# bok-ai-lab-20250404-research

[full research](https://docs.google.com/document/d/18WolO_KNzxXVdbl8-D13QiDohGSI2GoQaGFuJFJDrTU/edit?tab=t.0)

# Polling Tools in Higher Education: An Overview (Focus on Poll Everywhere)

(o1 Pro Deep Research)

## **Introduction to Classroom Polling Tools and Their Purpose**

([Promoting active learning in large classes | Poll Everywhere](https://www.polleverywhere.com/case-studies/lecture-method)) *Students in a large lecture hall often use personal devices for interactive polls.*
Classroom polling tools (also known as **student/audience response systems**) are technologies that let instructors pose questions and collect real-time responses from students during class. The goal is to boost engagement and give every student a voice, even in large classes. For example, an instructor might begin class by polling students about their understanding of last night’s reading, or end with an exit survey to gauge what they learned. Using a **“bring your own device”** model (students respond via their phones, laptops, etc.), modern polling platforms allow everyone to participate simultaneously and often **anonymously**, which helps reduce anxiety and encourage honest input ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=Furthermore%2C%20our%20own%20internal%20polling,a%20more%20interactive%20classroom%20space)). In effect, polling tools turn one-way lectures into two-way conversations, providing immediate feedback to both students and instructors. This live feedback can be used as a **formative assessment** – checking for understanding, misconceptions, or opinions in the moment – so the teacher can adjust instruction on the fly. Popular polling systems in higher ed include Poll Everywhere, Mentimeter, iClicker, and Socrative, among others. In this overview, we will focus on **Poll Everywhere** as a representative example to illustrate the features, use cases, technical workflow, and emerging roles for AI in such tools.

Poll Everywhere is a web-based polling platform widely used in universities for its flexibility and ease of use. It supports both in-person and online classes via cloud-based technology, meaning no extra hardware is required beyond student devices ([Poll Everywhere: Overview | Discover Instructional Tools | Canvas @ Yale](https://help.canvas.yale.edu/a/1334907#:~:text=Poll%20Everywhere%20is%20Yale%27s%20supported,be%20used%20to%20ask%20a)). Instructors create questions (polls) through a web interface, and students respond using a link or SMS code; results are aggregated instantly. Poll Everywhere offers a variety of question formats – from multiple-choice and open-ended questions to word clouds, rank-order polls, clickable images, and surveys ([Teachinghistory.org](https://teachinghistory.org/digital-classroom/tech-for-teachers/25829#:~:text=,ended%20questions)). This variety allows instructors to choose the format that best fits their pedagogical goal, whether it’s quizzing factual knowledge, collecting opinions, or visualizing ideas. By seeing responses **in real time**, teachers can identify confusion (e.g. if many students choose a wrong answer) and address it immediately, or spark discussion by highlighting diverse answers. In short, polling tools like Poll Everywhere serve the purpose of **increasing student engagement, checking comprehension, and making learning active** ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=Furthermore%2C%20our%20own%20internal%20polling,a%20more%20interactive%20classroom%20space)) ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=PollEv%20can%20help%20to%20illuminate,comfortable%20in%20providing%20an%20answer)). In the sections below, we explore how such tools are used across different disciplines, then delve into how they work behind the scenes, and finally consider how AI can enhance their effectiveness.

## **Pedagogical Use Cases Across Disciplines**

One of the strengths of classroom polling is its adaptability to almost any subject. Educators in the humanities, social sciences, and STEM fields have each found creative ways to integrate polls into their teaching. Below are a few use cases illustrating how Poll Everywhere (and similar tools) support pedagogy in various disciplines:

### **Humanities (e.g. History, Language, Literature)**

In humanities courses, polling tools can transform passive discussions into interactive dialogues. For instance, in a **history** lecture with 200 students, Professor Sarah Shields used Poll Everywhere to give each student a voice despite the large class size. At the University of North Carolina, she began each session with an **attendance poll** that doubled as a warm-up question on historical facts, immediately engaging students at the start of class. During the lecture, she would pose big-picture questions (“Why did this event happen the way it did?”) and have students submit responses via their devices. At the end, she often prompted small-group discussions on a major historical issue and then collected their ideas through a live **word cloud** poll. The word cloud allowed everyone to see the range of thoughts in the room, visualizing common themes by making frequently submitted words larger. This technique not only kept students attentive, but also helped them “think like historians” by evaluating and prioritizing evidence collectively, rather than just listening to facts. The anonymity of polling was key – students could contribute ideas or take a stance on a historical debate without fear of embarrassment, which **emboldened even shy students to participate** both through the tool and later aloud in class discussions.

