Fundamentals of Artificial Intelligence

This self-paced, online course introduces university faculty to the fundamentals of artificial intelligence, including its origins, societal impact, and evolving role in higher education.

Module Outline

Course Description: The Fundamentals of Artificial Intelligence online course is one of the self-paced online courses developed under the UNG-DETI's AI in Learning Certification Program as a professional development opportunity designed to equip UNG faculty with essential knowledge and skills to integrate artificial intelligence (AI) into their teaching practices.
Course Objectives:
By the end of this course, the participant will be able to:
CO1. describe what is artificial intelligence or A.I.
CO2. identify various A.I. tools applicable to college or university students' learning and knowledge development.
CO3: identify new trends of A.I. developments affecting higher education in relation to academic integrity, plagiarism, and academic workload.
CO4. apply a decision-making process to address policies and procedures to prepare students and faculty about using A.I. applications and utilizations.

Module 1- Historical Implementations

Module 1 will offer some brief information about the historical implementations of A.I. and its influence on current global society.

By the end of this module, the participants will be able to:

MO 1.1: state historical implementations of A.I. from its foundational origin to its effect upon the current global society (CO1)
MO 1.2: distinguish the A.I. discoveries and its influence within the eras of A.I. implementations (CO1).

Module 2- Types of Artificial Intelligence and its examples as A.I. tools

Module 2 will identify several types of artificial intelligence with examples of A.I tools that may benefit UNG students and UNG faculty members based on functionality and specific academic use.

By the end of this module, the participants will be able to:

MO 2.1: identify several types of artificial intelligence (e.g., intelligent tutoring systems or ITS, reactive machines, reactive systems, generative A.I., general A.I., and narrow A.I.) based on their functionality and level of intelligence (CO2).
MO 2.2: identify several types of A.I. tools from the types of artificial intelligence that may be beneficial to UNG students in content learning and knowledge development (CO2).
MO 2.3: choose specific A.I. tools for UNG students and guide them to use effective best practices and strategies for completing course work such as instructional materials, assessments, and learning activities (CO2, CO3).

Module 3- Applying instructional strategies involving A.I. tools and applications

In module 3, R.O.B. will address these topics and offer examples of popular A.I. applications used by college students and faculty members. In addition, R.O.B. will offer suggestions for applying several instructional strategies in using the selective A.I. tools for instructional content, course topics development, and learning activities in aiding student success.

By the end of this module, the participants will be able to:

MO 3.1: recognize popular A.I. applications used by university or college students and faculty of higher education (CO2, CO3).
MO 3.2: apply instructional strategies in using selective A.I. tools that are applicable for instructional content or course topics development (CO2, CO3).
MO 3.3: guide students into using A.I. tools for their learning and knowledge development of content learning (CO2,CO3).
MO 3.4: identify pros and cons of Ai applications used by university or college students and faculty of higher education (CO2, CO3).

Module 4- Establishing policy initiatives of A.I. tools in content learning
and knowledge development

In module 4, R.O.B will address topics involving student and faculty usage in higher education that underlines course policies, moral judgement, academic integrity, ethical behavior, ethical concerns, privacy issues, and practical implementation (e.g., pros and cons) of A.I. tools.

By the end of this module, the participants will be able to:

MO 4.1: guide students in applying appropriate moral judgement and ethical behavior by adhering to course policies reflecting in the use A.I. tools (CO3, CO4).
MO 4.2: identify some pros and cons in using A.I. tools in higher education (CO3, CO4).
MO 4.3: address ethical concerns, privacy issues, educational goals, and practical implementation of utilizing A.I. tools in higher education (CO3, CO4).