How to Cite AI in APA, MLA, and Chicago

How to cite AI in APA, MLA, and Chicago with examples and templates

Using generative AI tools is pretty cool because they can help improve your writing or you can make images, videos, and audio of basically anything you can think of. But then APA, MLA, and Chicago citation styles* showed up with a bunch of rules and policies we have to follow.

*fun-ruiners

The good news? This article has examples and copy/paste templates for citing AI in each style.

We’ll update this page as the citation guidelines change (which is pretty often) so save the link/bookmark it for quick reference. To bookmark, press Ctrl+D (Windows) or Cmd+D (Mac).

Links to share specific sections with learners

Copy the link to a citation style to share with your learners.

  • APA: honorlock.com/blog/how-to-cite-ai/#apa
  • MLA: honorlock.com/blog/how-to-cite-ai/#mla
  • Chicago: honorlock.com/blog/how-to-cite-ai/#chicago

Share links to specific sections with your learners

  • APA: honorlock.com/blog/how-to-cite-ai/#apa
  • MLA: honorlock.com/blog/how-to-cite-ai/#mla
  • Chicago: honorlock.com/blog/how-to-cite-ai/#chicago

How to cite AI in APA

APA AI citation format examples

Citing AI-generated text in APA

Reference list entry
  • Template: Author. (Date). Title (Month Day version) [Additional Descriptions]. Source
  • Example: OpenAI. (2025). ChatGPT (May 14 version) [Large language model]. https://chatgpt.com/
In-text citations
  • Parenthetical citation: (Author, Year) (OpenAI, 2025)
  • Narrative citation: Author (Year) OpenAI (2025)
Context for each part of the APA AI citation template​
  • Author: The company that owns the AI tool (e.g., OpenAI owns ChatGPT)
  • Date: The year of the version you used.
  • Title: The name of the model (e.g. ChatGPT, Claude, Gemini). The version number is included after the title in parentheses. According to APA, you don’t need to include the specific version, like ChatGPT-3 or ChatGPT-4, in the title because “ChatGPT” is the general name.
  • Bracketed text: Describe the type of AI model. We used "Large language model" in the example above because that's how OpenAI refers to ChatGPT. If it's an AI tool that creates images or videos, use "AI image generator" or "AI video generator"
  • Source: Use a link that takes readers directly to the tool or model, not just the company’s homepage. For example, link them to https://chatgpt.com/ instead of https://openai.com/.

How to cite AI generated images and videos in APA

APA hasn’t published specific guidelines for citing AI-generated images or videos, but you can cite them in a format similar to the examples below.

Example APA citations for AI images:
  • Reference: Krea. (2025). Krea (Idealogram 3.0) [AI image generator]. https://www.krea.ai/image
  • In-text citations: Krea (2025) or (Krea, 2025)
  • Add a note that’s similar to the one under this AI-generated image of a chameleon.
Example APA citations for AI videos
  • Reference: OpenAI. (2025). ChatGPT (Sora) [AI video generator]. https://sora.chatgpt.com/
  • In-text citations: Open AI (2025) or (Open AI, 2025)
AI-generated image of a chameleon walking on a green leaf covered in water droplets with a rainforest background.
Note. Image generated using the prompt “Create a photorealistic close-up image of a chameleon walking on a leaf,” by Krea, Idealogram 3.0, 2025 (https://www.krea.ai/image)

Key points to know about APA policies for citing AI

Here are important points to know about APA policy guidelines for citing AI-generated content by ChatGPT, Claude, and Gemini.

How does APAP define AI?

APA defines AI as generative LLM tools, but it doesn’t include other forms of AI tools, such as grammar checkers, citation tools, or plagiarism detectors.

What to do if you cite AI in an APA publication

If you cite AI in an APA publication, you need to: 

  • Cite it using the software citation format
  • Disclose it in the Methods section
  • Upload the full output of the AI in an appendix or as supplemental material, including the prompts you used

You can use AI for editing, but you need to disclose how it was used.

AI can’t be listed as an author on research papers

According to APA guidelines, AI tools like ChatGPT and Gemini can’t be listed as authors because they don’t meet authorship criteria since they can’t take responsibility for the work or consent to its publication.

Author responsibility

Authors are entirely responsible for verifying the accuracy of all AI-generated content, which includes text and any citations it provides.

NEW ebook: How to Prevent Chatbot Cheating

6-part ebook with everything you need to know about chatbots and how to control if, how, and when they’re used in online learning.

How to cite AI in MLA

MLA formatting AI examples

How to cite AI-generated text in MLA

Works cited MLA AI citation
  • Template: “Prompt text” prompt. Title of Container, Day Month version, Publisher, Day Month Year, location.
  • Example: “Explain how Edgar Allan Poe used alliteration in his writing” prompt. ChatGPT, 14 May version, OpenAI, 20 May 2025, https://chatgpt.com/.
MLA AI in-text citation example:
  • (“Explain how Edgar Allan Poe used alliteration in his writing”)
Context for each part of the MLA AI citation template​
  • Prompt text (Title of Source): Add the prompt you used or briefly describe what the AI tool generated. 
  • Title of Container: The name of the AI tool (e.g., ChatGPT, Claude, etc.)
  • Version: Include the AI tool version and the release date, if it's available.
  • Publisher: Company that made the AI tool (e.g., OpenAI, Anthropic, etc.)
  • Date: The date the content was generated
  • Location: URL for the AI tool.

How to cite AI-generated images in MLA

AI-generated images require a caption that includes a description of the prompt along with the AI tool, version, and date the image was created.

The text below the image of the napping golden retriever shows how to cite an image generated with ChatGPT’s image generation tool, DALLE-3.

DALL-E lets users create a shareable link. If you use a shareable link, include that specific URL instead of the general site link.

Oil painting of a golden retriever sleeping on a brown couch.
Fig. 1. “Oil painting of a golden retriever napping on a couch” prompt, DALL·E, version 3, OpenAI, 20 May 2025, https://chat.openai.com/.

Key points to know about MLA guidelines for citing AI

Here are a few key points to know about citing generative AI in MLA:

How does MLA define AI?

MLA defines generative AI as a tool that can as a tool that analyzes and/or summarizes content from a set of information available on the internet (e.g., web pages, books, and other writing), and uses that information to generate original content.

Be transparent about how you use generative AI in your work

Always cite when and how you use generative AI tools, whether it’s paraphrasing, quoting, translating, or generating content like text, images, video, and even code or data.

However, if you use an AI tool to find a source, just cite the source itself; you don’t need to cite that you used the AI tool specifically to find that source or that you found it through the tool. For example, if Google Gemini directs you to a research study that you use in your work, you’d only cite the research study, not Google Gemini.

Do not treat the AI tool as an author

MLA guidelines are clear that AI can’t be listed as authors.

Author responsibility

Similar to APA guidelines, MLA indicates that it’s up to the author(s) to verify any AI-generated content used in their work.

How to cite AI in Chicago Style

Citing AI in Chicago style is less rigid than APA and MLA. Chicago says to cite AI content in a note, not in the bibliography because the chat can’t be shared like a source. But some AI tools offer shareable links, so this rule MIGHT change.

Example AI citations in Chicago

In most cases, you can simply acknowledge the AI tool in your text (e.g., “The list of tropical fish was generated by ChatGPT”).

However, if you need a more formal citation for a research paper, for example, you’d add a numbered footnote or endnote like this: Text generated by Claude, Anthropic, May 20, 2025, https://claude.ai/.

If you’ve edited the AI-generated text, just mention it at the end of the note, like this: Text generated by Claude, Anthropic, May 20, 2025, https://claude.ai/. Edited for style and content.

Detecting and preventing AI cheating

If you have concerns about chatbot cheating, you aren’t alone. While AI detectors and plagiarism checkers tools won’t really help because they’re ineffective when AI-generated text is edited, remote proctoring software can detect and block AI tools during exams and written assignments.

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ChatGPT vs. Honorlock Online Proctoring

Using online proctoring services to stop students from cheating with ChatGPT

ChatGPT has had educators nervous since it became available to the public in the fall of 2022. It wasn’t the first generative AI chatbot, but it was the one that got everyone’s attention. Since then, many similar AI chatbots have popped up, like Gemini and Claude, and other chatbot-like tools such as Perplexity and NotebookLM are gaining popularity.

And people use chatbots for just about everything now. They can write everything from long-form essays to punny jokes, solve math problems, summarize and simplify text, and write code. Some even use them to organize their schedule or just to vent about their day.

The problem is that ChatGPT and other chatbots have been used to cheat on exams (which is why you’re here). ChatGPT is highly capable and there are very few exams it can’t help with.

Early-ish versions of ChatGPT passed these exams

ChatGPT exam scores for UBI, CPA, LSAT, and GRE

2025 Guide to Preventing Chatbot Cheating

6-part guide on how chatbots work, ways to use them in courses, how to prevent cheating, and guidance to help start AI initiatives.

Book with text saying Guide to Preventing Chatbot Cheating

Can ChatGPT be detected as plagiarism?

Plagiarism tools can’t reliably detect ChatGPT because they look for text that’s copied exactly from the source or looks pretty similar to it. That’s a big problem because ChatGPT doesn’t just copy from the resources it was trained on, like websites, research studies, news, code, etc.

It’s similar to how you learn from all kinds of different sources. But if someone asks you a question about it, you don’t just recite answers word for word. You put it into your own words, make connections, and you can explain it differently depending on who you’re talking to. It isn’t an perfect analogy, but that’s the gist of how ChatGPT works and why plagiarism detection doesn’t.

Can AI detectors detect ChatGPT?

If a student copies text directly from ChatGPT without making any edits, AI detectors are usually accurate. But realistically, students will probably make a few changes before submitting. Once AI-generated text is altered, even if another AI tool is used to make the changes, the accuracy of AI detection decreases (Liu et al., 2024; Weber-Wulff et al., 2023).

How does AI detection work?

AI detection assesses how predictable the writing is (perplexity), how sentence length and structure vary, and whether it sounds a little too “cookie cutter.”

Human writing usually has more variety and specific details, so when text is predictable or the sentences are all a similar length, AI detectors might flag it as AI-generated.

What is an acceptable AI detection score?

That’s the million dollar question, but there’s no real answer. Whether the AI detector indicates that the text is 10%, 30%, or 85% AI-generated, educators have to make that call.

How can Honorlock’s online proctoring software prevent the use of ChatGPT for written assignments?

Honorlock’s hybrid proctoring solution prevents the use of ChatGPT using a combination of AI and live proctors. Some of the proctoring features we use to control AI chatbots are covered below.

Detect cell phones and other secondary devices

Several of Honorlock’s remote proctoring features work together to detect cell phones and other secondary devices (other laptops, tablets, smartwatches, etc.), so you don’t have to rely on a live proctor to catch it in real time.

Honorlock detects when test takers try to access test bank content using a cell phone or other device, and it uses exclusive AI-powered Apple Handoff technology to spot nearby Apple devices during the exam.

Lock the browser

With Honorlock’s BrowserGuard, instructors can block access to all external resources, like websites, applications (like ChatGPT), and browsers—or allow access to specific resources, like research journals and case studies, software such as Word, or other online word precessors like Google Docs.

This gives educators the flexibility to allow learners to access supplemental materials while still securing it from unauthorized use of chatbots and other AI writing.

Honorlock’s BrowserGuard also records the participants’ desktops and prevents keyboard shortcuts, like copying and pasting. If copy/paste is attempted, the participant receives a notification that it isn’t allowed and the AI marks it as a medium flag.

However, locking the browser is just one piece of the puzzle to preventing chatbot cheating. If you’re only using browser lockdown software, there’s no way to know if someone is:

  • Using a phone to access ChatGPT or browse the internet
  • Asking Siri or Alexa to access apps/sites
  • Having someone else write the essay or take the exam
  • Typing what a friend is reading to them from off-camera
Use smart voice detection

If your proctoring platform doesn’t have smart voice detection, participants can use voice assistants like Siri or Alexa to open ChatGPT, ask questions, and have the answers read aloud.

Honorlock’s Smart Voice Detection listens for specific keywords or phrases, like “Hey Siri” or “OK Google,” and it records and transcribes audio while the exam is in progress. If it detects potentially dishonest behavior, a live proctor is alerted to review the situation and intervene if necessary.

Scan the room and record behavior

Honorlock’s remote proctoring platform makes it quick to check the room for unauthorized resources, like cell phones, notes, and even other people. And our platform monitors and records behavior throughout the exam.

This way, you’ll know that test takers aren’t accessing ChatGPT from other devices, using their notes, or asking other people for help.

Set the amount of time they have to write the essay once they begin

Instructors can create rules that specify a certain number of hours participants have to complete the written assignment once they begin. Honorlock’s remote proctoring software and services are available 24/7/365, so they can write their essays anytime they’re ready within your set time frame, and you’ll know it’s being proctored.

Get More Info
Other online proctoring tools from Honorlock
Live Pop-In® (AI + live proctoring)

Honorlock’s Live Pop-In secures online assessments and assignments with a hybrid proctoring approach that uses AI to monitor the test environment and behavior, and a live proctor reviews anything the AI flags to determine if they need to intervene or not.

The AI monitors exams and assignments and alerts a live proctor if something looks suspicious. The proctor reviews the situation and only steps in if absolutely necessary, so test takers aren’t interrupted unless there’s a real concern. Our blended proctoring solution delivers a less intimidating and non-invasive experience for participants.

