May 6, 2025, by Ben Atkinson

AI and Optical Character Recognition (OCR) in PDF Learning Resources

AI and Pedagogy: Exploring the Role of OCR in Enhancing Research and Learning

Throughout May, this series of posts will examine the evolving relationship between artificial intelligence (AI) and pedagogy, with particular focus on emerging tools and methods that enhance teaching, learning, and research productivity. In this initial post, we explore recent advancements in Optical Character Recognition (OCR) technology—specifically its growing accessibility and implications for academic work.

The Role of OCR in Academic Contexts

OCR, a long-established technology, enables the conversion of scanned images or photographs of text into machine-readable formats. Historically, its application has been limited within educational settings due to the reliance on proprietary software and technical complexity. As a result, OCR has often been inaccessible to many research students and educators, particularly those without institutional licenses or technical expertise.

Recent Developments: Google Chrome’s Native OCR Integration

In April, Google introduced a significant enhancement to its Chrome browser: a built-in OCR feature labeled “Get What You Need From Scanned PDFs.” Previously, Chrome allowed users to view PDFs but did not support text selection, searchability, or screen reader functionality in scanned or image-based PDF files. These limitations particularly affected students and researchers working with digitized print materials, as well as those relying on assistive technologies.

The new OCR integration now enables Chrome to automatically recognise and convert scanned text, rendering it interactive. Users can search, highlight, copy, and employ screen readers with these documents—capabilities that were previously limited to digitally created PDFs (e.g., those authored in Microsoft Word or other word processors). Google summarizes the update as follows:

“Previously, if you opened a scanned PDF in your desktop Chrome browser, you wouldn’t be able to use your screen reader to interact with it. Now with Optical Character Recognition (OCR), Chrome automatically recognizes these types of PDFs, so you can highlight, copy and search for text like any other page and use your screen reader to read them.”

This enhancement has meaningful implications for academic work. Accessing and referencing text from scanned materials such as book chapters or journal articles no longer requires manual transcription—reducing the likelihood of transcription errors and improving research efficiency. Furthermore, the ability to search scanned PDFs enables quicker identification of key themes and passages, facilitating more effective engagement with source material.

The Emergence of AI-Powered OCR Tools

In parallel with browser-based developments, numerous AI-driven tools are emerging that combine OCR capabilities with natural language processing. These tools not only convert scanned PDFs into searchable text or HTML formats but also allow for further semantic analysis. While the accuracy and reliability of such tools can vary, their utility in academic research is increasingly evident, particularly when applied to large volumes of archival or print-based content.

Importantly, having access to machine-readable versions of scanned documents enables researchers to leverage additional AI tools for analysis, summarisation, or knowledge synthesis. In forthcoming posts, we will explore how this approach—particularly when combined with tools such as Google NotebookLM—can significantly enhance research workflows for postgraduate students and academic staff.

 

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