Adeleh Mazaherian | Searcharxiv

arXiv2025

Unveiling User Perceptions in the Generative AI Era: A Sentiment-Driven Evaluation of AI Educational Apps' Role in Digital Transformation of e-Teaching

The rapid integration of generative artificial intelligence into education has driven digital transformation in e-teaching, yet user perceptions of AI educational apps remain underexplored. This study performs a sentiment-driven evaluation of user reviews from top AI ed-apps on the Google Play Store to assess efficacy, challenges, and pedagogical implications. Our pipeline involved scraping app data and reviews, RoBERTa for binary sentiment classification, GPT-4o for key point extraction, and GPT-5 for synthesizing top positive/negative themes. Apps were categorized into seven types (e.g., homework helpers, math solvers, language tools), with overlaps reflecting multifunctional designs. Results indicate predominantly positive sentiments, with homework apps like Edu AI (95.9% positive) and Answer.AI (92.7%) leading in accuracy, speed, and personalization, while language/LMS apps (e.g., Teacher AI at 21.8% positive) lag due to instability and limited features. Positives emphasize efficiency in brainstorming, problem-solving, and engagement; negatives center on paywalls, inaccuracies, ads, and glitches. Trends show that homework helpers outperform specialized tools, highlighting AI's democratizing potential amid risks of dependency and inequity. The discussion proposes future ecosystems with hybrid AI-human models, VR/AR for immersive learning, and a roadmap for developers (adaptive personalization) and policymakers (monetization regulation for inclusivity). This underscores generative AI's role in advancing e-teaching by enabling ethical refinements that foster equitable, innovative environments. The full dataset is available here(https://github.com/erfan-nourbakhsh/GenAI-EdSent).

cs.CY↗

arXiv2025

Beyond the Hype: Critical Analysis of Student Motivations and Ethical Boundaries in Educational AI Use in Higher Education

The rapid integration of generative artificial intelligence (AI) in higher education since 2023 has outpaced institutional preparedness, creating a persistent gap between student practices and established ethical standards. This paper draws on mixed-method surveys and a focused literature review to examine student motivations, ethical dilemmas, gendered responses, and institutional readiness for AI adoption. We find that 92% of students use AI tools primarily to save time and improve work quality, yet only 36% receive formal guidance, producing a de facto "shadow pedagogy" of unguided workflows. Notably, 18% of students reported integrating AI-constructed material into assignments, which suggests confusion about integrity expectations and compromises the integrity of the assessment. Female students expressed greater concern about abuse and distortion of information than male students, revealing a gendered difference in awareness of risk and AI literacies. Correspondingly, 72% of educators use AI, but only 14% feel at ease doing so, reflecting limited training and uneven policy responses. We argue that institutions must adopt comprehensive AI literacy programs that integrate technical skills and ethical reasoning, alongside clear AI-use policies and assessment practices that promote transparency. The paper proposes an Ethical AI Integration Model centered on literacy, gender-inclusive support, and assessment redesign to guide responsible adoption, protect academic integrity, and foster equitable educational outcomes in an AI-driven landscape.

cs.CY↗