Running head: RESEARCH PROPOSAL 1
EXPLORING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE
ACADEMIC PERFORMANCE: A STUDY OF BS MARINE
TRANSPORTATION STUDENTS
In partial fulfilment
of the requirements for the subject
NGEC 5: Purposive Communication
Submitted to
Cathyrine B. Homecillo – Fabrero, Instructor
Bachelor of Science in Marine Transportation
College of Maritime Education
Educational Systems Technological Institute – Boac
By
Moreno, Richard L.
Villena, Jorvin
Osinsao, Jhon Renz
Mendeja, Alvin James
Garcia, Jhon Marc
Valenzuela, Jhon Rey
Puertellano, Guernan
Largo, Mark Lloyd
Montellana, Ariel
Orillos, James Yhvan
Rosas, Prince Russel
Lota, Shaolo
Reanzares, John Benedict
Vitor, Victor
Hutalla, Jhon Michael
13 February 2024
RESEARCH PROPOSAL 2
Table of Contents
Introduction ................................................................................................................................ 3
Background and context ....................................................... Error! Bookmark not defined.
Problem statement ................................................................ Error! Bookmark not defined.
Research questions ............................................................... Error! Bookmark not defined.
Relevance and importance of the research ........................... Error! Bookmark not defined.
Literature review ........................................................................................................................ 4
Key concepts, theories and studies ....................................... Error! Bookmark not defined.
Key debates and controversies ............................................. Error! Bookmark not defined.
Gaps in existing knowledge .................................................. Error! Bookmark not defined.
Research design and methods .................................................................................................... 9
Aims and objectives................................................................................................................ 9
Methods and sources .............................................................................................................. 9
Practicalities and potential obstacles .................................................................................... 11
Implications and contributions to knowledge .......................................................................... 12
Practical implications ........................................................................................................... 12
Theoretical implications ....................................................................................................... 12
Reference list ........................................................................................................................... 13
Research schedule .................................................................................................................... 14
Research phase ..................................................................................................................... 14
Objectives ............................................................................................................................. 14
Deadline ................................................................................................................................ 14
RESEARCH PROPOSAL 3
Introduction
The integration of Artificial Intelligence (AI) into education has become a prominent
force, shaping the academic landscape across various disciplines where it become
transformative, raising questions about the impact on students' performance. For all we know,
Artificial intelligence perform different tasks include learning, reasoning, problem solving,
understanding natural language and so much more wherein its aim is to stimulate or replicate
human cognitive functions, enabling machines to carry out complex functions automatically.
With the broaden field of Marine Transportation, Artificial Intelligence become
prevalent in maritime operations. It is important to explore how these advancements in
technologies are incorporated it to the curriculum and also how students adapt to these changes.
This exploration is very essential for assessing the potential effects on the academic
performance of Marine Transportation students in Educational Systems Technological
Institute. Since Artificial Intelligence can analyze vast amount of data on different field of
marine transportation such as oceanography, navigation, marine ecology and others, the
researcher come up with this research topic.
By exploring how Artificial Intelligence technologies are incorporated into their
curriculum and assessing potential correlations with academic performance, this research aims
to contribute or provide insights into the relationship between Artificial intelligence and
academic achievement of Marine Transportation students as well as to determine the impact of
Artificial Intelligence on the students' academic performance.
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Literature review
The beginning of artificial intelligence dates to 1950, when the technology behind it
was invented by Alan Turing, a computer pioneer, who had already previously talked about the
concept of an in telligent machine. In year 1950 Alan Turing did a test known as the Turing
Test, to see whether a computer can think like a human. This test includes a computer, human
interrogator, and a human respondent. The interrogator asks any type of questions to the
computer and the respondent, and based on the answers must then guess which is the computer.
The human respondent must try to help the interrogator make a right guess, but the computer
is allowed to answer in any way it is ca pable to not be identified (Copeland, 2023).
Artificial intelligence (AI) is defined in many different ways; some consider it to be a
kind of invented technology that allows computers and machines to function properly. Some
see it as the machine that replaces human labor to work for men a more effective and speedier
result. Others see this as a system that is capable of accurately interpreting external data,
learning from it and applying these lessons in order to achieve certain objectives and tasks by
means of flexible adaptation (Pallathadka Hrikumar et.al, 2022).