In smaller **seminar-style humanities courses**, polls can likewise encourage broad participation. In literature or philosophy classes, an instructor might poll opinions on an interpretive question (“Which character do you sympathize with most?”) and use the spread of answers as a discussion starter. Because responses can be submitted silently, *every* student – not just the outspoken few – gets to weigh in on contentious or abstract questions. University teaching consultants note that this is especially useful when discussing **sensitive or controversial topics**: an anonymous poll can surface diverse viewpoints that students might hesitate to voice publicly. For example, a religious studies teacher could poll reactions to an ethical scenario, then reveal the (anonymous) distribution of responses to the class. Seeing the mix of opinions can validate minority viewpoints and prompt students to ask each other why they answered as they did, enriching the discussion. Similarly, in a language class, an instructor could use a poll as a quick **comprehension check** (e.g. show a sentence and ask which translation is correct) or even for a word cloud where students submit one word they learned from a reading. These strategies in humanities courses help students find their voice and actively engage with the material, rather than remaining passive listeners ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=Furthermore%2C%20our%20own%20internal%20polling,a%20more%20interactive%20classroom%20space)).

### **Social Sciences (e.g. Sociology, Political Science, Psychology)**

Polling tools align naturally with the social sciences, where understanding perspectives, opinions, or conceptual frameworks is key. In a large **introductory sociology** course, for example, Professor Joe Harris faced the challenge of making a big class feel intimate and interactive. He adopted Poll Everywhere as a low-cost way to foster discussion, noting that *“for those of us who teach large classes, this is a way to connect to students and generate the feeling of a small class discussion”*. Harris would pose provocative questions to his 100+ students, such as *“How much ‘free will’ do we have?”* – a question aimed at getting students thinking about individual agency versus structural forces. Students would submit their initial votes anonymously via Poll Everywhere, producing an instant bar chart of the class’s stance. Seeing the results on screen (often a wide range of opinions) served as a **conversation starter**: *“When you get votes anonymously and you put that on the board, then the class can unpack that,”* Harris explains. In this case, the poll allowed the class to openly debate the influence of social structures (like class, gender, or race) on personal choice. As the course progressed, Harris could poll the **same question again** to see if opinions shifted after students learned more sociology. Indeed, he found that as students understood the powerful constraints of social structures, their collective responses to the free-will question changed – a powerful visual of learning in action. Poll Everywhere thus enabled him to capture a snapshot of students’ beliefs, ignite a dialogue, and then track how learning altered those beliefs over time.

Beyond gauging opinions, social science instructors use polling for formative quizzes and checking understanding of concepts. In psychology, an instructor might present a short scenario and poll which psychological principle students think it illustrates. In political science, before explaining a public policy concept, a professor could ask students to vote on a relevant current issue (e.g. *“Should college be free for all?”* as a lead-in to a lesson on education policy). The live results can make abstract concepts concrete – for instance, showing polarization in the class’s responses could segue into a discussion of public opinion data. Polling can also help with **sensitive topics** in social sciences. When discussing social justice issues or controversial subjects, a tool like Poll Everywhere allows students to contribute their perspectives or personal experiences anonymously. This can create a safer space for discussing topics like race, gender, or politics: the instructor can display a range of student viewpoints from the poll (without attaching names), ensuring that even quieter students or those with minority opinions are represented. Such inclusive Q\&A sessions *“provide an avenue of increasing participation \[on\] difficult or sensitive topics”* by letting students respond freely under the protection of anonymity ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=PollEv%20can%20help%20to%20illuminate,comfortable%20in%20providing%20an%20answer)). Overall, in social sciences polls are used to **engage students in critical thinking and reflection**, making large classes feel interactive and surfacing opinions or misconceptions that fuel deeper discussion.

