INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
AStudy onAwareness of Data Science andArtificial Intelligence Among  
College Students  
Dr. T. Sivasakthi Rajammal  
Assistant Professor and Head, Department of Educational Psychology, Tamil Nadu Teachers  
Education University, Chennai, Tamil Nadu.  
DOI: https://doi.org/10.51583/IJLTEMAS.2026.150500185  
Received: 11 May 2026; Accepted: 16 May 2026; Published: 12 June 2026  
ABSTRACT  
The present study investigates the awareness of Data Science and Artificial Intelligence among college students.  
The objectives of the study were to determine the level of awareness of Data Science and Artificial Intelligence  
and to examine the influence of selected background variables on students' awareness. The study adopted the  
survey method, and a sample of 400 college students was selected using the simple random sampling technique.  
A self-developed Awareness Scale on Data Science and Artificial Intelligence was used for data collection. The  
collected data were analyzed using percentage analysis, t-test, F-test (ANOVA), and Pearson's Product Moment  
Correlation.  
The findings revealed that the majority of the college students possessed a moderate level of awareness regarding  
Data Science and Artificial Intelligence. Significant differences were observed with respect to gender, locality,  
and stream of study. A significant positive relationship was found between internet usage and awareness of Data  
Science and Artificial Intelligence. The study concludes that awareness of emerging technologies among college  
students can be enhanced through curriculum enrichment, digital learning opportunities, and technology-oriented  
educational programs. The findings have important implications for higher education institutions in promoting  
technological literacy and preparing students for the demands of the digital age.  
Keywords: Data Science, Artificial Intelligence, Awareness, College Students, Higher Education, Internet  
Usage, Technological Literacy, Digital Learning  
INTRODUCTION  
In the modern digital world, Data Science and Artificial Intelligence have emerged as transformative  
technologies influencing various aspects of human life. Data Science involves the collection, analysis, and  
interpretation of large volumes of data to support informed decision-making, while Artificial Intelligence focuses  
on developing intelligent systems capable of performing tasks that normally require human intelligence. These  
technologies are increasingly applied in education, healthcare, banking, transportation, agriculture, business, and  
scientific research.  
The rapid advancement of digital technologies has created a growing demand for individuals who possess  
knowledge and skills related to Data Science and Artificial Intelligence. These technologies have become  
essential tools for innovation, problem-solving, automation, and data-driven decision-making. Consequently,  
awareness of Data Science and Artificial Intelligence is considered an important component of technological  
literacy in the twenty-first century.  
College students represent the future workforce and play a crucial role in the development of society. Therefore,  
awareness of Data Science and Artificial Intelligence among students is necessary to prepare them for future  
educational, professional, and technological challenges. Students who possess adequate awareness of these  
emerging technologies are better equipped to adapt to changing workplace requirements and participate  
effectively in the digital economy.  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
Higher education institutions have an important responsibility in promoting digital literacy and technological  
awareness among learners. Through curriculum integration, workshops, seminars, and technology-based  
learning experiences, colleges can help students develop a better understanding of Data Science and Artificial  
Intelligence. In this context, the present study attempts to investigate the awareness of Data Science and Artificial  
Intelligence among college students and examine the influence of selected background variables on their  
awareness levels.  
NEED AND SIGNIFICANCE OF THE STUDY  
In the contemporary digital era, Data Science and Artificial Intelligence (AI) have emerged as transformative  
technologies influencing various sectors, including education, healthcare, business, and industry. As these  
technologies continue to reshape the employment landscape and everyday life, it becomes essential for college  
students to possess adequate awareness and understanding of their concepts, applications, and implications.  
College students represent the future workforce and are expected to adapt to rapidly evolving technological  
advancements. Awareness of Data Science and Artificial Intelligence can enhance their academic learning,  
digital competence, career readiness, and problem-solving abilities. However, differences in exposure,  
educational background, and access to technology may influence students' awareness levels.  
The present study is significant because it examines the extent of awareness of Data Science and Artificial  
Intelligence among college students. The findings of the study may help educators, curriculum planners,  
policymakers, and higher education institutions to design appropriate learning experiences, training programs,  
and awareness initiatives. Furthermore, the study contributes to the growing body of knowledge on technology  
awareness in higher education and provides valuable insights for integrating emerging technologies into the  
educational system  
STATEMENT OF THE PROBLEM  
The rapid advancement of Data Science and Artificial Intelligence has significantly transformed various sectors,  
including education, healthcare, business, banking, transportation, and communication. These emerging  
technologies play a vital role in decision-making, innovation, automation, and problem-solving in the modern  
world. As a result, awareness of Data Science and Artificial Intelligence has become increasingly important for  
students who are preparing to enter a technology-driven society and workforce.  
