Journal of
Systemics, Cybernetics and Informatics
HOME   |   CURRENT ISSUE   |   PAST ISSUES   |   RELATED PUBLICATIONS   |   SEARCH     CONTACT US
 



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.

Indexed by
DOAJ (Directory of Open Access Journals)Benefits of supplying DOAJ with metadata:
  • DOAJ's statistics show more than 900 000 page views and 300 000 unique visitors a month to DOAJ from all over the world.
  • Many aggregators, databases, libraries, publishers and search portals collect our free metadata and include it in their products. Examples are Scopus, Serial Solutions and EBSCO.
  • DOAJ is OAI compliant and once an article is in DOAJ, it is automatically harvestable.
  • DOAJ is OpenURL compliant and once an article is in DOAJ, it is automatically linkable.
  • Over 95% of the DOAJ Publisher community said that DOAJ is important for increasing their journal's visibility.
  • DOAJ is often cited as a source of quality, open access journals in research and scholarly publishing circles.
JSCI Supplies DOAJ with Meta Data
, Academic Journals Database, and Google Scholar


Listed in
Cabell Directory of Publishing Opportunities and in Ulrich’s Periodical Directory


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


Quantitative Endosurgery Process Analysis by Machine Learning Method
Bojan Nokovic, Andrew Lambe
(pages: 1-7)

Modelling Student Performance in a Structural Steel Graduate-Based Module: A Comparative Analysis Between K-Nearest Neighbor and Dummy Classifiers
Masengo Ilunga, Omphemetse Zimbili, Phahlani Mampilo, Agarwal Abhishek
(pages: 8-15)

Interoperable Digital Skills for Foreign Languages Education in the COVID-19 Paradigm
Rusudan Makhachashvili, Ivan Semenist, Iryna Vorotnykova
(pages: 16-20)

Education, Training and Informatics Go Hand in Hand in (Foreign) Higher Education Institutions (HEIs) – Case Studies From Live and Online Classrooms
Ekaterini Nikolarea
(pages: 21-29)

Enhancing Pedagogical and Digital Competencies Through Digital Tools: A Proposal for Semi-schooled Language Teaching Programs in Oaxaca, Mexico
José de Jesús Bautista Hernández, Eduardo Bustos Farías, Norma Patricia Maldonado Reynoso
(pages: 30-35)

Railway Track Degradation Modelling Using Finite Element Analysis: A Case Study in South Africa
Ntombela Lunga, Masengo Ilunga
(pages: 36-50)

Continuum of Academic Collaboration: Issues of Inconsistent Terminology in Multilingual Context
Cristo Leon, James Lipuma, Marcos O. Cabobianco, Maria B. Daizo
(pages: 51-62)

Peat Resource Management and Climate Change Mitigation Issues – Case of Latvia
Anita Titova, Natalja Lace
(pages: 63-70)

Using Geospatial Computation Intelligence for Mapping Temporal Evolution of Urban Built-up in Selected Areas of the Ekurhuleni Municipality, South Africa
Jo-Anne Correia, Masengo Ilunga
(pages: 71-80)

Cybernetics and Informatics of Generative AI for Transdisciplinary Communication in Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 81-88)

Navigating Psychological Riptides: How Seafarers Cope and Seek Help for Mental Health Needs
Coleen Abadicio, Stella Louise Arenas, Rosette Renee Hahn, Angel Berry Maleriado, Ramon Miguel Mariano, Rodolfo Antonio Ma. Zabella, Genejane Adarlo
(pages: 89-98)


 

Abstracts

 


ABSTRACT


To AI Is Human: How AI Tools with Their Imperfections Enhance Learning

Martin Cwiakala


The education community's sentiment regarding artificial intelligence (AI) is divided. Many see it as a means to cheat and prevent students from developing their intellectual abilities because it is generative and can provide results for many domains. Just as some had predicted that paper use would go down when computers were created, the opposite occurred. AI in the classroom, when utilized effectively, promotes critical thinking and not cheating. New technology can shock and awe those who see it for the first time. Upon closer investigation, the actual capabilities are revealed. While large language models can quickly create reports from very little information, we must examine their ability to create specific reports on topics we desire. Any large language model currently available states that it can make mistakes. Students will grow by learning how to prompt AI tools to provide meaningful results, spot mistakes, and validate their results. Knowing when it is appropriate to use an AI tool and reflecting on the consequences of results being wrong brings a student to a higher level of awareness. Performing these tasks concerning AI results also brings the user into the consciousness of their fallibility.

Full Text