### **STEM Fields (Science, Technology, Engineering, Math)**

Polling systems have a rich history in STEM education, often associated with the **“clicker” methodology** and peer instruction pioneered in physics classes. In large STEM lectures, instructors use polls to actively engage students in problem-solving and concept tests. A classic example is **Eric Mazur’s Peer Instruction** technique in physics: the teacher poses a conceptual question (often a multiple-choice **concept test**) and students submit their individual answers via a polling device. The instructor then displays a histogram of the responses (without revealing the correct answer). Typically, if there’s a mix of answers (which is desired for stimulating thought), students are prompted to **discuss in pairs or small groups** to convince each other of their answer. After a few minutes of debate, students vote again on the same question. The expectation (as Mazur found) is that the percentage of correct answers increases after peer discussion, because students learn by explaining the concept to one another. Finally, the instructor clarifies the correct answer and reasoning. Poll Everywhere (or similar tools) facilitate this entire workflow digitally – no physical clickers needed – and instructors in disciplines like biology, chemistry, and engineering have adopted it. The key is asking a good conceptual question that provokes discussion (e.g. a physics question about force where common misconceptions lead to different answers). This approach has been shown to improve understanding and keeps students actively thinking during lectures.

STEM instructors also use polling for **predictive questions and experiments**. For example, a chemistry professor might ask: *“What do you predict will happen if we mix X and Y?”* Students vote on the outcome *before* a live demonstration. This engages their prior knowledge and curiosity. After the demo, a follow-up poll can ask them to explain what did happen, reinforcing the lesson. Such prediction polls turn students from passive observers into participants in the scientific process. In mathematics or computer science, an instructor could poll students on the next step of a problem solution or the output of a piece of code, respectively, to check understanding in real time. Poll Everywhere even supports LaTeX formatting for equations, which is helpful for displaying math and scientific notation in questions or answer choices.

Another use in STEM is incorporating polls into **flipped classrooms** or problem-solving sessions. Students might be polled on a homework problem result, or asked to submit an answer to a challenging concept question after some group work. The instructor can instantly see the distribution of answers to gauge if the class is grasping the concept or if further review is needed. Research has found that using Poll Everywhere in a flipped classroom can increase effectiveness of the teaching-learning process, as it ensures students are continually processing and testing their knowledge during class. Finally, polls in STEM can add a bit of gamification – for instance, using Poll Everywhere’s **competition mode** (a quiz that awards points) to run a short trivia contest on course content can energize the class and reinforce key facts in a fun way. Overall, across STEM fields, polling tools serve to **transform lectures into interactive learning sessions**, enabling immediate application of concepts and providing feedback to both students and instructors about where understanding is strong or where misconceptions persist.

## **How Polling Tools Work: A Technical Walkthrough**

Poll Everywhere and similar polling systems might seem “magical” from the classroom perspective – questions and answers flying back and forth instantly – but under the hood they rely on a classic **client–server architecture**. For faculty new to coding, it’s helpful to break down how these tools operate in simple terms. Below is a conceptual walkthrough of a typical polling workflow, with analogies to familiar technologies (like Slack bots, Next.js web apps, and Python data analysis notebooks) to illustrate the moving parts:

1. **Creating a Poll (Instructor Side – *Client to Server setup*):** The process begins with the instructor (presenter) creating a question using the Poll Everywhere interface. This is done on a website or app – effectively the **front-end client** that the instructor interacts with. For example, you log in to Poll Everywhere, click “Create Activity,” and type a question with multiple-choice options. When you hit save, that information is sent to Poll Everywhere’s **servers** (the back-end). In coding terms, this is like using a content management UI built with a web framework (imagine a simple form in a Next.js app) that triggers an API call to store the new poll in a database. The Poll Everywhere server assigns the poll an ID or unique URL (e.g. **PollEv.com/YourUsername** with the question queued) and makes it available for students to respond. This part of the workflow is akin to configuring a Slackbot: you (the “presenter”) define what the bot (poll) will ask or listen for. Just as a Slackbot written in Node.js might register certain trigger phrases on the server side, Poll Everywhere’s back-end now “knows” there’s an active poll waiting for input. All this setup happens behind the scenes via standard web requests. In short, the instructor’s front-end (web dashboard) communicates with the poll service’s back-end to create and broadcast a new question.