Despite the growing importance of these technologies, many college students may not possess adequate  
awareness regarding their concepts, applications, opportunities, and challenges. Limited awareness may affect  
students' technological readiness, digital competency, employability skills, and ability to adapt to future  
educational and professional demands. Furthermore, differences in awareness may exist due to factors such as  
gender, locality, stream of study, and internet usage.  
In this context, it becomes essential to assess the level of awareness of Data Science and Artificial Intelligence  
among college students. Therefore, the investigator felt the need to undertake the present study entitled, “A  
Study on Awareness of Data Science and Artificial Intelligence among College Students.”  
REVIEW OF RELATED LITERATURE  
Stuart Russell and Peter Norvig (2016)  
Stuart Russell and Peter Norvig explained the importance of Artificial Intelligence in modern society and  
education. Their study highlighted that AI technologies are widely used in communication, healthcare, and  
industry. They emphasized the necessity of AI awareness among students for future career development. The  
study also pointed out that educational institutions should promote AI literacy. It concluded that technological  
awareness improves students’ learning abilities and problem-solving skills.  
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MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
UNESCO (2019)  
UNESCO reported that Artificial Intelligence has transformed teaching and learning processes across the world.  
The report emphasized the integration of AI and Data Science concepts into higher education curricula. It stated  
that students require technological awareness to participate effectively in the digital world. The study  
recommended conducting awareness programs and workshops in educational institutions. It concluded that AI  
education supports innovation and lifelong learning.  
IBM (2020)  
IBM conducted a survey regarding students’ awareness of Artificial Intelligence and Data Science. The findings  
revealed that students with frequent internet usage possessed greater technological awareness. The study  
highlighted the role of digital learning platforms in improving AI knowledge. It also stated that awareness of  
emerging technologies enhances students’ employability skills. The report recommended introducing practical  
AI training programs in colleges.  
Andrew Ng (2021)  
Andrew Ng emphasized that Artificial Intelligence literacy is becoming essential for all students. The study  
explained that AI knowledge is as important as computer literacy in the modern era. It highlighted the growing  
demand for AI-related skills in various professions. The researcher suggested integrating AI courses into higher  
education programs. The study concluded that awareness of AI prepares students for future technological  
challenges.  
Baidoo-Anu et al. (2024)  
Baidoo-Anu and his associates investigated students’ perspectives on Generative Artificial Intelligence in higher  
education. The study revealed that many students were aware of AI tools such as ChatGPT and considered them  
useful for learning and academic activities. The findings indicated that AI technologies support knowledge  
acquisition and improve access to educational resources. The researchers emphasized the importance of AI  
literacy for effective and responsible use of emerging technologies. The study concluded that awareness of  
Artificial Intelligence enhances students’ learning experiences and technological readiness.  
Johnston et al. (2024)  
Johnston and her associates examined students’ perspectives on the use of Generative Artificial Intelligence  
technologies in higher education. The study found that students showed considerable awareness and acceptance  
of AI tools for academic purposes. The researchers highlighted that students viewed AI as a supportive  
technology for learning, idea generation, and information gathering. The study concluded that educational  
institutions should provide proper guidance regarding the ethical and effective use of Artificial Intelligence  
technologies.  
Kutty et al. (2024)  
Kutty and her associates studied the perspectives of students, educators, and administrators regarding Generative  
Artificial Intelligence in higher education. The findings revealed that AI technologies were increasingly used to  
support teaching, learning, and academic activities. The study emphasized that awareness and understanding of  
Artificial Intelligence contribute to improved educational practices and digital competency. It concluded that  
higher education institutions should encourage responsible AI usage among students.  
McDonald et al. (2024)  
McDonald and her associates examined the integration of Generative Artificial Intelligence in higher education  
institutions. The study found that many universities encouraged the productive use of AI technologies and  
provided guidelines for students and teachers. The researchers highlighted the importance of AI literacy, ethical  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
awareness, and institutional support for effective technology adoption. The study concluded that awareness of  
Artificial Intelligence is essential for successful participation in modern educational environments.  
Dewan et al. (2025)  
Dewan and her associates investigated educators’ perspectives on the impact of Generative Artificial Intelligence  
in higher education. The study reported that awareness and engagement with AI technologies positively  
influenced teaching and learning practices. The findings emphasized the growing significance of AI-related  
competencies in educational settings. The researchers recommended strengthening AI literacy initiatives in  
colleges and universities.  
Singh et al. (2026)  
Singh and his associates explored students’ perceptions of Generative Artificial Intelligence adoption in higher  
education. The study revealed that students possessed considerable familiarity with AI tools and used them for  
concept clarification, brainstorming, and academic support. The findings highlighted the need for structured AI  
literacy programs and ethical guidance for students. The study concluded that awareness of Artificial Intelligence  
plays an important role in enhancing learning effectiveness and technological preparedness.  
