In November 2022, OpenAI unveiled ChatGPT – an innovative generative language AI system capable of engaging in sophisticated, human-like conversations. This development has sparked concerns regarding the potential misuse of ChatGPT by students who may exploit its capabilities to craft essays or fulfill coursework assignments, evading easy detection (e.g., Cotton et al., 2023; Dehouche, 2021). Indeed, preliminary reports indicate that essays or exam responses generated using ChatGPT can attain a level of quality that aligns with university assignment standards (Choi et al., 2023; Malinka et al., 2023). This poses significant challenges for higher education. As outlined by Rudolph et al. (2023), educators are particularly apprehensive that ChatGPT could render traditional essay assessments obsolete, allowing students to "outsource" their writing tasks to AI. Nevertheless, the adoption of AI for assignments is not a foregone conclusion. Informal discussions with students reveal varying levels of skepticism towards AI, with some believing that utilizing the tool may not necessarily lead to improved grades and that overreliance on it could potentially dull their academic skills. Historical evidence suggests that the mere possibility of students resorting to cheating in assignments does not guarantee widespread misconduct, with prevalence rates differing across studies (e.g., Haney & Clarke, 2006; Whitley, 1998). Additionally, prevalence varies across assessment types, cheating methods, and the means employed to detect dishonesty. For example, Honz et al. (2010) demonstrated that the prevalence of cheating on examinations was higher (68.4%) than for take-home tests (59.5%) and reports (44%). Newton (2018) reported the prevalence of "contract cheating," where students enlist someone else to complete their work (Clarke & Lancaster, 2007), as low as 3.52% among 54,514 students. None of these prevalence rates reaches 100%, highlighting that not every student would engage in cheating under identical circumstances.
Project-based learning, recognized widely as an effective educational methodology fostering critical thinking, problem-solving skills, and collaborative abilities among students, faced intricate challenges in successful management and completion within an educational context for both educators and students. In recent years, the integration of Artificial Intelligence (AI) technologies in education emerged as a transformative force, offering innovative solutions to address these challenges and enhance the learning experience.
This experimental research delved into the role of AI in education, specifically exploring its potential to facilitate and augment project-based learning. The study focused on the deployment of an AI-driven project completion support system designed to assist students in various aspects of project work. The objective was to assess the impact of AI on critical elements such as time management skills, student engagement, and overall academic performance within a carefully controlled educational environment.
As educational landscapes underwent dynamic shifts driven by technological advancements, the incorporation of AI held great promise for revolutionizing traditional teaching and learning methods. The ability of AI to process vast amounts of data, adapt to individual learning needs, and provide real-time feedback positioned it as a valuable tool in the educational arsenal.
This research aimed to contribute empirical evidence to the ongoing discourse on the integration of AI in education, with a specific focus on its influence on project completion—a cornerstone of experiential learning.
A) The study is guided by three key hypotheses
Hypothesis 1: The implementation of an AI-driven project completion support system will lead to a substantial improvement in students' time management skills.
Hypothesis 2: The implementation of an AI-driven project completion support system will result in a substantial increase in student engagement.
Hypothesis 3: The implementation of an AI-driven project completion support system will have a pronounced positive effect on students' academic performance.
These hypotheses serve as the foundation for a comprehensive investigation into the multifaceted impact of AI in educational project work. The research aims to unravel the nuanced ways in which AI technologies can contribute to the efficiency and effectiveness of project-based learning, ultimately enriching the educational experience for students.
B) To achieve the overarching aim of evaluating the impact of AI on project work in education, the study delineates the following specific research objectives
Objective 1: To assess the impact of an AI-driven project completion support system on students' time management skills.
Objective 2: To examine the influence of the AI system on students' engagement levels.
Objective 3: To determine the effect of the AI-driven support system on students' academic performance.
Objective 4: To compare the performance and engagement levels of students using the AI system (Experimental Group) with those not using it (Control Group).
These objectives serve as a roadmap for systematically investigating the potential benefits of integrating AI into educational settings, with a focus on project-based learning. The study employs a rigorous methodology, including participant randomization and a range of data collection methods, to ensure the reliability and validity of the findings.
In the subsequent sections, the research methodology, results, and discussion has presented to shed light on the intricate dynamics of AI's impact on time management, engagement, and academic performance within the context of project-based learning. The ultimate goal is to contribute meaningful insights that inform educators, policymakers, and stakeholders about the transformative potential of AI in shaping the future of education.