2. **Students Join and Submit Responses (Student Side – *Client interactions*):** Once the poll is active, students can participate using their own devices. Typically, the instructor will show on the projector screen a slide or link that instructs students how to join (for instance, *“Go to PollEv.com/ProfSmith and respond to the question”* or a QR code to scan). When students access that link (on a phone, tablet, or laptop), what loads is essentially a **front-end web page** (the client interface for participants) showing the question and answer choices or an input box for open responses. This front-end is often a mobile-friendly web app (built with HTML/JS – conceptually similar to a page one might build in React or Next.js to display a question). Students then select an option or enter their answer and hit submit. Each submission is sent from the student’s device to the Poll Everywhere **server** via the internet. This is analogous to a user sending a message to a Slackbot – the message leaves the client (Slack on the user’s phone) and reaches the server where the bot logic runs. Here, each student response is essentially an HTTP request or web socket message to Poll Everywhere’s back-end, saying “Student X (or anonymous) answered ‘B’”. The system is designed to handle many responses at once (for a large class) reliably. Importantly, Poll Everywhere can accept responses even if students remain anonymous or if they are not individually logged in – in that case, the data is tagged just by the session or poll ID without personal identifiers, whereas if students are registered, the response can be tied to their name for grading purposes. From a technical standpoint, the **client-side** code ensures the interface is easy to use (one click to vote, etc.), while the **server-side** code handles receiving and recording each vote in a database.

3. **Data Flow to the Back-End (Real-Time Collection):** The moment a student submits a response, the data is in the hands of the Poll Everywhere back-end. The server application (which could be built with any server-side framework; the specifics are proprietary, but one can imagine it structured like a Node.js or Python server managing incoming data) appends the new vote to the poll’s dataset. Each poll thus accumulates a list of responses in the database or in-memory storage. The magic of “real-time” polling is that this happens in fractions of a second. Poll Everywhere’s infrastructure uses techniques like web sockets or frequent AJAX polling to update results live. In practice, once the poll is activated, the instructor’s screen (and sometimes the students’ devices too) will continuously check with the server for updates, or the server will push updates to the clients. This is similar to how a live chat app works – for example, a Slackbot might use the Slack Events API or a websocket to get notified immediately when a user posts a message, rather than constantly refreshing. In a modern full-stack app like one built with Next.js, one might use something like Next.js API routes in combination with React state updates to achieve a live update: the front-end opens a connection to the back-end and when new data comes in, it triggers a re-render of the results chart. Poll Everywhere does this under the hood so that as responses stream in, the aggregated results change before your eyes – **bar charts fill up, word cloud words grow larger, or texts appear on screen in real time** ([8 Word Cloud Examples Created with a Live Audience](https://blog.polleverywhere.com/live-word-cloud-examples#:~:text=You%20create%20the%20question%20or,the%20mic%20and%20respond%20aloud)). The client–server interaction here is continuous: every few seconds (or via an open channel), the front-end asks “any new votes?” and the server responds with the latest tally. This ensures that both the instructor’s view and, in some cases, the participants’ view can reflect the crowd’s responses live.

4. **Aggregating and Displaying Results (Instructor Side – *Front-End output*):** As data flows into the back-end, Poll Everywhere aggregates the responses for display. The instructor typically has a live presentation view – either embedded in slides (via a PowerPoint or Google Slides plugin) or in the Poll Everywhere web interface – that shows the poll results updating. Technically, this presentation view is also a **client** (front-end) that subscribes to the poll data. It might be the same web dashboard or a special fullscreen chart view. Continuing the analogy, this is like the Slack channel where the bot posts a summary after collecting inputs, or a real-time dashboard in a web app that updates when new data arrives. For example, if 60% of students chose option B and 40% chose A, the instructor’s screen will show a bar graph with those percentages, adjusting as more votes come in. If it’s an open-ended question, the screen might show a scrolling list of responses or a word cloud morphing as new words are added. Poll Everywhere’s system handles the **aggregation logic** (e.g. counting votes for each choice) on the server, so what gets sent to the instructor’s front-end is essentially the computed result set. The front-end then visualizes it (drawing the bars or assembling the word cloud). This separation of concerns – back-end doing heavy lifting and front-end focusing on presentation – is common in web development. Think of a Next.js app where an API route returns JSON data (say, vote counts) and the React component renders a chart based on it. Here, Poll Everywhere gives a polished, ready-made interface for that. The result is a seamless experience: the instructor and students see the class’s responses updated live, which closes the feedback loop. Students get to instantly **see their contribution** in context of their peers (which itself can be a learning moment, like realizing “oh, most people answered differently than me”), and instructors get a real-time assessment of understanding or opinion. Poll Everywhere emphasizes that this live visualization helps “hear from the entire audience in the time it would take one person to respond aloud,” democratizing participation ([8 Word Cloud Examples Created with a Live Audience](https://blog.polleverywhere.com/live-word-cloud-examples#:~:text=You%20create%20the%20question%20or,the%20mic%20and%20respond%20aloud)).

