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Quantifying the Influence of Artificial Intelligence Dependency on
Computer Engineering Students in Bulacan State University
Lech Walesa M. Navarra
1
, Hanna Larissa Marcelo
2
, John Rosewell Borromeo
3
123
College of Engineering/Bulacan State University, Philippines
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000541
Received: 20 October 2025; Accepted: 30 October 2025; Published: 18 November 2025
ABSTRACT
Artificial intelligence (AI) is rapidly transforming education, with tools like ChatGPT offering instant
solutions and explanations. This study aims to investigate the growing reliance on AI among computer
engineering students at Bulacan State University exploring the extent of this dependency and its factors
influencing their academic performance. The study of of Liu and Wang showed that the application and
merging of AI to engineering education is essential for managing innovation, strategic thinking and
multidisciplinary skills. The study also proved that the emergence of AI boosts the increase of publication of
papers related to engineering education then stated that AI is already starting to mold the change the way
engineering education is going to be and its significant impact to colleges and universities. Utilizing a
quantitative approach with a descriptive method, the research surveyed thirty (30) 3rd Year computer
engineering students during the Second Semester of Academic Year 2023 2024. The findings reveal a high
level of AI dependency with a mean score of 3.5 on a 5-point Likert scale. The research concludes that a
significant portion of Bulacan State University’s computer engineering students heavily rely on AI for
academic support. Time constraints, perceived academic benefits, accessibility, and the rising trend of AI use
were identified as key influencing factors. Furthermore, a correlation between students' AI reliance and their
academic achievement was observed. Based on these findings, the study recommends strategies to address this
issue, including improved time management support for students, integration of AI education into the
curriculum, and development of new learning materials that equip students to navigate the challenges and
opportunities presented by AI in the field of computer engineering. By proactively preparing its students for
the evolving technological landscape, Bulacan State University can ensure its computer engineering program
fosters responsible development and utilization of AI for the benefit of society.
Keywords: Artificial Intelligence, ChatGPT, Dependency, educational context, academe support.
INTRODUCTION
The increasing integration of Artificial Intelligence (AI) within educational context is causing a fundamental
change on how the learning environments function. Several kinds of AI technology are used in this field
including plagiarism checkers, paraphrasing tools, and the most popular, the ChatGPT. These tools are capable
of generating answers almost instantly, whether they are writing an essay, creating a summary, generating a
code for a program, or explaining difficult math problems. Students were suddenly granted access to new,
powerful technologies. The use of artificial intelligence has advantages and problems, particularly among
students. It gives an optimal method to problem solving as well as step-by-step answers, which is extremely
important in terms of improving the quality of learning and education. While this integration offers efficiency
and innovation, it also raises questions about the potential drawbacks and challenges associated with an
overreliance on these technologies. Local survey showed that 83% of students rely on AI such as ChatGPT in
order to provide answers for their inquiries. A result such as that is alarming in terms of progressive
development in our society due to the majority of students’ dependency on AI.
Despite all the drawbacks of using AI, it is empirically true that with proper usage, especially in the field of
engineering education, may create a greater impact in terms of accuracy, reliability and lessen the form of bias,
misinformation, and data gathering malpractice (Johri, 2023). The recent popularity and reliability of
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
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generative AI applications and web sites like ChatGPT shows a new era in terms of learning, understanding
and developing knowledge in the field of engineering education. But to be able to grasp this, the addition of
human touch and ethical use of AI is strictly needed. These may help and support the educations and
pedagogy for Filipino learners.
In a study of Liu and Wang (2025), The application and merging of artificial intelligence to engineering
education is quite essential for managing innovation, strategic thinking and multiple interdisciplinary skills up
to this date. In their study, it was proven that from 2018 to 2023, there was a significant increase of
publication related to engineering education and suggests it marks the new era for creating various researchers
in that field making the use of AI more relevant. Data mining, machine learning and block chain helps
researchers find better, more reliable and secure sources of information. These evolutions proved to be very
beneficial where information is abundant but lacks reliability and trust.
Another study from Nuñez (2020) supported the aforementioned statement above. He stated that artificial
intelligence is already starting to mold and change the way engineering education and system are conceived.