AI researchers have created many tools to solve the most difficult problems in computer
science and other fields. The current AI performance ranges between sub-human, optimal, and
super-human performance. A wide range of tasks can be solved by AI applications including
facial recognition, speech recognition, object recognition, images classification and surpassing
human-level intelligence (Kayid Amr, 2020). AI is also becoming more and more common in
education, with different tools students and teach ers can use for their advantage. AI is
reforming the methods students use for studying. Different study fields can benefit from AI
tools in different ways. These tools can save time, function as a tu tor, help dyslexic students,
assist to write code, and it can even adjust to the student’s learning style. This thesis covers
RESEARCH PROPOSAL 5
also what possible disadvantages and risks there are of AI in education, including ethical
considerations (Nilsone, Amanda Laura, 2023).
When we talk about students’ performance, we usually mean their academic
performance, which includes their performance in a certain course they are enrolled in or a
certain class of students they are part of. But we cannot keep ourselves limited to only the
academic performance of the students, as that is not the only thing that society depends on. It
may be that an academically sound student is of no use to society, whereas an academically
not-so-well student serves his or her society much better. It’s solely because of the personality
the student holds—his attitude, body language, and all (Chatterjee, Rana et al., 2020). Thus,
the personality of a student can be thought of as an important factor we should look for in a
student, and hence, the performance of a student towards her or his personality development
should also be taken into consideration.
One of the key roles of modern educational system is that it creates competences that
allow people to participate in the economic sphere of life. The history of educational systems
is closely linked with the development of the industrial society, and wage labour is still a central
organizing principle in industrial societies and their everyday life. In high-level policy
discussions, education is therefore often understood as a source of employment. Education, in
this interpretation, is a key driver of economic productivity and competitiveness, and
educational policies are framed in the context of economic growth. It is therefore important to
ask also in the context of educational policies how AI will transform work and employment.
For economists, a central question has been whether automation and computerization increase
unemployment. As machines increase (Ikka, T. 2018).
A study conducted by Langin Z. et.al 2023 titled the effectiveness of artificial
intelligence on learning achievement and learning perception: A meta-analysis reveal that AI
had a high effect size on learning achievement and a small effect size on learning perception.
RESEARCH PROPOSAL 6
The effect sizes of 13 moderator variables were analyzed, including sample levels, sample size,
learning domains, learning methods, research design, research settings, intervention duration,
types of organization for treatment, role of AI, areas of AI application, AI software, AI
hardware, and AI technologies. It was found that sample size, sample level, learning domains,
types of organization, roles of AI, and hardware significantly moderated the effectiveness of
AI.
Similarly, Idroes G.m et.,al 2023 conducted similar study about Student Perspectives
on the Role of Artificial Intelligence in Education: A Survey-Based Analysis which reveals
through survey that targeted students from diverse academic backgrounds and educational
levels. The results show that, in general, students have a positive perception of AI and believe
AI is beneficial for education. However, they are still concerned about some of the drawbacks
of using AI. Therefore, it is necessary to take steps to minimize the negative impact while
continuing to take advantage of the advantages of AI in education.
Likewise, a study conducted by Wang 2019 titled Development and validation of an
artificial intelligence anxiety (AIA) scale: an initial application in predicting motivated learning
behavior through analyzing data from the respondents, it reveals that the proposed AIAS has
well-established psychometric properties, which facilitate the work of both AI developers and
practitioners, who are responsible for applying and implementing AI technologies and
products, and scholars and educators involved in developing and testing IS theories that explain
and predict AI adoption behavior. The findings of this study provide a preliminary insight into
the relationship between AIA and motivated learning behavior. However, more research in this
area is required. In order to determine how these concepts are related to each other, other
methods including cross-sectional studies will be useful in terms of analyzing a representative
subset including AIA, learning behaviors and other potential factors on relevant learning
processes at a particular time. The AIAS demonstrates satisfactory reliability and validity
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across various AI technologies/products. Educators, scholars, and practitioners are encouraged
to employ the AIAS in AI and learning environments.