5. **Post-Session Analysis and Integration (Instructor Side – *Analysis step*):** After the live polling activity, the data doesn’t disappear – Poll Everywhere stores the responses, and instructors can analyze or export them. This is the **analysis step**, which can be as simple or sophisticated as needed. Instructors can log into their Poll Everywhere account later and see reports (e.g. how each student responded, if tracking, or overall percentages for each question). They might download a spreadsheet of the responses for record-keeping or grading (especially if polls were used as quizzes or attendance). For a deeper dive, this data can be brought into external tools. Here’s where a platform like a **Python notebook (e.g. Google Colab)** might come in handy for tech-savvy faculty: one could use Poll Everywhere’s API or an exported CSV to load the data into Python and perform custom analysis. For example, using pandas and matplotlib in a Colab notebook, a professor could look at trends (did section A perform differently than section B on these poll questions? Did scores improve from the first poll to the last?). They could also do textual analysis on open-ended responses – perhaps using natural language processing to find common themes in students’ muddiest-point feedback. In fact, this step is analogous to how one might analyze survey results or chat logs: you have a dataset of all responses, and you can code or use AI to find patterns. Poll Everywhere itself provides some basic analytics (correct answer grading, filtering by class, etc.), but the data can be taken further. Some instructors integrate Poll Everywhere with their LMS (Learning Management System) so that grades or participation points are automatically recorded. Technically, this integration means the Poll Everywhere back-end communicates with other systems (via LTI or API calls) to pass along data like who responded and what score they got. From a workflow perspective, after class you have a rich set of data about student learning. The **analysis step** closes the loop: the instructor reflects on the poll results to inform future teaching. For example, if a significant percentage got a certain question wrong, that topic might need to be reviewed next class. If opinion polls showed a split in viewpoints, the instructor might plan a follow-up activity to address misconceptions held by part of the class. In sum, the technical workflow of polling tools involves a **continuous cycle of information**: instructor’s front-end to server (question setup), student clients to server (responses), server to instructor’s front-end (aggregate results), and finally server storing data for later analysis. This client–server dance is similar to many interactive web applications, with the added twist of real-time feedback which makes the classroom experience interactive and data-driven.

## **Roles for AI in Polling Workflows (Data Analysis and Feedback)**

As artificial intelligence technologies advance, they are beginning to intersect with classroom polling tools in exciting ways. While Poll Everywhere itself has traditionally not been AI-driven, one can imagine (and indeed start to see) **AI augmenting each stage of the polling process** – from creating questions, to analyzing responses, to generating feedback. Here we highlight a few potential roles for AI throughout the technical stack of a polling system, especially focusing on how AI can assist in data analysis and providing feedback in an educational context:

* **Intelligent Question Generation:** Crafting good poll questions (especially distractor options for multiple-choice) can be challenging and time-consuming. AI language models (like GPT-4) could help instructors generate high-quality questions or suggest poll prompts based on course material. For example, an instructor could ask an AI, *“Propose a thought-provoking poll question to test understanding of the French Revolution causes,”* and use that as a starting point. This is a more nascent use case, but it shows promise in saving faculty time. AI can also adjust the phrasing or difficulty of questions based on a desired complexity level. While this happens before polling, it sets the stage for more effective polls.

* **Real-time Moderation and Dynamic Polling:** During a live poll, AI could assist by monitoring incoming responses and providing on-the-fly insights. For instance, if an open-ended poll is receiving a flood of text responses, an AI system could **automatically categorize or flag themes** in those responses in real time. In a large class, if you ask “What’s still confusing you about today’s lesson?” you might get 100 text answers. AI clustering algorithms could group similar responses (e.g. 30 students all mentioned “Chapter 2 formula”), and display a word cloud or summary to the instructor even as the poll is ongoing. Additionally, AI might detect inappropriate responses (in the case of wholly open submissions) and filter them out, or translate non-English responses if needed. Dynamic adaptation is another intriguing possibility: if early responses to a poll indicate that everyone is getting it right (i.e. the question is too easy), an AI could suggest a follow-up, more challenging question in the moment. Conversely, if most are getting it wrong, AI might prompt the instructor to review the concept before moving on. This kind of real-time pedagogical aid would make the polling tool even more responsive to student needs on the fly.

