INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 190
Chat Generative Pre-Trained Transformer (ChatGPT): Boon or
Bane – A Qualitative Meta-Synthesis
Ella Rose C. Palomar & Elaine B. Sobrevega, MMBM, LPT
College of Business and Information Technology, St. Paul University Iloilo
DOI: https://doi.org/10.51583/IJLTEMAS.2024.130723
Received: 18 July 2024; Revised: 06 August 2024; Accepted: 10 August 2024; Published: 20 August 2024
Abstract: Interest in Artificial Intelligence (AI) has increased dramatically since the launch of ChatGPT (Generative Pre-
trained Transformer) in November 2022. While ChatGPT has captured the imagination of students and educators alike,
several concerns have also emerged (Torrey et al., 2023). In this study, the researcher conducted a qualitative meta-synthesis
that focused mainly to the range of ChatGPT by obtaining interrelated data from peer-reviewed publication or journals
searched through the academic databases and meta-search engines (Google Scholar, JSTOR, EBSCO, and OVID). With the
initial samples of 21 ChatGPT studies, ten (10) were selected based on the inclusion criteria. Conceptual translation was used
to express the research findings. The data from each theme were synthesized and integrated to create a synthesis that
represented the category as a whole. ChatGPT is here to stay, and individuals would undoubtedly use it for the rest of their
lives. Integrating ChatGPT in a variety of settings, including education, particularly in business courses, offers numerous
opportunities to improve learning experiences, personalize instruction, and rethink educators' roles. This change, however,
poses restrictions classified as intrinsic and usage-related issues that make assessments, digital literacy, and ethical
considerations challenging. To realize ChatGPT's full potential in education and overcome these barriers, stakeholders should
develop solutions for ethical and equitable adoption in a naturally based and proactive approach.
Keywords: Business course, ChatGPT (Generative Pre-Trained Transformer), Education, Peer-reviewed publication or
journals, Meta-synthesis
I. Introduction
In 1950, Alan Turing proposed the Turing Test to assess artificial intelligence, aiming to make computers indistinguishable
from humans in conversation. Despite successes like Eliza, these programs often prioritize passing exams over genuine
intelligence. Recent advancements, such as OpenAI's ChatGPT, have addressed conversational limitations in chatbots.
Released in 2022, ChatGPT stands out for its consistent and versatile responses. In education, particularly business courses,
its potential impact has sparked research interest, with a focus on curriculum design implications. While existing studies offer
general insights, this research aims to fill a gap by conducting a meta-synthesis to assess ChatGPT's specific benefits or
drawbacks in the context of Business Administration courses at St. Paul University Iloilo.
II. Methodology
This study utilized a qualitative meta-synthesis design that is a contemporary development in qualitative inquiry that
enhances the contribution of qualitative results to develop a more formalized knowledge (Zimmer, 2006). Atkins et al.
(2008) added that qualitative meta-syntheses enhance understanding by integrating diverse qualitative studies, expanding
comprehension of a phenomenon and its theoretical implications. Clemmens (2003) emphasizes that meta-synthesis goes
beyond summarization, aiming to provide fresh interpretations of primary study findings. It involves reconceptualizing and
interpreting these findings to generate insights that surpass those derived from individual studies, leading to a nuanced
perspective on critical variables within the studied theme or phenomenon.
The research primarily took place at St. Paul University Iloilo's University Library, sourcing data from reputable scholarly
databases and meta-search engines, including Google Scholar, JSTOR, EBSCO, and OVID. Strictly relying on legal and
peer-reviewed publications, data collection and synthesis occurred in May 2023, followed by the analysis, which extended
from May 2023 until the study's conclusion. This study abstained from participant involvement, relying solely on qualitative
insights synthesized from related case studies and peer-reviewed articles obtained from scholarly databases. The
comprehensive (representative) sampling approach was employed to establish the study's sample. Rather than amalgamating
intent, the research justified its methodology by integrating data from distinct yet related qualitative studies with interpretive
focus, aiming to explore the entire significant phenomenon of ChatGPT. The selection criteria for qualitative findings
encompassed aspects such as research design, academic peer-review status, relevance to investigating ChatGPT, primary data
utilization, recognized qualitative methods, English publication, and recency within the last five (5) years to ensure
contemporary insights.