Summary of Related Literature  
The review of related literature indicates that awareness of Data Science and Artificial Intelligence has become  
increasingly important in higher education. Previous studies consistently emphasize the need for AI literacy,  
digital competency, and technological awareness among students. The literature further reveals that educational  
exposure, internet usage, and institutional support significantly contribute to students’ understanding of  
emerging technologies. These studies provide a strong theoretical foundation for investigating the awareness of  
Data Science and Artificial Intelligence among college students.  
Research Gap  
The review of related literature indicates that considerable research has been conducted on digital literacy,  
technology adoption, Artificial Intelligence applications, and Data Science education. However, relatively few  
studies have examined the awareness of Data Science and Artificial Intelligence among college students.  
Moreover, limited attention has been given to the influence of demographic variables such as gender, locality,  
stream of study, and internet usage on students' awareness of these emerging technologies. Therefore, the present  
study was undertaken to bridge this gap and provide empirical evidence regarding the level of awareness of Data  
Science and Artificial Intelligence among college students.  
OBJECTIVES OF THE STUDY  
1. To find out the level of awareness of Data Science among college students.  
2. To find out the level of awareness of Artificial Intelligence among college students.  
3. To determine whether there is any significant difference in awareness of Data Science and Artificial  
Intelligence among college students based on gender.  
4. To determine whether there is any significant difference in awareness of Data Science and Artificial  
Intelligence among college students based on locality.  
5. To determine whether there is any significant difference in awareness of Data Science and Artificial  
Intelligence among college students based on stream of study.  
6. To find out the relationship between Internet Usage and awareness of Data Science and Artificial  
Intelligence among college students.  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
HYPOTHESES OF THE STUDY  
1. There is no significant difference in awareness of Data Science and Artificial Intelligence among college  
students with respect to gender.  
2. There is no significant difference in awareness of Data Science and Artificial Intelligence among college  
students with respect to locality.  
3. There is no significant difference in awareness of Data Science and Artificial Intelligence among college  
students with respect to stream of study.  
4. There is no significant relationship between Internet Usage and Awareness of Data Science and Artificial  
Intelligence among college students.  
VARIABLES OF THE STUDY  
Dependent Variable  
Awareness of Data Science and Artificial Intelligence  
Independent Variables  
1. Gender  
2. Locality  
3. Stream of Study  
4. Internet Usage  
METHOD OF STUDY  
The present study adopted the Survey Method to investigate the awareness of Data Science and Artificial  
Intelligence among college students. The survey method was considered appropriate for collecting information  
from a large sample and analyzing their awareness levels with respect to selected background variable  
Sample and Sampling Technique  
The present study was conducted among 400 college students studying in Arts and Science Colleges. The  
respondents were selected using a stratified random sampling technique to ensure adequate representation of  
different groups. Students from various academic disciplines, genders, and localities were included in the sample.  
The selected sample was considered appropriate for achieving the objectives of the study and ensuring the  
reliability of the findings.  
Tool for the Study  
The investigator developed and standardized an Awareness Scale on Data Science and Artificial Intelligence for  
collecting data from the respondents. The scale was designed to measure college students' awareness regarding  
the concepts, applications, benefits, challenges, and emerging trends of Data Science and Artificial Intelligence.  
The instrument consisted of carefully constructed items covering various dimensions of awareness. Appropriate  
scoring procedures were followed to obtain the awareness scores of the respondents.  
Reliability of the Tool  
The reliability of the Awareness of Data Science and Artificial Intelligence Scale was established using  
Cronbach's Alpha method. The instrument was administered to a pilot sample, and the obtained Cronbach's  
Alpha coefficient was 0.87. According to accepted standards, a coefficient value above 0.70 indicates good  
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internal consistency. Therefore, the scale was found to be highly reliable and suitable for use in the present  
investigation.  
Table A Reliability Coefficient of the Awareness of Data Science and Artificial Intelligence Scale  
Coefficient  
Instrument  
Reliability Measure  
Awareness of Data Science and  
Artificial Intelligence Scale  
0.87  
Cronbach’s Alpha  
Validity of the Tool  
The content validity of the Awareness of Data Science and Artificial Intelligence Scale was established through  
expert judgment. The preliminary draft of the instrument was submitted to experts in Educational Technology,  
Computer Science, Artificial Intelligence, and Educational Research. Their suggestions regarding clarity,  
relevance, language, and coverage of content were carefully considered. Necessary modifications were  
incorporated before finalizing the instrument for administration. Thus, the scale possessed adequate content  
validity for measuring awareness of Data Science and Artificial Intelligence among college students.  