More studies and researches achieved its goals due to the use of AI specially in both technical and theoretical
manner. The study also analysed the potential impact of the use of artificial intelligence in improving the
overall operation of schools, colleges and universities since AI was able to handle vast amounts of data
simultaneously.
The researchers aim to address the challenges posed by the growing reliance on AI among computer
engineering students at Bulacan State University. The research entitled “Quantifying the Influence of Artificial
Intelligence Dependency on Computer Engineering Students in Bulacan State University” seeks to explore the
extent to which AI is utilized and reasons behind this dependency.
Objectives of the Study:
To be able to identify to what extent computer engineering students rely on artificial intelligence
technologies in their academic pursuits
To be able to identify the factors influencing the dependancy of computer engineering students to AI.
Identify how does the level of dependency on artificial intelligence among computer engineering students
affect their academic performances
METHODOLOGY
Research Design
For the research design of the study, it used the mixed method type wherein the quantitative research design, it
emphasizes objective measurements, statistical, mathematical, or numerical analysis of data collected through
the research instrument used. Additionally, according to Dr. McLeod (2019), while in the quantitative research,
it is a process of objectively collecting and analyzing numerical data to find patterns and averages, make
predictions, test causal relationships, and generalize results to wider populations. In quantitative analysis, the
researchers respond to the research questions by determining the trend of individual responses and noting how
the trend differs. The descriptive method of analysis was used in the study. According to McCombes (2023),
descriptive research focused on providing accurate and systematic descriptions of populations, situations, or
phenomena. It can answer what, when, and how questions, but not why. It is also the approach that aims to
understand the underlying reasons about a certain topic.
Participants and Sampling Technique
For the population, sample and location of the study, it was conducted in order to quantify the dependency on
artificial intelligence of Computer Engineering students in Bulacan State University. The population of the
study consisted of thirty (30) 3rd year students enrolled during the 2nd Semester of Academic Year 2023-
2024. This sample was obtained from three sections of the Computer Engineering department where ten (10)
students per section were chosen as respondents. The sampling technique used in this study is simple random
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
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sampling. Simple random is a technique in which the researchers select a random subset of a bigger group or
population. It gives each member of the group an equal probability of being selected. This is often used in
statistics to generate a sample that is representative of the wider population (Horton, 2024). Research
Instrument In the present study, the researchers used an online survey questionnaire entitled “Quantifying the
Influence of Artificial Intelligence Dependency on Computer Engineering Students in Bulacan State
University” via Google Forms as the main instrument for data collection. The answers provided by the
respondents in the said questionnaire will be processed and statistically analyzed in order to provide a
graphical representation of the results. The researchers gathered all of the insights of the respondents with
different demographic profiles in order to seek answers with regards to the study.
Data Gathering Procedure
The researchers had allotted vigorous time, effort, and cooperation in developing and verifying the
questionnaire so as to serve its intended respondents. The questionnaire consisted of eight (8) statements which
were related to determining the students’ dependency on AI. For the factors influencing their dependency, six
(6) statements were rated by respondents. The last section of the form consists of a question indicating their
general-weighted average (GWA) for the last semester. In the survey questionnaire, 5-point Likert scale was
used to determine how the respondent agreed or disagreed in the question statement. The researchers began the
process of collecting data by distributing questionnaires to the 30 respondents online through Facebook
Messenger. The data will be automatically collected after the respondents have answered. All the data gathered
from this survey questionnaire were tallied and computed for interpretation. The interpretation served as the
basis to determine the students’ dependency on AI. Data Processing and Statistical Treatment The data
gathered from the study were presented in tabular forms. These served as the basis of presenting the results of
the analysis. Appropriate statistical treatments were used to analyze the data. For this study, responses that are
accumulated through the surveys will be statistically analyzed using mean, frequency, and percentage
distribution used to determine and to see the differences gained in terms of the results of computer engineering
students’ dependency on AI technologies in their academic pursuits and factors influencing their dependency.
Data Analysis Procedure
The method used in this research is “Descriptive Method” since this aims to describe the interconnection of the
two variables in conflict with the intervening variable. The method used in gathering data is random sampling
method which is further elaborated at the respondents and sampling section wherein, each the respondents are
picked randomly giving them equal probabilities from the selected sample size with a total population of 30.