Finds leaked test content on the internet
Honorlock’s Search and Destroy™ technology scours the internet automatically for leaked test content and gives instructors the ability to send takedown requests with one click. This way, you’ll know your test content isn’t available on sites like Quizlet, Chegg, Reddit, and Quora.
Verifies test takers’ identity

You need to know that the person taking the proctored exam is the same person getting credit in the class. Honorlock’s ID verification takes about 60 seconds. It captures a picture of the test-taker along with their photo ID.

Stay ahead of AI cheating

ChatGPT and many of the AI chatbots are powerful tools that have advantages and disadvantages in online learning. Use Honorlock’s solution to stay ahead of the curve and in control of if, how, and when chatbots and other AI are used in your courses and assessments. 

Fill out the form to see how Honorlock works.

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Tyler Stike

Tyler is Honorlock's Director of Content and a doctoral student at the University of Florida focused on educational technology.

AI Prompting Examples, Templates, and Tips For Educators

Text says AI Prompting 101 For Education. Examples and Templates

Prompt engineering is a complex, delicate art form that requires sophisticated training and ongoing, dedicated effort. Even then, only a prestigious few can hope to master advanced AI prompting techniques… Sike.

Writing effective prompts is actually pretty simple if you’re clear, specific, and provide the chatbot with context.We cover the basics below and reveal the latest prompting technique, Quad-shotting, and you can skip to the prompt examples, templates, and tips.

What is a prompt?

A prompt is the message you type into a chatbot or other generative AI to tell it what you want. Prompts can be a question, requesting help, or giving it a task like summarizing text, generating code, and even translating text to other languages.

What is prompt engineering?

Prompt engineering is just how to write your requests to get the response you’re looking for from a chatbot. “Engineering” makes it sound like a really technical (sometimes it can be), but for most educators’ use cases, you just need to be clear and specific about what you want and provide details to help the chatbot tailor its response.

What is the best AI chatbot?

The best AI chatbot really depends on what you’re doing. If it’s a general writing task, ChatGPT and Claude are likely your best bet. If it’s technical writing, Gemini and DeepSeek Chat are solid options. You can compare AI chatbots here.

Guide to preventing the use of chatbots in online learning. Laptop with a quiz on screen and a hand holding phone with a chatbot displayed

Types of prompting techniques + unnecessary terms

There are a ton of terms that make prompting seem like an extremely complex and technical process, but they mostly just describe things people naturally do when they use AI.

Take shot prompting, for example. It includes Zero-shot, One-shot, and Few-shot. It just refers to the number of examples you provide in your prompt that show the chatbot what you want.

  • Zero-shot = 0 examples
  • One-shot = 1 example
  • Few-shot = a few examples

Then there’s prompt chaining and chain of thought prompting, which sound similar but are different, and neither is overly technical.

  • Prompt chaining means giving the chatbot one prompt at a time instead of everything at once. The idea is that each answer helps with the next step/response.
  • Chain of Thought (CoT) prompting asks a chatbot to show its reasoning before answering. It can be as simple as adding, “Explain your steps before answering,” to the end of a prompt.

Not so daunting, right? Not so fast. Here’s the real expert revealer…

Have you heard of Quadrillion-shot prompting, which is the latest and greatest prompting technique? Quadrillion-shot prompting, also called Quad-shotting, is when you use a quadrillion examples in your prompt. We just made it up to show how unnecessary some prompting terms are, especially the ones in the dropdown below.

Unnecessary prompting terms

Thread of Thought (ToT) prompts just include something like, “Walk me through how [topic/subject] works in a step-by-step manner while summarizing each one.”

Contrastive Chain of Thought (CCoT) prompting gives the chatbot correct and incorrect examples/reasoning.

Generated Knowledge prompting is when you ask the chatbot about a topic and then ask it to answer a question based on its response. 

  • Prompt 1: Explain how [topic/subject] works and create a list of key concepts.
  • Prompt 2: Using the information you provided, explain the steps to [related aspect of topic/subject].

Meta-prompting is basically just asking the chatbot to create its own prompt (or improve the one you provided), then following up with another prompt asking it to answer the prompt it created or improved.

Chatbot prompting tips for educators:

Provide specific context and clear instructions

Providing specific, relevant details can improve the chances of getting the response you want.

Think of writing a prompt like writing a grocery list for someone who’s shopping for you. The chatbot will usually get the items on your list, but if you want something specific—like a brand, flavor, or amount—you have to say so.

If you want vanilla ice cream, adding “snacks” to your list doesn’t really help. Even adding “ice cream” might get you the wrong flavor. Be specific: ½ gallon of Haagen-Dazs Vanilla Ice Cream.

Details to consider providing when writing prompts for AI chatbots:

  • Voice: Who should it write like? e.g., “Write as a historian” or “Write like [specific person]
  • Tone: Casual, formal, humorous, academic, dramatic?
  • Audience: Who’s reading this? Students? What kind—third graders, college freshmen, PhD researchers? What’s their major? How much do they already know?
  • Format: How should the response be provided to you? Paragraphs or bullet points? If you want a chart or table, be specific about the type, how many rows and columns, titles, etc.
  • Length: How many words, sentences, paragraphs, bullet points, etc.?
  • Context: Any key details? What information and nuances are needed?
  • Examples: Provide good and bad examples so the chatbot understands what you want.

AI prompt examples and templates

Use these prompting examples and templates as a starting point, and tailor your prompt with information specific to your assignments and assessments.

Template: Based on the text I provided, create [number] [question type] questions to assess [audience] on their understanding of [topic(s)]. [Q&A requirements and specifications.]

Example: Based on the text I provided, create 30 multiple-choice questions to assess participants preparing for a Food Safety Manager Certification exam on their understanding of methods to prevent cross-contamination. Each question should be objective, concise, and written in plain language. Provide four answer choices per question, with only one correct answer.

More tips on how to write better exam questions.

Template: Based on the following [question type] questions, create a [alternative question type] question(s) that assesses the same underlying concepts or skills. The new question should encourage [objective/outcomes (e.g., critical thinking and practical application rather than recall)]. [Add questions here.]

Provide a clear explanation of your reasoning for how you adapted the original questions into this format. Then, include a concise description of what an appropriate student response should contain.

Example of the 1st paragraph from above: Based on the following multiple-choice questions, create an essay question that assesses the same underlying concepts or skills. The new essay question should encourage critical thinking and practical application rather than recall. [Add questions here.]

Note: If you’re repurposing the question for a different audience or subject, briefly describe them so the chatbot can adapt its response. 

Learn more about writing better exam questions.

Writing objective exam rules is waaaay trickier than it seems. Many times, rules that seem crystal clear can still be misinterpreted by test takers. Here’s a complete guide with examples of objective exam rules, and you can give the prompt below to a chatbot.

Prompt to use: Create objective online rules for test takers. The rules should comprehensively address:
*Behavior (e.g., no talking or using cell phones to look up answers)
*System requirements (e.g., computer with a functioning webcam and microphone)
*Test environment (e.g., quiet room, clear desk/surface, no other people present)

Use direct, unambiguous language that leaves no room for misinterpretation. Provide the rules in a numbered list that can be copied and pasted into the assessment platform/LMS. 

Here are two examples of basic test rules followed by improved versions. Use the improved versions as examples of the level of clarity and specificity expected as you create the set of rules:

*Rule 1 (basic): No talking during the test.
*Rule 1 (improved): No communicating with other individuals by any means, whether verbal, non-verbal, or electronic.

*Rule 2 (basic): Your desk must be clear of all items except for the device you use to take the test.
*Rule 2 (improved): The testing area and any surface your device is placed on must be clear of all items except the device used to complete the test. This includes books, papers, electronics, and other personal belongings.

Note: When you type an asterisk (*) at the start of a line, chatbots, generally speaking, get the gist that you’re trying to create a bullet point. 

Template: Based on the project instructions I provided below, create a rubric that evaluates [add what’s being assessed, e.g., specific skills and competencies]. Each item should include [type of performance scale, e.g., a five-point numeric scale from 1 to 5 (1 = Novice, 5 = Excellent) or a three-point scale with the levels: Excellent, Developing, and Needs Improvement].
Format the rubric in a [type, e.g., table or chart] to use in [format, e.g., Word Doc, Google Sheets, LMS, etc.]. Here are the assignment details and instructions: [add information]

Example: Based on the project instructions I provided below, create a rubric that evaluates practical application skills. Each item should include five performance levels using a numeric scale from 1 to 5 (1 = Novice, 5 = Excellent).

Format the rubric in a table to use in a Word Doc and include a column for written feedback. Here are the assignment details and instructions: [add information]

Note: This prompt template is just that: a template—a starting point. You’ll really need to fill in the blanks with as much information and context as possible—learning goals, topics/subjects, specific characters, realistic issues and scenarios—to help the chatbot tailor the case study to your course needs.

Create a [length]-word case study about [specific scenario/situation] for [audience, e.g., undergraduate business students, professionals in a certification program, etc.].

The case study should include:

*Comprehensive, realistic background information about [scenario/situation]

*Key characters, stakeholders, and/or groups involved

*Specific opportunities, challenges, and decision points for the learner to evaluate

*Five short-answer questions that require in-depth problem-solving and a proposed plan to address the situation

Write an engaging two-part discussion prompt for [audience, e.g., undergraduate business majors, adult learners in professional development programs, etc.] focused on [topic/subject/situation].

Part 1 (initial response): Prompt learners to connect their real-world experiences and/or prior knowledge to [topic/subject/situation] by sharing specific examples or situations that highlight how the topic applies to their personal, academic, or professional life.

Part 2 (respond to peers): Ask learners to review and analyze at least two of their peers’ posts and respond with [e.g., thoughtful questions, alternative viewpoints, etc.] to extend the discussion.

Prompts that summarize text—whether it’s an entire research paper or a paragraph from an article—can be as simple as, “Summarize this.”

But you can also ask the chatbot to summarize it in specific formats or focus on certain topics. Just copy and paste the text into the chatbot or upload the document, then start the prompt with something like “summarize” or “simplify” (or any other related terms), and then include details on the length, format, and focus. 

Here are a few example prompts you can try:

  • Summarize this research study into 2-3 concise sentences, then provide bullet points on the important information in each section, especially the sections about data collection methods and results. 
  • Simplify this text and explain it in practical, easy-to-understand language.
  • Explain what this text is saying in simple terms that [audience] can understand.
  • Shorten this text into a [resource type, e.g., study guide, FAQ, etc.] for [audience].

I’m a [job role] using this image in my [online course module, presentation, article, etc.] about [subject/topic]. Please write the following for the image:

  1. Descriptive alt text (approximately 125 characters or fewer)
  2. Detailed image description for accessibility
  3. Suggested file name (use lowercase letters and hyphens, no spaces)
  4. Text caption to display alongside the image

Note: You can upload images to most AI chatbots like as ChatGPT, Gemini, and Claude.

Don’t overthink it

  • Don’t worry about order: Chatbots use machine learning to process your whole prompt at once, so the order of the information you provide usually doesn’t matter that much in most cases. Just focus on providing the right information.
  • Write naturally: Chatbots can “understand” everyday language (even our slang and sarcasm) thanks to a technology called natural language processing, which is part of how large language models (LLMs) work. So, you don’t need to use special wording or commands. Just write to it like you would a real person, and it’ll usually get the gist of what you’re saying.

Remember chatbots’ original purpose and fact-check everything

Chatbots are used for many things, but their original purpose is still the same: to chat with you. 

You might ask them to explain complex topics, check facts, or even solve math problems—but at their core, chatbots are built to converse. They aren’t inherently designed to conduct research, verify information, or solve math problems. They can help with those tasks, and some even have features like “Deep Research,” but those are just extensions of their original purpose.

That said, always, always, always fact-check chatbot responses because they don’t generate text based on facts. They just predict what word is most likely to come next.

Treat all conversations with AI like public conversations

Regardless if it’s a public or private chatbot, don’t include any personally identifiable information (PII) or sensitive organizational details in your prompts or files you upload (Excel, Word, etc.).

Anonymize information to protect learners, yourself, and your organization. For example, use “University/Company ABC” instead of your company name, or “Student/Employee A” instead of specific names.

Control AI use during exams and assignments 

Generative AI chatbots have plenty of benefits for educators and learners.

They can serve as a smart assistant that helps educators develop course materials, personalize learning experiences, and even improve accessibility. When learners use them appropriately—which means not overly relying on them or simply copying and pasting the responses as their own—chatbots can increase engagement, improve learning and retention of information, and sharpen critical thinking and problem-solving skills. That said, when they’re overused, the exact opposite is true.

The good news? You can control if, when, and how learners use AI during online exams and assignments by using hybrid virtual proctoring. It allows you to block AI entirely or allow it at certain times. So, whether it’s a traditional online exam, a written assignment, or even a math test (online or handwritten), you’ll know learners didn’t use AI.

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Tyler Stike

Tyler is Honorlock's Director of Content and a doctoral student at the University of Florida focused on educational technology.

How Students Justify Academic Dishonesty

5 ways students justify cheating

Students cheat for all sorts of reasons beyond wanting better grades or just because they can, but what’s really fascinating is how they justify it. Understanding how students justify misconduct can help faculty get to the root of academic dishonesty. This article breaks down common mindsets and shares practical ways to address them before they lead to bigger issues, like a “cheating culture.”

5 ways students justify cheating

1. "Teeeeechnically, I didn’t cheat."

Some behaviors are unethical but not technically against the rules—and students know it.