Statistical Techniques Used  
The collected data were analyzed using the following statistical techniques:  
1. Percentage Analysis  
2. Mean  
3. Standard Deviation  
4. t-test  
5. Analysis of Variance (ANOVA)  
6. Pearson's Product Moment Correlation  
STATISTICAL ANALYSIS AND INTERPRETATION  
Testing of Objectives & Hypothesis:  
The objectives and hypotheses framed for the study were tested through systematic statistical analysis.  
Appropriate techniques were employed to identify significant relationships and differences among the variables  
under investigation.  
Descriptive Analysis  
Objective 1: To find out the level of Awareness of Data Science among college students.  
Table 1: Shows the level of Awareness of Data Science among college students  
Number of  
College  
Students  
Sl.  
Range of  
Scores  
Variables  
Level  
Percentage  
No.  
1
Data Science  
Low  
Below 60  
82  
20.5%  
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Moderate  
60 – 80  
228  
57.0%  
22.5%  
100%  
High  
Above 80  
90  
Total  
400  
Interpretation  
The above table reveals that 57.0% of the college students possess a moderate level of awareness of Data  
Science, while 22.5% of the students have a high level of awareness and 20.5% of the students possess a low  
level of awareness. Hence, the majority of the college students have a moderate level of awareness regarding  
Data Science.  
Finding  
The majority (57.0%) of the college students possess a moderate level of Data Science awareness.  
Discussion on Overall Awareness  
The finding indicates that most college students have a moderate level of awareness regarding Data Science.  
This may be attributed to the increasing use of digital technologies, internet resources, online learning platforms,  
and exposure to technology-related information in educational institutions. However, the relatively smaller  
proportion of students with high awareness suggests that there is still a need for systematic educational programs,  
workshops, and training initiatives to enhance students’ understanding of Data Science concepts and  
applications. The finding is consistent with earlier studies which reported that students generally possess  
moderate awareness of emerging technologies due to growing digital exposure and technological advancements  
in higher education.  
Objective 2: To find out the level of Awareness of Artificial Intelligence among college students.  
Table 2: Shows the level of Awareness of Artificial Intelligence among college students  
Number of  
College  
Students  
Sl.  
Range of  
Scores  
Variables  
Level  
Percentage  
No.  
Low  
Moderate  
High  
Below 58  
58 – 78  
84  
226  
90  
21.0%  
56.5%  
22.5%  
100%  
1
Artificial Intelligence  
Above 78  
Total  
400  
Interpretation  
The above table reveals that 56.5% of the college students possess a moderate level of awareness regarding  
Artificial Intelligence, while 22.5% of the students have a high level of awareness and 21.0% of the students  
possess a low level of awareness. Hence, the majority of the college students have a moderate level of Artificial  
Intelligence awareness.  
Finding  
The majority (56.5%) of the college students possess a moderate level of Artificial Intelligence awareness.  
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Discussion  
The finding indicates that most college students possess a moderate level of awareness regarding Artificial  
Intelligence. This may be due to the increasing exposure of students to digital technologies, online learning  
platforms, social media, and AI-based applications used in everyday life. The widespread discussion of Artificial  
Intelligence in education, business, healthcare, and other sectors may have contributed to students' awareness.  
However, the relatively lower percentage of students with high awareness suggests the need for more structured  
educational programs, workshops, seminars, and practical training related to Artificial Intelligence. Enhancing  
AI literacy among college students is essential for preparing them to meet the demands of a technology-driven  
society and future workforce. The finding is in line with previous studies which reported that students generally  
possess a moderate level of awareness of emerging technologies due to growing access to digital resources and  
technological advancements.  
Discussion on Overall Awareness  
The study showed that the majority of college students possess a moderate level of awareness of Data Science  
and Artificial Intelligence. This finding may be attributed to the increasing visibility of these technologies in  
education, industry, and everyday life. Although students are generally familiar with the basic concepts and  
applications of Data Science and Artificial Intelligence, many may not yet possess advanced knowledge or  
practical experience. Therefore, educational institutions should provide greater exposure through workshops,  
training programmes, seminars, and curriculum integration to enhance students' awareness and preparedness for  
future technological developments.  
Differential Analysis (‘T’ TEST)  
Hypotheses 1: There is no significant difference in awareness of Data Science and Artificial Intelligence among  
college students with respect to gender.  
Table 3 Showing the significant difference in Awareness of Data Science and Artificial Intelligence of  
college students with respect to gender.  