In the course of this qualitative study, Noblit and Hare's seven-phase combined methodological model was systematically
employed. Phase 1 involved the identification of the phenomenon of interest, aimed at contributing scientifically to the extant
knowledge. Subsequently, Phase 2 focused on the conceptual relevance, entailing a comprehensive search for pertinent
studies across various databases and meta-search platforms. Phase 3 necessitated meticulous reading and re-reading of
selected ChatGPT studies, informing the extraction of pertinent data and methodological considerations. Phase 4
encompassed the intricate process of determining inter-study relationships by identifying and grouping key themes. The
ensuing Phase 5 involved the translation of studies into one another, facilitating the comparison of similarities and
differences. In Phase 6, higher-level interpretation occurred, yielding new understandings through the synthesis of translated
themes. The researcher, in Phase 7, further synthesized these interpretations to construct a cohesive line of argument or
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 191
synthesis, encapsulating the entire thematic category. The resultant findings, comprising conclusions, interpretations, and
conceptual models, were disseminated through publication in scientific journals and monographs during the conclusive stage
of the meta-synthesis process, facilitating knowledge transfer and ensuring methodical adherence to the prescribed
methodological model. This systematic adherence aimed to effectively synthesize existing works, uncovering transcendent
concepts and arguments.
III. Results and Discussion
The researcher meticulously devised inclusion and exclusion criteria to systematically discern and categorize the relevance of
data, ensuring the acquisition of reliable and high-quality information for the study. Each information source underwent a
thorough analysis based on the following criteria:
1. Qualitative research design.
2. Academic and peer-reviewed publication.
3. Investigation, exploration, and experiences related to the phenomenon of interest (ChatGPT) and its context.
4. Utilization of primary data.
5. Employment of recognized qualitative methods for data collection.
6. Publication in the English language.
7. Temporal limitation to the last five (5) years.
The acquired data were securely stored on a designated Google Drive within the College of Business and Information
Technology (CBIT), accessible only through encrypted passwords provided to the faculty, researcher, and research adviser.
Distinct codes were assigned to each published and peer-reviewed publication.
Table 1. Inclusion and exclusion criteria for literature search
Author
Step 1
Step 2
Step 3
Step 4
False
Positive
Quantitati
ve
Illustra
tive
Source
Year
Publish
ed
Publication
Type
Decision
Haleem, A.,
et al
Elsevier
2023
Research
Report
Included
Williams, A.
University of
Plymouth
2023
Journal
Included
Nguyen, K.
Irreleva
nt
Excluded
Debby, R.E.,
et al
University of
Plymouth
2023
Journal
Included
Rampton, J.
Quantitati
ve
Excluded
Duckworth,
A., & Ungar,
L.
Irreleva
nt
Excluded
Trust, T., et
al
CITE
(Contemporary
Issues in
Technology and
Teacher) Journal
2023
Research
Report
Included
Sohail, S.S.,
et al
SSRN (Social
Science
Research)
2023
Research
Report
Included
Rathore, B.
Eduzone
Multidisciplinary
Journal
2023
Journal
Included
Firat, M.
Quantitati
ve
Excluded
George, S.
Revie
Excluded
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 192
w
Awasthi,
B.A.
PUIIJ (Partners
Universal
International
Innovation
Journal)
2023
Journal
Included
Lund, B.D.,
& Wang, T.
Revie
w
Excluded
Shoufan, A.
Quantitati
ve
Excluded
Feller, B.
Quantitati
ve
Excluded
El Baz, D.
Quantitati
ve
Excluded
Huang, K.
Quantitati
ve
Excluded
Budzianowki
, P., & Vulić,
I.
Revie
w
Excluded
Kokku, R. et
al
International
Society of the
Learning
Sciences
2018
Conference
Paper
Included
López-
Meneses, E.,
et al
MDPI
(Multidisciplinar
y Digital
Publishing
Institute)
2023
Research
Report
Included
Lo, L.