On top of that, cheating may be unintentional because students don’t always realize that certain actions count as academic violations, especially because expectations vary across classes and disciplines (Waltzer & Dahl, 2023).

All of this blurs the line between what’s considered cheating and what’s simply unethical—and it’s been that way for years.

A student survey from 2010 about whether behaviors were cheating, unethical, or neither found predictable trends in students’ opinions but also highlighted inconsistencies that can make life difficult for educators.

Here are some interesting takeaways from the student survey:

96.4% believe copying exam answers is cheating, but only 73% think letting classmates copy your answers is cheating.

Nearly 40% say working with peers on an online exam without permission is cheating, while the other 60% are split between calling it unethical or not a problem at all.

Just over 9% think witnessing cheating without reporting it is cheating, almost 60% see it as unethical but not cheating, and about 30% say it’s neither.

Cheating
Unethical
(not cheating)
Neither
Copy classmates’ answers
during an exam
96.4%
2.3%
1.1%
Witnessing cheating but not reporting it
9.2%
59.6%
30.3%
Allowing others to look at
your answers during exams
73.3%
3.4%
23.3%
Working with peers on online exams without permission
39.8%
29%
30.2%
Asking classmates about exam questions before taking it
26.7%
45.6%
26.6%
Falsely claiming you submitted an assignment
61.1%
33%
4.5%
Copying homework from classmates
72.9%
22.6%
3.9%
Copying work from other students’ past assignments
52.3%
31.1%
16%
Storing answers/formulas in a calculator used in an exam
74.5%
15.6%
9.8%

How to help

Writing clear, objective rules for tests and assignments helps reduce confusion and prevent academic dishonesty. The challenge is making them comprehensive enough to cover key details while keeping them concise—because what seems clear and straightforward often has just enough wiggle room for students to take advantage of.

Give students a detailed definition of what you consider cheating, and talk through example situations. The example situations should be specific because broad examples are ineffective (Awosoga et al., 2021). This makes your definition more relatable and helps them better understand how it applies in real scenarios. 

It’s easy to assume that talking to students about academic integrity will go in one ear and out the other, but it can actually make a difference in reducing cheating in some situations (Malesky, 2022; Tatum & Schwartz, 2017). 

That said, it should be just one small part of a larger strategy—it helps, but it’s not nearly enough on its own.

2. “Professors don’t seem to care when people cheat.”

Most faculty members believe academic integrity is important, and most realize it’s an issue in higher education (MacLeod & Eaton, 2020; Awosoga et al., 2021), but unfortunately, academic dishonesty is often unreported*.

Why is academic dishonesty underreported if it’s so important? 

According to a few faculty surveys, academic dishonesty is underreported because it’s a slow process, evidence of cheating is rarely conclusive, and they have little faith that the institution will enforce consequences for cheating*. 

Learn more about why faculty often avoid reporting cheating.

Some faculty survey responses indicated that the process took so long that they forgot the case details.

“When the feedback finally got back to me I’d actually forgotten what had happened… I thought oh jeez, yeah, I remember that now, that was a while ago.” 

“I think it takes too long… It does take weeks sometimes for a decision to come back down.”

What happens if a school allows cheating?

If students believe faculty don’t care about cheating—or don’t care enough to address it—it can quickly become the norm, creating a culture where academic dishonesty is accepted and even expected (Tolman, 2017). And when that happens, academic misconduct happens more often, and each time it happens, students see it as a less serious offense (Shu et al., 2011).

How to help

Talking to students about suspected cheating is awkward and stressful, but these conversations are important because addressing each instance of academic dishonesty helps decrease future cheating (Tatum & Schwartz, 2017)

These conversations don’t have to be as negative as they seem either. But what should you say? What shouldn’t you say? What evidence do you need? This guide to talking to students about cheating has everything you need.

A hybrid proctoring solution provides objective evidence—audio, video, images, clicks, and more—that can support misconduct cases. It offers clear, conclusive evidence that helps faculty and the teams involved in the reporting process.

Universities should focus on faculty training on academic dishonesty to create awareness of school policies and a shared definition of what counts as misconduct. This is particularly important for newer faculty members to get acclimated and up to speed on integrity policies (Awosoga et al., 2021).

Make it easier to report cheating by asking faculty and staff where the process gets stuck and how it can improve. Use their feedback to cut out unnecessary steps, add helpful tools like electronic forms or scheduling software, and create a system that supports everyone better.

*(Carpenter et al. 2010; MacLeod & Eaton, 2020; Staats et al., 2009)

3. “At work, they’d call it being resourceful, not cheating.”

A student survey by Cole et al. (2014) found that many justify academic dishonesty, like using internet resources or sharing answers during online exams, by arguing that they’ll be able to do it in the workplace.

This rationale also influences students’ prioritization of grades over learning, as one survey response explained: “When you get to the workplace, they teach you what you want to know, your diploma is just your foot in the door for the most part.” (Cole et al., 2014, p. 43).

How to help

Faculty need to show why the learning material and activities matter in real life to help students understand the importance and why they should care about it. When students feel they’re learning for themselves, especially when it’s practical information they’ll use in the future, they’re much less likely to cheat (Anderman & Won, 2018; Carpenter et al., 2010).

4. “I was paraphrasing, not plagiarizing.”

Sometimes, students knowingly plagiarize because they see it as a way to save time—especially when they don’t care about the subject or think it’s relevant to their futures (Moss, 2018).

Others may not even realize they’re plagiarizing, like the 70% of students who believe internet resources are public information that doesn’t need to be cited (Larkin & Mintu-Wimsatt, 2015). Students can also unintentionally plagiarize when they’re trying reeeeeally hard to sound overly academic, which is a struggle that some doctoral students face (Fatemi & Saito, 2020).

“Plagiarism can be particularly difficult for students to perceive. The lines between plagiarism and appropriate paraphrasing are often blurry, which can generate considerable disagreement among students and instructors about what constitutes plagiarism.” (Waltzer & Dahl, 2023, p. 131)

How to help

APA or MLA? Chicago, maybe? When do you need to cite a source? What counts as common knowledge? Questions like these can make plagiarism feel confusing, especially with all the gray areas. Make it easier for students by providing helpful resources in the course and teaching them how to cite properly.

Tie written assignments to students’ future work when you can. This can be challenging when teaching students who are taking the course as an elective, not out of interest.

For example, if a business administration major is in an art history class, offer flexibility to write a plan for a profitable art gallery business. While this kind of flexibility isn’t always realistic, even small connections to their future goals can make a difference.

Long and short-form written assignments can be proctored just like online exams.

During proctored written assignments, students WON’T be able to:

  • Access unauthorized websites, applications, and extensions (including chatbots) unless faculty permit access to them (e.g., allowing students to visit specific articles and case studies.
  • Use their cell phones to look up information.
  • Use books or notes unless approved by the instructor.
  • Paste content into the word processor that was copied before the assignment started.
  •  Ask voice assistants like Siri or Alexa for help.

Share links to helpful citation resources at your institution, like the writing center, and from reliable citation websites.

5. "I was so anxious."

Tests are inherently stressful; the more anxious a student gets, the more likely they are to cheat (Eshet et al., 2024). Test anxiety and the fear of failing the test make cheating hard to resist, even for students who typically wouldn’t cheat (Eshet et al., 2024; Salgado et al., 2022).

How to help

Offering practice exams gives students a chance to familiarize themselves with the testing platforms and check to make sure their device meets the minimum system requirements.

Talk to students about accommodations, like extended time or assistive technologies, and how to request them or get help if they need it.

Give students a clear idea of what the test will cover, its format, the types of questions, time limit, etc.

Knowing how and why cheating happens is important for educators to be proactive against academic dishonesty and create a culture of honesty and fairness. Hybid online proctoring supports this effort by helping detect and prevent dishonest behavior so educators can focus on teaching.

Anderman, E. M., & Won, S. (2019). Academic Cheating in Disliked Classes. Ethics & Behavior, 29(1), 1–22. https://doi.org/10.1080/10508422.2017.1373648

Awosoga, O., Nord, C. M., Varsanyi, S., Barley, R., & Meadows, J. (2021). Student and faculty perceptions of, and experiences with, academic dishonesty at a medium-sized Canadian university. International Journal for Educational Integrity, 17(1), 1–26. https://doi.org/10.1007/s40979-021-00090-w

Carpenter, D. D., Harding, T. S., & Finelli, C. J. (n.d.). Using Research to Identify Academic Dishonesty Deterrents Among Engineering Undergraduates.

Cole, M. T., Swartz, L. B., & Shelley, D. J. (2014). Students’ Use of Technology in Learning Course Material: Is it Cheating? International Journal of Information and Communication Technology Education, 10(1), 35–48. https://doi.org/10.4018/ijicte.2014010104

Eshet, Y., Grinautsky, K., & Steinberger, P. (2024). To behave or not (un)ethically? The meditative effect of mindfulness on statistics anxiety and academic dishonesty moderated by risk aversion. International Journal for Educational Integrity, 20(1), 6–18. https://doi.org/10.1007/s40979-024-00151-w

Fatemi G., Saito E. (2020) Unintentional plagiarism and academic integrity: the challenges and needs of postgraduate international students in Australia. J Furth High Educ 44(10):1305–1319. https://doi.org/10.1080/0309877X.2019.1683521

Larkin, C., & Mintu-Wimsatt, A. (2015). Comparing cheating behaviors among graduate and undergraduate online business students. Journal of Higher Education Theory and Practice, 15(7), 54–62.

MacLeod, P. D., & Eaton, S. E. (2020). The Paradox of Faculty Attitudes toward Student Violations of Academic Integrity. Journal of Academic Ethics, 18(4), 347–362. https://doi.org/10.1007/s10805-020-09363-4

Malesky, A., Grist, C., Poovey, K., & Dennis, N. (2022). The Effects of Peer Influence, Honor Codes, and Personality Traits on Cheating Behavior in a University Setting. Ethics & Behavior, 32(1), 12–21. https://doi.org/10.1080/10508422.2020.1869006

Moss, S. A., White, B., & Lee, J. (2018). A Systematic Review Into the Psychological Causes and Correlates of Plagiarism. Ethics & Behavior, 28(4), 261–283. https://doi.org/10.1080/10508422.2017.1341837

Salgado, J. F., Cuadrado, D., & Moscoso, S. (2022). Counterproductive Academic Behaviors and Academic Performance: A Meta-Analysis and a Path Analysis Model. Frontiers in Psychology, 13, 893775–893775. https://doi.org/10.3389/fpsyg.2022.893775

Shu, L. L., Gino, F., & Bazerman, M. H. (2011). Dishonest deed, clear conscience: When cheating leads to moral disengagement and motivated forgetting. Personality and Social Psychology Bulletin, 37(3), 330–349. https://doi.org/10.1177/0146167211398138

Staats, S., Hupp, J. M., Wallace, H., & Gresley, J. (2009). Heroes Don’t Cheat: An Examination of Academic Dishonesty and Students’ Views on Why Professors Don’t Report Cheating. Ethics & Behavior, 19(3), 171–183. https://doi.org/10.1080/10508420802623716

Tatum, H., & Schwartz, B. M. (2017). Honor Codes: Evidence Based Strategies for Improving Academic Integrity. Theory into Practice, 56(2), 129–135. https://doi.org/10.1080/00405841.2017.1308175

Tolman, S. (2017). Academic Dishonesty in Online Courses: Considerations for Graduate Preparatory Programs in Higher Education. College Student Journal, 51(4), 579–584.

Waltzer, T., & Dahl, A. (2023). Why do students cheat? Perceptions, evaluations, and motivations. Ethics & Behavior, 33(2), 130–150. https://doi.org/10.1080/10508422.2022.2026775

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2025 AI Trends in Higher Education

5 AI trends to expect in higher education in 2025

Click below to skip ahead

  1. Investing in secure chatbots
  2. Using AI to improve accessibility
  3. AI will be the go to study partner
  4. More faculty will proctor written assignments
  5. Building assignments that evaluate students’ use of AI
Important information to consider before reading

Think of AI as a hammer. It’s a tool. One tool. Assuming you have lumber and nails, can you build a house with a hammer? Technically, yes? Maybe? But would you want to live in it? Doubt it.

You can gather every tool and material imaginable, but it takes skills, knowledge, and expertise to use them effectively—and safely—that’s where you come in.

AI can help improve accessibility (discussed later), but the tools themselves need to be accessible. Each AI tool is built for a specific task or set of tasks—like generating text. Some tools can help improve accessibility by generating text to better support students with specific disabilities, like using decodable words and formatting to help students with dyslexia. It may do that well, but that doesn’t mean it works with screen readers or other assistive technologies.

In other words, helping improve accessibility doesn’t mean they’re accessible or meet accessibility compliance standards.

Whether you’re implementing AI across the institution or just looking for some course content, one thing is non-negotiable: always, always, always have the right people review and approve it for data privacy and security before using it.

Use AI purposefully, not just because it’s there. It should be a supplemental tool that genuinely helps improve teaching and learning. Otherwise, it’s just another thing students have to figure out how to use without adding real value.

Also, consider whether you’re using each tool for its true purpose. Have you ever seen LinkedIn “experts” bragging that they’ve stumped a chatbot… with a math problem Pretty impressive—as long as you ignore the fact that chatbots aren’t designed to do math.

Would you use a calculator to write an essay? Hopefully not.

While some AI tools can handle tasks outside their main functionality, they work best when used for what they’re actually designed to do.

