasks, which can impact their critical thinking and problem-solving skills, amplifying laziness and apathy towards their own investigation.
In
[4], several concerns with ChatGPT use regarding academic honesty and plagiarism are raised, and it is suggested that the universities should ensure ethical and responsible use of the tool by developing policies, as well as providing training to staff and students. Their key suggestion is to drop the essay-style assessments in favor of interactive activities (group discussions, presentations, etc.) where students can demonstrate the application of knowledge and skills, or else use real-time invigilated assessments.
To mitigate the issue of academic misconduct in the wake of ChatGPT,
[6] suggests against essay-style assessments. To manage this problem, the authors of the study suggest that the teachers should conduct physical closed-book exams or use surveillance software for online exams. Although, it is usually argued that mastering the skills required for closed-book exams is irrelevant to employability. It is recommended to include digital literacy where AI technology should be part of the curriculum while emphasizing faculty training. It is also suggested that the academic integrity policies should include the use of AI and provide student training on academic integrity
[6].
It is recommended in
[7] that teachers should use LLM-based tools as a complementary supplement for instruction generation, to promote critical thinking and problem-solving skills by incorporating it into the curriculum. They also suggest incentivizing tutors in generating teaching strategies using LLMs, to engage students in the problem-solving process while monitoring and evaluating the use of these tools for any negative impact on learners.
One question regarding the problems that using ChatGPT may cause is why not use something like a plagiarism detection tool to detect the texts generated by ChatGPT? This is a valid question; however, the answer is not straightforward. Turnitin
[28][29] and some other software have been developed to detect plagiarism. The difficulty here is that the texts produced by ChatGPT are original, so it is very hard for the plagiarism detection software to detect them. Although new software may be developed to detect AI-generated texts, because ChatGPT is being improved and learns from experience to generate better and more realistic texts, it is a matter of time before ChatGPT outcompetes these detection tools. As the tools built to detect AI-generated text learn to differentiate between the text generated by humans and those of machines, ChatGPT learns to be more human-like to avoid detection. It is shown in
[30] that the successor LLM model of GPT3.5, called GPT4, outcompeted all of the existing LLMs in many evaluation tasks and it can generate longer sequences of data than GPT3.5. GPT 4 is now available to generate text on the ChatGPT platform as a premium service
[31].