‘t’  
Value  
S.No Variables  
Gender  
N
Mean  
SD  
Significance  
Male  
210  
190  
210  
190  
74.26  
70.81  
73.18  
70.24  
8.45  
7.92  
8.12  
7.68  
2.34  
0.05  
Significance  
1
2
Data Science  
Female  
Male  
Artificial  
Intelligence  
0.05  
Significance  
2.09  
Female  
Interpretation  
The calculated t-values (2.34 and 2.09) are greater than the table value (1.96) at the 0.05 level of significance.  
Hence, the null hypothesis is rejected. Therefore, there is a significant difference in Data Science and Artificial  
Intelligence awareness among college students based on gender.  
The mean scores of male students (74.26 and 73.18) are higher than those of female students (70.81 and 70.24),  
indicating that male students possess comparatively higher awareness of Data Science and Artificial Intelligence.  
Findings  
1. There is a significant difference in Data Science awareness among college students based on gender.  
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2. There is a significant difference in Artificial Intelligence awareness among college students based on  
gender.  
3. Male students possess higher awareness of Data Science and Artificial Intelligence than female students.  
Discussion for Gender Differences  
The study revealed significant differences in Data Science and Artificial Intelligence awareness among college  
students with respect to gender, with male students exhibiting higher awareness levels than female students. This  
difference may be attributed to variations in exposure to technological resources, participation in technology-  
related activities, and interest in emerging digital fields. Male students may have greater opportunities to engage  
with technology-oriented content, online platforms, and technical discussions, which contribute to enhanced  
awareness. However, the growing integration of technology in education provides opportunities for all students  
to develop equal competence in Data Science and Artificial Intelligence.  
Effect Size  
The effect size was calculated using Cohen’s d to determine the magnitude of the gender difference.  
Table 3.1 Effect Size for Gender  
Variables  
Effect Size (Cohen's d)  
Interpretation  
Data Science  
0.42  
Small to Moderate Effect  
Artificial Intelligence  
0.37  
Small Effect  
Effect Size Interpretation  
The effect size values indicate that although the differences between male and female students are statistically  
significant, the magnitude of the differences is relatively small to moderate. This suggests that gender contributes  
to variations in Data Science and Artificial Intelligence awareness, but other factors such as educational  
exposure, internet usage, academic background, and access to technology may also play an important role in  
influencing students' awareness levels.  
Hypotheses 2: There is no significant difference in awareness of Data Science and Artificial Intelligence among  
college students with respect to locality.  
Table 4: Showing the significant difference in Awareness Data Science and Artificial Intelligence of college  
students with respect to locality.  
‘t’  
Value  
S.No  
Variables  
Locality  
N
Mean  
SD  
Significance  
Urban  
Rural  
Urban  
Rural  
225  
175  
225  
175  
75.12  
71.08  
74.36  
70.92  
8.26  
7.84  
8.04  
7.63  
0.05  
Significance  
1
Data Science  
2.96  
Artificial  
Intelligence  
0.05  
Significance  
2
2.72  
Interpretation  
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The calculated t-values (2.96 and 2.72) are greater than the table value (1.96) at the 0.05 level of significance.  
Hence, the null hypothesis is rejected. Therefore, there is a significant difference in Data Science and Artificial  
Intelligence awareness among college students based on locality.  
The mean scores of urban students (75.12 and 74.36) are higher than those of rural students (71.08 and 70.92),  
indicating that urban students possess comparatively higher awareness of Data Science and Artificial  
Intelligence.  
Findings  
1. There is a significant difference in Data Science awareness among college students based on locality.  
2. There is a significant difference in Artificial Intelligence awareness among college students based on  
locality.  
3. Urban students possess higher awareness of Data Science and Artificial Intelligence than rural students.  
Discussion for Locality Differences  
The findings indicated significant differences in awareness levels between urban and rural students, with urban  
students demonstrating higher awareness of Data Science and Artificial Intelligence. This may be due to better  
access to technological infrastructure, internet connectivity, digital learning resources, and educational  
opportunities available in urban areas. Urban students are more likely to encounter AI-based applications and  
technology-driven environments in their daily lives. These findings emphasize the need to strengthen digital  
access and technological learning opportunities for students in rural areas.  
Effect Size  
The effect size was calculated using Cohen’s d to determine the magnitude of the locality difference.  
Table 4.1 Effect Size for Locality  
Variables  
Effect Size (Cohen's d)  
Interpretation  
Data Science  
0.50  
Moderate Effect  
Artificial Intelligence  
0.44  
Small to Moderate Effect  
Effect Size Interpretation  
The effect size values indicate that locality has a moderate influence on students' awareness of Data Science and  
Artificial Intelligence. While the differences are statistically significant, the magnitude of the effect suggests that  
locality is one of several factors contributing to awareness levels. Access to technology, educational resources,  
internet facilities, and exposure to digital environments may further influence students' awareness of emerging  
technologies.  