Faculty can use chatbots to:
  • Write long and short-form course content
  • Make writing sound more professional
  • Break down complex tasks to complete them step by step
  • Summarize and organize information seconds
  • Double-check answers to test questions

Students can too. Download our 6 part guide to preventing chatbot cheating in higher education.

1. More schools investing in secure AI chatbots

The benefits of AI chatbots in higher education are clear, but so are the data privacy and security risks. That’s why you can expect to see more colleges and universities offering AI chatbots, but taking a more secure approach either by self-hosting them or only through strict agreements where the provider (Google, Amazon, Microsoft Azure) does not use the data to train larger public models.

In other words, students, faculty, and staff can interact with the chatbot and the information won’t be used publicly.

Plus, when colleges offer these and other similar tools, all students can access them, not just those who can afford a subscription.

Benefits of AI chatbots in higher education

Aside from privacy and security, colleges and universities can still enjoy many of these benefits regardless of the approach, but a secure approach adds peace of mind and aligns with the ethical responsibility to protect sensitive information.

Commonly used chatbots: ChatGPT, Microsoft Copilot, Google Gemini, Claude

Creating, developing, and repurposing course content

Faculty can use chatbots for just about any course-related task, from drafting comprehensive exam rules and rewriting test questions to creating discussion prompts and generating mock datasets for assignments.

Click below to see templated prompt examples and screenshots.

Prompt template: Write a discussion prompt for a [type/level (e.g., online graduate)] course within a module about [topics/subjects]. Use open-ended questions that encourage students to share specific personal experiences and challenges them to analyze and relate their experience to [add subject details] to demonstrate their understanding and critical thinking skills.

Example prompt output for an accounting course: Think about a time when you had to create or manage a personal budget. How did your approach compare to the principles of accrual accounting discussed in this module? Reflect on whether you followed a cash-based approach (tracking money when it is received or spent) or an accrual-based approach (tracking income and expenses when they are earned or incurred). What challenges did you face, and what does this reveal about the benefits and limitations of each method? Use specific examples from your experience and connect them to the concepts covered in this module.

Example prompt templates:

“Rewrite the following test question(s) to assess the same concepts. Maintain the same difficulty level and word count, but alter the phrasing and structure.”

“Convert these [existing format (e.g., true or false, matching, etc.)] test questions into [new format (e.g., multiple-choice, fill in the blank, etc.)]”

For better results, include an example of a test question with a revised version.

Prompt template: Create an mock dataset for [type/level, e.g., undergraduate accounting] students to analyze. The dataset should represent a [specific scenario (e.g., a small online retail business, or a personal budget]. Include data spanning [time period, e.g., 12 months] with the following categories: [list categories (e.g., expenses, income, etc.)

Prompt template: Adapt this [activity, resource, etc.] about [subject/topic] in a [type/level] course to be repurposed for an [new use case]: [insert text from original activity]

Economics 101 comparison chart
Comparison chart (created with Claude)

Prompt: Create a side-by-side visual comparison of Macroeconomics and Microeconomics. Structure it with two main columns (use contrasting but complementary colors). Include three key comparison sections:

  1. Focus (what they study/address)
  2. Key metrics (measurements/benchmark)
  3. Policy examples

Use a clear visual hierarchy with section headers and bullet points. Make it suitable for college students in an introductory economics course.

Simple Venn Diagram comparing macroeconomics and microeconomics
Venn Diagram (created with ChatGPT)

Prompt: Create a simple but informative Venn diagram comparing and contrasting macroeconomics and microeconomics at a high level for an introductory college economics course. Label the overlapping section 'Shared Concepts'.

Use these text colors and background colors for each part:

*Left (Macroeconomics): text: #ffffff background: #00259c

*Middle (Shared Concepts): text: #000000 background: #a0e79e

*Right (Macroeconomics): text: #000000 background: #ffe63d

Simple table comparing microeconomics and macroeconomics
Table (created with Google Gemini)

Prompt: Create a simple but informative Venn diagram comparing and contrasting macroeconomics and microeconomics at a high level for an introductory college economics course. Label the overlapping section 'Shared Concepts'.

Prompt to create the table below: Write HTML code for a table I can embed into my course that has 4 rows and 4 columns. Use placeholder text that I can edit as needed (for example “Column 1 Title” “Column 1 Text”). Make this the background color for the first row #ababab. Make this the background color of the first column ##d9d9d9.

The table below is the result of the code provided by Claude.

Column 1 Title Column 2 Title Column 3 Title
Row 1 Text Row 1, Column 1 Row 1, Column 2 Row 1, Column 3
Row 2 Text Row 2, Column 1 Row 2, Column 2 Row 2, Column 3
Row 3 Text Row 3, Column 1 Row 3, Column 2 Row 3, Column 3

Learn more about AI prompting techniques and find more templates and examples.

2. Improving accessibility

AI has the potential to make education more accessible and inclusive in some unexpected ways, like recognizing accents, localizing content, and detecting emotions. On top of that, it can automatically check for compliance and make changes to meet accessibility standards—almost like a set-it-and-forget-it solution for specific areas.

Languages

AI is making communication smoother, not just with basic translation tools but also through localization, accent recognition, and name pronunciation. Here are some AI tools to consider, how they work, and why they’re important.

Accent recognition AI does exactly what you’d expect—it recognizes and understands accents. It’s like Siri, but more fluent (and cultured?)

Why does that matter for online learning? Think about students who rely on speech-to-text because using a keyboard isn’t an option. Or a faculty member with an accent whose live lecture captions are filled with errors. It’s a frustrating and limiting experience.

Accent recognition AI can help fix this by making captions and transcripts more accurate and voice-controlled assistive technology more usable.

Check out these accent recognition tools: Lokalise, Smartling, Fluent AI

Did you know there are around 160 different English dialects? Some have only slight variations, while others differ significantly in pronunciation, grammar, spelling, and even word meanings.

For example, what Americans and Canadians call french fries or fries, Brits and Australians call chips. And Americans write center and localize, while Canadians, Brits, and Australians often use centre and localise.

Most of the spelling differences don’t affect understanding. But it can be confusing when words have entirely different meanings. What if a term with different meanings was used on exam or assignment and the student didn’t know?

Localization AI helps by adapting your content to specific dialects and cultures. You can also use chatbots to help localize your content and review it for language that may be confusing for some people.

AI sign language translation software can translate speech into sign language in real time.

The AI chooses from a huge collection of real videos of people signing to create smooth and accurate translations. Some solutions integrate into your websites and can be added to videos or other content in a simple picture-in-picture format.

Check out Signapse AI and Slait AI. They provide real videos of people signing, unlike previously existing tools that provide cartoon-like avatars.

If your name is even remotely unique you’ve probably heard it mispronounced. The really unfortunate part is that rather than correcting people, some just accept it and answer to all kinds of mispronunciations.

That’s where name pronunciation AI like Namecoach come into the picture. Namecoach integrates with the LMS, SIS, and most other platforms and browsers.

Students create a voice recording of their names or use audio databases for accurate pronunciation. These recordings and phonetic spellings are accessible to instructors and other students so that whether it’s a virtual event or support call, names are pronounced correctly.

Adapting content to support students with learning disabilities and diverse learning needs

Chatbots can assist faculty with adapting content to better support students with learning disabilities and diverse learning needs.

For example, faculty can ask the chatbot to adjust exam questions to meet a wider range of cognitive abilities and language comprehension levels. Chatbots can further support accessibility by creating descriptive elements for images and completing other accessibility-related tasks.

Click below to see templated prompt examples.

Shorter prompt: Please provide alternative text (125 words or less) and an image description for this photo: [attach photo]

Detailed prompt: I’m using this image on a [course page, email, etc.] about [subject/topic]. Please generate: descriptive alt text (125 words or less); detailed image description; suggested file name; and caption for this photo: [attach photo]

You can also try out this step-by-step alt-text creator.

Prompt example: Rewrite these [object (e.g., instructions, questions, etc.)] to make them clearer and more accessible for students with dyslexia. Simplify the language by using shorter sentences, straightforward vocabulary, and decodable words where possible. Break the text into smaller sections, use bullet points or numbered lists, and highlight key terms or steps. Keep the instructions concise and avoid unnecessary jargon. Here are the instructions: [add your instructions]

Example using the prompt:

Original instructions: Write a 500 word essay analyzing the themes in the assigned text. Your essay must include an introduction with a thesis statement, at least three body paragraphs with textual evidence, and a conclusion that summarizes your argument. Cite all sources using APA formatting. Submit your essay in a Word document via the course portal by Friday at 11:59 PM. Late submissions will incur a penalty of 10% per day.

Revised version for students with dyslexia (Note: This is a generic example. You’ll need to adapt the prompt based on your students and the specific activity and provide any necessary context.

Write a 500-word essay about the themes in the assigned text. Follow these steps:

  • Introduction: Start with a short paragraph that states your main idea (thesis statement).
  • Body Paragraphs: Write at least three paragraphs. Use examples from the text to support your ideas.
  • Conclusion: End with a short paragraph that sums up your main points.

Remember:

  • Use APA format to include references for any sources you use.
  • Check your spelling and grammar before submitting.

How to Submit:

  • Save your essay as a Word document.
  • Upload it to the course portal by Friday at 11:59 PM.

Important: If you turn it in late, 10% will be taken off for each day it’s late.

Emotion detection AI

Emotion AI detects and interprets emotions by analyzing text, voice (audio), and video (facial expressions and gestures) and associating specific components with related emotions.

This technology can help:

  • Students with cognitive and/or physical disabilities communicate
  • Detect signs of stress, confusion, frustration, happiness, etc.
  • Understand which course activities students are most interested or uninterested in

The images below show how video emotion AI could work to give instructors insight into learner engagement during specific activities.

  • High Attention: Learner attention increases with eye contact.
  • Low Attention: Attention drops when they look away.

While eye contact doesn’t always mean focus, and looking away doesn’t mean they’re not listening, combining this with other data—like duration, facial expressions, and body language—gives a clearer picture of behavior. Educators can use this to identify course activities that increase engagement, create confusion and frustration, and more.

High Attention

Low Attention

  • High attention example for emotion detection AI

  • Example of low levels of attention in video emotion software

But these tools aren’t perfect, and they probably never will be. That’s because of how they work. With facial expression recognition, for example—the AI looks at things like raised eyebrows and lip movements and tries to match them to emotions it’s been trained to recognize. In reality, it’s just grouping facial features into preset emotion categories, not actually figuring out the person’s true emotional state. Plus, we all express emotion differently, and some emotions are expressed in pretty similar ways—how easy would it be for happiness to be misinterpreted as surprise?

AI accessibility checkers

AccessiBe and Equally AI are two AI-powered tools that help institutions, faculty, and staff check their websites, courses, and content for accessibility. These solutions continuously monitor resources and automatically make adjustments to improve accessibility and meet compliance standards.

This isn’t AI, but Accessibility Desk provides a hub of free accessibility tools to check websites and content for accessibility.

Learn more about web accessibility compliance standards and guidelines.

3. AI will incrementally become a staple for studying

AI can be the ultimate study partner because of its diverse capabilities and interactiveness. After providing it with text, notes, files, or images, here’s how students use AI to study smarter.

Creating study guides​ and outlines

Summary about using either Notebook LM or chatbots

Chatbots

Example prompts: Based on the sources I’ve provided, create a detailed [outline or study guide] for [sections/chapters e.g., chapters 2-4]. [Add follow up text from the examples below].

Organize the outline using [preferred format e.g., headers, bullet points, etc.]. Focus on [specific information/goals (e.g., identifying connections between X and Y, comparing and contrasting X and Y)].

Include the following information for each chapter: a high-level summary paragraph, a section explaining key concepts and why they’re important, a bulleted list of terms and definitions that are easy to understand, and a list of potential exam questions.

NotebookLM

With NotebookLM, students can upload PDFs, websites, YouTube videos, audio files, Google Docs, or Slides. NotebookLM quickly turns these into detailed outlines, study guides, FAQs, or even conversational “podcasts” using all or some of the uploaded sources.

NotebookLM interface for students creating study guides

Students upload the sources here, which can range from PDFs and websites to videos and audio files. We picked a video, Google Doc, website article, and three PDFs.

Students can ask the AI questions based on the sources. The AI provides answers based on the sources and cites which source(s) the information is from.

Always check the accuracy of anything AI generates. This is their disclaimer: "NotebookLM can be inaccurate, please double check its responses."

An audio overview can be created where two AI voices discuss the sources in a podcast-like format that actually sounds realistic.

Students simply click the buttons below for comprehensive study guides, briefing docs, FAQs, and timelines.

NotebookLM interface for students creating study guides

Students upload the sources here, which can range from PDFs and websites to videos and audio files. We picked a video, Google Doc, website article, and three PDFs.

Students can ask the AI questions based on the sources. The AI provides answers based on the sources and cites which source(s) the information is from.

Always check the accuracy of anything AI generates. This is their disclaimer: "NotebookLM can be inaccurate, please double check its responses."

An audio overview can be created where two AI voices discuss the sources in a podcast-like format that actually sounds realistic.

Students simply click buttons below to comprehensive study guides, briefing docs, FAQs, and timelines.

Flashcards

Here’s an example prompt students can use to engage in an interactive flashcards activity with a chatbot: Create 10 flashcards to test my knowledge of the different parts of a cell based on their function. Present the “front” of the flashcard first, then I’ll answer, and then you present the “back” of the card so I know if I’m correct or not. If my answer is incorrect, please provide the correct answer and 1-2 sentences of additional context.

