Submitted by Tony Shannon

A book review 

​The authors themselves state that “The book is designed to stimulate and advance discussion and debate” (p.21). I shall try to explain briefly why I believe the book under review has achieved its goal. 

Submitted by Tamra S. Connor
​Written by chatGPT

I asked chatGPT to write a blog post by using this prompt:  Write a blog post about the benefits of generative ai

​This is the response.  Read the post and comment your thoughts!  ~Tamra

Unleashing Creativity and Efficiency: Exploring the Benefits of Generative AI
In the digital age, artificial intelligence has become an indispensable tool, transforming the way we live, work, and play. One particularly exciting facet of AI is generative AI, a technology that has rapidly evolved and is opening new horizons in various fields. Generative AI, powered by models like GPT-3, has made significant strides in natural language processing, image generation, and creative content creation. In this blog post, we'll explore the multifaceted benefits of generative AI and its impact on diverse industries.

1. Enhanced Creativity: Generative AI allows for the automation of creative processes. It can produce art, poetry, music, and even storytelling, demonstrating its ability to generate imaginative content. Creative professionals are finding it a valuable tool for inspiration and ideation. Musicians can compose melodies, writers can brainstorm plot ideas, and artists can create unique designs with the help of AI-generated content.
   
2. Content Generation: For businesses and marketers, content generation is a critical task. Generative AI streamlines this process by producing high-quality, relevant content on a massive scale. This can be used for anything from blog posts and product descriptions to social media posts and ad copy. Content generation not only saves time and resources but also ensures a consistent and engaging online presence.
   
3. Personalization: Generative AI can analyze vast amounts of data to create personalized content and recommendations. For example, e-commerce platforms can provide users with product recommendations tailored to their preferences, increasing conversion rates and customer satisfaction. In the healthcare industry, generative AI can assist in creating personalized treatment plans based on a patient's medical history and genetic information.
   
4. Language Translation: Language barriers are no longer an obstacle to global communication. Generative AI can translate text, speech, and even videos in real-time, enabling individuals and businesses to connect with people from around the world. This technology promotes cultural understanding, eases international business transactions, and enhances the user experience for travelers and tourists.
   
5. Natural Language Processing: One of the most significant applications of generative AI is in natural language processing (NLP). Chatbots and virtual assistants powered by generative AI are increasingly sophisticated, offering more human-like interactions. They can answer questions, provide information, and even engage in meaningful conversations, improving customer service and user experience.
   
6. Education and Training: Generative AI can also revolutionize education and training. It can generate interactive lessons, create practice quizzes, and even simulate real-world scenarios for learners. This technology is especially valuable in e-learning and corporate training, as it can personalize learning experiences and adapt content to individual needs.
   
7. Automation and Efficiency: Business processes benefit greatly from the automation capabilities of generative AI. It can automate repetitive tasks, such as data entry, document summarization, and customer support inquiries. By freeing up human resources, companies can allocate their employees to more strategic and creative tasks.
   
8. Research and Development: In the field of research and development, generative AI has proven invaluable. It can assist scientists and researchers by generating hypotheses, conducting experiments, and even analyzing results. This accelerates the pace of discovery and innovation across various domains, from pharmaceuticals to materials science.
   
9. Design and Creativity: Architects, graphic designers, and other creative professionals use generative AI to generate innovative designs and concepts. AI can help in creating architecture blueprints, graphic design templates, and even fashion designs. The potential for groundbreaking innovation in design is limitless.
   
10. Predictive Analytics: Generative AI can predict future trends and outcomes by analyzing historical data. This is crucial for industries like finance, where AI can forecast market trends and optimize investment strategies. Additionally, it's instrumental in supply chain management, helping companies anticipate demand and optimize inventory levels.
    

In conclusion, generative AI is a transformative technology with far-reaching benefits across various sectors. It enhances creativity, streamlines processes, personalizes experiences, and automates tasks. As AI technology continues to evolve, we can expect even more remarkable applications and innovations. However, it's essential to consider the ethical implications and challenges associated with generative AI, such as bias in algorithms and data privacy, to ensure responsible and equitable deployment of this powerful tool. The future is undoubtedly exciting for generative AI, and it promises to shape a more efficient, creative, and connected world.

Submitted by Tamra S. Connor

Submitted by Gordon A. McKenzie

People suffered from ignorance when they do not know where to turn for help when it is needed, or they suffer from not knowing the rules of living. People also suffered because they could not get on with their associates, being in a job that they found unsatisfying, and from all of the other everyday situations that arose in clashes between the person and his surroundings. Things did not change: there could be no change to the needs of people.