Furthermore, the result will then be interpreted in accordance with the three variables that were mentioned and
provide some sort of guidelines in answering the questions in the Statement of the Problem that will determine
the hypotheses that were used. Lastly, the mean scores of the test were analyzed using the following scale
shown in Table 1 titled “Levels of the Students’ Dependency on AI”. The factors influencing their dependency
can also be interpreted using this table.
Furthermore, the use of mean, median and mode is needed in order to get the quantitative values needed in
order to get an interpretation based of the answers of the respondents to the questionnaire.
Ethical Considerations
To ensure the confidentiality of the respondents, aliases and codes will be shown instead of their actual
names. Also, the online form that submitted by the respondents does not include their names or
private/sensitive information. Lastly, all the respondents shall be informed about where their responses will
be used, as such, will be solely on this study.
Table I Level Of Students’ Dependency On Artificial Intelligence
Mean Scores
Classification
1.00 – 1.56
Very Low
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
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1.57 – 2.42
Low
2.43 – 3.28
Average
3.29 – 4.14
High
4.15 – 5.00
Very High
Mean = Sum of all values / Total number of values
Median = Middle value
Mode = Most common value
RESULTS AND DISCUSSION
Table Ii Mean And Interpretation Of Specific Question 1
Dependency on AI Statements
Mean
1. I will use AI as an academic helping tool
4.13
2. I will rely on AI-based code generation and
optimization for my programming
assignments
3.23
3. I utilize AI-assisted debugging tools to
identify and fix errors in my code.
3.73
4. I use AI-powered tools for circuit
simulation and analysis
2.93
5. I will ask AI to generate sentences of
paragraphs
3.37
6. I will ask AI to paraphrase my essays
4.07
7. I rely on AI-powered documentation
generation
2.8
8. I believe AI technologies can improve my
problem-solving skills in computer
engineering.
3.73
Overall
3.5
Table II shows the results of the students’ dependency on AI using mean. Data gathered from the survey
questionnaires are observed, verified and made into tabular form for further interpretation and analyzation.
Result shows that the respondents have high level of dependency of AI with the mean score of 4.13 in the
statement “I will use AI as an academic helping tool.”, average level with the mean score of 3.23 in the
statement “I rely on AI-based code generation and optimization for my programming assignments.”, high with
a mean score of 3.73 in the statements “I utilize AI-assisted debugging tools to identify and fix errors in my
code.” and “ I believe AI technologies can improve my problem-solving skills in computer engineering.”
respectively, average level with means of 2.93 in the statement “ I use AI-powered tools for circuit simulations
and analysis.”, high level with the mean of 3.37 in the statement “I will ask AI to generate sentences or
paragraphs.”, high with the mean of 4.07 in the statement “I will ask AI to paraphrase my essays.” and also
Average level with mean of 2.8 in the statement “I rely on AI powered documentation generation for my
technical reports or project presentations.”. The overall AI dependency level of computer engineering students
in Bulacan State University is high with a mean score of 3.5.
Table Iii Mean And Interpretation Of Specific Question 2
Factors Influencing the Dependency on AI
Mean
Interpretation
1. I use AI because it saves me time on doing
3.77
High
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difficult tasks.
2. I find AI explanations of complex concepts
clearer than traditional methods.
3.6
High
3. I find AI-generated summaries and study
materials helpful for comprehending complex
topics.
3.63
High
4. The availability of user-frindly AI platforms
encourages exploration and experimentation
3.9
High
5. AI-powered research assistants help me find
relevant sources and information for projects
more efficiently.
2.9
Average
6. The growing trend of AI Integration in
various engineering domains motivates its use
in studies
3.7
High
Overall
3.58
High
Table III shows the results of the factors influencing the dependency of computer engineering students on
artificial intelligence. First statement shows that the interpreted level regarding the intervening variable “time”
is high with a mean score of 3.77 in the statement “I used AI because it saves me time on doing difficult tasks.
Second statement shows that the interpreted value of the intervening variable “academic capabilities” is high
with a score 3.6 in the statement “I find AI explanations of complex concepts clearer than traditional
methods.”, high with a score of 3.63 in the statement “I find AI-generated summaries and study materials
helpful for comprehending complex topics.”, high with a score of 3.9 in the statement “The availability of
user-friendly AI platforms encourages exploration and experimentation.”, average with a score of 2.9 in the
statement “AI-powered research assistants help me find relevant sources and information for projects more
efficiently.”, and high with a mean score of 3.7 in the statement “The growing trend of AI integration in
various engineering domains motivates its use in studies.”. The overall mean result of Table 3 indicates that
time, use for its academic capabilities, availability, and trend of AI is high with a mean score of 3.58.
