# Guide Recommends AI Tools To Improve Student Study > Source: > Published: 2026-05-30 22:20:11.678852+00:00 # Guide Recommends AI Tools To Improve Student Study SmashingApps published a guide titled "Best AI Tools for Students in 2026" that highlights AI products intended to help students learn and research more efficiently. The guide recommends **NotebookLM**, **Claude.ai** (free), **Anki** with AI-generated cards, **Otter.ai**, and **Perplexity AI** (free), and emphasizes using these tools to learn and understand material rather than to produce work the student cannot explain, according to the article. The piece frames AI as a study aid that accelerates comprehension, flags academic integrity concerns, and advises ethical use in line with university rules. ### What happened SmashingApps published a guide called "Best AI Tools for Students in 2026" that lists recommended consumer tools for study and research. The article highlights **NotebookLM** as best for research with source uploads and cited answers, **Claude.ai** (free) for explaining hard concepts, **Anki** with AI-generated cards for memorization, **Otter.ai** for lecture transcription and highlights, and **Perplexity AI** (free) for quick research with cited sources. The guide explicitly states these tools are intended to help students understand material, and it warns against submitting AI-generated work a student cannot explain. ### Editorial analysis - technical context The tools named illustrate two technical themes common in education-focused AI: retrieval-augmented study environments and automation of low-value study tasks. Retrieval-augmented tools like **NotebookLM** and **Perplexity AI** combine source ingestion with citation-capable answers, while transcription and summarization services such as **Otter.ai** reduce note-taking overhead. Flashcard generation workflows, as with AI-assisted **Anki** decks, automate spaced-repetition content creation. These are generic industry patterns, not claims about any vendor roadmap. ### Industry context Observers of education technology note that combining comprehension aids and workflow automation shifts where student effort is spent, from mechanical tasks to higher-order reasoning. Widespread adoption of such tools tends to increase demand for assessment methods that verify conceptual mastery rather than surface-level output. Academic-integrity debates remain central, and platform-level citation and provenance features are increasingly marketed as mitigation tools. ### What to watch - •Uptake of citation and provenance features in student-facing tools, which alter how instructors verify sources. - •Integration of transcription and summarization into learning management systems, which changes note-sharing norms. - •Institutional policy updates on permissible AI use in coursework, which will affect instructional design and assessment. ## Scoring Rationale This is a practical, consumer-focused roundup with limited direct relevance to ML practitioners. It is useful for education-technology observers but does not introduce new models, architectures, or industry-changing developments. Practice interview problems based on real data 1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with. [Try 250 free problems](/problems)