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AI-Enhanced Assessment Methods in Education: Innovations and Challenges

EasyChair Preprint no. 14027

8 pagesDate: July 18, 2024

Abstract

AI-enhanced assessment methods in education offer innovative ways to evaluate student learning by providing personalized feedback and adaptive testing environments. These technologies can analyze student performance in real time, allowing educators to identify strengths and areas for improvement more accurately. AI-driven assessments can support diverse learning styles by customizing questions and resources to fit individual needs. However, challenges remain, such as ensuring data privacy, maintaining assessment fairness, and addressing potential biases in AI algorithms. Balancing technological advancements with ethical considerations is crucial for successfully integrating AI into educational assessment practices. This approach holds the promise of more equitable and effective evaluation systems.

Keyphrases: Artificial Intelligence (AI), Education, pedagogical approaches

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:14027,
  author = {James Henry and Asher Daniel},
  title = {AI-Enhanced Assessment Methods in Education: Innovations and Challenges},
  howpublished = {EasyChair Preprint no. 14027},

  year = {EasyChair, 2024}}
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