* **AI-driven Analysis of Poll Results:** The most immediate role for AI is in **post-poll analysis**. Instead of the instructor manually poring over the data, AI can quickly crunch numbers and read text to extract insights. For example, AI tools can instantly summarize hundreds of open-ended responses into key points. MIT educators have demonstrated using ChatGPT’s data analysis capabilities to examine survey responses, significantly speeding up the feedback process. In the context of Poll Everywhere, one could feed the collected responses (especially qualitative ones) into an AI and get a report like: *“Out of 100 responses, the most common themes were X, Y, Z. Students generally understood A but were confused about B.”* This saves the instructor time and ensures no trend is overlooked. Even for quantitative polls, AI can highlight patterns – e.g., *“Students who answered Q1 incorrectly mostly chose option B, which suggests a specific misconception.”* An AI could compare current poll results to past data, noting improvements or regressions. There are already prototype solutions that do this: for instance, one AI EdTech platform advertises the ability to *“evaluate poll results and offer concise explanations to address common misconceptions, using data-driven insights”*. In practice, that means if a majority of the class selected a wrong answer that corresponds to a known misunderstanding, the AI can provide the instructor with an explanation of that misconception and perhaps advice on clarification. Essentially, AI becomes a teaching assistant, digesting the poll data and preparing a brief for the human teacher.

* **Personalized Feedback and Support:** Building on analysis, AI can help generate **feedback for students**. Suppose a poll is used as a quiz and a student gets a question wrong – an AI system could automatically deliver a hint or explanation to that student. For example, via integration with an LMS or even a chatbot (imagine a Slackbot DMing a student: “I noticed you answered B to that poll question. Here’s an explanation of why the correct answer was A, and some resources to review.”). This kind of personalized feedback loop can significantly enhance learning, as each student gets targeted help. AI could also tailor subsequent poll questions to different cohorts of students (adaptive polling). While Poll Everywhere doesn’t natively do this yet, one could envision linking it with an AI tutor system. After class, students might receive an AI-generated summary of the polls with explanations, turning each polling activity into a learning resource rather than just a moment-in-time check.

* **Enhanced Decision-Making for Instructors:** From the instructor’s perspective, AI can surface the most important information from polling activities so they can make instructional decisions. For instance, if a poll during class reveals confusion, the AI might suggest, *“80% of the class missed Question 3 (poll at 10:15am) which involved concept X; consider revisiting that concept tomorrow.”* It could even recommend additional materials or question banks for that concept if integrated with a content library. AI can also help in **longitudinal analysis**: looking at poll data over a semester to see which topics consistently trip up students, thereby informing curriculum improvements. All of this falls under using AI to turn raw polling data into actionable feedback for teaching strategies.

* **Natural Language Interfaces:** Another role for AI is making the polling tools themselves easier to use via natural language. Imagine telling a voice assistant or chatbot, *“Set up a poll asking my students what they found most unclear today,”* and the AI configures the poll in Poll Everywhere for you. Or during a session, you could ask, *“AI, summarize these 50 open-ended responses for me,”* and get a spoken or written summary on the spot. These applications are on the horizon as AI language understanding improves and can interface with edtech APIs.

In conclusion, while the core functionality of classroom polling tools like Poll Everywhere is already a boon for interactive teaching, the integration of AI can elevate their impact even further. AI contributes by **analyzing large volumes of responses swiftly**, identifying patterns or misconceptions that a human might miss, and generating helpful feedback or next steps. It can make the feedback loop almost instant: students respond, AI analyzes, and within seconds the instructor might get a prompt or the students get an explanation. This is especially powerful for open-ended questions, where historically instructors would need to manually read and digest responses. Now, AI can do initial processing – for example, clustering student questions or reflections – allowing the instructor to address the most common issues live in class. By offloading routine analysis to AI, instructors can focus on the human aspects of teaching: facilitating discussion around the poll results and guiding students to deeper understanding. Moreover, AI can help in designing better polls (through suggestions) and ensuring inclusive participation (through moderation and translation features). In an **aiLab context** for higher ed faculty, these possibilities mean that polling tools are not just simple clickers anymore; they are becoming smart assistants in our pedagogy. With AI in the stack, tools like Poll Everywhere could provide an even more **conceptually rich and personalized learning experience**, where data from every quick poll is leveraged to enhance student learning outcomes and provide timely, targeted feedback. The combination of live polling and AI analytics exemplifies data-driven teaching: a blend of real-time engagement and intelligent insight that can help educators continuously adapt and improve their instruction.

