The rapid emergence of generative AI in higher education has fueled heated debates about its usefulness, potential harm, and effects on teaching, learning, and research. Our panel aims to dispel several common misconceptions regarding the role of AI in higher education and showcase concrete examples of effective AI integration.
AI & Teaching
AI & Learning
AI & Research
The misconceptions covered here focus on various aspects of teaching, such as instruction, assessment, mentorship, etc.
This section focuses on myths related to learning, such as skill-building, problem-solving, and critical thinking, among others.
Here, we discuss misconceptions related to doing academic research, from thesis formulation and finding sources to citations and bibliographies.
Common AI myths addressed by the panelists:
MYTH: Faculty cannot create engaging assignments and authentic learning experiences for students using AI.
This myth is addressed by Melissa Panek in her presentation.
MYTH: AI will replace professors.
This myth is addressed by Melissa Panek in her presentation.
MYTH: AI erodes academic integrity.
This myth is addressed by Melissa Panek in her presentation.
MYTH: Banning AI from the classroom forces students to think critically.
This myth is addressed by Kelly Karst in her presentation.
MYTH: AI tools prevent “authentic learning” and work produced by students using AI is not “authentic”.
This myth is addressed by Kelly Karst in her presentation.
MYTH: When students are allowed to use AI tools for writing assignments they fail to master important writing skills..
This myth is addressed by Mariya Gluzman in her presentation.
MYTH: Students get enough exposure to AI technology outside of the classroom, they do not need to learn how to use this technology in their college courses.
This myth is addressed by Mariya Gluzman in her presentation.
MYTH: Using AI contributes to the shrinking of students’ attention spans.
This myth is addressed by Mariya Gluzman in her presentation.
MYTH: Students use AI as a shortcut to doing coursework.
This myth is addressed by Norman Eng in his presentation.