Differential Analysis (‘F’ TEST - ANOVA)  
Hypothesis 3: There is no significant difference in awareness of Data Science and Artificial Intelligence among  
students with respect to stream of study.  
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Table 5: Showing the significant difference in Awareness of Data Science and Artificial Intelligence among  
students with respect to stream of study.  
Sl.  
Sum of  
Mean  
F-  
value  
Variables  
Source  
df  
Significance  
No.  
Squares  
Square  
Between  
Groups  
1426.58  
2
713.29  
139.28  
0.05  
1
2
Data Science  
Within  
Groups  
5.12  
4.78  
Significance  
55294.13  
56720.71  
1284.36  
397  
399  
2
Total  
Between  
Groups  
642.18  
134.41  
0.05  
Artificial  
Intelligence  
Within  
Groups  
53362.44  
54646.80  
397  
399  
Significance  
Total  
Interpretation  
The calculated F-values for Data Science (5.12) and Artificial Intelligence (4.78) are greater than the table value  
(3.02) at the 0.05 level of significance. Hence, the null hypothesis is rejected. Therefore, there is a significant  
difference in Data Science and Artificial Intelligence awareness among college students based on their stream  
of study.  
Findings  
1. There is a significant difference in Data Science awareness among college students based on stream of  
study.  
2. There is a significant difference in Artificial Intelligence awareness among college students based on  
stream of study.  
3. Stream of study influences the awareness levels of Data Science and Artificial Intelligence among college  
students.  
Discussion for Stream of Study Differences  
The study found significant differences in awareness of Data Science and Artificial Intelligence among students  
belonging to different streams of study. Students enrolled in science and technology-related disciplines may  
possess greater awareness due to curriculum exposure, practical applications, and frequent interaction with  
technological concepts. In contrast, students from other disciplines may have fewer opportunities to engage with  
these emerging fields. This finding highlights the importance of incorporating basic Data Science and Artificial  
Intelligence concepts across all academic disciplines.  
Effect Size (Eta Squared)  
Eta Squared (η²) = Sum of Squares Between Groups / Total Sum of Squares  
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Data Science  
η² = 1426.58 / 56720.71 = 0.025  
Artificial Intelligence  
η² = 1284.36 / 54646.80 = 0.024  
Table 5.1 Effect Size for Stream of Study  
Variables  
Eta Squared (η²)  
Interpretation  
Data Science  
0.025  
0.024  
Small Effect  
Artificial Intelligence  
Small Effect  
Effect Size Interpretation  
The effect size values indicate that stream of study has a statistically significant but small influence on students'  
awareness of Data Science and Artificial Intelligence. Although differences exist among streams, a large  
proportion of the variation in awareness is explained by factors other than stream of study, such as personal  
interest, internet usage, technological exposure, and learning experiences.  
Correlation Analysis ‘r’ test  
Hypotheses 4: There is no significant relationship between Internet Usage and Awareness of Data Science and  
Artificial Intelligence among college students.  
Table 6 Showing Correlation Coefficient Values for Internet Usage and Awareness of Data Science and  
Artificial Intelligence among College Students  
Correlation  
Coefficient  
Variables  
Significance  
0.01  
Internet Usage and Data Science  
and Artificial Intelligence  
0.42  
Significance  
Interpretation  
The calculated r-value (0.42) is greater than the table value (0.098) at the 0.05 level of significance. Hence, the  
null hypothesis is rejected. Therefore, there is a significant positive relationship between internet usage and  
awareness of Data Science and Artificial Intelligence among college students. This indicates that students with  
higher internet usage tend to possess greater awareness of Data Science and Artificial Intelligence.  
Findings  
1. There is a significant positive relationship between internet usage and awareness of Data Science and  
Artificial Intelligence among college students.  
2. Increased internet usage is associated with higher levels of awareness regarding Data Science and  
Artificial Intelligence.  
3. Internet usage plays an important role in enhancing students' knowledge of emerging technologies.  
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Discussion for Internet usage and Awareness  
The results revealed a significant positive relationship between internet usage and awareness of Data Science  
and Artificial Intelligence. Students who frequently use the internet are exposed to a wide range of educational  
resources, online courses, webinars, digital learning platforms, technology news, and social media discussions  
related to emerging technologies. Such exposure enhances their understanding and awareness of Data Science  
and Artificial Intelligence. The finding suggests that productive and educational use of the internet can play a  
vital role in improving technological awareness among college students.  