MDPI
(Multidisciplinar
y Digital
Publishing
Institute)
2023
Journal
Included
Table 1 delineates the applied Inclusion and Exclusion Criteria. An initial screening resulted in the exclusion of two (2)
ChatGPT articles deemed false positives due to their irrelevant scope for the meta-synthesis. The remaining studies were
categorized into quantitative, qualitative, or illustrative studies (conceptual work or review articles). Adhering to qualitative
meta-synthesis best practices, quantitative and illustrative studies were excluded. With a focus on exploring ChatGPT's
implications in business courses, the ten (10) remaining qualitative case studies underwent screening to ensure they were
sourced from academic databases and meta-search engines, specifically addressing ChatGPT's opportunities, challenges,
implications, and recommended improvements or actions. All qualitative case studies successfully passed the screening
process. From the initial sample of 21 ChatGPT studies, ten (10) were judiciously selected for inclusion in this meta-
synthesis.
The research endeavor, titled "ChatGPT: Boon or Bane — A Meta-Synthesis," was conducted with the primary objective of
discerning the implications of ChatGPT, evaluating its potential benefits or disadvantages. Data collection transpired
diligently from May 4, 2023, to May 12, 2023, adhering rigorously to ethical norms throughout the process. Subsequent to
this, Noblit and Hare's Seven-Phase Process was systematically employed, delineating the comprehensive approach to
obtaining qualitative case studies pivotal for the meta-synthesis. The process is expounded below:
1. Phenomenon Identification: The researcher initiated the study by formulating crucial research questions pertaining
to the phenomenon of interest, i.e., ChatGPT. These inquiries, designed to strike a balance between broad interest
and manageable scope, guided subsequent investigations.
2. Inclusion and Exclusion Criteria: Rigorous criteria were established to discern relevant research for inclusion,
guided by the centrality of ChatGPT to the qualitative method. In alignment with the study's focus on the
implications of ChatGPT in Business courses, criteria encompassed challenges, opportunities, curriculum design
implications, and recommended improvements or actions. Qualitative studies in English published on or after 2022
were deemed pertinent, considering the evolving nature of ChatGPT.
3. Database Searches: A thorough search yielded twenty-one (21) ChatGPT studies within the education and business
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
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course domain. After screening, ten (10) qualitative studies met the criteria, as detailed in Table 1.
4. Active Reading: This phase involved meticulous reading and re-reading of each acquired study, characterized by
active engagement to appraise, identify, extract, organize, and compare information. Extracted data were
systematically, with subsequent categorization through coding.
5. Thematic Analysis: Key concepts were classified into distinct categories, namely benefits, opportunities,
challenges, implications, and recommended improvements or actions, as outlined in Tables 2. The researcher
scrutinized themes, discerning correlations to develop final categories for detailed description and transparency in
the process.
6. Conceptual Translation: Employing conceptual translation, the researcher translated essential themes into the
context of each study, enhancing the interpretative depth (Cochrane, 2017). High-level interpretation ensued,
wherein the researcher synthesized data across themes to construct a cohesive line of synthesis reflecting the
overarching category. This facilitated the development of conceptual models based on literature review and meta-
synthesis.
7. Emergent Themes: In the conclusive phase of synthesis, the researcher, guided by judgment and insights,
cultivated final emergent themes, as documented in Table 2. This subjective phase encapsulated the culmination of
the meta-synthesis, integrating findings and insights derived from the selected articles.
This comprehensive dissemination strategy also serves as an evaluative analysis of internal components of innovation,
furnishing educational professionals at St. Paul University Iloilo's College of Business and Information Technology with
insights conducive to formulating a well-rounded curriculum design, thereby ensuring the production of globally adept
graduates. Simultaneously, the amassed data from this study can potentially serve as a foundational resource for future
researchers, contributing substantively to informational pursuits within the academic domain.
Table 2. Thematic Analysis of ChatGPT in Education
CATEGORY
INITIAL THEMES GENERATED
FINAL EMERGENT THEMES
AUTHORS
Benefits
● Improved Learning Outcomes:
Enhanced understanding retention
of material.
● More Interactive Experiences:
Increase engagement through
interactive tools.
● Enhanced user experience:
Personalized feedback and support.
● Enhanced Learning
Experience: Overall
improvement in student
engagement and learning
outcomes through interactive
and personalized learning
tools.
Haleem A., et al
William, A.
Trust, T., et al
Rathore, S.S., et al
Awasthi, B.A.
Kokku, R., el al
Lo, L.
Opportunities
● Enhanced Engagement: Greater
student participation and interest in
learning.
● Personalized Learning: Tailored
educational experiences based on
individual needs.