**Sources:** Poll Everywhere case studies and user guides; teaching center resources on polling pedagogy; academic technology blogs ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=Furthermore%2C%20our%20own%20internal%20polling,a%20more%20interactive%20classroom%20space)) ([Engage students with Poll Everywhere – ITS Blog – Carleton College](https://www.carleton.edu/its/blog/engage-students-with-poll-everywhere/#:~:text=PollEv%20can%20help%20to%20illuminate,comfortable%20in%20providing%20an%20answer)); MIT AI teaching guide; Rolai AI polling solution; Yale Canvas Poll Everywhere overview ([Poll Everywhere: Overview | Discover Instructional Tools | Canvas @ Yale](https://help.canvas.yale.edu/a/1334907#:~:text=Poll%20Everywhere%20is%20Yale%27s%20supported,be%20used%20to%20ask%20a)); and Poll Everywhere documentation ([Teachinghistory.org](https://teachinghistory.org/digital-classroom/tech-for-teachers/25829#:~:text=,ended%20questions)).

# Super Grok Deeper Search

### **Key Points**

- Research suggests classroom polling tools like Learning Catalytics and Poll Everywhere enhance engagement and provide real-time feedback.
- It seems likely that these tools are used in sciences for concept checks and in humanities for discussion stimulation.
- The evidence leans toward a client-server architecture for polling, with front-end for user interaction and back-end for data processing.
- AI can potentially improve polling by aiding in question creation, response analysis, and personalized feedback, especially in data analysis.

---

### **General Overview**

Classroom polling tools, such as Learning Catalytics and Poll Everywhere, are designed to make lectures more interactive by allowing instructors to create polls that students can answer in real-time using their devices. These tools help gauge understanding, encourage participation, and provide immediate insights, making them popular in higher education settings.

### **Pedagogical Use Cases**

- **Sciences:** Polling is often used to check students' understanding of concepts, predict experiment outcomes, and facilitate peer instruction where students discuss answers to deepen learning.
- **Humanities:** These tools stimulate discussions on subjective topics, gather opinions on debates, and measure attitudes, enhancing engagement in large classes.
- **General Applications:** Beyond specific disciplines, polling supports attendance tracking, assessing prior knowledge, and testing comprehension, fostering active participation.

### **Technical Explanation**

The technical workflow of polling tools like Poll Everywhere involves a client-server architecture:

- **Client and Server Basics:** The client is the device (like a web browser) where users interact, sending requests to the server, which processes and stores data. For example, when an instructor creates a poll, the client sends this to the server, which saves it.
- **Front-End:** This is the user interface, built with web technologies like HTML, CSS, and JavaScript, often using frameworks like React for dynamic updates. Students see and respond to polls here.
- **Data to Back-End for Analysis:** Responses are sent from the front-end to the back-end via API requests. The back-end, possibly using Node.js or Python, stores data in databases like MongoDB and processes it for real-time display or later analysis.
- Given your familiarity with Slackbots (Node.js), Next.js (full-stack/front-end), and Python notebooks in Google Colab, you can think of the front-end as similar to building a Next.js app for user interaction, and the back-end as akin to setting up a Node.js server or using Python scripts for data handling.

### **Roles for AI in Improving the Stack**

AI can enhance polling at various stages:

- **Poll Creation:** AI could suggest relevant questions based on course content, easing the burden on instructors.
- **Response Analysis:** Especially in the final step, AI can use natural language processing (NLP) to analyze open-ended responses, identify themes, or detect sentiment, providing deeper insights.
- **Real-Time Feedback:** AI can analyze response patterns to flag common misconceptions, helping instructors adjust teaching on the fly.
- **Personalized Learning:** Based on individual responses, AI might recommend resources or follow-up questions, tailoring education to student needs.
- In a Next.js app, you could integrate AI for real-time analysis, displaying insights directly. In Python notebooks, you could use libraries like Pandas and scikit-learn to analyze polling data offline, enhancing reports with AI-driven visualizations.

---

### **Survey Note: Comprehensive Analysis of Polling in the Classroom**

This note provides a detailed examination of classroom polling tools, focusing on Learning Catalytics and Poll Everywhere, with a technical breakdown tailored for an aiLab of new-to-coding academics familiar with Slackbots (Node.js), Next.js (full-stack/front-end), and Python notebooks in Google Colab. The analysis covers general overviews, pedagogical use cases across disciplines, and the technical workflow, including potential AI integrations, particularly for data analysis.

