Assessment with Artificial Intelligence in Ibero-American Higher Education: Innovations, Challenges, and Ethical Perspectives

Artificial Intelligence (AI) has emerged as a transformative tool in various sectors, including education. In recent years, its application in teaching-learning processes has made it possible to personalize content, automate administrative tasks and, particularly, innovate assessment methods (Holmes et al., 2019; Luckin et al., 2016). AI-based assessment systems offer new ways to assess learning through automated analytics, immediate feedback, and adaptability to individual learner needs (Chen et al., 2020). However, these innovations have also brought with them several technical, pedagogical, and ethical challenges. Concerns about fairness, algorithm transparency, data privacy, and potential bias in automated systems call for deep reflection on how and under what conditions AI should be employed in educational assessment (Zawacki-Richter et al., 2019; Williamson & Eynon, 2020). As these technologies are integrated into classrooms, it becomes necessary to study their impact, efficacy, and the ethical implications they entail, especially in formal educational contexts where evaluative decisions can have significant effects on students' academic and personal futures (Holmes et al., 2019).

This research topic aims to analyze the main innovations that AI has introduced in educational assessment processes in Ibero-America, identifying its benefits and limitations, as well as to reflect on the ethical challenges associated with its implementation in university school contexts.

Despite the boom in studies on AI in education, most of them come from Anglo-Saxon contexts. There is a significant gap in the literature that analyses the phenomenon from Ibero-American realities, which positions this proposal as a novel and necessary contribution.

In recent years, Ibero-American governments and universities have begun to incorporate AI-based solutions into their education systems. However, there is an urgent need for critical and contextualized research on how these technologies affect assessment processes, teaching practices and student rights. The Ibero-American context offers opportunities for academic collaboration between countries with common historical and linguistic ties, which favors the development of shared frameworks of ethics, public policies and digital pedagogies.

This research topic welcomes articles that address themes such as, but not limited to:

• Exploring generative AI applied to educational evaluation.
• Identifying relevant use cases in the context of Higher Education in Ibero-America.
• Evaluate the pedagogical and operational advantages of AI in learning assessment.
• Analyze the main ethical risks and challenges posed by the use of AI, including privacy, algorithmic bias, transparency and accountability.
• Propose recommendations for an effective and ethical integration of AI in educational assessment processes.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Registered Report
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Artificial Intelligence, Educational Assessment, Automated Assessment, Adaptive Learning, Ethics in Education

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.