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ARXIV:2605.13532 · GENERATIVE AI TOOLS · SUBMITTED 14 MAY · 20:10 UTC · FRESHNESS FRESH
ARXIV:2605.13532GENERATIVE AI TOOLSSUBMITTED 14 MAY · 20:10 UTCFRESHNESS FRESHJuho Leinonen · Lisa Zhang · Arto Hellas · arXiv
Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides.
Opportunity summary
Pain Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides.
Evidence 0 refs | 0 sources | 0% coverage
Blocker Evidence unverified
Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides. To that end, this paper examines using GenAI…
As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines using GenAI to help generate slides from instructor authored course…
ScienceToStartup currently rates this 4.0/10 on the public viability pass. As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors.
Generative AI Tools moved forward this cycle; last verified May 2026. Public score 4.0/10.
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Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides.
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10.48550/arXiv.2605.13532Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides.
Abstract
As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines using GenAI to help generate slides from instructor authored course notes, emphasizing instructor and student perceptions. We examine an end-to-end education tool (NotebookLM), two general-purpose LLMs (Claude, M365 Copilot), and two coding assistants (Cursor, Claude Code). We first analyze whether GenAI generated slides are ``good'' via narrative assessment by educators. We choose the best slides to use (with some modification) in a real course setting, and compare the student perception of human vs. AI generated slides. We find that coding assistant tools produce slides that were most accurate, complete, and pedagogically sound. Additionally, students rate GenAI slides to be of similar quality as instructor-created slides, and cannot reliably identify which slides are AI-generated. Additionally, we find a negative correlation between a high quality rating and a high ``AI-generated'' rating, suggesting students associate poor quality with the source of the slides being AI. These findings highlight promising opportunities for integrating GenAI into instructional design workflows and call for further research on how educators can best harness such tools responsibly and effectively.
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PROBLEM
Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides. To that end, this paper examines using GenAI to help generate...
METHOD
As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines using GenAI to help generate slides from instructor authored course notes, emphasizing instructor and student perceptions.
RESULT
ScienceToStartup currently rates this 4.0/10 on the public viability pass. As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors.
WHY NOW
Generative AI Tools moved forward this cycle; last verified May 2026. Public score 4.0/10.
Abstract-backed public claims while anchored extraction refreshes.
Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides. To that end, this paper examines using GenAI to help generate slides from instructor authored course notes, emphasizing instructor and student perceptions.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines using GenAI to help generate slides from instructor authored course notes, emphasizing instructor and student perceptions.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 4.0/10 on the public viability pass. As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Generative AI Tools moved forward this cycle; last verified May 2026. Public score 4.0/10.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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Investigating the quality of AI-generated presentation slides and student perception, finding coding assistants produce the best results and students cannot reliably distinguish AI-generated from human-created slides.
Segment
Generative AI Tools
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Commercial read
4.0/10 public viability
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proof status
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