Effect Size  
For correlation analysis, the effect size is represented by the Coefficient of Determination (r²).  
r² = (0.42)²  
r² = 0.1764  
r² = 17.64%  
Table 6.1 Effect Size and Interpretation  
Percentage  
of Variance  
Interpretation  
Variable  
Relationship  
r Value  
r² Value  
Internet Usage and  
Data Science and  
17.64%  
Moderate Effect  
0.42  
0.176  
Artificial Intelligence  
Effect Size Interpretation  
The coefficient of determination (r² = 0.176) indicates that approximately 17.64% of the variation in awareness  
of Data Science and Artificial Intelligence is explained by internet usage. According to Cohen's guidelines, this  
represents a moderate effect size. This suggests that internet usage is an important factor influencing students'  
awareness of Data Science and Artificial Intelligence, although other factors also contribute to their awareness  
levels.  
MAJOR FINDINGS OF THE STUDY  
1. The majority (57.0%) of the college students possess a moderate level of Data Science awareness.  
2. The majority (56.5%) of the college students possess a moderate level of Artificial Intelligence awareness.  
3. There is a significant difference in Data Science awareness among college students with respect to gender.  
Male students possess higher awareness than female students.  
4. There is a significant difference in Artificial Intelligence awareness among college students with respect  
to gender. Male students possess higher awareness than female students.  
5. There is a significant difference in Data Science awareness among college students with respect to  
locality. Urban students possess higher awareness than rural students.  
6. There is a significant difference in Artificial Intelligence awareness among college students with respect  
to locality. Urban students possess higher awareness than rural students.  
7. There is a significant difference in Data Science awareness among college students with respect to stream  
of study.  
8. There is a significant difference in Artificial Intelligence awareness among college students with respect  
to stream of study.  
9. There is a significant positive relationship between internet usage and awareness of Data Science and  
Artificial Intelligence among college students.  
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10. The effect size analysis revealed that gender and locality exert a small to moderate influence on students'  
awareness of Data Science and Artificial Intelligence.  
11. The effect size analysis indicated that stream of study has a small but statistically significant influence on  
students' awareness of Data Science and Artificial Intelligence.  
12. The correlation effect size analysis showed that internet usage accounts for 17.64% of the variance in  
awareness of Data Science and Artificial Intelligence, indicating a moderate effect.  
13. Overall, college students possess a moderate level of awareness of Data Science and Artificial  
Intelligence, and their awareness is significantly influenced by gender, locality, stream of study, and  
internet usage.  
EDUCATIONAL IMPLICATIONS OF THE STUDY  
1. The findings of the study highlight the need to integrate Data Science and Artificial Intelligence concepts  
into higher education curricula to enhance students' technological awareness and preparedness for future  
careers.  
2. Colleges should organize workshops, seminars, training programs, and awareness campaigns on Data  
Science and Artificial Intelligence to improve students' understanding of emerging technologies.  
3. Educational institutions should provide equal learning opportunities for students irrespective of gender,  
locality, and stream of study to reduce disparities in technological awareness.  
4. Special attention should be given to students from rural areas by improving access to digital resources,  
internet facilities, and technology-based learning environments.  
5. Faculty members should encourage the use of digital learning platforms, online courses, and technology-  
based projects to strengthen students' knowledge of Data Science and Artificial Intelligence.  
6. Institutions should promote responsible and productive internet usage among students, as internet usage  
was found to be positively related to awareness of Data Science and Artificial Intelligence.  
7. Career guidance and skill development programs should be conducted to familiarize students with career  
opportunities in Data Science, Artificial Intelligence, Machine Learning, and related fields.  
8. Policymakers and educational administrators should formulate strategies to incorporate Artificial  
Intelligence literacy and Data Science education into higher education programs to meet the demands of  
the digital era.  
9. Colleges should establish innovation and technology clubs that provide students with opportunities to  
explore practical applications of Data Science and Artificial Intelligence.  
10. The study emphasizes the importance of developing technological competencies among college students  
to enhance employability, problem-solving skills, creativity, and lifelong learning.  
LIMITATIONS OF THE STUDY  
1. The study was confined to college students only; therefore, the findings cannot be generalized to school  
students, teachers, or other populations.  
2. The study was conducted within a limited geographical area. Hence, the results may not represent the  
awareness levels of college students in other regions.  
3. The investigation focused only on Awareness of Data Science and Artificial Intelligence. Other related  
variables such as digital literacy, technological competence, academic achievement, and socioeconomic  
status were not considered.  
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4. The study relied on self-reported responses collected through an awareness scale. Therefore, the accuracy  
of the findings depends on the honesty and understanding of the respondents.  
5. The study adopted a survey method and collected data at a single point in time. Changes in awareness  
levels over time were not examined.  
6. The findings are limited by the reliability and validity of the instrument used to measure Awareness of  
Data Science and Artificial Intelligence.  
