THEORETICAL ASPECTS IN THE FORMATION OF
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AGE COHORT EFFECTS IN AI-SUPPORTED LEARNING: AN
ANALYSIS OF GRADES FOR 2021–2023 ENTRANTS AT JAPAN
DIGITAL UNIVERSITY
Boboyev Lochinbek Boymurotovich
PhD, head of IT department of Japan Digital University, lochinbek.b@jdu.uz ,
Ziyodullayev Amirbek Akmalovich,
student of Japan Digital University ziyodullayevamirbek238@gmail.com
https://doi.org/10.5281/zenodo.16605896
Abstract.
This paper investigates the transformative impact of artificial
intelligence (AI) on higher education, with a specific focus on Japan Digital
University between 2021 and 2023. Drawing on empirical data, cohort-based
performance trends, and technological developments, the study explores how
the systematic integration of AI tools—such as adaptive learning platforms,
intelligent tutoring systems, and automated feedback mechanisms—contributed
to measurable academic improvements. During the three-year period, the
percentage of students receiving top grades significantly increased, while failure
rates declined, indicating a positive shift in learning outcomes.
The analysis reveals that these changes were driven by a combination of
factors: increased digital literacy among Generation Z students, institutional
investments in AI infrastructure, faculty training, and the normalization of
hybrid learning models. Moreover, the study highlights the psychological
readiness of post-pandemic student cohorts, who benefited from a stable and
supportive digital environment. Ethical considerations, such as responsible AI
use and the prevention of cognitive offloading, were also embedded into the
university’s educational model, fostering academic integrity and independent
thinking. Ultimately, this case study presents Japan Digital University as a
forward-thinking institution that effectively aligned technological innovation
with human-centered pedagogy. It demonstrates that AI, when thoughtfully
implemented, can serve as both a cognitive enhancer and an equity enabler in
higher education. The findings offer valuable insights for policymakers,
educators, and institutions aiming to navigate the evolving intersection of AI and
academic excellence.
Keywords:
Artificial Intelligence (AI), Higher Education, Japan Digital
University, Student Performance, Educational Technology, Digital Learning,
Academic Achievement, Generative AI, Grade Trends, Post-Pandemic Education
Introduction. The integration of artificial intelligence (AI) into higher
education has radically transformed traditional approaches to teaching and
learning. Universities around the world are rapidly adopting AI tools—ranging
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International scientific-online conference
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from adaptive learning systems to intelligent tutoring agents and automated
feedback platforms—creating a more dynamic, personalized, and data-driven
educational environment [1]. These technologies not only aim to optimize
instructional delivery, but also adjust learning experiences in real time based on
individual student progress, behavioral patterns, and engagement levels.
AI in education is no longer a futuristic concept—it is a present reality with
measurable pedagogical and cognitive consequences. Recent empirical studies
demonstrate that AI-enhanced learning can significantly improve students’
academic outcomes. A comprehensive meta-analysis conducted by Wang and
Fan (2025) revealed that AI-supported instruction led to substantial gains in
student performance, with an effect size of g = 0.86 in achievement metrics and g
= 0.45 in higher-order cognitive skills such as critical thinking, analysis, and
synthesis [2]. This confirms AI's dual role as both a teaching instrument and a
cognitive enhancer capable of supporting complex academic tasks.
However, the effectiveness of AI-assisted learning is not uniformly
distributed. Individual learner characteristics—particularly age, digital literacy,
and confidence in using technology—play a crucial role in determining the
impact of AI tools [3]. As these technologies evolve, generational differences in
learning strategies, technology comfort levels, and educational preferences are
becoming increasingly pronounced.
Children and teenagers typically interact with AI through educational apps,
games, or AI-powered platforms without deeply understanding the underlying
mechanisms. While AI is seamlessly embedded into their daily digital
environment, its educational potential is not always fully harnessed [4]. In
contrast, university students, especially those from Generation Z (born after
1997), are generally more digitally literate, quick to adopt AI technologies, and
tend to evaluate AI positively. They often use AI for writing assistance, coding
support, language translation, and even exam preparation [3].
Meanwhile, older students and adults (Millennials and Generation Y) often
exhibit skepticism, digital fatigue, or even anxiety when working with AI
platforms [4]. Their lower AI readiness may stem from limited exposure to
advanced digital environments or concerns about technological overreach.
Despite this, many are actively engaging in re-skilling programs to remain
competitive in the AI-driven academic and professional landscape.
In addition to cognitive benefits, AI use in education also raises important
pedagogical concerns. One such issue is cognitive offloading—the tendency to
rely excessively on AI for tasks such as summarization, problem solving, or
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writing. Deroy and Maity (2024) warn that overdependence on AI, especially
without proper supervision, could impair essential cognitive functions like
memory, reasoning, and independent thinking [5]. This is particularly relevant
for younger students who begin engaging with AI at early stages and may
develop long-term habits of intellectual passivity.
