Generation Alpha: Understanding the Next Cohort of University Students
- URL: http://arxiv.org/abs/2202.01422v1
- Date: Thu, 3 Feb 2022 05:47:43 GMT
- Title: Generation Alpha: Understanding the Next Cohort of University Students
- Authors: Rushan Ziatdinov and Juanee Cilliers
- Abstract summary: The research employed a theoretical analysis based on the characteristics and traits that distinguishes Generation Alpha.
The research identified the influence of social media, social connections, high levels of perceptions and the Generation Alpha's ability to interpret information as strengths to consider in future teaching-learning approaches in the higher education environment.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Technology is changing at a blistering pace and is impacting on the way we
consider knowledge as a free commodity, along with the ability to apply skills,
concepts and understandings. Technology is aiding the way the world is
evolving, and its contributions to education are not an exemption. While
technology advances will play a crucial part in future teaching-learning
approaches, educators will also be challenged by the next higher-education
generation, the Alpha Generation. This entrepreneurial generation will embrace
the innovation, progressiveness, and advancement with the expectation that one
in two Generation Alphas will obtain a university degree. In anticipating the
educational challenges and opportunities of the future higher education
environment, this research reflected on Generation Alpha as the next cohort of
university students, considering their preferred learning styles, perceptions
and expectations relating to education. The research employed a theoretical
analysis based on the characteristics and traits that distinguishes Generation
Alpha, spearheaded by technology advances. The empirical investigation
considered three independent studies that were previous conducted by authors
from Slovakia, Hungary, Australia, and Turkey to understand the challenges and
opportunities pertaining to Generation Alpha. The research identified the
influence of social media, social connections, high levels of perceptions and
the Generation Alpha's ability to interpret information as strengths to
consider in future teaching-learning approaches in the higher education
environment. This research concluded with recommendations on how universities
could be transformed to ensure a better learning experience for Generation
Alpha students, aligned with their characteristics, perceptions and
expectations.
Related papers
- The GenAI Generation: Student Views of Awareness, Preparedness, and Concern [1.5709900716890133]
Outpacing the development of uniform policies and structures, GenAI has heralded a unique era and given rise to the GenAI Generation.<n>This study examines students' perceptions of GenAI through a concise survey with optional open-ended questions.<n>Students with greater curricular exposure to GenAI tend to feel more prepared, while those without it more often express vulnerability and uncertainty.
arXiv Detail & Related papers (2025-05-04T19:37:13Z) - Form-Substance Discrimination: Concept, Cognition, and Pedagogy [55.2480439325792]
This paper examines form-substance discrimination as an essential learning outcome for curriculum development in higher education.
We propose practical strategies for fostering this ability through curriculum design, assessment practices, and explicit instruction.
arXiv Detail & Related papers (2025-04-01T04:15:56Z) - Synergizing Self-Regulation and Artificial-Intelligence Literacy Towards Future Human-AI Integrative Learning [92.34299949916134]
Self-regulated learning (SRL) and Artificial-Intelligence (AI) literacy are becoming key competencies for successful human-AI interactive learning.
This study analyzed data from 1,704 Chinese undergraduates using clustering methods to uncover four learner groups.
arXiv Detail & Related papers (2025-03-31T13:41:21Z) - Generative AI in Modern Education Society [0.6798775532273751]
Transitioning from Education 1.0 to Education 5.0, the integration of generative artificial intelligence (GenAI) revolutionizes the learning environment.
Our understanding of academic integrity and the scholarship of teaching, learning, and research has been revolutionised by GenAI.
arXiv Detail & Related papers (2024-12-10T09:11:06Z) - From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents [78.15899922698631]
MAIC (Massive AI-empowered Course) is a new form of online education that leverages LLM-driven multi-agent systems to construct an AI-augmented classroom.
We conduct preliminary experiments at Tsinghua University, one of China's leading universities.
arXiv Detail & Related papers (2024-09-05T13:22:51Z) - Foundation Models for Education: Promises and Prospects [24.75073974210808]
We discuss the strengths of foundation models, such as personalized learning, education inequality, and reasoning capabilities.
We highlight the risks and opportunities of AI overreliance and creativity.
We envision a future where foundation models in education harmonize human and AI capabilities, fostering a dynamic, inclusive, and adaptive educational ecosystem.
arXiv Detail & Related papers (2024-04-08T15:59:37Z) - Large Language Models for Education: A Survey and Outlook [69.02214694865229]
We systematically review the technological advancements in each perspective, organize related datasets and benchmarks, and identify the risks and challenges associated with deploying LLMs in education.
Our survey aims to provide a comprehensive technological picture for educators, researchers, and policymakers to harness the power of LLMs to revolutionize educational practices and foster a more effective personalized learning environment.
arXiv Detail & Related papers (2024-03-26T21:04:29Z) - Bringing Generative AI to Adaptive Learning in Education [58.690250000579496]
We shed light on the intersectional studies of generative AI and adaptive learning.
We argue that this union will contribute significantly to the development of the next-stage learning format in education.
arXiv Detail & Related papers (2024-02-02T23:54:51Z) - Generative AI and Its Educational Implications [0.0]
We discuss the implications of generative AI on education across four critical sections.
We propose ways in which generative AI can transform the educational landscape.
Acknowledging the societal impact, we emphasize the need for updating curricula.
arXiv Detail & Related papers (2023-12-26T21:29:31Z) - From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the
Generative Artificial Intelligence (AI) Research Landscape [5.852005817069381]
The study critically examined the current state and future trajectory of generative Artificial Intelligence (AI)
It explored how innovations like Google's Gemini and the anticipated OpenAI Q* project are reshaping research priorities and applications across various domains.
The study highlighted the importance of incorporating ethical and human-centric methods in AI development, ensuring alignment with societal norms and welfare.
arXiv Detail & Related papers (2023-12-18T01:11:39Z) - Education in the age of Generative AI: Context and Recent Developments [0.8313693615194309]
It is vital to notice that artificial intelligence adoption in education dates back to the 1960s.
This white paper serves as the inaugural piece in a four-part series that elucidates the role of AI in education.
The series delves into topics such as its potential, successful applications, limitations, ethical considerations, and future trends.
arXiv Detail & Related papers (2023-08-17T19:56:57Z) - The Future of Fundamental Science Led by Generative Closed-Loop
Artificial Intelligence [67.70415658080121]
Recent advances in machine learning and AI are disrupting technological innovation, product development, and society as a whole.
AI has contributed less to fundamental science in part because large data sets of high-quality data for scientific practice and model discovery are more difficult to access.
Here we explore and investigate aspects of an AI-driven, automated, closed-loop approach to scientific discovery.
arXiv Detail & Related papers (2023-07-09T21:16:56Z) - Students' Voices on Generative AI: Perceptions, Benefits, and Challenges
in Higher Education [2.0711789781518752]
This study explores university students' perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education.
Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities.
Concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed.
arXiv Detail & Related papers (2023-04-29T15:53:38Z) - Personalized Education in the AI Era: What to Expect Next? [76.37000521334585]
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to meet her desired goal.
In recent years, the boost of artificial intelligence (AI) and machine learning (ML) has unfolded novel perspectives to enhance personalized education.
arXiv Detail & Related papers (2021-01-19T12:23:32Z) - Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI)
Curriculum [58.86139968005518]
The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education.
A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum.
The co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
arXiv Detail & Related papers (2021-01-19T11:26:19Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.