Rethinking assessment in response to generative artificial intelligence

Abstract

By considering the significant implications of generative AI for assessment, the authors suggest reclaiming oral assessment, when there is value in assessing unassisted understanding, and embracing AI for assisted assessment.

Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review

“…Generative AI models’ impressive performances on diverse standardized assessments in medical education not only demonstrate the abilities of these tools but also suggest a reevaluation of our current assessment methods. This sentiment aligns with the viewpoint of Pearce and Chiavoroli [ 30 ] that we must rethink our learner assessment methods in a world where generative AI is increasingly prevalent. Even though the quality of these assessments might remain the same, their relevance needs reconsideration in an era when a chatbot can effortlessly provide answers to multiple choice questions.…”

“…An overdependence on this technology could potentially curtail learners’ capacities for critical thinking and intricate problem-solving [ 15 , 24 , 25 , 36 ]. As AI usage becomes increasingly prevalent among learners, there may be a need to adapt assessment methods, given the potential effects on the validity of knowledge evaluations [ 30 , 46 ].…”

La inteligencia artificial generativa y la evaluación: ¿Qué pasará con los exámenes?

“…1 . Las sofisticadas herramientas de la inteligencia artificial generativa (IAGen), como ChatGPT, continúan creando muchas inquietudes en docentes e instituciones, ya que introducen aspectos éticos, técnicos y académicos que siguen sin tener una respuesta definida que satisfaga a todos los actores del proceso educativo 2,3 . Una de las áreas más controversiales es la que tiene que ver con los retos de evaluación del y para el aprendizaje que surgen con la IAGen.…”

“…De esta forma se genera un equipo colaborativo profesorado-estudiantado que se involucra en un proceso continuo de aprendizaje sobre el uso efectivo, ético y sensato de las herramientas, al mismo tiempo que se mantiene actualizado en el tema. Por supuesto que deben tomarse en cuenta las limitaciones de la IAGen, como son las alucinaciones y la confianza con la que afirma datos que pueden ser falsos e incorrectos 2,3 .…”

Large language models in physical therapy: time to adapt and adept

“…It is defined as a branch of ML that translates innovative content in the form of text, images, and audio-visual into computer codes ( 8 ). Generative AI ranges of standardized assessments in medical education not only underscore their capabilities but also prompt a reconsideration of our existing evaluation methods ( 9 ). Generative AI delves into the burgeoning field of generative AI and its applications within the medical domain.…”