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Let’s talk about student data insights. Educators (implicitly and explicitly) track data at many points of teaching--and the data you gather can then guide instruction and improve student learning.

Sensing if the light bulbs are appearing over students’ heads in a classroom discussion or noticing whether or not your students are exhausted and stressed that particular day is core to teaching efficacy. These data points inform an educator on whether to review material in “real-time” or switch directions and pull up a different lesson plan to match your classroom’s energy.

Data insights carry on through assessment via assignments, quizzes, and exams, transforming assessment from an endpoint into a milestone in student learning. What kinds of questions did 95% or 5% of your students get correct (aka were your questions effective in sussing out what your students learned)? How many times was a particular rubric applied (aka what concepts were consistently overlooked)? What was the average score on that particular assessment (aka was your test too easy)?

These insights then help you teach more effectively by shoring up specific and relevant student learning gaps.

In Turnitin’s suite of solutions, Feedback Studio and Gradescope provide student data insights, helping educators to pinpoint and support students who are on the cusp of learning.

If you use Gradescope, item analysis features and increased grading efficiency may encourage you to provide more assessments, which in turn, provide educators with further data to provide specifics insights into ongoing student learning.

What Role Does AI Play at Turnitin?

When it comes to AI in EdTech, there are a lot of factors to consider: bias, transparency, interpretability, accessibility - just to name a few. We tend to weigh these factors by separating our users into two groups: Educators and Students.

In general, our educator tools are designed to give greater context around complex decisions; for example, our authorship features automatically check a new piece of writing against a student’s historical writing based on paper metadata and language stylometrics in real-time and at scale. This information provides important and useful statistics to an instructor or Academic Integrity Officer. Our tool saves significant time in the data collection and aggregation process, allowing the user to spend more time carefully considering the case in front of them using the rich data, all while keeping student anonymity and privacy at the forefront.

In contrast, our student-facing products have to consider that students are in the process of learning, so our goal is not just to provide context, but also feedback that guides and improves their skills and knowledge. For this reason, it’s even more important for our student-facing tools to be “right” - this is why our student-facing product development cycles are generally longer, there are many more considerations and factors!

It’s clear that AI and data play important roles in Turnitin’s products; after all, we were one of the first big data companies in EdTech. Over the years, we’ve built AI to improve student writing (Revision Assistant), assist instructors in grading with speed and consistency (Gradescope), and help Academic Integrity Officers and administrators triage the increasing problem of contract cheating, just to name a few. Underpinning these amazing products is a complex ecosystem of interconnected, cutting-edge AI algorithms developed by our AI teams, ranging from powerful language comprehension machines to state-of-the-art handwriti

Where is AI Headed?

In general, things that are purely Artificial Intelligence are things that aren’t quite possible yet (or might be just getting within reach), while Data Science and Deep Learning are widely accepted and adopted ML technologies. Face detection in your camera, speech recognition on your phone, the Roomba, and automatic sentence completion on Gmail are all examples of things that once were considered AI and have now firmly entered the realm of ML technology.

ML technologies can be used to replace jobs formerly done by people, or they can be used to help people to be even more effective in their lives and work. At Turnitin, we are firmly in the second group - for over twenty years, we’ve built tools that have reduced the burden on teachers and supported students so that more time can be spent on learning. We believe that learning is most effective when it is an interactive activity, and our mission is to build products and experiences that make the process of teaching, learning, and administration more accessible, engaging, and authentic for everyone, whether they are a student, a teacher, or an administrator.

What are Artificial Intelligence and Machine Learning?

Intrigued? We hope so. But, before you dive in, you may be wondering where to begin. The Venn Diagram below illustrates some concepts and nomenclature in the field as they appear to us. While definitions differ somewhat, at Turnitin we define AI as the idea of machines that can think and reason. Within AI, there is a subset of algorithms called “machine learning” or ML, that can make data-driven predictions by finding patterns in historical data.

In the last decade, “Deep Learning” or “Neural Network” machines have superseded many older ML approaches in performance, and are currently considered state-of-the-art in performance in fields ranging from computer vision and natural language understanding to playing complex games like Chess and Go. Finally, there’s a large field called “Data Science,” which is really just applied statistics and ML for data understanding. Data scientists seek to answer questions about and from the data in better and more efficient ways.

Turnitin Tech Talk: Artificial Intelligence and Machine Learning at Turnitin

There are few ideas in our world more pervasive and less defined than “Artificial Intelligence” (AI). From doomsday machines in movies to job-stealing, economic woes in the news, talk of how AI will reshape our personal and professional lives is seemingly everywhere. But AI (or more accurately, a subset of AI called Machine Learning) is also making massive inroads in improving our lives and society: helping to optimize power grids for greater efficiency, understanding internet search queries with near-human intuition to bring the world to our fingertips and helping doctors diagnose diseases with greater accuracy in shorter time just to name a few.