Summarize, simplify, paraphrase, or rephrase content

Whether students provide an entire study or a paragraph of text, chatbots can help summarize and simplify the information. Here’s how a few chatbots responded to a basic prompt to simplify a few sentences of overly complicated text (text & prompt below).

Text provided to the chatbot*: “Educational technology influenced in many and often centrifugal ways educational innovation as part of societal development. Successive behaviorist, cognitive, constructivist, and socio-constructivist approaches to learning and the concomitant use of technologies suggest a clear, straightforward contribution to education based on the internal dynamics of that field.”

Prompt used: Shorten and simplify this text into two sentences that are very easy to understand. Use practical, simple language instead of complex terms.

*Text is from Lowyck, J. (2014). Bridging learning theories and technology-enhanced environments: A critical appraisal of its history. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of Research on Educational Communications and Technology (pp. 3–20). Springer New York. https://doi.org/10.1007/978-1-4614-3185-5_1 

Prompt response: Educational technology has helped education grow and adapt over time. Approaches like using rewards to encourage learning, understanding how people think, and learning through real-world experiences have guided how technology is used in teaching.

Prompt response: Educational technology has driven many changes and improvements in education as society develops. Different learning approaches and the use of technology have consistently made education better.

Prompt response: Technology has played a big role in how education has changed over time. Different ways of thinking about learning, like focusing on how people behave, how they think, how they learn by doing, and how they learn from others, have all been shaped by technology and have helped improve education.

Prompt response: Educational technology has helped drive changes in how we teach and learn as society has evolved over time. Different theories about how people learn have shaped how we use technology in education, from simple cause-and-effect approaches to more collaborative learning methods.

4. More faculty will proctor written assignments

With the right prompts, chatbots can generate human-like text on basically any topic from any perspective. The downside is that students can use them to complete written assignments. But the good news is that written assignments can be proctored just like online exams.

During proctored written assignments, students WON’T be able to do the following:

  • Use chatbot applications, websites, or browser extensions.
  • Visit unauthorized websites unless the instructor permits access to specific resources like links to specific studies or articles.
  • Refer to books or notes unless approved by the instructor.
  • Paste pre-copied content into the word processor.
  • Search for information on their cell phones.
  • Ask for help from voice assistants like Siri or Alexa.

5. Engaging students with assignments that involve AI

Some instructors will design assignments that actively incorporate chatbots. For example, students might be asked to:

  • Use a chatbot to generate an essay on a specific topic, then analyze its response by identifying errors, making corrections, and explaining their reasoning.
  • Compare responses from different chatbots on the same topic to evaluate their accuracy and identify inconsistencies.
  • Teach the AI about a concept by starting with a prompt like, “Pretend you don’t know much about [topic/subject] other than [specific aspect of the topic]. I’ll explain how it works. Ask me clarifying questions throughout.”

AI is slowly being embraced in higher education—sometimes as a helpful tool, other times as something students try to sneak past their professors. As schools and faculty rethink assignment and assessment strategies, they also need to consider the challenges around privacy, security, and academic integrity at every stage. But when used the right way, AI can make learning more effective, engaging, and fair.

More resources for educators

Online guide about how faculty can address students suspected of cheating
This article will show you what a browser lockdown can and cannot do and provide additional proctoring solutions to solve for areas that browser lockdown software may miss.
Does Honorlock detect cell phones?
What is online proctoring for remote testing

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The Real Reasons Why Students Cheat

Why do students REALLY cheat?

Between 50-80% of college students cheat at some point.1 These estimates vary, but it’s safe to say that cheating is common in higher education. And since people tend to downplay negative behaviors like academic dishonesty, the true numbers are likely higher.2

Scenario 1: Anything less than a 90% on your last final exam means failing the course, delaying graduation, and paying to retake it—an expense you didn’t plan for, and can’t afford. Meanwhile, you know your classmates are cheating, but the instructor seems to ignore it.

Scenario 2: An elective you’re aren’t interested in requires a long essay. Would you use ChatGPT to “help” write it so you can focus on studying for finals in your career-related courses—especially since you can make a few edits and AI detection won’t catch it?

Many studies suggest that students are likely to cheat in these scenarios.

Sometimes, the reasons for cheating are obvious, like wanting good grades or just because they can. Other times, they’re more complex, like students’ assumptions of how much instructors actually care and gray areas where opinions of what counts as cheating differ—even among faculty. 1(Cantiello & Geschke, 2024; Janke et al., 2021; MacLeod & Eaton, 2020) 2(Newton, 2024)

When cheating becomes a culture

Cheating isn’t because of a few “bad apples.” And it isn’t just your students’ fault. Instructor communication and teaching style, as well as institutional policies and procedures—or lack thereof—play a significant role in creating a learning environment where academic dishonesty is the norm.

But shouldn’t students’ strong values and unwavering moral compasses steer them away from unethical behavior and guide them toward honesty and academic integrity? Not always… especially when students know their peers are cheating and the instructor doesn’t do anything about it.

Why wouldn’t faculty address cheating?

A 2020 survey of over 400 faculty from 17 institutions offered some insight. Unless the behavior is blatantly obvious, some faculty won’t report it because it’s a time-consuming process, and they don’t believe the institution will support them (MacLeod & Eaton, 2020).

Faculty survey insights about why cheating is underreported​:

  • 66% said their institution doesn’t handle academic dishonesty consistently.
  • 48% have ignored cheating when evidence wasn’t entirely conclusive.
  • 30% said it’s too time-consuming to formally report cheating.
  • 24% indicated that their institution’s integrity policies were effective.
  • 10% didn’t believe protecting academic integrity was their responsibility.

Faculty survey insights about why cheating is underreported

0 %

said their institution doesn’t handle academic dishonesty consistently.

0 %

have ignored cheating when evidence wasn’t entirely conclusive.

0 %

said it’s too time-consuming to formally report academic misconduct.

0 %

indicated that their institution’s integrity policies were effective.

0 %

said academic integrity wasn’t their responsibility.

Although a bit dated, a survey by Staats et al. (2009) reinforced the above findings and added a few more reasons that faculty believe contribute to non-reporting of academic dishonesty:

  • Students could take legal action.
  • Accusing students is stressful.
  • Professors lack the courage to address students who cheat.
  • Worries about the situation escalating if a student denies misconduct.
  • A reluctance to potentially damage the student’s future.

Addressing a culture of cheating

When students assume others are cheating and that faculty and the institution don’t care or won’t do anything about it, a “cheating culture” emerges (Tolman, 2017). But the thing about cheating is that the more it happens, the more it happens—and with each instance, students see it as a less serious offense (Shu et al., 2011).

So, what can you do about it?

Slap an academic integrity policy on the school website? Ask students to sign course honor codes? Those can help if they’re part of larger efforts. If not, you’re just wasting time.

How about setting up online proctored exams? These help detect and reduce cheating and give faculty evidence to prove it. But proctoring vendors don’t—and shouldn’t—determine the consequences of academic integrity violations. That responsibility falls to the faculty and institution.

You need the right technology, but you also need the right people and processes.

“Faculty and administrators need to focus their attention on creating a culture that discourages cheating as much as they do on acquiring and implementing technological resources to catch cheating students.” (Malesky, 2022, p. 18)

Why do students cheat?

According to McCabe (2016), Simkin & McLeod (2010), and just about every study exploring this topic, there are a few common (and very predictable) reasons for student cheating, like pressure to earn good grades, lack of preparedness, and simply because the opportunity was there with little risk of getting caught. Overall, no surprises here. 

Beyond that, academic dishonesty has gray areas related to differing opinions, peer behaviors, specific situations, and whether students feel that the institution and instructor genuinely care, among other factors.

Personality, values, morals, attitudes, and emotions?

Although personalities, values, morals, and attitudes impact students’ intentions to cheat, they have little influence on reducing cheating in most cases (Ababneh et al., 2022; Johnson‐Clements et al., 2024; Kasler et al., 2023).

Think of it like this: we may not intend to eat too much dessert over the holidays, but we still grab the extra slice(s) of pie and a few too many cookies.

Neutral attitudes and anonymity amplify academic misconduct in online learning environments

Neutral and disengaged attitudes make it easier for students to justify academic misconduct and disconnect from their behavior—even when they know it’s wrong (Lee et al., 2020; Sevnarayan & Maphoto, 2024). The impact of these attitudes is amplified in online learning environments because there’s a sense of anonymity and less personal accountability, both making it easier for students to justify dishonest behavior (Sevnarayan & Maphoto, 2024).

Students’ test anxiety is linked to academic misconduct

The more anxious a student feels, the more likely they are to act unethically in academic settings (Eshet et al., 2024). If a student is anxious and expects a poor grade (because they’re unprepared, for example) they’re more likely to take risks like academic fraud compared to students who expect to perform well (Salgado et al., 2022).

Students view cheating differently

We usually think of cheating as intentional behaviors like peeking at another student’s test or using a cell phone to look up answers during an online exam. But that isn’t always the case.

Sometimes, what seems like intentional unethical behavior may stem from a misunderstanding or a different view of cheating. Other times, students know their behavior is unethical but not technically cheating, and they find it easier to justify in situations where they don’t believe it’s particularly harmful or deceptive (Waltzer & Dahl, 2023).

Students and faculty opinions differ on the severity of certain behaviors

For the most part, students and faculty have similar views on what counts as cheating, but they don’t always see eye-to-eye on the severity of certain behaviors (Pautler et al., 2013). For example, both groups agree that taking a test for another student, using unauthorized notes, and intentional plagiarism are serious offenses.

But when it comes to behaviors like signing in for another student, gathering test question banks from previous years, and unintentional plagiarism, faculty usually interpret these more severely than students do.

Dishonesty or teamwork? Many students don’t consider group work on take-home tests as cheating—even when they don’t have permission from the instructor; they view it more as teamwork than dishonesty (Carpenter et al., 2010; Forkuor et al., 2019).

Students see some behavior as unethical but not cheating

Students recognize that some behaviors are unethical but not academic misconduct. For example, 65.5% indicated that making up an excuse to delay an exam or paper is unethical but not cheating (Carpenter et al., 2010).

Student survey results: cheating vs. unethical behavior

Copying classmates' answers during an exam

96.4% of agreed that this is cheating

Witnessing cheating but not reporting it

Almost 60% indicated this is unethical, but not cheating. Over 30% said this isn’t cheating or unethical.

Allowing others to look at your answers during an exam

Nearly 3 out of 4 respondents said this is cheating, but most of the remaining 25% said this isn’t cheating or unethical.

Taking online exams with classmates without permission

About 40% said this is cheating. The other 60% was evenly split between those who said it’s unethical and those who said it isn’t cheating or unethical.

Asking classmates about exam questions before taking it

45% said it’s unethical, while the remaining 55% was divided between those who think it’s cheating and those who don’t believe it’s either one.

Claiming you submitted an assignment when you didn't

61% believe this is cheating while most others indicated that it’s unethical but not cheating.

Copying assignment work from previous students

Over 52% agreed this is cheating. 31% found it to be unethical, although not cheating, while 16% said it’s neither.

Cheating
Unethical
(not cheating)
Neither
Copy classmates’ answers
during an exam
96.4%
2.3%
1.1%
Witnessing cheating but not reporting it
9.2%
59.6%
30.3%
Allowing others to look at
your answers during exams
73.3%
3.4%
23.3%
Working with peers on online exams without permission
39.8%
29%
30.2%
Asking classmates about exam questions before taking it
26.7%
45.6%
26.6%
Falsely claiming you submitted an assignment
61.1%
33%
4.5%
Copying homework from classmates
72.9%
22.6%
3.9%
Copying work from other students’ past assignments
52.3%
31.1%
16%
Storing answers/formulas in a calculator used in an exam
74.5%
15.6%
9.8%

While most students’ views on academic dishonesty align with what we believe is academic dishonesty, there are some concerning outliers here. For example, while about 40% think taking an exam with classmates without the instructor’s permission is cheating, the other 60% either see it as unethical but not cheating—or don’t think it’s wrong at all. These differences in opinion cause serious academic integrity violations and larger problems in higher education, especially in e-learning.

Rationalizing cheating as “real world” behavior

In a survey of almost 600 college students, many said that people can access resources and share information in real life, so they don’t see that behavior as misconduct (Cole et al., 2014).

Tying that into their future work plans, one student said, “Getting a good grade is more important than learning anything anymore… because when you get to the workplace, they teach you what you want to know, your diploma is just your foot in the door for the most part.” (Cole et al., 2014, p. 43).

Unintentional plagiarism

A survey of graduate and undergraduate students found that 70% view Internet resources as public information that’s free to use without citing (Larkin & Mintu-Wimsatt, 2015). 

Students may also unintentionally plagiarize because they’re trying too hard to sound academic, which often happens to doctoral students (Fatemi & Saito, 2020).

0 %

of students view Internet resources as public information that’s free to use without citing

Courses are focused on grades, not learning

Students are more likely to cheat when they feel the course focuses on grades (Anderman & Koenka, 2017). This is different from a student’s personal focus on earning good grades. When a course is focused on grades, students feel like everything revolves around grades rather than learning (Anderman & Koenka, 2017; Anderman & Won, 2019). This can happen for many reasons, such as when instructors rely heavily on high-stakes exams to assess knowledge or when every exam or assignment seems to be high-stakes.

Focusing on grades also makes academic integrity violations feel more acceptable in classes students dislike or aren’t interested in (Anderman & Won, 2019). This is especially troubling for instructors who typically have students taking their course as an elective (remember the scenario in the beginning with the elective you don’t even care about?)

