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


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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


Utilization of Artificial Intelligence by Students in Interdisciplinary Field of Biomedical Engineering
Shigehiro Hashimoto
(pages: 1-5)

Transdisciplinary Applications of Data Visualization and Data Mining Techniques as Represented for Human Diseases
Richard S. Segall
(pages: 6-15)

Beyond Status Quo: Why is Transdisciplinary Communication Instrumental in Innovation?
James Lipuma, Cristo Leon
(pages: 16-20)

How We Can Locate Validatable Foundations of Life Themes
Jeremy Horne
(pages: 21-32)

Bringing Discipline into Transdisciplinary Communications -The ISO 56000 Family of Innovation Standards-
Rick Fernandez, William Swart
(pages: 33-39)

To AI Is Human: How AI Tools with Their Imperfections Enhance Learning
Martin Cwiakala
(pages: 40-46)

Knowledge, Learning and Transdisciplinary Communication in the Evolution of the Contemporary World
Rita Micarelli, Giorgio Pizziolo
(pages: 47-52)

Human Complexity vs. Machine Linearity: Tug-of-War Between Two Realities Coexisting in Precarious Balance
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 53-62)

A Cybernetic Metric Approach to Course Preparation
Russell Jay Hendel
(pages: 63-70)

The Impact of Artificial Intelligence on Education
John Jenq
(pages: 71-76)

Bridging the Gap: Harnessing the Power of Machine Learning and Big Data for Media Research
Li-jing Arthur Chang
(pages: 77-84)

Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?
Richard S. Segall
(pages: 85-92)

Identification – The Essence of Education
Jeremy Horne
(pages: 93-99)

The Greek-Roman Theatre in the Mediterranean Area
Maria Rosaria D’acierno Canonici Cammino
(pages: 100-108)

Examination of AI and Conventional Teaching Approaches in Cultivating Critical Thinking Skills in High School Students
Luis Castillo
(pages: 109-112)

Thoughts, Labyrinths, and Torii
Maurício Vieira Kritz
(pages: 113-119)

Can Two Human Intelligences (HIs or Noes) and Two Artificial Intelligences (AIs) Get Involved in Interlinguistic Communication? – A Transdisciplinary Quest
Ekaterini Nikolarea
(pages: 120-128)


 

Abstracts

 


ABSTRACT


Integration of Inquiry-Based Learning with Real -World Problem-Solving

Suzanne K. Lunsford


Our chemistry courses are focused on developing real-world problem solving skills. These real-world problem skills developed in our laboratory and field trips require students to acquire knowledge as researching the question to solve accordingly. As stated by Arthur L. Costa ““The critical attribute of intelligent human beings is not only having information but also knowing how to act on it.” Our Inquiry-based activities/labs/field trips are organized, open-ended approach that promotes creativity, design of experiment, with testing and analysis which lead to solving the problem. Our students utilize inquiry-based learning skills and gather, critique, analyze, and interpret information; create working theories; pose new questions; bring forward evidence; integrate new technology to solve the problem. The main steps to successful IBL module involves 1) professor needs to start with a question , problem-based question; 2) students need to design a plan for the project; 3) students need to create a scheduled plan; 4) professor needs to facilitate the students; 5) professor needs to assess the outcomes and possibly continue the facilitation process; 6) professor needs to evaluate the experiences and how to improve the experience (reflection time). This paper will discuss the novel inquiry-based labs developed and discuss the pre- and post-test analysis data to illustrate the content gains in our chemistry courses. These novel inquiry-based labs require each student to obtain a different project/problem to solve. The novel aspect has prevented cheating and requires students to become independent thinkers and not looking for the answers on-line or from previous students that have taken the chemistry course in the past. The IBL example will be detection of acetaminophen, ascorbic acid and caffeine without the need to prior separation using a novel electrode sensor.

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