Due to the unparalleled development in the area of artificial intelligence (AI), specifically with large language models like ChatGPT, the field of education has been in a state of flux and confusion given the extreme capabilities that AI now gives to students. Students at all levels can now use these AI systems to answer virtually any assignment/assessment question and complete any written task (and even some visual task), (Anders, 2023; OpenAI, 2023). Faculty now need to first ensure that they have developed AI literacy in order to understand AI (Anders, 2023) to then be able to better modify and enhance previous versions of their assessments to address this new AI reality, ensuring that students are properly learning the intended student learning outcome (SLOs). The SHARE Technique, developed by Brent A. Anders, PhD, Director of the Office of Institutional Research and Assessment, Center for Teaching and Learning, and Lecturer at the American University of Armenia, is a conglomeration of different ideas and aspects regarding the creation of assignments and assessments in a way where the use of AI can be much more controlled and orchestrated by an instructor (Anders, 2023b).
The SHARE Technique is based on multiple educational principles such as Rosenshine’s Principles of Instruction (2010, 2012) , Creemers and Kyriakides’ Dynamic Model (2011), experiential learning (Kolb & Kolb, 2017) with important aspects of role-play and simulation as described by Humpherys, Bakir, and Babb (2022), some of the instructional recommendations from Linda Nilson’s book “Teaching at Its Best” (2010), and grounding (meaning requiring students to reference in-class and original content on the topic being learned), (Baker et al., 1999; Holt et al., 2015). Additionally, the SHARE technique was specifically designed to be as simple as possible to allow for easy implementation by teachers and professors at all levels who are already busy with different academic responsibilities. Each letter of the SHARE Technique stands for an aspect that can be implemented within an assignment/assessment. Although all aspects of the SHARE Technique do not have to be implemented to greatly enhance an assignment or assessment, using multiple aspects can create improved control of the use of AI by students, depending on how the instructor wishes to guide the educational process. It should be noted however that, given the importance of AI Literacy as expressed by both the United Nations and NBC news, students must develop the capability of using AI effectively in order to compete in today’s economy (Elkeiy, 2022; Tong, 2023). The topic and controlled utilization of AI should be fully considered and implemented by all instructors at all levels.
SHARE Technique Breakdown:
S: Strong and Authentic - Assignments need to have increased rigor, realism, and grounding. These are important components that should always be part of good assignments, but are even more important now that AI has increased students access to knowledge. Additionally, increasing realism in instruction and assignment requirements creates a better learning experience that will help students learn and retain the information (DeMaria et al., 2010; Rahm et al., 2021). Instead of requiring a simple essay, consider creating a scenario that requires students to write a report, a research article, a blog entry, a documentary movie script, a cases study, etc. The enhanced realism will create increased excitement and motivation to complete the assignment which will lead to additional neural connections. The grounding aspect will help minimize use of AI such as ChatGPT in the creation of the content by “grounding” at least some of the content to the actual class. This means that the assignment will require students to not only use the “book” information presented on the subject, but also unique class information such as from special examples given in class, guest speakers, course videos, original case studies and handouts, class experiments, etc. This grounded information will not be available to an AI and will therefore make the use of AI in completing the assignment much more difficult. Although a student could feed this information into an AI manually, they would at least be interacting with the course content that much more.
H: High Price of False Information - In the past many instructors have only marginally taken off points for an incorrect citation or an improper fact or quote within a written assignment. Given that this is now an indication of an AI hallucination (AI term meaning made up/false information), greater penalties should be given for this type of problematic content. Explicit explanations should be given to students to help them understand that this isn’t an act of being nit-picky, this is an important part of the learning process. Credibility of the document and author is becoming more and more important, meaning that students must understand that they need to ensure that all content and sources of information are fully real, logical, and credible. Students must avoid overreliance and understand that the AI will not be at fault, instead it will be the author (the students) who will be held accountable for the contents of their assignment (OpenAI, 2023). This is also an important aspect of flow of the reading experience and a display of students’ understanding of the material. Given this change in the dynamics of grading/assessing, instructions and rubrics will need to be modified to clearly express this importance.
