[論文レビュー] Generative AI in Education: A Study of Educators' Awareness, Sentiments, and Influencing Factors

Aashish Ghimire, James Prather+1 more|arXiv (Cornell University)|Mar 22, 2024

Diverse Approaches in Healthcare and Education Studies被引用数 14

ひとこと要約

本研究は大学教員を対象に、Generative AIとLLMsに対する認識、感情、および態度の推進要因を調査し、分野や慣れの差はあるものの全体的には肯定的な態度が示された。CS教育者は非CSの同僚と比較して技術的理解と感情が高いことを示している。

ABSTRACT

The rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. This study delves into university instructors' experiences and attitudes toward AI language models, filling a gap in the literature by analyzing educators' perspectives on AI's role in the classroom and its potential impacts on teaching and learning. The objective of this research is to investigate the level of awareness, overall sentiment towardsadoption, and the factors influencing these attitudes for LLMs and generative AI-based tools in higher education. Data was collected through a survey using a Likert scale, which was complemented by follow-up interviews to gain a more nuanced understanding of the instructors' viewpoints. The collected data was processed using statistical and thematic analysis techniques. Our findings reveal that educators are increasingly aware of and generally positive towards these tools. We find no correlation between teaching style and attitude toward generative AI. Finally, while CS educators show far more confidence in their technical understanding of generative AI tools and more positivity towards them than educators in other fields, they show no more confidence in their ability to detect AI-generated work.

研究の動機と目的

• 部門を超えてGenerative AIツールに対する教育者の認識を評価する。
• 教育現場でAIツールの採用に対する教育者の感情を評価する。
• Generative AIに対する教師の態度の差異に影響を与える要因を特定する。
• CS教育者と非CS教育者の態度を比較する。
• 教室でのAIに関して教育者が挙げる機会と懸念を明らかにする。

提案手法

• Likertスケールの調査と任意の追跡インタビューを組み合わせた混合研究デザイン。
• 記述統計、推定検定、回帰分析を用いた定量分析。
• 質的インタビューのコーディングにはグラウンデッド・セオリー手法を用い、評定者間信頼性を85%を超える。
• 質的・定量的結果を統合して教員の態度を三角測定する。

実験結果

リサーチクエスチョン

• RQ1 RQ1 How aware are educators of Generative AI-based tools across various departments?
• RQ2 RQ2 What are educators’ perceptions and sentiments about these AI tools?
• RQ3 RQ3 What factors contribute to variations in teachers’ attitudes toward generative AI based tools?
• RQ4 RQ4 How do the attitudes and perceptions of CS educators differ from those of educators in different departments?
• RQ5 RQ5 What are the biggest opportunities and concerns identified by the educators?

主な発見

• Most educators have heard of or tried Generative AI tools, with over 40% using them periodically or regularly.
• Overall sentiment toward AI tools is positive (mean 3.99; median 4.5; third quartile 5).
• CS educators show higher technical understanding (83% vs 10% non-CS) and higher familiarity (M=4, SD=.71 vs M=3.15, SD=1.08).
• CS instructors are more confident in students' use of tools (M=4.22) than non-CS instructors (M=3.23).
• Top factors shaping sentiment: benefits outweigh risks, perceived educational quality gains, and ease of integration positively influence attitudes; concerns about creativity loss and cheating negatively influence attitudes.
• Regression analyses (Linear, Random Forest, Gradient Boost, XGBoost) yield MSEs between 0.4 and 0.5 for predicting sentiment based on identified features.]
• table_headers:[]
• table_rows:[]} } }```
• table_headers: []
• table_rows: []} }}}```
• table_headers: []
• table_rows: []} </GeneratedReview>