Table Iv Percentage of Students’ General Weighted
GWA
Frequency
Percentage (%)
1.00-1.25
0
0
1.26-1.50
2
6.7
1.51-1.75
12
40
1.76-2.00
11
36.7
2.01-2.25
4
13.3
2.26 below
0
0
Total
30
100.0
Table IV presents the general weighted average (GWA) of the students, along with the frequency and
percentage distributions. The data aligns with the questions and responses from the earlier part of the survey.
Among the thirty students, 6.7% (2 students) have a GWA of 1.26 to 1.50, 40% (12 students) have a GWA of
1.51 to 1.75, 36.7% (11 students) have a GWA of 1.76 to 2.00, 13.3% (4 students) have a GWA of 2.01 to
2.25, and 3.3% (1 student) have a GWA below 2.26. The results indicate a correlation between students'
average scores, their level of reliance, and their academic achievement over the semester. This implies that
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students' average scores align with their level of reliance and their academic performance during the semester.
However, these findings might differ due to the intervening variables mentioned in the previous chapter.
SUMMARY OF FINDINGS
The data were analyzed, and the following findings were formulated in accordance with the specific given
questions under the survey questionnaires providing credible information needed to answer the questions
presented in the Statement of the Problem. • The overall AI dependency level of computer engineering
students in Bulacan State University is high with a mean score of 3.5. • The mean results indicate that time, use
for academic capabilities, availability, and trend are the factors influencing the students’ dependency on AI •
The findings reveal a correlation between students' average scores, their level of reliance, and their academic
achievement over the semester. Conclusion Based on the results and findings of this study, the following
conclusions are formulated: Specific question 1. To what extent are computer engineering students at Bulacan
State University dependent on artificial intelligence technologies in their academic pursuits?
According to the statistics reported in the previous chapter, there is a high mean score indicating respondents'
dependency on artificial intelligence academic assistance resources. As previously stated, this addresses the
issue in the first Statement of the Problem, which might be taken as implying that the majority of students rely
on AI. Specific question 2. What are the factors influencing the dependency of computer engineering students
on artificial intelligence? The overall mean score for question number two is 3.58, which is considered high.
With all of the possible conditions determined by the survey questionnaires, this answers the question in the
Statement of the Problem number 2: the factors associated with the intervening variables mentioned previously
are time, academic capabilities, and their overall weighted average. It can be shown that the criteria described
above are strongly associated to their responses in the reliance of AI surveys. Specific question 3. How does
the level of dependency on artificial intelligence among computer engineering students affect their academic
performances? The results show a correlation between their average scores and their level of reliance, as well
as their academic achievement over the semester. This suggests that their average scores are consistent with
both their level of reliance and their academic achievement during the semester. The findings may vary based
on the intervening variables discussed in the preceding chapter. To summarize, the impact of artificial
intelligence (AI) is evident. AI is increasingly altering our environment by automating tasks and adapting
experiences. As AI technology advances, the demand for qualified computer engineering students, notably at
Bulacan State University, will only increase. These students will help shape the future of AI and ensure its
ethical and useful usage for society. The potential for AI to enhance our lives is enormous, and Bulacan State
University has the possibility to take a major role in this promising subject. By developing the next generation
of AI professionals, the institution can contribute to ensuring that AI is utilized for good and that its
advantages are enjoyed by everybody.
RECOMMENDATION
Based on the findings of the survey, it can be concluded that the majority of students rely heavily on Artificial
Intelligence to assist them in their academic activities.
1. The researchers recommend further enhancing or assisting their students in disseminating their tasks and
academic loads properly and orderly, taking into account the students' time and availability.
2. It is also recommended to integrate and cultivate AI learnings in the future; as technology evolves, the
precision of these AIs can be improved. With all of the variables considered and based on the data
analysis shown, the researchers recommend that new lessons be developed.
3. By developing the next generation of AI professionals, the institution can contribute to ensuring that AI is
utilized for good and that its advantages are enjoyed by everybody.
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