About this Research Topic
The omnipresence of artificial intelligence (AI) in modern education presents unprecedented opportunities and challenges. Regardless of whether educators formally adopt AI, students are increasingly utilizing these tools, prompting a significant shift in traditional educational paradigms. This evolution raises critical questions about the nature of assessment, the skills that should be nurtured and evaluated, and the ethical implications of AI in education. Noteworthy is the potential of low-cost AI to provide accommodations for differently-abled learners, democratizing access to education. This scenario necessitates a re-evaluation of conventional assessment methods, urging educators to consider how AI can enhance educational equity, foster diverse skill sets, and redefine the metrics of academic success. The integration of AI in assessment alters how we evaluate learning and challenges our understanding of what constitutes valuable knowledge and competencies in the digital age.
This research aims to investigate how artificial intelligence (AI) can improve both formative and summative assessment practices in education and what shifts in pedagogy and assessment methodology are required to realize these improvements. The focus is on critically examining the transformative influence of AI on traditional assessment approaches, exploring how it can broaden and enhance the evaluation of learner abilities and knowledge. This entails thoroughly exploring AI's role in creating more dynamic, inclusive, and effective assessment strategies suitable for diverse learning environments. Additionally, the research will address the ethical implications and challenges associated with integrating AI into educational assessments, including issues of academic integrity and potential biases in AI algorithms. Particular attention will be given to developing AI tools that cater to the needs of differently-abled learners, thereby advancing accessibility in education. The goal is to provide actionable insights and recommendations for educators and policymakers in higher education to harness AI's potential in formative and summative assessments, ultimately leading to a significant shift in educational practices, and thus a more adaptive, fair, and comprehensive evaluation system.
The proposed research topic aims to delve into the dynamic landscape of educational evaluation in the context of the rapidly evolving field of Artificial Intelligence (AI). As AI technologies continue to permeate various aspects of education, understanding their impact on evaluation practices becomes crucial for ensuring effective and meaningful assessments. In line with this, the following themes are envisioned:
- Enhancement of assessment practices;
- Dynamic and inclusive assessment strategies;
- Ethical implications and challenges;
- Best practices: Actionable insights and recommendations.
The proposed research topic aims to encapsulate the following types of contributions:
- Technical;
- Case studies;
- Conceptual;
- Ethical;
- Meta-analyses;
- Systematic reviews.
This research aims to investigate how artificial intelligence (AI) can improve both formative and summative assessment practices in education and what shifts in pedagogy and assessment methodology are required to realize these improvements. The focus is on critically examining the transformative influence of AI on traditional assessment approaches, exploring how it can broaden and enhance the evaluation of learner abilities and knowledge. This entails thoroughly exploring AI's role in creating more dynamic, inclusive, and effective assessment strategies suitable for diverse learning environments. Additionally, the research will address the ethical implications and challenges associated with integrating AI into educational assessments, including issues of academic integrity and potential biases in AI algorithms. Particular attention will be given to developing AI tools that cater to the needs of differently-abled learners, thereby advancing accessibility in education. The goal is to provide actionable insights and recommendations for educators and policymakers in higher education to harness AI's potential in formative and summative assessments, ultimately leading to a significant shift in educational practices, and thus a more adaptive, fair, and comprehensive evaluation system.
The proposed research topic aims to delve into the dynamic landscape of educational evaluation in the context of the rapidly evolving field of Artificial Intelligence (AI). As AI technologies continue to permeate various aspects of education, understanding their impact on evaluation practices becomes crucial for ensuring effective and meaningful assessments. In line with this, the following themes are envisioned:
- Enhancement of assessment practices;
- Dynamic and inclusive assessment strategies;
- Ethical implications and challenges;
- Best practices: Actionable insights and recommendations.
The proposed research topic aims to encapsulate the following types of contributions:
- Technical;
- Case studies;
- Conceptual;
- Ethical;
- Meta-analyses;
- Systematic reviews.
Keywords: Artificial Intelligence, Educational Assessment, Ethical Considerations in AI, AI in Learning Analytics, Teaching Methodologies and AI, Opportunities in AI Evaluation, Challenges in AI Assessment, AI and Academic Integrity, AI's Role in Student Evaluation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