They believe other students are cheating

Students are more likely to cheat if they believe their peers cheat, especially when they witness it firsthand, which makes it seem like normal and acceptable behavior, and it can even lead them to justify it (Bath et al., 2014; O’Rourke et al., 2010; Tatum, 2017). 

Knowing that their peers are cheating is one of the strongest predictors of a student’s own academic dishonesty (O’Rourke et al., 2010). Peer influence also shapes students’ views on dishonest and acceptable behavior more than the rules set by instructors or the school (Forkuor et al., 2019).

“Clearly, cheating among college students is prevalent and it is even common among students who acknowledge that it is morally wrong. Morality does not seem to be a major influence on student decisions to cheat or not to cheat. Peer disapproval of cheating and the behavior of peers are clearly much greater influences and may help explain the success of academic honor codes in reducing cheating.”

(McCabe, 1997, p. 444)

11 strategies to prevent cheating in online learning

Addressing and preventing cheating can feel like you’re running through a never-ending obstacle course. And just when you think you’re getting ahead, a new challenge pops up. While it’s an endless effort, a few core strategies can help clear the path in your courses and across your institution.

Reduce test anxiety

Anxious students are more likely to cheat, especially when they’re unprepared and/or fear bad grades, as stress increases risky shortcuts (Eshet et al., 2024; Salgado et al., 2022). Aside from those stressors stress, a student survey by Honorlock and a partner university found that students also worry about using test technologies. Managing these concerns can help improve performance, reduce unethical behavior, and encourage academic integrity.

Tips to help reduce student test anxiety:

  • Set expectations: Let students know what the test will cover, its format, and any other details (time limit, grading criteria, etc.) to reduce uncertainty and help them prepare.
  • Review the rules, instructions, and procedures: Go over the test rules, instructions, and procedures, and answer any questions students may have to avoid confusion and uncertainty.
  • Make sure students can use the technologies: Show them how to use any tools, platforms, or software they’ll use to take the exam. Provide a live demonstration if needed.
  • Offer practice exams: Practice exams help students get familiar—and hopefully comfortable—with technologies and confirm their device meets system requirements.
  • Show students how to access technical support: Provide technical support contact information and show them how to access it.
  • Provide information about accommodations: Discuss available accommodations (e.g., extended exam time, assistive technologies, etc.) and provide information on how to access those resources.
Did you know? Many college students with disabilities don’t disclose them because they’re unaware of available support or how to access it, and they fear stigma, judgment, and unequal treatment from peers and instructors. (Adam & Warner-Griffin, 2022; Herrick et al., 2020)

Prevent the use of generative AI chatbots

Generative AI chatbots, such as ChatGPT, Gemini, Claude, and Microsoft Copilot, are a double-edged sword in higher education. They’re great for faculty because they assist with content creation and lesson planning, and students can use them for tutoring and interactive learning activities like language practice and debates. Unfortunately, students also use AI to generate written responses for assignments, whether it’s long-form essays or short answers.

Teaching strategies to mitigate AI cheating in online learning

While it’s an uphill battle to some extent, there are ways faculty can adapt their course activities and assessment and technology that can help.

Does AI detection work?

AI detection works when students copy and paste AI-generated text without changing it. But students are smart and savvy. They’ll edit, paraphrase, and rework the text to make it their own; when that happens, AI detection software is ineffective and unreliable at best.

Aside from using remote proctoring technology to block AI, here are a few examples (below) of how to discourage students from using AI to complete their coursework.

Baron (2024) tested the largest commercial plagiarism and AI detection platform against ChatGPT-generated text. The study found that the detection tool was accurate when the text was unaltered, but when Quillbot paraphrased the text, the AI detection platform’s accuracy score dropped to 31% and 0% after two rephrases.

A study by Weber-Wulff et al. (2023) tested 14 AI detection platforms (12 publicly available and 2 commercial) against ChatGPT. The researchers concluded that AI detection is often inaccurate when text is manually edited, paraphrased, or reordered, and struggles with identifying AI-translated content.

Gupta and Gupta (2024) discuss the accuracy issues of AI detection platforms, stating that, “The market teems with AI detection tools, each boasting superior precision and competitive advantages. Yet, research reveals a stark reality: these tools often fall short in accuracy and reliability.”

Scaffolded assignments are basically just a series of smaller tasks/assignments that build up to a larger assignment. For example, instead of one long-form essay, have students brainstorm topics and submit a proposal and outline, then write a rough draft for peer review, and the final assignment is an essay followed by a reflection.

You can also ask students to submit each task in a different format. For example, the brainstorm could be presented as a mind map; the proposal and outline could be presented in PowerPoint with visuals; the rough draft and final essay could be in Word or Google Docs; and the peer review and reflection could be done through audio or video submissions.

Authentic assessments offer students an opportunity to apply their skills and knowledge by completing realistic tasks they may face in the real world.

For example, instead of asking accounting students to answer a series of multiple choice test questions, an authentic assessment may ask them to prepare cash flow statements, balance sheets, multi-year depreciation schedules, etc.

Connect assignments to information directly from class, such as comparing and contrasting discussion responses from two classmates or aligning a theory with a particularly interesting comment from a live discussion.

While this isn’t foolproof, students would likely spend more time giving the AI the right information and tweaking the response than simply writing the response themselves.

Scaffolded assignments are basically just a series of smaller tasks/assignments that build up to a larger assignment. For example, instead of one long-form essay, have students brainstorm topics and submit a proposal and outline, then write a rough draft for peer review, and the final assignment is an essay followed by a reflection.

Authentic assessments offer students an opportunity to apply their skills and knowledge by completing realistic tasks they may face in the real world.

For example, instead of asking accounting students to answer a series of multiple-choice test questions, an authentic assessment may ask them to prepare cash flow statements, balance sheets, multi-year depreciation schedules, etc.

Connect assignments to information directly from class, such as comparing and contrasting discussion responses from two classmates or aligning a theory with a particularly interesting comment from a live discussion.

While this isn’t foolproof, students would likely spend more time giving the AI the right information and tweaking the response than simply writing the response themselves.

AI resources from universities

Several universities have developed excellent resources for faculty to control the use of AI, whether blocking it entirely or integrating it thoughtfully in their course activities.

Involve students in the process

Students significantly influence their peers’ academic behavior, both positively and negatively, so faculty and institutions should collaborate with students to align on acceptable behavior and build a culture of academic honesty where students reject cheating and lead by example (Daumiller & Janke, 2020; Forkuor et al., 2019).

Students learn more about academic integrity when their peers teach them, and having student delegates address integrity issues and guide them through processes like requesting hearings creates a more positive, lasting impact (Malizia and Jamenson, 2018; Zivcakova et al., 2014).

Orr & Orr (2019) suggest that peer-to-peer discussions about academic misconduct can deepen students’ understanding of academic integrity and recommend training student delegates to:

  • Conduct respectful, supportive conversations 
  • Understand academic integrity policies, procedures, and processes
  • Practice real-life scenarios to prepare for handling cases

Institutional leadership should continually talk to those involved in handling dishonesty cases and educating peers about academic integrity to understand how the institution can improve efforts, such as streamlining specific processes and offering students practical training and resources like citation workshops and digital guides with citation tips.

Clearly define academic dishonesty

As we mentioned earlier, students struggle to understand which actions are considered cheating (Carpenter et al., 2010; Tatum & Schwartz, 2017). However, when students are provided with clear examples of what counts as cheating, it can help them understand their own actions and whether they qualify as cheating (Burrus et al., 2007).

Tips to create a shared definition of cheating:

  • Define it: Provide detailed descriptions of what you consider cheating along with examples and share them throughout the course.
  • Write clear rules and instructions: Write clear, objective rules for exams and assignments. Review them with students and discuss scenarios to define cheating together.
  • Emphasize the value of integrity: Discuss how academic integrity contributes to academic growth and prepares them for future success instead of enforcing compliance.1
  • Remind them of the course honor code: Mention the course honor code before each exam because studies show this can reduce cheating.2 This shouldn’t be the only time you discuss the honor code though.

Bonus tip: Teach students how to cite their work. Plagiarism can be confusing and so can citation requirements—APA or MLA? Chicago, maybe? When do you cite sources? What’s considered “common knowledge”? Teach students how to cite sources and provide helpful resources in the course.

Recommendation from: 1Forkuor et al., 2019; 2Zhao et al., 2023

Reading definitions of cheating can change how students view their behavior

After reading definitions of behaviors that are considered cheating, students reported much higher rates of cheating (Burrus et al., 2007).

Write objective rules and instructions

As discussed throughout this article, confusion and different interpretations of cheating often lead to dishonest behavior. One piece of the puzzle to help reduce confusion is writing clear and objectives rules and instructions for tests and assignments. 

Writing these can be difficult. They need to be comprehensive but also clear and concise, which is a tough balancing act.

Original rule
Your desk must be clear of all items except the device you use to take the test.
Updated rule

The testing area and any surface your device is placed on must be clear of all items except the device used to complete the test. This includes books, papers, electronics, and other personal belongings.

Rationale: The original rule doesn’t account for situations where a student’s only option is to place their device on the floor or a kitchen counter, for example, instead of a desk or table. Students might argue, “I was at a table, not a desk,” or, “The rule says ‘your desk,’ but I don’t own this desk.”

That rationale may seem far-fetched, but the point is that word choices matter and they can be exploited. And if nuances in word choices didn’t matter, attorneys and contract specialists would have way more free time.

Support faculty & remove friction from the reporting process

Two faculty surveys found that they don’t report cheating because it’s so time-intensive, and they don’t believe their institution handles cases of academic dishonesty consistently or effectively, all contributing to faculty feeling unsupported (MacLeod & Eaton, 2020; Staats et al., 2009).

Survey faculty and staff involved in academic misconduct cases to identify issues and gather improvement ideas, then use their input to review the process with these initial considerations:

  • What’s holding things up? Identify bottlenecks and specific steps that cause delays and frustration.
  • Revamp and remove: Are there outdated steps or unnecessary requirements that can be updated, changed, or removed?
  • Identify quick fixes and long-term changes: Start with quick fixes while planning and working toward larger, long-term improvements.
  • Use technology to make things easier: Can any technologies reduce manual work and streamline processes?
    • Examples: Electronic forms to eliminate paperwork, scheduling software to automate case-specific meetings, proctoring tools to collect evidence, such as video recordings of misconduct, etc.
  • Collect feedback: After making changes, provide time for those involved in the reporting process to adjust and test the updates. Then, ask for their feedback on the process and what’s working or not working as planned.

Because every institution has its own resources, staff, structure, and technology, these tips are simply a starting point for improving the process of reporting academic misconduct, and they should be adapted to fit your specific needs.

Proctor online exams

While online exam proctoring effectively reduces cheating1, its impact on exam scores is less significant and straightforward than it might seem. Unproctored exam scores are usually higher than proctored ones—sometimes by a lot2, but the difference is usually relatively small3.

Shouldn’t unproctored exam scores ALWAYS be higher if students cheat? Not always.

Proctoring may change how students prepare for exams (in a good way)

Students may prepare more thoroughly for proctored exams because they know they can’t rely on using outside resources like the internet for help, which, according to Howard (2020), leads to exam scores comparable to those of students using those resources during unproctored exams. This extra preparation may explain why students who took proctored exams scored higher on recall tests months later (Howard, 2020; Zhang, 2024).

These findings align with a survey of over 1,500 students, where many said taking remotely proctored exams helped them prepare and stay focused, including one who stated, “I can’t cheat [during proctored exams]. Therefore, I have to push myself to learn.”

Students indicated that proctoring:

“… keeps me focused and not think[ing] about distractions.”

“… helps me focus more since I’m in my own environment.”

“… makes you accountable for actually learning the material, not just cheating your way through.”

“… keeps me focused on my work.”

“… challenges you to really try your best.”

“… helps me focus more and reduces the urge to cheat on things.”

“… keeps me in the right head space.”

“… keeps me focused on finishing the test.”

“… gives students the feeling of being alone and gets them in the right mindset to take a test.”

However, we aren’t saying that better grades on unproctored exams are only because students can cheat. Other factors contribute to higher scores on unproctored exams, like question formats and the testing environment itself (Zhang, 2024).

And most importantly, we can’t lose sight of the fact that many students prepare diligently for every exam whether they’re proctored or not.

Finding the right proctoring solution

Comparing proctoring vendors can be tricky because there are so many tools and types to choose from. Below is a brief overview of proctoring tools and the different types available.

Online proctored exam tools and features

Most services that use AI, whether entirely or as part of a hybrid solution, offer basic proctoring tools for online exams, like browser lockdowns and video monitoring. Those are a good start, but you’ll need more advanced tools to stop students from using cell phones or AI during exams.

  • Browser lockdown software: Restricts access to other websites and blocks keyboard shortcuts.
  • Video/audio monitoring: Uses the webcam and microphone to record behavior and the testing environment.
  • Identity verification: Confirms that the test taker is the student getting credit. Typically, it involves holding a form of identification up to the webcam.
  • Cell phone detection: Detects when students use cell phones, so you don’t have to rely on a proctor seeing a cell phone in real time.
  • AI blocking: Prevent students from using AI like ChatGPT unless faculty want to allow it.
  • Exam content protection: Searches the internet for your leaked exam content; offers a one-click takedown request.
  • Speech detection: Specifically listens for words/phrases, like commands that activate voice assistants like Alexa or Siri, which could provide students with answers.
  • Exam analytics: In-depth, actionable reporting on proctored assessments in one easy-to-use portal.
Types of proctoring software and services

The proctoring service’s approach also matters—some only use AI, others rely on humans, and some use both. Each type creates a different testing experience for students, so finding the right one is important for your institution, faculty, and especially your students.