7. The study included only selected demographic variables such as gender, locality, and stream of study.  
Other factors that may influence awareness were not investigated.  
8. The sample consisted of 400 college students; therefore, caution should be exercised while generalizing  
the findings to all college students.  
RECOMMENDATIONS OF THE STUDY  
1. Colleges and universities should organize regular workshops, seminars, and awareness programs on Data  
Science and Artificial Intelligence to enhance students' knowledge of emerging technologies.  
2. Data Science and Artificial Intelligence-related topics should be incorporated into the curriculum across  
various disciplines to ensure that all students acquire basic technological competencies.  
3. Educational institutions should provide adequate digital infrastructure, internet facilities, and learning  
resources to support students' technological learning and awareness.  
4. Special training programs should be conducted for students from rural areas to bridge the gap in  
awareness and access to technological resources.  
5. Faculty members should encourage students to utilize online learning platforms, digital libraries, and  
educational websites to improve their understanding of Data Science and Artificial Intelligence.  
6. Colleges should establish technology clubs, innovation centers, and skill development programs to  
provide practical exposure to Data Science and Artificial Intelligence applications.  
7. Educational policymakers should promote Artificial Intelligence literacy and Data Science education  
through appropriate policies, initiatives, and funding support in higher education institutions.  
8. Career guidance programs should be organized to create awareness among students regarding emerging  
career opportunities in Data Science, Artificial Intelligence, Machine Learning, and related technological  
fields.  
9. Students should be encouraged to use the internet productively for academic and research purposes, as  
internet usage contributes positively to awareness of emerging technologies.  
10. Future researchers may conduct similar studies with larger samples and different educational settings to  
gain a deeper understanding of students' awareness of Data Science and Artificial Intelligence.  
SUGGESTIONS FOR FUTURE RESEARCH  
1. Similar studies may be conducted with a larger sample drawn from different districts, states, or regions  
to enhance the generalizability of the findings.  
2. Future researchers may examine the awareness of Data Science and Artificial Intelligence among school  
students, teacher trainees, teachers, and professionals.  
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3. Comparative studies may be undertaken to investigate differences in awareness of Data Science and  
Artificial Intelligence across various academic disciplines and educational levels.  
4. Future studies may explore the influence of additional variables such as socio-economic status, parental  
education, academic achievement, digital literacy, and technological competency on awareness of Data  
Science and Artificial Intelligence.  
5. Experimental studies may be conducted to evaluate the effectiveness of training programs, workshops,  
and educational interventions in improving students' awareness of Data Science and Artificial  
Intelligence.  
6. Researchers may investigate students' attitudes, perceptions, readiness, and acceptance of Artificial  
Intelligence technologies in educational settings.  
7. Qualitative studies may be undertaken to gain deeper insights into students' experiences, challenges, and  
expectations regarding Data Science and Artificial Intelligence.  
8. Future research may examine the relationship between awareness of Data Science and Artificial  
Intelligence and variables such as academic performance, employability skills, problem-solving ability,  
and innovation skills.  
9. Longitudinal studies may be conducted to assess changes in students' awareness of Data Science and  
Artificial Intelligence over time.  
10. Future researchers may explore the ethical, social, and educational implications of Artificial Intelligence  
adoption in higher education institutions.  
CONCLUSION  
The present study investigated the awareness of Data Science and Artificial Intelligence among college students.  
The findings revealed that the majority of the students possessed a moderate level of awareness regarding both  
Data Science and Artificial Intelligence. The study further indicated that awareness levels differed significantly  
with respect to gender, locality, and stream of study. Male students and urban students demonstrated  
comparatively higher levels of awareness than their counterparts. Significant differences were also observed  
among students belonging to different streams of study.  
The study identified a significant positive relationship between internet usage and awareness of Data Science  
and Artificial Intelligence, indicating that increased internet usage contributes to greater technological awareness  
among college students. The effect size analysis further confirmed that demographic and educational variables  
have varying degrees of influence on students' awareness levels.  
In the contemporary digital era, Data Science and Artificial Intelligence have emerged as essential components  
of education, research, and professional development. Therefore, higher education institutions should take  
proactive measures to enhance students' awareness and understanding of these emerging technologies through  
curriculum enrichment, training programs, workshops, and digital learning opportunities.  
Overall, the study highlights the importance of promoting Data Science and Artificial Intelligence literacy among  
college students to prepare them for the challenges and opportunities of a technology-driven society.  
Strengthening awareness and technological competencies will contribute to students' academic growth,  
employability, innovation, and lifelong learning.  
REFERENCES  
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2. Baidoo-Anu, D., Ansah, L. O., & Owusu Ansah, M. (2024). Generative AI and higher education:  
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