Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


Re-Published in
Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Analogical and Logical Thinking – In the Context of Inter- or Trans-Disciplinary Communication and Real-Life Problems
Nagib Callaos, Jeremy Horne
(pages: 1-17)

Artificial Intelligence for Drone Swarms
Mohammad Ilyas
(pages: 18-22)

Brains, Minds, and Science: Digging Deeper
Maurício Vieira Kritz
(pages: 23-28)

Can AI Truly Understand Us? (The Challenge of Imitating Human Identity)
Jeremy Horne
(pages: 29-38)

Comparison of Three Methods to Generate Synthetic Datasets for Social Science
Li-jing Arthur Chang
(pages: 39-44)

Digital and Transformational Maturity: Key Factors for Effective Leadership in the Industry 4.0 Era
Pawel Poszytek
(pages: 45-48)

Does AI Represent Authentic Intelligence, or an Artificial Identity?
Jeremy Horne
(pages: 49-68)

Embracing Transdisciplinary Communication: Redefining Digital Education Through Multimodality, Postdigital Humanism and Generative AI
Rusudan Makhachashvili, Ivan Semenist
(pages: 69-76)

Engaged Immersive Learning: An Environment-Driven Framework for Higher Education Integrating Multi-Stakeholder Collaboration, Generative AI, and Practice-Based Assessment
Atsushi Yoshikawa
(pages: 77-94)

Focus On STEM at the Expense of Humanities: A Wrong Turn in Educational Systems
Kleanthis Kyriakidis
(pages: 95-101)

From Disciplinary Silos to Cyber-Transdisciplinary Networks: A Plural Epistemic Model for AGI-Era Knowledge Production
Cristo Leon, James Lipuma
(pages: 102-115)

Generative AI (Artificial Intelligence): What Is It? & What Are Its Inter- And Transdisciplinary Applications?
Richard S. Segall
(pages: 116-125)

How Does the CREL Framework Facilitate Effective Interdisciplinary Collaboration and Experiential Learning Through Role-Playing?
James Lipuma, Cristo Leon
(pages: 126-145)

Narwhals, Unicorns, and Big Tech's Messiah Complex: A Transdisciplinary Allegory for the Age of AI
Jasmin Cowin
(pages: 146-151)

Playing by Feel: Gender, Emotion, and Social Norms in Overwatch Role Choice
Cristo Leon, Angela Arroyo, James Lipuma
(pages: 152-163)

Responsible Integration of AI in Public Legal Education: Regulatory Challenges and Opportunities in Albania
Adrian Leka, Brunilda Haxhiu
(pages: 164-170)

The Civic Mission of Universities: Transdisciplinary Communication in Practice
Genejane Adarlo
(pages: 171-175)

The Promise and Peril of Artificial Intelligence in Higher Education
James Lipuma, Cristo Leon
(pages: 176-182)

They Learned the Course! Why Then Do They Come to Tutorials?
Russell Jay Hendel
(pages: 183-187)

To Use or Not to Use Artificial Intelligence (AI) to Solve Terminology Issues?
Ekaterini Nikolarea
(pages: 188-195)

Transdisciplinary Supersymmetry: Generative AI in the Vector Space of Postdigital Humanism
Rusudan Makhachashvili, Ivan Semenist
(pages: 196-204)

Why Is Trans-Disciplinarity So Difficult?
Ekaterini Nikolarea
(pages: 205-207)


 

Abstracts

 


ABSTRACT


Repurposeable Learning Objects Linked to Teaching and Learning Styles

Jeremy Dunning, Donald Cunningham, Larry Vandermolen, Tom Hunt, Ari Vidali, Abtar Kaur


Multimedia learning objects are an essential component of high quality, technology-mediated instruction. Learning objects allow the student to use the content learned in a particular part of a course and; 1. demonstrate mastery of the content, 2. apply that knowledge to solving a problem, and 3. use the content in a critical thinking exercise that both demonstrates mastery and allows the student to place the content within the context of the larger topic of the course. The difficulty associated with the use of learning objects on a broad scale is that they require programming skills most professors and instructors do not possess. Learning objects also tend to be custom productions and are defined in terms of the programming and code terminology, further limiting the professor’s ability to understand how they are created. Learning objects defined in terms of styles of learning and teaching allow professors and instructors to develop a deeper understanding of the learning objects and the design process.

A set of learning objects has been created that are designed for some of the important styles of learning and teaching. They include; visual learning, writing skills, critical thinking, time-revealed scenarios, case studies and empirical observation. The learning objects are designed and described in terms that the average instructor can readily understand , redesign and incorporate into their own courses. They are also designed in such a way that they can readily be repurposed for new applications in other courses and subject areas, with little or no additional programming.

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