● Greater Accessibility to
Resources: Access to resources
and support beyond traditional
classroom settings.
● Efficient Troubleshooting: Quick
solution for common issues
● Enhanced Learning
Experience: Increases
engagement and personalized
support.
● Access to Resources: Better
availability of educational
materials and support.
Haleem A., et al
William, A.
Debby, R.E., et al
Rathore, S.S., et al
Awasthi, B.A.
Kokku, R., el al
Challenges
● Privacy Concerns: Issues related
to data security and user privacy.
● Technical Issues: Problems such
as system failures and usability
issues.
● Technical Difficulties:
Challenges with integrating
technology into existing systems.
● Bias in Responses: AI responses
may reflect or perpetuate biases.
● Over-Reliance on AI:
● Technology Integration
Issues: Difficulties
integrating AI tools into
existing educational
framework.
● Bias and Technical
Challenges: Concerns over
AI biases and technical
limitations affecting
effectiveness.
Haleem A., et al
Debby, R.E., et al
Trust, T., et al
Sohail, S.S., et al
Rathore, S.S., et al
Awasthi, B.A.
López-Meneses, E., et al
Kokku, R., el al
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Dependence on technology
potentially reducing critical
thinking
Lo, L.
Implications
● Need for Better Integration into
Curricula: AI tool must align
with educational goals.
● Potential to Transform Teaching
Methods: AI could significantly
change traditional teaching
approaches.
● Impact on Decision-Making:
Influence on how educational
decisions are made.
● Curricular Integration:
Ensuring AI tools are
effectively incorporated into
teaching strategies.
● Transformative Potential:
The ability of AI to redefine
teaching and learning
processes.
William, A.
Trust, T., et al
Sohail, S.S., et al
Rathore, S.S., et al
Awasthi, B.A.
López-Meneses, E., et al
Lo, L.
Recommended
Improvement or
Actions
● Increase Teaching Training:
Professional development to better
utilize AI tools.
● Improve Privacy Measures:
Strengthening data Protection
protocols.
● Invest in Advanced Technology:
Upgrading to more sophisticated
AI Systems.
● Address Bias Issues:
Implementing measures to reduce
AI bias.
● Regular Updates: AI Algorithms
current and effective.
● Professional Development
Needs: Enhancing teacher
skills for effective use of AI.
● Data Security Measures:
Implementing robust privacy
and security practices.
● Algorithm Updates:
Ensuring continuous
improvement and relevance of
AI tools.
Haleem A., et al
Trust, T., et al
Sohail, S.S., et al
Rathore, S.S., et al
Awasthi, B.A.
López-Meneses, E., et al
Lo, L.
Table 2 presents a comprehensive synthesis of data obtained through extensive literature searches on ChatGPT's impact in
various educational realms, particularly business courses. The researcher's nuanced understanding highlights ChatGPT as a
transformative innovation, sparking debates on its educational and societal implications. Thematic content analysis
underscores its potential for personalized learning and advanced writing support, yet acknowledges inherent risks like
misinformation and bias. Aligning with Kranzberg's perspective, the study emphasizes that technology, including ChatGPT,
is not inherently good or bad but necessitates a reflective examination of its integration into daily professional practices. The
enduring presence of ChatGPT urges stakeholders to proactively educate themselves on its moral and ethical use,
acknowledging both benefits and challenges in its integration into higher education and workplaces.
The incorporation of AI into educational environments holds transformative potential, offering significant enhancements to
student engagement, personalized learning experiences, and access to a broader range of resources. AI tools can improve
learning outcomes by tailoring educational content and support to individual needs, thus fostering a more interactive and
responsive learning environment. However, realizing these benefits involves addressing several critical challenges. Effective
integration of AI into existing educational frameworks presents difficulties, including alignment with current curricula and
overcoming technical limitations. There are also concerns about AI biases, which can affect the fairness and accuracy of the
educational experience. To mitigate these issues, educational institutions must develop robust strategies for incorporating AI
in a way that complements rather than disrupts established teaching practices. Moreover, the success of AI in education
depends on continuous advancements in technology, necessitating regular updates to algorithms to maintain relevance and
effectiveness. Data security is a paramount concern, requiring stringent measures to protect sensitive educational information
from breaches and misuse. Professional development for educators is crucial, as teachers need to acquire new skills and
knowledge to effectively utilize AI tools in their teaching. This ongoing training is essential to ensure that AI integration is
both effective and ethically sound. In summary, while AI has the potential to redefine educational processes and enhance
learning experiences, its successful implementation hinges on addressing integration challenges, mitigating biases, ensuring
data security, and fostering continuous professional development for educators. Balancing these factors is key to harnessing
AI’s transformative power in education.
