Artificial Intelligence in Higher Education
Artificial
intelligence (AI) tools have emerged as some of the most positively disruptive
and contested technologies in higher education. The rapid advancement of
digital connectivity has fueled exponential growth in AI adoption, development,
integration, and accessibility, transforming how academic institutions teach,
assess, and navigate the educational environment. Consider, for example, the
stark contrast in user adoption between Instagram and ChatGPT. Instagram,
launched in 2010, took over two years to reach 100 million users, while
ChatGPT—introduced in 2022—achieved the same milestone of attracting 100
million users in less than three months (Meeker, 2024). This drastic comparison
underscores society’s broad receptiveness to AI while simultaneously highlighting
how exponential increases in interconnectivity have accelerated the momentum of
emerging technologies.
For higher
education, these fast-paced trends place a dual responsibility on institutions
and educators to equip students with knowledge of emerging technologies, such
as AI, and to integrate these tools into instructional environments
thoughtfully. Doing so can enhance learning experiences and help move beyond
the limitations of a one-size-fits-all educational model (Robert et al., 2025).
The Los Angeles Pacific University is among the forward-leaning institutions
actively integrating AI assistants into academic environments to enhance
student experiences. The university strategically incorporated an AI assistant
into active learning strategies (e.g., Think-Pair-Share), with preliminary
findings suggesting improvements in student engagement and comprehension (Los
Angeles Pacific University, 2024). While these early results are promising,
skeptics caution that the growing integration of AI in education and broader
society—often referred to as human-AI symbiosis—may undermine human autonomy
and creativity (Robert et al., 2025). In response to these concerns, it becomes
increasingly important to design AI implementations in ways that preserve human
independence and originality.
Forces of
Technology and Ethics in Educational AI
The integration of AI in higher education is influenced by the forces of technology and ethics that simultaneously enable and constrain innovation. In the context of this post, the influential force of technology originates from improvements in advanced computing (e.g., machine learning) that have made AI more accessible, scalable, and applicable to diverse audiences and applications. These developments are prompting educational institutions to reconsider traditional approaches by incorporating AI to provide new opportunities for personalized instruction, real-time feedback, and adaptive learning experiences. However, the pace of these innovations presents ethical challenges that institutions cannot ignore. Provided that a university does not develop these AI systems or has the staff to understand the complexity of an open-source codebase, there are growing concerns with data privacy, algorithmic bias, training discrepancies, and, most importantly, the potential to erode student creativity, which highlights a need for model scrutiny. As noted by Robert et al. (2025), there is a growing concern about the balance between the promise of AI’s ability to enhance education and the risk of overreliance on these systems, which could deskill educators and reduce students to mere data points. This relationship highlights the vital importance of ethical stewardship in technology implementations, ensuring that the convergence of AI and education does not compromise ethical boundaries at the expense of academic integrity.
A
Technology Trend in Student Transcripts
From high
school diplomas to college degrees, academic institutions are exploring new and
innovative ways to supplement traditional student transcripts, which often lack
comprehensive information. Traditional student transcripts often fail to
recognize students’ achievements outside of a somewhat ambiguous course name
and grading criterion (e.g., A+) (Gagnon, 2023). For instance, a cybersecurity
curriculum could include topics such as communication, collaboration,
leadership, and critical thinking; however, this information does not get
reported on traditional transcripts. Seeding this topic in a real-world
example, in 2022, the author of this post was a recent college graduate in
cybersecurity, eager to contribute to the skilled workforce. What happened next
was unexpected—rather than being welcomed for holding a relevant cybersecurity
degree (i.e., cyber forensics and vulnerability management), he quickly
realized most employers were prioritizing “experience” over education. This
disconnect became more apparent when he discovered that transcripts listing
courses like “vulnerability management” failed to acknowledge the hands-on
offensive security labs, reverse engineering exercises, collaborative projects,
and teamwork skills developed throughout the course. Despite submitting over 65
job applications, he eventually secured a promising position as a vulnerability
analyst that would jumpstart his career in cybersecurity. This experience,
echoed by other students, highlights a critical issue in the education and
employment pipeline: traditional transcripts often fail to convey the full
breadth of a student’s skills and readiness. Collectively, this highlights
the growing need for next-generation credentials that more accurately represent
applied competencies and real-world capabilities.
