AI Programming Courses for Early Childhood Educators

    Children with special needs and those in economically disadvantaged communities often lack access to education and tutoring services. By rewarding working professionals for educating early learners, the entire community can benefit.

    What is visualized is an AI course for educators which rewards teaching topics in basic logic by allowing the educator to apply this basic logic and related topics to creating computer programming applications in the artificial intelligence domain. Educators in the program would be able to write application in Prolog, an AI logic programming language. In other words. If you help students understand logic, you can apply what was being taught to writing applications in Prolog.

     If scaled, the solution could many educators in schools with little financial resources. 100,000 educators with the ability to create AI applications can assist one million students.    

   School Districts often have limited resources for the inner city schools and special needs programs. What is proposed is way to help these children in inner cities and those with learning disabilities gain access to educational services by means of rewarding the educator.  

   The educator can be offered personal enrichment as well as an economic benefit in a design that incorporates what was taught into giving the ability to write artificial intelligence applications.

    To elaborate, educators can traditional exercises that promote logical thinking:

For example,

What is going to happen if the child goes out in the rain?

     This in Prolog, with the complete information, can be answered by the AI system using what is called forward chaining.

     In summary, underfunded schools and the various needs for resources in schools systems can be aided by this proposed system.  

    Inner city and economically disadvantaged preschool students with learning disabilities. These are students generally 5 and younger. The solution is working is helping to understand their needs by means of empowering their educators by means of rewarding teaching experience by allowing it to be applied to the educator learning material that gives them the ability to create AI applications.

    Many parts of the world have school systems that struggle to have the financial resources to fund teacher salaries for the education for early learners. By providing AI education to educators, an optimal use of resources may be able to be obtained for the education of early learners.

    For example for early learners age 5 and less, a mathematic exercise that is appropriate for their age is sequencing, as shown below:

X I O X I O....

  What is the next letter? An instructor teaching the students this exercise may feel comfortable taking an AI class later in the day where they are shown that an AI system can also answer this question with "forward chaining". 

  Children in economically disadvantaged communities often lack access to the best schools. By rewarding working professionals for teaching preschool with online/live instruction professional education, these students could benefit.

  The solution visualized is rewarding educators teaching the basic logic coursework with the ability to apply what was taught into writing artificial intelligence applications. This brings the future of artificial intelligence for the instructors of the classrooms most in need of assistance.

For example, someone instructing young students on family trees could explain:

Bill is the father of Joe and Joe is the father of Mark, who is Mark's grandfather?

The instructor could then later on apply this and likely feel comfortable learning to write the application in Prolog. 

NON-MONOTONICITY OF AI

   As mentioned elsewhere in this application, AI distinguishes itself from the traditional theory of automation in that an AI system can change a monotonic series of actions when conditions change. For example, not tell students to go outside for recess when it is raining, even though it is programmed to make the announcement the same time everyday. Teachers dealing with "changes in the program" can feel comfortable taking an AI class where this topic is presented as something they are familiar with.

 A example of coursework incorporating real world applications for educators is the following:

DATA SECURITY EXAMPLE

  In order to give a real world example not directly related to teaching, data security topics are one envisioned presentation:

Backward Chaining and Forward Chaining

   If you receive a suspicious email with a link that was clicked, later your computer later stops working....what happened?

  With Prolog approach to AI, the logical conclusion a person can draw is much like the conclusion a person can get by writing this as an application....this would be "forward chaining".

   Your computer stops working, and earlier their was a suspicious email with link that was clicked.....why may have this have happened?

  The "why" can be answered by means of Backward Chaining in Prolog.

Non-Monotonic Logic

   Everyday people open their email and may receive documents. In terms of data security, some documents may have "red flags" that they are dangerous to open. As a human operator may be able to detect signs that the regular routine may need to to be altered, so AI systems differentiate themselves from other systems in that AI systems are capable of this feature of non-monotonic logic and also detect not to open the file.

  Instead of using rewards for student behavior, educational benefits based on possible personal interests of the instructor are presented. Rewards have been used in the past for students, but research in psychology has shown that there is the risk that when the reward ends, the learning ends. One study tried paying children to learn in school, when funding stopped the learning stopped. 

  Rewarding teachers with greater salaries is effective. However, what if a program could be designed to empower teachers to have more skills in the Information Age as well become more incorporated into the school administration system? A standard computer programming course could be considered more work on top a busy schedule. What if the computer course was based on verbal skills and what the teachers taught during the day? This should creates an intrinsic motivation to learn the course plus allow teachers to create their own applications for the classroom as the well the school system.