Nevertheless, a growing div of international research from universities in
Asia, Europe, and North America confirms the existence of an "AI readiness gap"
across age groups. Students from Generation Z not only adopt AI tools more
frequently but also report higher satisfaction and achieve stronger learning
outcomes [3]. Their comfort with rapid feedback, self-directed learning, and
technological ecosystems grants them a significant advantage in AI-rich
educational settings.
Yet this observation leads to a crucial question: Do these generational
differences in AI engagement lead to statistically significant learning gaps? To
explore this, we now turn to a comparative case study conducted at Japan Digital
University, where AI has been systematically integrated into teaching since
2021. The following section presents a cohort-based analysis of students
enrolled in 2021, 2022, and 2023, highlighting how their academic outcomes
evolved in parallel with AI's increasing sophistication and accessibility.
Main Part.
In recent years, the role of artificial intelligence (AI) in education has
significantly expanded, prompting universities around the world to reconsider
how they approach teaching, learning, and student support. Japan Digital
University stands as a compelling case study in this transformation. From 2021
to 2023, the university experienced notable shifts in student performance and
engagement, reflecting the integration of AI-assisted technologies and the
evolution of academic culture. This main part explores the multifaceted changes
that occurred during this period, with a focus on academic results, technological
adaptation, and the psychological readiness of students.
To understand the depth of change, it is essential to examine the
distribution of student grades over the three years. In 2021, the number of
students achieving an “A” grade was relatively low at 18%, while the largest
group, 42%, received a “C.” A significant 12% of students failed. However, by
2023, the percentage of “A” grades had more than doubled to 42%, while “C”
grades declined to 20% and failures dropped to just 5%. This clear upward
trend signals that something substantial changed within the university
environment.
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This diagram provides a visual representation of the academic
performance evolution, clearly illustrating the positive changes in the grading
pattern over three consecutive years. But numbers alone do not tell the full
story. To understand why this improvement occurred, we must consider the
technological and human factors at play.
One of the primary drivers behind this academic transformation was the
university’s decision to implement AI-based learning systems across all
departments starting in late 2021. These systems included personalized learning
platforms, automated feedback systems, AI-powered tutoring, and real-time
performance analytics. Students were no longer limited to traditional lectures
and assignments. Instead, they had access to adaptive learning environments
that could adjust to their pace, style, and level of understanding.
These tools offered several advantages. First, they enabled students to
engage in self-directed learning. For instance, if a student struggled with a
specific topic, the AI system could identify the problem and recommend
supplementary material. In contrast, students who mastered content quickly
could progress to more challenging topics without waiting for the rest of the
class. Second, AI feedback systems provided immediate insights into student
work, allowing them to correct mistakes in real time. As a result, learning
became more interactive and responsive.
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Additionally, the role of professors shifted from being sole lecturers to
facilitators of learning. Instructors were trained to use AI data dashboards to
monitor student progress and intervene when necessary. This led to more
timely support and personalized mentorship, fostering a collaborative
educational environment. Professors at Japan Digital University began to act
more like academic coaches, guiding students through their individual learning
journeys, rather than enforcing a one-size-fits-all approach.
Another critical aspect of this transformation was the psychological state of
students. The 2021 cohort began their studies in the midst of the global
pandemic, dealing with uncertainty, online learning fatigue, and lack of face-to-
face interaction. Many struggled with motivation and time management. In
contrast, students entering in 2023 faced a more stable academic landscape,
where hybrid learning had become normalized and support systems were
already in place. They were mentally more prepared and familiar with digital
tools, having used them extensively in their high school years. This emotional
and cognitive readiness played a significant role in academic success.
The changing culture at Japan Digital University also contributed to better
outcomes. As the use of AI tools became normalized, students were encouraged
to take more responsibility for their learning. Rather than relying entirely on
teachers or peers, students learned how to seek answers, analyze information,
and apply critical thinking with the help of AI support. Over time, this
independence nurtured a sense of ownership and confidence in their abilities.
Moreover, ethical AI usage was embedded into the curriculum. Students
were taught how to use AI responsibly—understanding that tools like ChatGPT,
Grammarly, or automated translators are aids, not substitutes for original
thought. Through these lessons, the university instilled in students the
importance of academic honesty and integrity. This emphasis helped reduce
plagiarism and encouraged genuine learning and expression.
Beyond academics, the university expanded its digital infrastructure to
support the holistic needs of students. Virtual counseling services, AI chatbots
for administrative queries, online collaboration platforms, and digital libraries
created an ecosystem where learning could happen anytime, anywhere. This
flexibility was especially beneficial for working students, parents, or those with
health limitations, allowing them to maintain academic continuity regardless of
personal circumstances.