Next-generation credentials, as described by Coffey (2024), are akin to a digital wallet that stores learning and employment credentials in a centralized space—much like an application. These digital representations of skill sets would broaden the depth and breadth of capturing student capabilities, including, but not limited to, academic engagements, research, technical certifications, leadership roles, extracurricular activities, community service, and much more. This approach would help bridge the divide between education and industry, enabling students to continue growing their digital portfolios as they progress through their professional careers. While this approach appears promising, it presents novel challenges to the implementation of next-generation credentials. For instance, this shift in focus would necessitate a storage medium for digital credentials, a training program for educators to learn about this new requirement, and effective cybersecurity solutions to ensure that digital credentials are authentic and not manipulated by the owner or a threat actor (Robert et al., 2025). In addition to these concerns, they should not be overburdensome for the staff or students, as this could deter them from using it and inadvertently cause the same issue as before. To succeed, academic institutions will need to gather input from educators and students to develop an intuitive user interface while also creating policies and training programs that prioritize usability and security.
Note. From Blockchain, self-sovereign
identity and digital credentials: Promise versus praxis in education, by
Grech et al., 2021 (doi: 10.3389/fbloc.2021.616779)
National and Technological Forces in Next-Generation Credentials
The transition to next-generation credentials is being driven by a convergence of national and technological forces that challenge the status quo of academic credentialing. Nationally, the growing skills gap between graduates and industry demands has sparked concern from students and educators. As workforce expectations shift toward demonstrable, real-world experiences—particularly in evolving fields like cybersecurity—traditional transcripts are increasingly seen as insufficient methods of communicating a student’s skill sets. This disconnect not only hinders new graduates from entering the workforce but also signals a broader issue with how academic achievements are communicated at a national level to fulfill critical positions. Advancements in digital infrastructure, blockchain authentication, and cloud-based storage, combined with technology, are enabling more dynamic, secure, and portable credentialing systems (Robert et al., 2025). These innovations make it possible and feasible to create lifelong, verifiable records of a student’s learning experiences, encapsulating their academic rigor. However, these same technologies introduce new challenges, such as data privacy, cybersecurity risks, system interoperability, and training requirements. As the nation works to modernize its education framework through innovative methods, a collaboration between academia, government, and industry will be essential to ensure that next-generation credentials are scalable, secure, and relatable, thereby facilitating the reformation of the new workforce.
References
Coffey, L. (2024, April 05). Digital wallets
explored as next generation transcripts. Retrieved June 26, 2025, from
www.insidehighered.com:
https://www.insidehighered.com/news/tech-innovation/alternative-credentials/2024/04/05/digital-wallets-next-generation-college
Gagnon, L. (2023, September 12). Colleges are
ditching the sat. the high school transcript should be next. Retrieved
June 26, 2025, from www.highereddive.com:
https://www.highereddive.com/news/next-gen-credentials-high-school-transcripts/692823/
Grech, A., Sood, I., & Arino, L. (2021, March
29). Blockchain, self-sovereign identity and digital credentials: Promise
versus praxis in education. doi:10.3389/fbloc.2021.616779
Los Angeles Pacific University. (2024). People
centered technology driven. Retrieved June 25, 2025, from
www.aicenter.lapu.edu:
https://aicenter.lapu.edu/horizon-report#people-centered-technology-driven
Meeker, M. (2024, July 01). AI and universities -
will masters of learning master new learnings? Retrieved June 25, 2025,
from www.bondcap.com: https://www.bondcap.com/reports/aiu
Robert, J., Muscanell, N., McCormack, M., Pelletier,
K., Arnold, K., Arbino, N., . . . Reeves, J. (2025). 2025 educause horizon
report: Teaching and learning edition. Retrieved June 25, 2025, from
www.library.educause.edu:
https://library.educause.edu/-/media/files/library/2025/5/2025hrteachinglearning.pdf