   An innovation of the presenting the following attributes of AI for educators is proposed:

         1. Non-Monotonic Logic

         2. Backward Chaining

         3. Forward Chaining

-A novel method of teaching Prolog for Artificial Intelligence education

Educators trained in writing Prolog can apply the skill to a variety of job skills in their profession. By working with school administrators on computer applications, the educators become part of the administration system. With AI technology, educators can write programs for customizing exams for students based on their skill levels.

One aspect of this is backward and forward chaining in Prolog. This can be summarized as follows:

Given the necessary information:

What will happen next?....Forward Chaining

Why did this happen?.......Backward Chaining.

  In classroom for preschoolers, age 5 and younger, a picture depicting an event can be held up in front of classroom, and the educator can ask the students the above questions in order for the students can develop their logical reasoning. The educator can then use the teaching experience to possible gain an interest in writing applications in AI using this unique function in Prolog.

  Finally, what separates AI from automation? AI systems can differentiate exclusions to the routine, giving it a separation to the theory of standard automation technology systems. Teachers explaining to students that within a certain context there certain rules that have changed can use that experience to write applications in non-monotonic logic for AI.

By rewarding educators with teaching early learners, schools benefit.

This is done by using the experience of teaching topics such as logical reasoning and related subjects as a tool to learn to write an application in artificial intelligence. 

  Educators empowered with the ability to write programs in AI can create applications for their classroom as well schools. With their new programming skills, they are more readily able to engage school administrators in education and computer issues.

   As mentioned earlier, creating funding for schools has tended to produce better schools. By providing AI courses to preschool teachers, a benefit can be provided that may be able to leverage school districts with limited financial resources. A benefit to preschool teachers can benefit preschools.

The programs is in the process of being implemented. At this moment, there are no participants. In one year, with proper funding, 100,000 educator may be able to enroll in the course. In 5 years, again with proper funding, 1 million educators enrolled online or in live instruction courses is a possibility.

Within the next year, to have a sustainable program that can implemented in various locations. Within five years, the goal would be able to help 1 million students by means of assisting 100,000 preschool teachers.

Recruiting skilled educators as well as developing efficient and effective software application developer kits for educators. Within the next five years, the barrier wold primarily be the need to translate any educational software and written material because of language barriers in various parts of the world.

-Strong incentives by means of quality online/live classroom courses.

 -Applying systems engineering techniques in order to develop software training kits. 

-Hiring translators for detailed translations into other languages.

It is just developing as a program.

1 for now

I have completed the training requirements for the BCABA, Board Certification in Applied Behavior Analysis.

None right now, but later this will be updated.

The program is non-profit. However, revenue is possible by means of developing intellectual property (e-books, online tutorials, and so on) based on the new methods for teaching computer programming to educators...in this case artificial intelligence computer programming. A future revenue source is possible in terms of applying these methods to corporations needing to staff trainers in the art of developing AI applications.

School, public and private, may be able to purchase the training system. School unions may also purchase the system as well. Grants and bartering with professional education providers is also another route for financial stability.

I believe this will promote this program of helping schools by means of letting educators gain AI skills based upon their teaching experience. Solve can help because the prize funding cane used hire programmers and educators to create an online training program for educators, as well as the needed funding for organization expenses.

  Professional education providers, software developers for training programs as well as Prolog applications, associations for computer science education, as well as AI societies.

The prize would be used to hire staff to create artificial intelligence training programs tailored to the design of this plan. AI is necessary for the solution and is the key element to the solutions because educators are rewarded for teaching early learners by applying what they just taught to learning to the create applications of Prolog, an AI software program.

 An innovation of presenting the following attributes of AI for educators is proposed:

         1. Non-Monotonic Logic

         2. Backward Chaining

         3. Forward Chaining

This can be summarized with the following examples:

Given the necessary information:

What will happen next?....Forward Chaining

Why did this happen?.......Backward Chaining.

If there a change in circumstances?....Non-Monotonic Logic.

 The following link provides more information on the AI as well as the data security applications in terms of learning:

https://www.scribd.com/documen...

The program empowers women educators, who tend to be a large part of the educator work force, as well as possibly helps girls introduuce computer science in a method that focuses on verbal skills.

The prize helps hire staff to apply artificial intelligence programming to education. Although big data is not used, data security education is envisioned as one aspect for teaching artificial intelligence. Students are taught to maintain data ethically and responsibly by means of the data security exercises in terms of an application of non-monoticity in AI.

 The following link provides more information on the AI as well as the data security applications in terms of learning:

https://www.scribd.com/documen...