Another notable factor was the integration of real-world projects and
digital internships. Starting in 2022, Japan Digital University partnered with tech
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companies, NGOs, and government agencies to offer remote internships and
digital fieldwork. Students could apply classroom knowledge in practical
settings, gaining valuable experience and motivation. These opportunities also
boosted confidence, encouraged engagement, and helped students build
professional networks early in their careers.
In addition, Japan Digital University emphasized cross-cultural
collaboration. Through virtual exchange programs and international AI
competitions, students interacted with peers from other countries, expanding
their global awareness and communication skills. These initiatives helped foster
a well-rounded academic experience and motivated students to push their limits
beyond classroom expectations.
It is also important to mention that the institution’s leadership played a
crucial role. The university’s decision-makers invested in AI technologies not as
a trend, but as a strategic move to enhance educational quality. They involved
faculty in every step, from system selection to implementation and evaluation.
Transparent communication and shared goals ensured smooth transitions and
minimized resistance. The administration prioritized both innovation and
empathy, ensuring that no student was left behind in the transition to digital-
first learning.
To summarize the key transformations observed during these three years:
AI learning systems personalized the educational experience.
Professors evolved into academic mentors using real-time analytics.
Students became more autonomous, responsible, and mentally prepared.
Ethical AI usage reinforced academic integrity.
Infrastructure improvements supported diverse learners.
Real-world experience and global connections enriched academic life.
All of these factors together explain the significant academic improvements
shown in the data. The university’s proactive and holistic approach to digital
transformation created an environment where students could thrive
intellectually, emotionally, and professionally.
Conclusion
In conclusion, the academic trajectory at Japan Digital University between
2021 and 2023 presents a compelling case study of how technological
integration, pedagogical innovation, and generational change can synergistically
transform educational outcomes. The remarkable improvement in academic
performance—demonstrated most strikingly by the rise in students achieving
grade A and the corresponding decline in those receiving grade F—cannot be
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viewed as a mere coincidence. Instead, it stands as evidence of a successful and
multifaceted adaptation to the demands of 21st-century education.
The role of artificial intelligence has emerged not just as a supportive tool
but as a transformative force. Platforms like ChatGPT, Grammarly, Notion AI,
and others have allowed students to organize, revise, and deepen their academic
engagement far more efficiently than before. The widespread familiarity with
prompt-based systems and AI-driven learning environments among the 2023
cohort indicates a cognitive shift in how students perceive and interact with
knowledge. Their learning habits are more autonomous, research-oriented, and
personalized, ultimately yielding better retention and performance.
Furthermore, the university’s strategic investment in faculty development
and curriculum redesign cannot be overstated. By empowering educators to use
AI as a dynamic assistant in lesson planning, grading, and feedback generation,
Japan Digital University ensured that instructors were not left behind in the
wave of digital transformation. Instead, they became co-creators of the new
academic ecosystem. These changes fostered an environment where critical
thinking, creativity, and ethical digital usage were prioritized over rote
memorization or passive consumption of information.
Another essential element in this transformation is the psychological and
emotional readiness of the students. Unlike the 2021 intake who had to deal
with the aftereffects of the global pandemic and emergency remote learning, the
2023 cohort entered university with more stable expectations, improved
infrastructure, and greater institutional support. This stability, combined with
technological comfort, allowed for better motivation, reduced anxiety, and
increased academic confidence. As a result, students were not merely reacting to
their educational environment but actively shaping it through participation and
feedback.
It is also important to recognize the cumulative nature of progress. The
positive changes in 2023 were built on the lessons learned from 2021 and 2022.
Mistakes were identified, support systems improved, and AI tools became more
advanced and responsive to user needs. This iterative process mirrors the
concept of educational resilience: the ability of a learning institution to evolve,
respond, and grow stronger through challenges. Japan Digital University
demonstrated such resilience not only through technological upgrades but also
through its commitment to inclusivity, student mental health, and data-informed
decision-making.
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The implications of these findings stretch beyond the confines of a single
institution. As universities worldwide grapple with the balance between
tradition and innovation, the Japan Digital University model serves as a potential
blueprint for the future. It shows that with careful implementation, ethical use of
AI, and student-centered pedagogy, it is possible to enhance academic integrity,
improve outcomes, and foster a generation of learners who are not just
consumers of knowledge but contributors to global progress.
To conclude, the dramatic improvement in academic performance from
2021 to 2023 is a story of adaptation, growth, and transformation. It highlights
the vital role of AI in modern education, the necessity of institutional agility, and
the power of a motivated and digitally fluent student div. As we move forward,
it becomes increasingly clear that success in education is no longer about access
to knowledge alone, but about how that knowledge is delivered, explored, and
applied. Japan Digital University’s journey provides an inspiring example of how
this can be achieved—where technology and humanity move forward together
in harmony.
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