A: Additional and/or Other Assessment Techniques – The very important question of whether the current assessment technique used is the best way to evaluate students needs to be asked. In the past, many of us have used a writing assignment as a default assessment, but with the new AI realities, other means should be strongly considered. If a writing assignment is still viewed as a needed process, consideration should be given to the use of an additional component as well. Other assessments that could be used instead of writing or in collaboration are: student presentations with questions and answers from the instructor and/or class (viva voche), the creation of visual works (poster, painting, drawing, sculpture, etc.) along with an explanation, student podcast/videos, and other similar, more dynamic assessment techniques. Additionally, in-class quizzes and writing can also be used to gage students understanding and capability in a formative manner. Some in-class writing is recommended, but not to the point where a majority of writing is done in-class. This does not match the real-world (realism) and introduces other issues (hand writing legibility, previous skills in hand-writing, students that usually write with a dictionary/thesaurus, speed of physical processes, differences with students that have English as a second or additional language).
R: Reflection/Critical Analysis of Feedback: Giving students an additional opportunity to reflect on what was learned helps students to complete the overall experiential learning cycle (Kolb & Kolb, 2017) of the topic presented. Students can critically think and write about the feedback provided, the assignment process, what was learned, and their actual experience (phenomenology). This helps students better integrate and realize what was learned and why certain feedback was obtained. This could be done in-class or out of class, as well as orally or via a written form, depending on how the instructor wants to control the possible use of AI.
E: Expand the Assignment into Multiple Pieces - Some assignments can be greatly enhanced by breaking them down into multiple smaller assignments thereby allowing for more formative assessment/feedback and allowing the instructor greater observation of students’ development and enhanced control of possible AI use. A prime example would be some sort of written assignment such as an essay. A typical process would be to cover a topic and then require an essay to be completed in two or three weeks. This could be expanded to allow for greater control by the instructor and for increased formative feedback, through the use of the 7-step writing process: choose a topic, brainstorm, outline, rough draft, proofreading, final review, and submission (Sowell, 2020). Different aspects of this could be done in class and the use of AI could be integrated, depending on the instructor’s developmental plan. A submitted rough draft could also be used for peer evaluation thereby giving students a physical process to learn from one another and obtain greater experience in using the assignment’s rubric (to evaluate a peer’s work). An instructor could also require a student to use Microsoft’s Track Changes option (or other word processing tool) to better observe how the student is directly addressing suggested improvements. Finally, instructors could require that a written assignment have an annotated bibliography addressing specific reasons why certain reference where used and how. This would require the student to work even more directly with the content and negate some use of AI if now directly desired by the instructor at that time.
Figure 1: The SHARE Technique for Redesigning Assignments & Assessments in the Age of AI (Anders, 2023b)
Given the ongoing need to address the issue of enhancing assignments and assessments due to the ever developing capabilities of AI, the SHARE Technique is strongly encouraged. This technique has been shared and used by faculty internationally and has received favorable reviews for its simplicity but effectiveness in addressing important aspects of assignment/assessments in the age of AI. A detailed video explaining this SHARE Technique is also available on the Sovorel educational YouTube channel at: https://youtu.be/QeSaeatThFg.
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Anders, B. (2023b). SHARE technique for designing assignments & assessments in the age of AI [Image]. Sovorel Publishing. https://i0.wp.com/sovorelpublishing.com/wp-content/uploads/2023/06/SHARE-Infographic-1024x576.jpg
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About the Author
Brent A. Anders, Ph.D., is a lecturer and director of institutional research and assessment as well as the center for teaching and learning at the American University of Armenia. He has a doctorate degree in Education (focus was in Adult Learning and online instruction) from Kansas State University, a Masters degree from the University of Nebraska at Kearney (focus was in instructional technology), and a Bachelor’s degree in Psychology (focus was in human-computer interactions/usability).
Anders has worked in higher education for over twenty-five years, concentrating on enhancing the educational experience for both instructors and students through the use of engaging media and online instruction. Anders has extensively worked as an educational media consultant (dealing with instructional technology, video production, student engagement, and user experience), as a university lecturer in professional communications, writing, instructional technology, and as a course developer/instructional designer. Since the launch of the ChatGPT AI, he has dedicated himself to helping everyone in academia better understand and use this technology to improve the educational experience for all. Helping all levels of academia develop AI Literacy is now a major focus of Anders' work.
Anders also does periodic speaking events and workshops internationally as well as authoring books, research articles, blog posts (sovorelpublishing.com) and video posts (https://www.youtube.com/@sovorel-EDU/videos) dealing with different aspects of instruction, online learning, and educational technology (such as ChatGPT AI).