Blocks sites, software, and keyboard shortcuts. Cheap, easy setup, but doesn’t stop cheating; students can still use phones and other resources.

AI monitors behavior (no humans) & flags potential academic misconduct. AI proctoring is cost effective and there’s no scheduling. However, no human oversight means overflagging, which can be distracting for students and takes longer for faculty to review.

Human proctors watch multiple students in real time and intervene if they see dishonest behavior. Offers human oversight and addresses misconduct immediately, but it’s expensive, scheduling is a hassle, and it increases student anxiety.

Hybrid proctoring blends live proctors with AI and a browser lock. AI monitors behavior during exams and alerts a proctor to review any suspicious behavior and intervene only if cheating is confirmed. There’s human oversight but this approach is less stressful for students because they aren’t being watched by a stranger. Hybrid proctoring also removes scheduling issues which improves scalability.

Institution staff or a proctoring service reviews recordings after exams are finished. Less stressful for students & offers human oversight, but there’s no real-time intervention & it’s expensive.

Focus on learning and mastery instead of grades

Initial strategies to help shift the focus of your course to learning and mastery:

  • Allow revisions to focus on mastery: Students are less likely to cheat when they can revise and improve their work because it shifts their focus to mastering the material instead of chasing grades (Anderman & Koenka, 2017; Ruth et al., 2024).
  • Provide detailed, constructive feedback: Providing feedback with examples, actionable tips, positive reinforcement, and supplemental resources helps students learn and improve their work.
  • Align coursework with real-world application: Course activities that reflect real-world situations help reduce dishonest behavior (Ruth et al., 2024). For example, accounting students could create balance sheets in Excel instead of answering multiple-choice questions.

These teaching strategies can help reduce students’ motivation to cheat and build toward a more positive, supportive culture focused on mastery (Malesky et al., 2022). 

And here’s some good news for instructors teaching elective courses to students who may only be there for credit: Focusing on mastery makes students less likely to rationalize cheating, even in classes they may be particularly interested in (Anderman & Won, 2019).

Address academic dishonesty every time it happens

Cheating decreases when faculty address every instance of dishonesty (Tatum & Schwartz, 2017). But as we mentioned earlier, faculty understand the importance of addressing cheating yet still hesitate to act on it for a number of reasons (MacLeod & Eaton, 2020).

Sometimes, it’s because reporting misconduct is too time-consuming, but some instructors avoid addressing cheating because of the stress and anxiety it causes (MacLeod & Eaton, 2020; Staats et al., 2009). And it’s just as tough on students, even though some see that as part of the consequences of breaking the rules.

But is that still true when a student cheated— let’s say they didn’t cite their sources—but genuinely didn’t realize it? Maybe they were never taught how to and when to cite them. Either way, you have to address it, or everyone loses.

How to talk to students about cheating

These conversations are as delicate to conduct as they are tough to prepare for. But they don’t have to be as negative and stressful as they seem.

What do you say? Better yet, what SHOULDN’T you say? What evidence do you need? What even counts as evidence? Do you email them first?

This article about how to talk to students about cheating has everything you need—even different email templates and talk tracks, depending on the situation.

Do more with academic integrity policies and honor codes

Academic integrity policies and honor codes won’t stop cheating altogether, but they can help reduce it to an extent. Sometimes, even just mentioning them before an exam reduces dishonest behavior, as students may think twice about their actions and potential consequences (Malesky, 2022; Tatum & Schwartz, 2017).

Most faculty are familiar with their institution’s academic integrity policy, but many only pay attention to it after incidents of academic misconduct occur or when they receive reminders to include policy details in their syllabi (MacLeod et al., 2020).

But they need to be more than a document on a school’s website or something you mention before a test. Institutions and faculty need to embed integrity into larger efforts that influence and encourage a culture of academic integrity, transparency, and accountability. 

In addition to the other strategies we’ve discussed, the tips below are a starting point to help faculty and leadership build a culture of academic integrity.

Regularly discuss integrity policies with students: Review and discuss academic integrity policies and class honor codes and link to them throughout your course syllabus, announcements, discussion boards, etc.

Be open and genuine: Have open, genuine conversations with students about why you care about academic integrity and how it impacts their education. Try sharing a bit about yourself.; tell them about your values and experiences or a relevant story to help them understand your perspective.

Assign class delegates: These students can help educate classmates about integrity policies and lead discussions about academic honesty.

Quick confirmation question: Add a question (graded or ungraded) at the start of a test where students acknowledge that they understand the instructions, rules, and policies. This is especially helpful when recent changes/updates have been made.

Build faculty and staff alignment: Hold semesterly training, require policy acknowledgments, create awareness of what counts as dishonest behavior, and centralize resources to keep faculty and staff aligned on integrity policies and updates.

Collect faculty feedback: Survey faculty (anonymously) to understand what questions and suggestions they have for academic integrity policies and the challenges they face in formally addressing academic dishonesty.

Train faculty to address cheating: Provide resources to help faculty conduct effective, healthy conversations with students they suspect of cheating. Hold workshops where faculty can engage in mock discussions for practice.

Learn from student delegates: Talk to those involved in handling dishonesty cases and educating peers about academic integrity to understand how the institution can improve efforts, such as streamlining specific processes and offering students practical training and resources like citation workshops and digital guides with citation tips.

No matter what strategies, policies, or technologies you have in place, there’s no cheat-proof system that lasts forever. Students are resourceful, and technology never stops evolving.

That’s why it’s not just about the tools and processes—it’s the people behind them. Faculty, staff, administrators, and students working together make the real difference. 

When everyone aligns, a culture of academic integrity emerges, where cheating becomes the exception, and learning comes first.

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Fatemi G, Saito E (2020) Unintentional plagiarism and academic integrity: the challenges and needs of postgraduate international students in Australia. J Furth High Educ 44(10):1305–1319. https://doi.org/10.1080/0309877X.2019.1683521

Forkuor, J. B., Amarteifio, J., Attoh, D. O., & Buari, M. A. (2019). Students’ Perception of Cheating and the Best Time to Cheat During Examinations. The Urban Review, 51(3), 424–443. https://doi.org/10.1007/s11256-018-0491-8

Gibson, Y., & Kuhn, R. (2024). E-Proctoring Tools: Is It a Necessary Inconvenience. Journal of Higher Education Theory and Practice, 24(7), 24–35. https://doi.org/10.33423/jhetp.v24i7.7088

Han, S., Nikou, S., & Yilma Ayele, W. (2023). Digital proctoring in higher education: a systematic literature review. International Journal of Educational Management, 38(1), 265–285. https://doi.org/10.1108/IJEM-12-2022-0522

Herrick, S. J., Lu, W., & Bullock, D. (2020). Postsecondary Students With Disabilities: Predictors of Adaptation to College. Journal of College Student Retention: Research, Theory & Practice, 24(2), 603–624. https://doi.org/10.1177/1521025120941011

Howard, D. (2020). Comparison of exam scores and time taken on exams between proctored oncampus and unproctored online students. Online Learning, 24(4), 204-228. https://doi.org/10.24059/olj.v24i4.2148

Hylton, K., Levy, Y., & Dringus, L. P. (2016). Utilizing webcam-based proctoring to deter misconduct in online exams. Computers and Education, 92–93, 53–63. https://doi.org/10.1016/j.compedu.2015.10.002

Janke, S., Rudert, S. C., Petersen, Ä., Fritz, T. M., & Daumiller, M. (2021). Cheating in the wake of COVID-19: How dangerous is ad-hoc online testing for academic integrity? Computers and Education Open, 2, 100055-.https://doi.org/10.1016/j.caeo.2021.100055

Johnson-Clements, T. P., Curtis, G. J., & Clare, J. (2024). Testing a Psychological Model of Post-Pandemic Academic Cheating. Journal of Academic Ethics. https://doi.org/10.1007/s10805-024-09561-4

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MacLeod, P. D., & Eaton, S. E. (2020). The Paradox of Faculty Attitudes toward Student Violations of Academic Integrity. Journal of Academic Ethics, 18(4), 347–362. https://doi.org/10.1007/s10805-020-09363-4

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Malizia, D. A., & Jameson, J. K. (2018). Hidden in plain view: The impact of mediation on the mediator and implications for conflict resolution education. Conflict Resolution Quarterly, 35(3), 301–318. https://doi.org/10.1002/crq.21212

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McCabe, D. L. (2016). Cheating and honor: Lessons from a long-term research project. In T. Bretag (Ed.), Handbook of academic integrity (pp. 187–198). Singapore: Springer Singapore.

Morin, M., Alves, C., & De Champlain, A. (2022). The Show Must Go On: Lessons Learned from Using Remote Proctoring in a High-Stakes Medical Licensing Exam Program in Response to Severe Disruption. Journal of Applied Testing Technology, 23, 15-.

Newton, P. M., & Essex, K. (2024). How Common is Cheating in Online Exams and did it Increase During the COVID-19 Pandemic? A Systematic Review. Journal of Academic Ethics, 22(2), 323–343. https://doi.org/10.1007/s10805-023-09485-5

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More resources for educators

How to Talk to Students About Cheating

A comprehensive guide with situational talk tracks, email templates, and realistic strategies for faculty to address academic dishonesty with students.

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Remote Proctoring 101: Software & Services

A comprehensive guide with situational talk tracks, email templates, and realistic strategies for faculty to address academic dishonesty with students.

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How to Proctor Written Assignments

Learn how to proctor essays and other written assignments to prevent the use of AI.

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How to Detect Cell Phones During Exams

Cell phones are the most common way students try to cheat on proctored tests. Learn how to stop it.

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Author
Tyler Stike
Tyler Stike
Tyler is Honorlock's Director of Content and a doctoral student at the University of Florida focused on educational technology.

Jason’s Fight to Keep Kids Safe Online

Jason Galasso holding his grandson. Text says Protecting Kids Online Takes a Village... And Jason

Did you know that 90% of children have a device (phone, tablet, etc.) in their bedroom at night, half of those children have given their information to strangers they met online, and almost 20% of those kids have met with a stranger?

Pretty scary, eh? That’s why Jason Galasso, Senior Security Engineer at Honorlock, dedicates his time to educating students, parents, teachers across the US, and even senior citizens about the very real dangers lurking online.

About ten years ago, Jason and his wife attended a class at their daughter’s high school on keeping kids safe on social media.

But to his surprise, only two other couples showed up, and that’s when it hit him: “I thought, ‘If the kids and their parents aren’t here, how will they learn about it? How can parents teach their kids if they don’t know what they don’t know?”

It was that nearly empty classroom that started his mission. “That was the turning point for me. I knew I had to do something.” So he did. 

Jason earned a Certified Information Systems Security Professional (CISSP) certification, a globally recognized certification for experienced security professionals.

Jason Galasso holding grandson

This certification gives him the credentials to educate others about security threats, and with over 25 years of IT experience, Jason is well-equipped to protect Honorlock from a wide range of risks. He oversees the defense against known threats, manages vulnerability and penetration testing programs, leads security awareness training, protects our computer systems and networks, and assesses security risks while managing our Vendor Security and Bug Bounty programs.

Want Jason to speak at your school?
Message him on LinkedIn
REACH OUT

While cybersecurity is complex, Jason’s goal is simple: “Protecting kids today and setting them up to be better cybersecurity citizens in the future.”

Part of that means providing students, parents, and teachers with timely, relevant training and information, “Kids need to learn how to use the internet and technology responsibly, and part of that means parents, teachers, and schools being able to reinforce that.”

Three aspects of Jason’s approach help accomplish that:

1. Stay relevant: “Anything you discuss has to connect with what students, teachers, and schools actually use. Whether it’s social media apps students use and video games they play at home, or the technology and devices they use at school, it has to be relevant to their everyday lives.”

2. Be available: “Even if a teacher called me at midnight with a question, I’ll talk all night if it’ll help them keep students safe.”

3. Keep it simple: “I keep things simple to address issues and what they can do about it… Here’s a problem. Here’s a solution. Here are more resources to help you learn about it.”

Many of those resources come from two cybersecurity programs Jason works with, Be Internet Awesome with Google and the Center for Cyber Safety & Education by ISC2. These programs offer excellent resources that are consistently updated to keep up with cybersecurity risks and happenings.

