Public Expenditures on Education and Health in Georgia Before and During the Global Crisis

Chitanava, Maka; Grigolia, Maya; Labadze, Lasha

doi:10.2139/ssrn.1895411

Cited by 1 publication

(1 citation statement)

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“…This allows for more precise feedback on strengths and weaknesses, offering students a deeper understanding of their learning progress. [5] In their review of AI in education 2010-2020, acknowledge the potential of AI to personalize learning experiences, potentially leading to improved outcomes. [6] ( Previous research highlights the positive impact of AI-driven feedback in formative assessment.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Self-Assessment through AI-Driven Questioner: AStudy on Efficacy and User Experience

2024

IRJMETS

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Assessments play a pivotal role in students' educational journeys, providing vital feedback on their understanding and progress. However, as learning increasingly transitions to digital platforms, traditional assessment methods often take a backseat, leaving a void in comprehensive self-assessment practices. This research explores the efficacy and user experience of enhancing self-assessment through the integration of an AI-based Questioner system in digital learning environments.In the context of self-study, where learners engage with educational content independently, the absence of structured assessments can hinder their ability to gauge comprehension and identify learning gaps. By leveraging AI-driven technologies, such as artificial intelligence (AI) and machine learning algorithms, the AIbased Questioner serves as a dynamic tool that actively engages learners in self-assessment activities while they engage with digital resources such as lectures or PDFs.This study investigates the effectiveness of AI-based self-assessment tools in comparison to traditional classroom-based assessments. It examines how students who engage in self-study, relying on AI-Based Questioner for assessment, fare in terms of learning outcomes compared to their counterparts in traditional classroom settings. Through a mixed-methods approach, incorporating quantitative analysis of user interaction data and qualitative feedback from participants, this research evaluates the impact of AI-driven interventions on learners' self-assessment practices and overall learning experiences.The findings of this study shed light on the potential of AI-based Questioner systems to enhance self-study and self-assessment practices in digital learning environments. By providing learners with personalized and timely feedback, the AI-based Questioner promotes active engagement and fosters metacognitive awareness.Ultimately, this research contributes to advancing our understanding of how technology can support learners in evaluating their own learning progress and fostering independent learning skills. By harnessing the power of AI-based Questioners, educators, and instructional designers can create more adaptive and learner-centric digital learning environments, empowering students to take ownership of their learning journeys.

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Section: Literature Reviewmentioning

confidence: 99%

Enhancing Self-Assessment through AI-Driven Questioner: AStudy on Efficacy and User Experience

2024

IRJMETS

View full text Add to dashboard Cite

show abstract

Public Expenditures on Education and Health in Georgia Before and During the Global Crisis

Cited by 1 publication

References 3 publications

Enhancing Self-Assessment through AI-Driven Questioner: AStudy on Efficacy and User Experience

Enhancing Self-Assessment through AI-Driven Questioner: AStudy on Efficacy and User Experience

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