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AI Literacy and Online Proctoring: Educational Perspectives and Strategies
Prihana Vasishta1*, Gitanjaly Chhabra2 and Noosha Mehdian2
1Centre of Management and Humanities (CMH), Punjab Engineering College (Deemed to be University), Chandigarh, India
2Arts, Communications, and Social Sciences Department (ACSS), University Canada West, Vancouver, Canada
Abstract
The integration of artificial intelligence (AI) in education is transforming teaching and learning paradigms, offering opportunities to enhance educational practices and prepare students for the digital age. This paper explores AI's theoretical foundations and practical applications in education, focusing on AI-assisted practices and strategies to strengthen teacher preparation for AI literacy. Theoretical frameworks in AI education provide a foundational understanding of integrating AI into educational settings. We examine the Hyper Sentient Syllabus concept, leveraging AI to dynamically adapt curriculum content for personalized learning. Additionally, the role of AI in redesigning assessment strategies is explored, highlighting its impact on fairness, efficiency, and academic integrity. The research also presents a framework for adopting AI-assisted online proctoring systems to enhance assessment security and support remote learning. Strategies to strengthen teacher preparation for AI literacy include updating teachers' knowledge of AI technologies, utilizing AI-enhanced tools for personalized learning, and integrating AI literacy within the TPACK framework. By synthesizing theoretical insights with practical applications, this paper underscores the importance of equipping educators with the necessary knowledge and tools to effectively leverage AI technologies, fostering personalized learning and preparing students for success in a technology-driven world.
Keywords: Artificial intelligence, AI literacy, generative AI, higher education, redesigning assessments, online proctoring, AI-assisted educational practices, professional development
1.1 Introduction
The education landscape has significantly transformed in recent years with the widespread adoption of online learning platforms and technologies [1, 2]. This shift, accelerated by global events that necessitated remote instruction, has brought to the forefront innovative tools such as AI-assisted online proctoring systems [3]. These systems play a crucial role in maintaining academic integrity during remote assessments but also raise complex questions and ethical considerations from the perspectives of both educators and learners [4]. Online proctoring involves using digital tools and technologies to monitor and invigilate remote examinations and assessments. Traditionally, in-person proctoring involved the physical presence of an invigilator to ensure fairness and prevent unfair means during exams. However, with the move toward virtual classrooms and online testing environments [5], the need for scalable and efficient proctoring solutions led to the development of AI-driven systems monitoring students remotely [6].
From the student's perspective, AI-assisted proctoring systems introduce a new layer of interaction and surveillance in the educational process. Students engaging with these technologies often express concerns about privacy, fairness, and the potential biases of AI algorithms [7, 8]. Additionally, by using these technologies, the learners are subject to anxiety [9], which may result in unfair results. Additionally, while numerous AI-based technologies are available to assist with simple and complex tasks in libraries, only a few have extensively implemented AI to enhance the student experience significantly [10]. Conversely, from the teacher's perspective, integrating AI into education extends beyond assessment to encompass broader pedagogical strategies. Concepts such as the "Hyper Sentient Syllabus" emerge, reflecting the dynamic adaptation of course content and instructional methods based on real-time student data and AI insights. This innovative approach personalizes learning experiences and necessitates rethinking traditional assessment methods to align with the principles of AI-driven education [14].
Additionally, it urges educators to review the existing learning objectives of each course and degree program to keep in sync with AI's accelerated pace of growth. However, integrating AI into the curriculum is not confined to technology enhancement or usage; instead, it is crucial to consider the challenges of deploying these technologies and monitoring their societal impacts [13]. The role of AI in redesigning assessment strategies is particularly transformative [15]. Traditional assessment methods often face challenges in scalability, objectivity, and adaptability to diverse learner needs [16]. AI offers opportunities to address these limitations through automated grading [17], personalized feedback [14], and adaptive assessments tailored to individual learning trajectories [18]. By leveraging AI, educators can shift focus from mere outcome measurement to continuous, data-driven improvement in student learning outcomes.
These apprehensions highlight the importance of understanding and developing AI literacy among students [11], enabling them to navigate and critically evaluate the use of AI in educational settings. The concepts mentioned above, including the transition of the digital era from the teacher and student perspective, should be based on their understanding of developing AI literacy. To ethically use and implement AI technologies in education, all the stakeholders should be aware of the use and impacts of these technologies. AI literacy involves developing a basic understanding and enhancing skills and competencies to use and implement these technologies [19]. Further, AI literacy can be defined as the ability to understand, interpret, and utilize artificial intelligence technologies effectively [12]. In the context of online proctoring, AI literacy empowers students to comprehend how these systems function, what data they collect, and how they impact the assessment process. With the growth of technology and AI permeating in all fields, it becomes crucial to synthesize contemporary knowledge with a deeper understanding of AI literacy [13]. For example, educators can tweak AI settings to reduce false positives and ensure fair monitoring while human proctors review flagged incidents for accurate assessments. This balanced approach ensures the effective and fair use of AI to maintain academic integrity.
This paper explores AI's theoretical foundations and practical applications in education, focusing on AI-assisted educational practices and strategies to strengthen teacher preparation for AI literacy in school curricula as shown in Figure 1.1. This study, based on the existing previous and current literature, presents arguments for updating teachers' knowledge of AI concepts and technologies, utilizing AI-enhanced technologies for personalized learning, and integrating AI literacy education within the Technological, Pedagogical, and Content Knowledge (TPACK) framework. We discuss the implications of AI-driven content adaptation on assessment design and explore frameworks for integrating AI proctoring tools ethically and effectively into educational practices. By examining these aspects, we aim to provide insights into the evolving role of AI in shaping assessment strategies and academic experiences.
Figure 1.1 AI literacy in shaping assessment strategies and educational experiences.
1.2 AI in Education - Theoretical Framework
In the realm of educational theory, Constructivism and Socio-cultural Theory emphasizes active learning processes and the influence of social interaction and cultural context on knowledge acquisition [20-22]. Constructivism posits that learners construct understanding through engagement with their environment [23], while Socio-cultural Theory underscores the role of social interaction and culture in shaping learning experiences [24]. Both theories advocate for meaningful activities and collaborative learning environments. When applied to assessment, they advocate for assessments mirroring real-world tasks, fostering authentic demonstrations of understanding. AI-powered assessment tools align with these principles by offering personalized, adaptive learning experiences tailored to individual student needs [18]. When integrated with technology, these approaches help foster lifelong learners [25]. As Gen Z are digital natives, using prior knowledge related to technology becomes easier for them [26].
Moreover, Cognitive Load Theory delves into how the human brain processes information and manages cognitive resources, asserting that learners have limited cognitive capacity [27]. In assessment, this theory stresses the importance of minimizing extraneous cognitive load to allow students to focus on demonstrating knowledge and skills [28]. AI-enabled assessment tools provide immediate feedback, scaffold learning experiences, and adjust task difficulty to match students' cognitive abilities. With AI-integrated curricula and assessments, learners are augmented with these technologies, thereby sharing cognitive load capacities between AI and learners, enhancing efficiency in the learning process. Intrinsic cognitive load refers to the type of content to be...