IV. Conclusion
The omnipresence of ChatGPT is undeniable, destined to be an enduring presence in the lives of individuals. Its integration
across diverse domains, particularly in education, offers myriad opportunities to enhance learning experiences, customize
instruction, and redefine the roles of educators. However, this transformative transition is not without constraints, manifesting
as intrinsic and usage-related challenges that impede assessments, digital literacy, and ethical considerations. Overcoming
these barriers and formulating ethical solutions is imperative for unlocking the full educational potential of ChatGPT. To
propel the comprehensive utilization of ChatGPT in education, addressing these impediments is paramount. Future research
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endeavors should concentrate on exploring the diverse applications and implications of ChatGPT in educational settings.
Additionally, efforts should be directed toward devising effective frameworks that seamlessly integrate AI into curricula,
evaluation practices, and instructional methodologies. While the thematic content analysis conducted in this study offers
valuable insights, the landscape of future research could benefit from a broader spectrum of qualitative and quantitative
methodologies. This would deepen our understanding of how ChatGPT influences the instructional process. This study
underscores the groundbreaking prospects AI technologies like ChatGPT hold for students and universities. It underscores the
necessity of mitigating potential risks and unintended consequences, emphasizing the imperative of ongoing discourse and
research to ensure the judicious integration of ChatGPT in education. Furthermore, this research advocates for continued
exploration and development to fully harness ChatGPT's vast potential across diverse application domains, offering both
scholars in the field and users a richer understanding of its capabilities.
V. Recommendation
In addressing the integration of ChatGPT within higher education, various responses have emerged, ranging from strict
restrictions to its inclusion in curricula. A nuanced approach is advocated, moving beyond a policy focused on detecting
academic misconduct. The researcher proposes a student-centric paradigm for teaching and learning assessments, aligning
learning objectives, pedagogical approaches, and assessments constructively. The following preliminary recommendations
are outlined for educators, students, and higher education institutions:
Recommendations for Educators:
1. Design assessments fostering creative and critical thinking, avoiding overly standardized assignments.
2. Incorporate in-class assessments, presentations, digital forms, and activities promoting social and critical thinking
skills.
3. Implement authentic assessments reflecting real-world scenarios, testing students' skills and knowledge in
meaningful contexts.
4. Foster an environment valuing students' voices and opinions, emphasizing authenticity in assignments.
5. Encourage the use of creative learning experiences to motivate students and provide a deeper understanding.
Ideally, educators should cultivate an environment where students actively engage in their learning, recognizing the intrinsic
value of the learning process.
Recommendations for Students:
1. Familiarize themselves with academic integrity policies and understand the repercussions of academic misconduct.
2. Enhance digital literacy, master AI tools like ChatGPT to bolster employability.
3. Utilize ChatGPT as a tool to improve writing skills and generate ideas rather than resorting to text duplication.
4. Exercise critical judgment, use high-quality sources, and discern misinformation.
5. Cultivate extensive reading habits to enhance critical and creative thinking.
6. Acquire skills in using AI language tools like ChatGPT to address real-world problems.
Recommendations for Higher Education Institutions:
1. Integrate digital literacy education into the curriculum, incorporating AI technologies such as ChatGPT.
2. Avoid creating an environment where faculty is overburdened, hindering student engagement and motivation.
3. Conduct faculty training on AI tools, specifically ChatGPT.
4. Provide academic integrity training for students.
5. Ensure curriculum coherence and relevance to avoid student disengagement.
6. Update academic integrity policies and honor codes to encompass the use of AI tools.
7. Develop clear guidelines for the ethical use of ChatGPT in learning and teaching.
8. Encourage, support, and disseminate research on ChatGPT's impact on learning and teaching.
These recommendations aim to explore the multifaceted dimensions of learning, encouraging individuals to become reflective
and innovative thinkers in the digital era.
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