In contrast to the studies conducted by Idroes 2023 and Wang 2019, one of the
technologies that ensure such equality or similarity is digital technologies that are being
introduced into the process of general and vocational training and education. However,
in addition to opportunities, the introduction of these technologies is accompanied by
numerous ethical problems that call into question the economic feasibility of their
widespread and uncontrolled creation and use. Having paid for "education" and having become
familiar with certain knowledge, skills and, even more, "spiritual and moral competencies" in
the course of a "training session" with a digital device of one type or another, human cannot
become a competent student and/or professional, to develop as a person or a subject of
professional-labor or intimate-personal relationships. Undoubtedly, all this is possible if we are
talking about the development of the ability to learn and the development of some other
qualities and skills of a person associated with the experience of using certain devices, with
the culture of their application. But it is impossible if we are talking about the formation
and development of man as a fully functioning being, a subject of culture as a whole. The idea
of comparing human (“robot-proof” subject) to artificial intelligence is interesting in the
context of testing some of its properties, but not interesting in the context of "value
comparison": a person initially cannot be less valuable than the machine he created. A machine,
artificial intelligence exists only as an extension of a person, otherwise, we are talking about
the fact that it exists against a person . the development of artificial intelligence systems is often
carried out by people who have such features of life orientations that direct the development of
these systems towards competition, manipulation, and destruction of a human. It should be
emphasized separately: there is no one artificial intelligence; there are different systems
of artificial intelligence: in terms of level it can be combined into types, just like sociopaths
(Wang et.al, 2022).
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Similar to the study of Wang et.al 2022 titled Unraveling the Complexity: A
DEMATEL Analysis of the Negative Impact of Artificial Intelligence (AI) Adoption among
students in higher education using DEMATEL analysis, the study revealed numerous key
findings that illuminate the complexities of integrating AI in education, with management
consequences. The emergence of privacy and security concerns as a central issue highlighted
the critical nature of solid data protection measures and ethical conduct in relation to artificial
intelligence (Rodzhi Z.2024).
Statement of the Problem
1. What is/are the influence of Artificial Intelligence on the Academic Performance of
Marine Transportation students?
2. What is/are the potential correlations between (AI) exposure and academic
performance?
3. What are the advantage and disadvantage of using Artificial Intelligence on academic
performance?
Significance of the Study
The significance of this study lies in unravelling the influence of Artificial Intelligence
(AI) on academic performance on Marine Transportation students in Educational Systems
Technological Institute. This study is important because it sheds light on how artificial
intelligence (AI) affects student performance in a variety of learning environments. Education
tactics, curriculum development, and the incorporation of technology into teaching techniques
can all benefit from an understanding of how artificial intelligence affects learning results. The
results could influence how educational policies and practices are developed in the future and
help institutions better adjust to how AI is transforming the field of education. Furthermore,
RESEARCH PROPOSAL 9
knowledge gained from this study may help educators and legislators take use of AI's potential
advantages while resolving possible issues for kids.
Research design and methods
This chapter will discuss all of the methodologies included in the entire study. This will
include the place where the study will be conducted, the measures that will be taken during the
study, the study design, the instrument to be used in data collection, as well as the methods to
ensure the validity, and reliability of the instrument.
Research design
This study is a quantitative type of research and will use the descriptive research design
specifically employing the use of survey questionnaires. Based on Research Connections
(2022), descriptive research focuses on describing the characteristics of a population and
answering questions pertaining to a particular population or group. The answer to this research
design was attainable through quasi-experimental and randomized studies and also a variety of
data collection strategies will be used. The method will be applicable in the study because the
researchers will aim to collect and analyze data about the impact of artificial intelligence in
academic performance of Marine Transportation students.
Methods and Sources
Research Instrument
Survey questionnaires are the primary tool that researcher will use. To get the
appropriate data needed, the researchers will create questionnaires with various parts. An
inquiry about the respondents' profiles will be made in the first section. The other component
will be the tool to determine the impact of artificial intelligence on the academic performance
of the students of Educational Systems Technological Institute.
RESEARCH PROPOSAL 10
Data Gathering Procedure
The researchers will make a request letter to the Department Head in order to ask
permission for the data collection. A letter will also send to the respondents to inform them
about the study. In the data collection process, there is an orientation that will be done regarding
the procedures. The questionnaire’s validity will be approved by professionals. The chosen
students will receive the answer sheet to be completed. For an easy approach, the participants
will be selected using stratified sampling.
After gathering all the data, the researchers will tabulate and total the survey with the
help of statistical analysis. The outcome should serve as the foundation for Educational
Systems Technological Institute – Marine Department for the possible interventions regarding
impacts of artificial intelligence on the academic performance.