Jason Galasso in a class teaching students about cybersecurity
Jason teaching students (faces blurred)

Cybersecurity tips & resources

Tips for different audiences

Online safety tips for kids
  • Create strong, unique passwords for every site.
  • Don’t share private information (like passwords) over email.
  • Never tell anyone your passwords—not even your friends!
  • When posting pictures on social media, deactivate geotagging from your photos.
  • If someone is cyberbullying you, tell an adult and remember it's not your fault!
  • Be careful what you post because once it’s online, it’s there forever.
  • Don’t meet people in real life that you only know from the internet.
  • Keep your social media accounts private and be careful about what you share.
  • Only accept messages and friend requests from people you know.
  • Don't post your address or photos of your house.
Tips above adapted from iamcybersafe.org
  • Create strong and unique passwords for every site.
  • Teach your children not to click on pop-ups.
  • Never send sensitive information over email.
  • If your children use social media, remind them to never meet with anyone they met online.
  • Restrict what your child can download until they are the appropriate age.
  • Many devices come with parental controls, use them!
  • Set up central charging stations in your home to keep all devices together.
  • Backup your data using cloud services or an external portable storage device.
  • Be vigilant about reviewing your credit card statements.
  • Shred all documents with personal information that you don’t need.
Tips above adapted from iamcybersafe.org
  • Use strong, different passwords for each website.
  • If you’re unsure about a scholarship, ask financial aid, especially if you didn’t apply for it.
  • Don’t check your bank info on public wifi.
  • Never email personal details like passwords or credit card numbers.
  • Turn off location on photos before sharing them online.
  • Keep your firewalls turned on and up to date.
  • Save your files using cloud storage or a portable drive.
  • Check your credit card statements carefully.
  • Shred papers with personal info that you no longer need.
Tips above adapted from iamcybersafe.org
  • Create strong and unique passwords for every site.
  • Never send sensitive information over email.
  • Do not check your bank information on open wifi.
  • Only accept friend requests on social media from people you know.
  • Shred documents with personal info that you no longer need.
  • Do not use online shopping sites that require you to enter personal information to access coupons or discount codes.
  • If you’re a victim of romance fraud, report it to the police.
  • Be mindful of email and phone call fraud attempts.
  • Question what you see in emails and pop-ups.
  • Download and stream from verified sites only.
Tips above adapted from iamcybersafe.org

Cybersecurity resources

Organization & link
Use cases
Have I Been Pwned
Check if your email address was leaked in a data breach
Identitytheft.gov
Report identity theft & resources to recover
FBI-SOS
Online safety tips for 3rd grade and up
ConnectSafely
General resources about online safety, privacy, security, and digital wellness
StopBullying.gov
Identify bullying and how to stop it
Stay Safe Online
Diverse resources about cybersecurity and staying safe online

Jason’s dedication to educating others shows how vital it is to stay informed and proactive because cybersecurity is everyone’s responsibility. With the right knowledge and tools, we can create a safer online environment for everyone.

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Honorlock Makes List of Top 10 Superstars in Emerging EdTech Companies for Higher Education by Emerge Education

Honorlock, the leading online exam proctoring service, earned a spot as one of the Top 10 Superstars for Higher Education on the 2024 EdTech 20:20 Vision list by Emerge Education. 

The list, compiled by Emerge Education with input from industry experts, analyzed over 1,000 companies to highlight the innovative edtech companies that can transform higher education.

Being selected as a Top 10 Superstar means that Honorlock and the other educational technology companies are well-established and well-funded, and each has a large customer base among higher education institutions worldwide.

List Methodology

Emerge Education’s Higher Education Edtech Advisory Board and Venture Partners compile this list through crowdsourcing and voting. 

To be considered, companies must meet the following criteria:

  • Range and quality of courses/content/teaching methods
  • Quality of features and capabilities
  • Industry presence, innovation, and influence
  • Strength of clients and global reach
  • Company size and growth potential
Logos of Top EdTech Companies for Higher Education Named by Emerge Education
Image Credit: Emerge Education & Medium.com

About Honorlock

While most online proctoring services sacrifice the entire test experience to catch cheating, Honorlock is different.

Our smarter proctoring approach combines AI and live human proctors to improve the testing experience for instructors and students while still protecting academic integrity. 

How does Honorlock work?

Pre-exam

It’s basically the same experience for instructors and students except for a few clicks.

  • For instructors: upload your exam to your LMS like you already do, choose which proctoring features you want to use, and set accommodations if needed.
  • For students: log into the LMS (no extra passwords/logins), verify ID and scan the room if the instructor requires, and then launch the exam.

During the proctored exam

  • If the AI detects potential misconduct, it alerts a live proctor to review the behavior. 
    • The proctor only intervenes if misconduct occurs. Otherwise, the student won’t be interrupted, and the instructor won’t have to review countless unimportant flags after exams are completed.

Post exam

Because Honorlock’s live proctors review exams in real time, instructors have significantly fewer exam sessions to review. 

Additionally, Honorlock offers filterable, easy-to-read reports with timestamped recordings, further streamlining the review process.

About Emerge Education

Emerge supports early-stage EdTech startups globally, providing capital and access to a network of industry professionals who are committed to democratizing education and fostering new learning opportunities.

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University of Florida Student Testimonial
Can in-person classes and blended courses benefit from online proctoring?
7 reasons online proctoring works for any course format
Using online proctoring to improve the online assessment experience
Online proctoring improves the testing experience
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Hint: Plagiarism detection can’t really detect AI
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Industry 4.0 Technologies & Certification Programs

What's next in industry 4.0?

What is Industry 4.0?

The simple answer is that Industry 4.0 uses really smart technologies to make companies bigger, better, faster, stronger. Tons of technologies are involved, but we’ll focus on a few that are foundational elements of the “Fourth Industrial Revolution”:

  • Artificial Intelligence (AI): machines learn and do tasks requiring human-like intelligence.
  • Machine Learning (ML): algorithms learn from data to improve AI performance.
  • Internet of Things (IoT): internet-connected devices that collect and exchange data.
  • Cloud Computing: delivers internet-based data storage, processing, and software.
  • Robotics: robots perform tasks to replace or assist humans.

The first and second industrial revolutions (Industry 1.0 & 2.0) used simple machines, assembly lines (think Henry Ford), and, eventually, electricity for mass production. The third (Industry 3.0), also called the Digital Age and Information Age, brought computers and automation into the mix.

Industry 4.0 relies on multiple technologies

Instead of any technology working by itself, Industry 4.0 depends on technologies working together. For example, IoT devices send real-time data to the cloud, where it’s stored and processed. Then, AI and ML analyze the data to find problems, predict trends, and suggest improvements to technologies and processes. This creates a cycle of improvement.

But there’s a catch:

you need people that can effectively implement and manage these technologies.

But there’s a catch:

you need people that can effectively implement and manage these technologies.

The first part of this article summarizes how the technologies work. The second part covers how organizations are investing in workforce upskilling and reskilling to prepare employees for the roles required to use these new technologies. Click to skip to part two.

Industry 4.0 technologies

Artificial intelligence, the cloud, machine learning, and the Internet of Things. You’ve probably heard these at some point, but they aren’t just trendy buzzwords; they’re powerful technologies that help organizations become more efficient, connected, agile, and ready for anything.

Artificial Intelligence (AI) and Machine Learning (ML)

Many technologies are involved in Industry 4.0, which relies on automation and data, but AI and ML are the brains and the foundation behind it all.

They make simple automation highly intelligent and adaptable, and data processing is more predictive and accurate. And because of that, organizations can be more proactive and flexible, rather than reactive and scrambling to catch up.

Without AI and ML, Industry 4.0 would be entirely different—or maybe not even a thing yet. Organizations would likely face slowed production, increased waste (time, resources, and materials), lower quality, missed opportunities in the market, and ultimately, decreased profits.

Sometimes the terms are used interchangeably, but they’re different. ML is just one branch of AI, which also includes technologies like natural language processing (NLP), large language models (LLM), robotics, speech recognition, and computer vision.

While both make machines smarter, they do it in different, but complementary ways:

  • AI helps machines learn, solve problems, and make smarter decisions.
  • ML uses algorithms to help machines learn from data and make their own decisions about their actions and future events.

Internet of Things (IoT)

The Internet of Things just means smart devices and technologies connected to the Internet that can collect and share data, and, in some cases, interact directly with each other.

Here are IoT technologies and how they’re used at home and at work:

IoT at home: Smartphones, TVs, thermostats, cameras, appliances, etc. For example, controlling your thermostat and security system from your smartphone.

IoT at work (Industrial Internet of Things): automated systems, machine sensors, security and remote monitoring, data analytics, robots, cloud computing, etc. For example, a self-driving forklift stacks pallets and relays progress data to cloud platforms

Without the constant stream of data from IoT, Industry 4.0 wouldn’t have the data it needs or the real-time communication between all the devices and technologies involved.

Cloud Computing

You’ve probably heard of cloud computing and other terms, like “the cloud.” So, what do they actually mean?

In simple terms, cloud computing just means using the internet to store data and access software and other resources instead of using physical hardware. It’s one of the major reasons that we can collaborate in real time while working remotely.

Cloud computing is usually a “pay-as-you-go” model, so companies only pay for what they actually use. It also means no setup fees and unpredictable overhead costs for physical hardware, which means saving a lot of money on equipment, electricity, etc.

How many companies use cloud computing?

Most companies use cloud computing in some way. Whether it’s just for accessing email and sharing documents or for managing internal operations and hosting their cloud-based products and services entirely online.

Robotics

Robots are great at performing repetitive (and hazardous) tasks all day, every day, and they can integrate with Industry 4.0 technologies, which means they can communicate, collect, and share data in real time.

Using robots doesn’t necessarily mean better quality products—some people pay more for handmade products—but they can help standardize production processes, making them more predictable and less prone to errors (hopefully).

Preparing the workforce for Industry 4.0

While companies are doubling down on Industry 4.0 technologies, they need workers who can effectively use them.

That’s why companies are investing in developing their people by upskilling and reskilling them through Industry 4.0 certification programs that train them to use these technologies.

Industry 4.0 certification programs

Industry 4.0 certifications come in all shapes and sizes. Some focus on learning the fundamentals of Industry 4.0 as a whole, while others are specialist programs for specific roles. 

For example, Smart Automation Certification Alliance (SACA), offers a Certified Industry 4.0 Professional certification, which requires participants to earn a series of micro credentials for a wide variety of technologies to earn the certification. In contrast, they also offer specialist certifications like Automation Systems Specialist and Electrical Systems Specialist, which are tailored for specific roles.

Regardless of the type, earning an Industry 4.0 certification usually requires a standard testing component, a written knowledge assessment, and a hands-on practical assessment. This proves that participants know the information and can apply what they’ve learned in real-life situations.

Securing Industry 4.0 certification exams

Any certification exams need to be remotely proctored to prevent cheating and protect the exam content and validity of the program.

Without remote proctoring, how would you know if participants are:
  • Sharing your exam content on the internet
  • Using their cell phones to look up answers
  • Getting ChatGPT or other generative AI to write responses
  • Asking Siri and Alexa for help
  • Having someone take the test for them (contract cheating)
You can’t just use any remote proctoring system, though. Locking the browser isn’t enough. Taking assessments has too many nuances to only use AI monitoring. And having live proctors watch test takers the entire time is distracting and expensive.

Proctoring certification exams with Honorlock

Honorlock’s remote proctoring solution secures certification exams from start to finish with a hybrid approach that combines live proctors and AI monitoring. 

Organizations get secure certification exam proctoring that’s scalable, affordable, and customizable, while participants enjoy the flexibility of taking their exams anytime, anywhere, without scheduling.

Here's how Honorlock works (scroll)

AI monitors each participant's behavior during the exam
Participants are monitored using video and other AI proctoring tools, like cell phone detection, voice detection, secure test browser, etc.
What if the AI detects potential misconduct?
If the AI detects any potential misconduct, it alerts a live proctor to review the behavior in an analysis window.
Proctors reviews & intervene if necessary
After reviewing, the proctor only intervenes if misconduct occurs or to help support participants. If there's no misconduct, the participant won’t be interrupted, and the exam admin won’t need to review unimportant flags.
Accessing exam reports and recordings
Administrators can access in-depth reports with time-stamped recordings in the learning platform after certification exams are complete.

Honorlock's Proctoring Features & Benefits

Exam content protection

Honorlock’s Search & Destroy™ proctoring technology automatically scans the internet to find leaked exam questions and offers a one click option to send content takedown requests.

Cell phone detection

Instead of relying on a proctor catching a participant using their phone in real-time, Honorlock’s cell phone detection toolkit can detect when test takers attempt to use their cell phones or other devices to access test bank content during the exam and when Apple devices in the testing area.

Block AI tools

A combination of virtual proctoring tools prevent participants from using AI like ChatGPT and Claude during certification exam activities.

ID verification & room scans

Exam administrators can require participants to verify their identity, (only takes about a minute) and scan the room for unauthorized resources like notes, secondary devices, etc.

Secure test browser

Honorlock’s BrowserGuard™ secures test browsers by recording desktops and preventing and flagging when participants try to access other browsers and use keyboard shortcuts, like copying and pasting.

Proctor exams in third-party platforms

Our online proctoring software integrates with third-party assessment platforms to secure certification exams taken outside of your assessment platform.

Smart voice detection

 Instead of flagging unimportant noises like coughing, Honorlock’s AI listens for certain keywords and phrases that may indicate cheating, like participants saying, “Hey Siri” or “Alexa,” to activate a voice assistant for help.

Integrating Honorlock with your assessment platform

Honorlock’s proctoring platform integrates with platforms like Docebo*, Intellum, SACA, CloudCME, Canvas, Blackboard, D2L, Moodle, and Open LMS*. Or you can integrate Honorlock directly into your platform with our APIs and Elements toolkit.

24/7 proctored certification exams with live support

Honorlock’s remote proctoring services and support are on-demand, which means certification exams can be taken anytime without scheduling, and live support is available in less than 15 seconds.

Flat-rate proctoring costs

Honorlock helps organizations avoid variable costs, like when tests take longer than expected, by offering a flat-rate cost per certification test or per test taker.  Even better, the cost includes implementation, training, and a dedicated success manager.

New technologies are always popping up with different, and sometimes better, ways to do things.

But the challenge—and opportunity—is to continuously upskill and reskill our workforce for today and tomorrow because keeping skills sharp and credentials current isn’t just beneficial—it’s required to stay competitive and innovative.

Schedule a demo with Honorlock