Submitted by Ms Danyan Chen BA MA 

​Since China joined the World Trade Organization in 2001, industries in China have participated in international activities more frequently, and the demand for versatile talents with both high English proficiency and business practice abilities has also increased significantly. As a result, students' enthusiasm for learning Business English has increased. To meet the needs of the labour market and promote the sustainable development, many universities and colleges have established Business English majors or related departments, as important bases for cultivating high-quality business English talents with compound abilities. The Business English major is always a foreign language major established to meet the demand for versatile foreign language talents in the context of opening up to the outside world and economic and social development (Wang, 2021).

Submitted by Dr. Nathan Polley FCES

This following article is adapted from a recent presentation prepared for a staff body about effective teaching and learning.
 
Let me open today by asking a provocative question: ‘How can we, as professional educators, create transformation in our classrooms?’
 
Although I planned to present on constructive alignment, I found it surprisingly difficult to separate teaching alignment from transformational learning as constructive alignment must start with an intent for transformation to be meaningful. The two concepts – although they may seem different, represent two sides of the one coin. In covering both topics, I intend to help you become a transformation agent over the next 20 minutes as we:

• Analyse the concept of a graduate profile to create transformation in your teaching.
• Discuss concepts of constructive alignment, Finks Taxonomy, and design-focused evaluation so you will constructively align and evaluate your teaching and learning.
• Evaluate regional qualifications frameworks so you can benchmark your teaching against international universities.

Submitted by Emeritus Professor Tony Shannon AM

​The major purpose of this discussion paper is to draw attention of CESA members to our links with the Société Internationale pour l’Enseignement Commercial [SIEC] and the International Society for Business Education [ISBE]. They are keen for our involvement. In their June 2023 International Newsletter, they have this request on the front page:
 
 
We Want to Hear from You!
 
Please share your ideas, news,
anything of interest to business educators around the world, or send your request to the “Collaboration Column”.
 
Articles and/or announcements to include in the next newsletter can sent to
 
Maree Liston
Newsletter Editor
[email protected]
 
 

Submitted by Tamra S. Connor

Alan Turing, first wrote about the concept of machines that could learn in a paper published in 1950.  In his paper Computing Machinery and Intelligence, he discussed how to build an intelligent machine and then test its intelligence. In 1956, a proof of concept was presented thanks to funding by RAND, the Research and Development Corporation.  The Logic Theorist, by Allen Newell, Cliff Shaw, and Herbert Simon was presented at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI).  

Over the next two decades, AI continued to grow and was refined by the researchers.  The attendees at DSRPAI were avid supporters and worked with the Defence Advance Research Projects Agency (DARPA) to fund AI research and several institutions.  Computers were extremely expensive and the patience of researchers and those who funded the research waned. The biggest limitation for AI was limited memory capacity of the current computers.  Even in the absence of government funding and public hype, AI research continued to grow and thrive.  Between 1990 and the early 2000s, the early goals of AI were realized.  In 1997, the grandmaster of chess, Gary Kasparov played a game of chess with the IBM creation, Deep Blue, a chess playing computer program.  Also in 1997, Microsoft introduced the speech recognition program Dragon.  

The limitation of computer storage has virtually been eliminated, allowing the rapid growth of AI in the public realm.  In today's world of big data it is virtually impossible for a human to process all the data that is available; however, with AI, this is not an issue.  When you call a company or use the chat feature, many times, your conversation is with the computer using AI.  

The future of AI here.  How we use AI is the big question.  There are so many questions that must be answered in the world of computers and ethics.

So, how are you using AI in your classrooms and in life?

Anyoha, R. (2017, Summer). History of AI. Science in the News:  Special Edition: Artificial Intelligence. ​https://sitn.hms.harvard.edu/special-edition-artificial-intelligence/

Submitted by Ms Qingyuan Yang

​There is an urgent need for improvements in engineering education to ensure graduates are equipped with essential skills (Piyush, Mohamed & Gabriella, 2022). This paper suggests the utilization of hybrid teaching approaches in the design of common courses in Architectural and Civil Engineering (ACE) education. The ideas are applicable to other disciplines.

Submitted by Dr. Tony Shannon AM

​Micro-credentials of varying forms have been mentioned in these papers previously[i] with mixed responses from readers. In many institutions, both academic and commercial, they are now evolving into more formal ‘micro-certificates’ or μcertificates. It is appropriate then to re-consider some of their emerging characteristics.


[i] Shannon, A.G. 2019. Micro-credentialling. Commercial Education Society of Australia Periodic Discussion Paper, No.10, October..