Sample and Population
This study will use a stratified sampling method that focuses solely on the population of
Educational Systems Technological Institute- first year Marine Transportation students. Since
the researchers are first year Marine Transportation students themselves, they are aware of the
challenges associated with the technological advancement, especially the artificial intelligence
application. With the help of this sampling technique, it allows the researchers to divide the
population into subgroups before selecting a sample from each of them. The study's target
population consists of Marine Transportation students
divided into six (6) sections.
Research Locale
The researchers will conduct the study in Educational System Technological Institute
specifically in the Marine Department building.
RESEARCH PROPOSAL 11
Data Analysis Procedure
The researchers will formulate the questionnaires according to the Statement of the
Problem (SOP). After this, the questionnaires will be distributed using a Google form link.
After the data collection, the researchers will organize the answers of the respondents in a
categorized manner. The researchers categorized and organized the answers with the use of a
table. After organizing, the researchers will analyse the data and will pattern it with the
questions of the SOP. The questions of the SOP will be answered using the answers from the
respondents.
Practical Considerations
Due to the possibility of human error, experimental research is highly subjective. Any
error, random or systematic, can reveal details about the other variables and compromise the
reliability of the study and experiment. Because variables are tightly controlled in experimental
research, unrealistic situations can be produced. As a result, the data may be skewed toward a
desired or favourable outcome, which can be detrimental for the researcher. Additionally,
positive results cannot be obtained outside of the context of experimental research because the
real-life environment is so dissimilar from the lab environment. Testing isolated variables as
part of experimental research is a labour-intensive process. If the product or idea never gets to
market, a significant number of resources are expended, and this expense might not be offset
by consumer sales. If the research is a theory, it may create a false sense of validity and alter
how other people conduct their own research.
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Implications and contributions to knowledge
Finish the proposal by emphasizing why your proposed project is important and what it will
contribute to practice or theory.
Practical Implications
Will your findings help improve a process, inform policy, or make a case for concrete
change?
Theoretical Implications
Will your work help strengthen a theory or model, challenge current assumptions, or create a
basis for further research?
RESEARCH PROPOSAL 13
References
Chatterjee, S., Rana, N., & Dwivedi, Y. (2020). Social media as a tool of knowledge shar-ing
in academia: An empirical study using valance, instrumentality and expectancy
(VIE) approach. Journal of Knowledge Management, 24(10), 2531–2552.
Copeland, B.J. 2023. Artificial Intelligence. Encyclopedia Britannica. URL: https://www.bri
tannica.com/technology/artificial-intelligence/Connectionism. Accessed: 22 April
2023.
Gulzhaina K.K et.al 2023. Ethical Problems of Digitalization and Artificial Intelligence in
Education: a Global Perspective. Institute of Metallurgy and Ore Beneficiation,
Satbayev University.
Idroes G.M et..al 2023. Student Perspectives on the Role of Artificial Intelligence in Education:
A Survey-Based Analysis. Journal of Educational Management and Learning. Vol
1. 8-9
Kayid A. 2020. The role of Artificial Intelligence in future technology. Department of
Computer Science, The German University in Cairo.
Lanqin Zheng, et.al 2023. The effectiveness of artificial intelligence on learning achievement and
learning perception: A meta-analysis, Interactive Learning
Environments, (31):9, 5650-5664
Nilsone, A.L 2023. The impact of artificial intelligence amongst higher education students.
Haaga-Helia University of Applied Sciences 10-12.
Pallathada, Harikumar et,al 2022. Investigating the impact of artificial intelligence in
education sector by predicting student performance. Materials Today (51) 2264-
2267.
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Tuomi, Ikka. 2018. The Impact of Artificial Intelligence on Learning, Teaching and
Education. JRC Science for Policy Report p.17.
Rodzi, Zahari M.d 2024. Unraveling the Complexity: A DEMATEL Analysis of the Negative
Impact of Artifificial Intelligence (AI) Adoption among students in higher
education. Journal Of Internet of things (11) 30-41.
Yu-Yin Wang & Yi-Shun Wang 2022. Development and validation of an artificial intelligence
anxiety scale: an initial application in predicting motivated learning
behavior, Interactive Learning Environments, 30:4, 619-634.
Research schedule
Research phase Objectives Deadline
RESEARCH PROPOSAL 15
