Establishing a delicate balance in the relationship between artificial intelligence and authentic assessment in student learning

Abstract

Across the past few decades, a gamut of technologies has emerged and been adopted as part of enabling student learning. These technologies and digital tools have been explored in terms of their affordances and their limitations during implementation in teaching practices. Teachers have actively worked to balance how a technology serves as a vehicle for learning against the challenges that are introduced through its implementation. In recent years, due to our increased reliance on digital tools and online learning environments, our education communities have first railed against, and then rallied for, each appearance of a new website, tool or platform. Whilst initial reactions can be negative (such as that recently observed on the appearance of the artificial intelligence (AI) based chatbot tool ChatGPT), many teachers will progress towards adoption of technologies in their practices once the affordances have been teased out. In some ways, as an analogy, teaching practice could be considered as an equilibrium reaction responding to the pressures of change. In this Editorial, I recognise that teachers are adaptive and creative therefore research that evidences authentic practice using AI to support student learning will increase. In parallel, as a journal, we are facing new challenges relating to the role of AI in authorship and peer review, most publishers are grappling with establishing their position on any authorship that involves AI generated text.

A study on factors affecting the decision of choosing university of high school pupils in Quang Ngai province

“…The results indicate that ChatGPT is proficient in generating accurate and informative responses for theory and factbased questions, enhancing students' understanding of core concepts [2,19]. However, it struggles with questions that require graphical illustrations, a common requirement in technical courses.…”

“…There is a growing interest in using artificial intelligence (AI) to improve teaching and learning [1,2]. Generative AI tools like ChatGPT understand and generate human-like responses in real-time [3].…”

Comparing Student and Generative Artificial Intelligence Chatbot Responses to Organic Chemistry Writing-to-Learn Assignments

“…25 Attention in the chemistry education literature has turned toward understanding the role generative AI may have for the future of assessments in chemistry. 46 Initial reports within the chemistry education literature indicate that generative AI responses tend to exhibit mixed accuracy with respect to factual or knowledge-based questions, especially facing challenges with problems requiring analysis or interpretation; findings within these studies focus on the correctness of chemistry content, suggesting that generative AI responses are generally well-written with persuasive logic and reasoning. 30,31,47−50 The present study contributes to this emerging literature by focusing specifically on evaluating the capabilities of generative AI chatbots to engage in mechanistic reasoning on organic chemistry WTL assignments.…”

Implementation of an R Shiny App for Instructors: An Automated Text Analysis Formative Assessment Tool for Evaluating Lewis Acid–Base Model Use

“…We encourage and hope that other researchers help bridge educational research and technological innovation into instructional practice . Technologies help facilitate learners’ access to and participation in learning resources that provide formative feedback . The development of this Shiny app based on our previous machine learning-based tool is a small start, adding to other machine learning-based resources to support the learning of chemistry topics. − We have made our R code freely available so that others might use our code to translate other assessment instruments and prompts into practical tools for educators more easily .…”