Capstone Final Research paper

For Online Classes Only, How Can Instructors Measure Student Knowledge Given The Availability Of Generative Artificial Intelligence (AI) Author’s Name The Institutional Affiliation Course Number and Name Instructor Name Assignment Due Date Executive Summary Generative Artificial Intelligence (AI) tools such as OpenAI's ChatGPT are proliferating in the educational front end – and with them come opportunities and challenges to assessing student knowledge in online classes. In response to this, Coker University has developed a dual-focused approach to capitalize on the potential of AI, using it to enhance the assessment process in ways consistent with academic integrity and accuracy. This paper illustrates an approach integrating adaptive quizzing platforms that personalize feedback and learner experiences, leading to better learning outcomes. The rise of online education and AI tools has historically made it challenging to guarantee that assessments accurately reflect student understanding. The quality of the AI-produced academic work is too high for the would-be; instead, it is rejected. Traditional plagiarism detection methods have proved inadequate and, consequently, have brought about the need for new assessment methodologies. Coker University adopted the Pugh Matrix method of evaluating every strategy possible by prioritizing project-based evaluations for adaptive quizzing and innovative evaluations that promoted critical thinking and ethical education practices to meet this education criterion. Adaptive quizzing platforms, which offer continuous and tailor-made feedback, are unique in being a recommended solution because they are the most effective tool in preserving academic integrity and enhancing deep learning. By meeting the challenges imposed by AI, this approach provides an educational process that shows that assessments reflect students' knowledge and progression in learning. Table of Contents TOC \o "1-3" \h \z \u Executive Summary PAGEREF _Toc182958290 \h 2Introduction PAGEREF _Toc182958291 \h 4Historical Perspective of Issue PAGEREF _Toc182958292 \h 4Current Issue - Need for Measuring Student Knowledge with AI in Online Classes PAGEREF _Toc182958293 \h 5Important Objectives in Achieving Success and Issue Importance PAGEREF _Toc182958294 \h 6Pugh Matrix Evaluation PAGEREF _Toc182958295 \h 6Recommendation for Decision and Implementation PAGEREF _Toc182958296 \h 7Reasons for Non-Selection of Other Alternatives PAGEREF _Toc182958297 \h 8Reflecting my Learning PAGEREF _Toc182958298 \h 8Financial Ramifications PAGEREF _Toc182958299 \h 9Implementation Method and Timeline PAGEREF _Toc182958300 \h 10Phase 1 - Preparation and Planning (1-2 Months) PAGEREF _Toc182958301 \h 10Activities PAGEREF _Toc182958302 \h 10Phase 2 – Customizing System (2-3 Months) PAGEREF _Toc182958303 \h 10Activities PAGEREF _Toc182958304 \h 11Phase 3 - Training and Development (1 Month) PAGEREF _Toc182958305 \h 11Activities PAGEREF _Toc182958306 \h 11Phase 4 - Pilot Testing (1 – 2 Months) PAGEREF _Toc182958307 \h 11Activities PAGEREF _Toc182958308 \h 11Phase 5 - Full Rollout (2 -3 Months) PAGEREF _Toc182958309 \h 12Activities PAGEREF _Toc182958310 \h 12Phase 6 - Continuous Improvement (Ongoing) PAGEREF _Toc182958311 \h 12Activities PAGEREF _Toc182958312 \h 12Other Metrics to Evaluate the Measures PAGEREF _Toc182958313 \h 13References PAGEREF _Toc182958314 \h 14Appendix PAGEREF _Toc182958315 \h 16 Introduction The advent of artificial intelligence (AI) tools in educational settings has resulted in significant development and challenges. As such technologies proliferate into the classroom, the effects on academic integrity are emerging concern in educational institutes. OpenAI's ChatGPT and other tools are both an educational aid and a source of academic deception, requiring reevaluating more traditional assessment methodologies (Jones, 2023). Like other academic institutions, Coker University has been working in online learning environments, leading to the prompter adoption of such AI tools in the university routine as part of regular practice. This shift brings enormous challenges to educators attempting to measure what students know accurately (Rane et al., 2024). This paper presents a Coker University framework that not only addresses these challenges but also takes advantage of AI capabilities to improve the effectiveness of the educational process while evaluating students accurately during online classes to uphold the standards of academics and compose coherent AI usage while remaining fair and just. Historical Perspective of Issue The trend of online education has proliferated across global academic institutions, with technology advancements supporting the proliferation aided by the pandemic. This shift has presented profound challenges regarding academic integrity due to the easy access to AI tools. It is problematic because generative AI, like ChatGPT, can generate high-quality work indistinguishable from human-generated work, enabling academic dishonesty (Jones, 2023). Denny et al. (2023) assessed that novice and experienced educators need help distinguishing between AI-generated and student-created content, challenging the validity of online assessments. AI tools also tend to give outputs so refined that traditional plagiarism detection software fails, leading to high false favourable rates and complicating the enforcement of academic honesty (Elkhatat, Elsaid & Almeer, 2023). Previously designed to prevent conventional plagiarism and cheating, using the means of plagiarism and cheating is invalid in modern times. This framework needs to fully address the nuances of AI tools, including ethical considerations for how such tools can be used to support assignments and how educators can be prepared to manage the impacts of AI effectively. For example, tools like Grammarly can improve grammar and writing. In addition, the reliance on conventional assessment mechanisms, like multiple choice or short answer tests administered online, overlooks the simplicity with which answers can now be created or confirmed using AI, failing to measure meaningful comprehension or expertise in a subject adequately. Current Issue - Need for Measuring Student Knowledge with AI in Online Classes In the case of Coker University, to successfully integrate AI tools within online classes, there is a need for a dual-focused approach to use the potential of AI to improve educational outcomes and to grapple with the limitations it creates for the educational assessment process. Students can leverage AI tools to learn quickly, get instant feedback, have personalized learning experiences, and access global data (Zohuri & Mossavar-Rahmani, 2024). Although they have the potential to provide such benefits, they can also make authentic assessments of student knowledge for challenging assignments, as all it takes is the AI capabilities to use them, and they will be used deceptively to complete assignments without actual understanding. Coker University's Pugh Matrix analysis illustrates the necessity for more advanced assessment approaches beyond conventional testing, particularly in a setting with abundant AI tools. It prioritized evaluation criteria such as accuracy, ethics, and reliability because they are essential for maintaining academic integrity and student learning. Highly effective strategies that emerged were project-based assessments and adaptive quizzing platforms. Such approaches emphasize knowledge and critical thinking and are relatively free from simply recalling the material but pursuing ethical education practices. AI has the additional potential to encourage academic deceit if not adequately managed. Therefore, it needs clear, stringent guidelines about its proper use. Stanford University, for example, could set explicit policies defining the acceptable uses of AI for coursework to avoid inappropriate use and promote an understanding of AI's utility and constraints (Rashid & Kausik, 2024). Creating in-depth guidelines that detail the ethical boundaries of AI use in student assignments and assessments is essential. Important Objectives in Achieving Success and Issue Importance Considering the problem identified at Coker University, the following are the objectives to focus on; * Incorporating AI in measuring student knowledge in online classes should be cost-effective, high-quality, and accurate. These measurements should be feasible in different educational settings and have the potent...