AI is even playing an important role in helping to address the ongoing COVID-19 pandemic, aiding scientists, doctors, and the many front-line workers in tasks ranging from understanding and making predictions from the vast amounts of information worldwide to unraveling the nature of its protein structure, potentially helping to guide the development of novel tests, treatments, and vaccines.

The rapid proliferation of AI into our personal and professional lives has rightly raised many questions and concerns, especially around the issues of data privacy, data ownership and over-reliance on AI. We build our AI systems in close collaboration with our product teams and our top priorities have always remained protecting the privacy of our users and building AI that is as fair, transparent, and unbiased as possible. We closely monitor the behavior of our AIs in production to ensure that they are behaving correctly. Above all, we seek to build AI that never makes a decision for you, but rather helps you make the best and most informed decision possible.

At Turnitin, we take shaping the role of AI and our responsibilities as thought leaders in the EdTech space very seriously. Our world-class AI teams work hard to build AI that complements and extends

At Turnitin, we believe in human-centered AI. This means putting the human user at the center of research, development, and function. We seek to build AI that assists, strengthens, and scales human abilities—not replace them. Our work with AI furthers our mission to ensure that students, educators, and institutions have the power to make data-driven decisions,” states Senior Director of Machine Learning, Eric Wang.

Ivan Bilous is a Machine Learning Software Engineer at Turnitin AI and focused on developing and supporting Turnitin services.

Finally, “At Turnitin, we believe in human-centered AI. This means putting the human user at the center of research, development, and function. We seek to build AI that assists, strengthens, and scales human abilities—not replace them. Our work with AI furthers our mission to ensure that students, educators, and institutions have the power to make data-driven decisions,” states Senior Director of Machine Learning, Eric Wang. Just as education aims to center student learning and uphold authentic voices, so does Turnitin.

Hanna Khanko is a Senior Machine Learning Scientist at Turnitin, where she works primarily on NLP tasks. “Every year new AI technologies revolutionize our lives,” Hanna says, “bringing new incredible solutions across a wide variety of industries. With recent breakthroughs in natural language processing and deep learning, we obtained great instruments for solving complex problems. On the other hand, we face a lot of challenges caused by them, for example, AI writing tools, which can generate high-quality text on any topic or paraphrasing tools that effectively mask plagiarism. I believe that AI can help us to detect such types of cheating and uphold academic integrity. It's great to be involved in this process and develop new solutions that will benefit people around the world.”

Peter Steinberg is Principal Machine Learning Software Engineer where he works on NLP models, psychometrics, exploratory data analysis, and backend engineering to support machine learning services. “I think AI helps us discover hidden patterns and new ways of looking at problems. My hope is that AI can be built into the learning experience to increase fairness, decrease bias, and make learning more efficient and enjoyable,” says Peter.

Saurabh Bipin Chandra is a Machine Learning Scientist, focusing on leveraging AI to improve the instructor grading experience. “AI pushes the boundaries of what can be solved using traditional Computer Vision (at least making it easier!). AI can enable building tools to assist and simplify assessment creation, delivery, and grading for an instructor, thereby giving back time to instructors to focus on what they do best—educate.”

Meet the passionate people who work on Turnitin’s AI

AI, as with all technology, ought to be designed with good intentions, and Turnitin is steadfast in its commitment to responsible AI. At Turnitin, AI is designed to help students, educators, and institutions advance integrity and learning outcomes, at scale.

Because AI relies heavily on its designers and engineers, we want to introduce you to our AI team at Turnitin. We aim to be inclusive and build a diverse team that makes continual improvements to ensure accessibility and fairness. As you read why they feel AI is important to learning and the reasons they dedicate their lives to AI design, we hope you see reflected in their answers Turnitin’s mission to uphold integrity and enable student learning. Because artificial intelligence is, bottom line, as good as its creators.

Who are the people behind Turnitin’s AI?

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Blog

11 min read

Monday 11 October 2021

Meet the passionate people who work on Turnitin’s AI

World AI Week



Christine Lee

Senior Marketing Writer, Adjunct Professor of Writing

“At Turnitin, we believe in human-centered AI. This means putting the human user at the center of research, development, and function. We seek to build AI that assists, strengthens, and scales human abilities—not replace them. Our work with AI furthers our mission to ensure that students, educators, and institutions have the power to make data-driven decisions,” states Senior Director of Machine Learning, Eric Wang.

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