#### General Overview of Polling Tools

Classroom polling tools are student response systems that enable instructors to create interactive polls, allowing students to respond in real-time using devices like smartphones or laptops. Learning Catalytics, associated with Pearson, integrates with MyLab or Mastering courses and offers rich question types beyond multiple-choice, suitable for both classroom-based and online settings [Learning Catalytics](https://www.pearson.com/en-us/learning-platforms/learning-catalytics.html). Poll Everywhere, a standalone web-based tool, supports various question types (e.g., multiple-choice, word clouds) and integrates with presentation software like PowerPoint, Keynote, or Google Slides, making it versatile for live polling [Poll Everywhere](https://www.polleverywhere.com/). These tools enhance engagement, provide real-time feedback, and are widely used in higher education to foster active learning.

#### Pedagogical Use Cases Across Disciplines

Polling tools have diverse applications, ranging from sciences to humanities, as evidenced by various educational resources:

- **Sciences:** In scientific disciplines, polling is crucial for checking conceptual understanding and facilitating peer instruction. For instance, physics courses use polling to pose questions, have students discuss with peers, and re-answer to improve conceptual learning, as noted in classroom research [Classroom Participation and Polling](https://atg.fas.harvard.edu/classroom-participation-and-polling). It also helps predict experiment outcomes, ensuring students engage with practical applications.

- **Humanities:** In humanities, polling stimulates discussions on subjective topics and gathers opinions on debatable issues. For example, a political psychology class used polling to measure students' attitudes on political behaviors, enhancing engagement in large lecture halls [Promoting active learning in large classes](https://www.polleverywhere.com/case-studies/lecture-method). It also supports attendance and assessing prior knowledge, making lectures more interactive.

- **General Applications:** Across disciplines, polling is used for attendance tracking, testing comprehension, and encouraging participation. It breaks the monotony of traditional lectures, as seen in cases where instructors use polls to mine questions from students, fostering a collaborative learning environment [Feedback / Polling Tools](https://poorvucenter.yale.edu/strategic-resources-digital-publications/instructional-tools/feedback-polling-tools).

#### Technical Explanation of the Polling Workflow

For an aiLab audience new to coding but familiar with Slackbots, Next.js, and Python notebooks, the technical architecture of polling tools like Poll Everywhere can be broken down conceptually:

- **Client and Server Basics:** The client is the user's device, such as a web browser, where interactions occur (e.g., creating polls, submitting responses). The server, located remotely, processes these requests, manages data, and sends back responses. For example, when an instructor creates a poll, the client sends a request to the server, which stores it in a database.

- **Front-End:** The front-end is the user interface, built using web technologies like HTML, CSS, and JavaScript. It often uses frameworks like React, which aligns with your Next.js experience, for dynamic updates. Students see poll questions here and submit answers, with real-time updates facilitated by technologies like WebSockets for live results.

- **Back-End and Data Flow:** The back-end, potentially built with Node.js (similar to your Slackbots) or Python (as in Google Colab notebooks), handles API requests from the front-end. It stores poll data in databases like MongoDB or PostgreSQL and processes responses for analysis. For instance, when students respond, their answers are sent to the back-end via API calls, which updates the instructor's view in real-time using WebSockets, ensuring immediate feedback.

- **Possible Improvements Using Familiar Tools:** In a Next.js app, you could enhance Poll Everywhere by building a custom front-end with React components for poll creation and response, integrating real-time updates with Socket.IO for Node.js. For Python notebooks, you could pull polling data (if an API is available, though Poll Everywhere no longer maintains a public API as of October 1, 2019 [The Poll Everywhere API](https://api.polleverywhere.com/)) and analyze it using Pandas, NumPy, or scikit-learn, creating visualizations or training models for deeper insights.

#### Roles for AI Throughout the Stack, Especially in Final Analysis

AI can significantly enhance polling tools at various stages, particularly in data analysis, aligning with your aiLab's goals:

- **Poll Creation:** AI can generate relevant poll questions based on course content, using NLP to suggest question types (e.g., multiple-choice for factual recall, open-ended for critical thinking). This reduces the instructor's workload and ensures alignment with learning objectives.

- **Response Analysis:** In the final analysis step, AI can employ NLP to analyze open-ended responses, performing sentiment analysis, keyword extraction, or clustering to summarize themes. For example, it could identify common misconceptions from student answers, providing actionable insights for instructors.

- **Real-Time Feedback:** AI can analyze response patterns in real-time, flagging areas where many students struggle, enabling instructors to adjust teaching immediately. This could be integrated into the front-end, displaying AI-generated insights alongside live results.

- **Personalized Learning:** Based on individual responses, AI can recommend additional resources or follow-up questions, tailoring education to student needs. This could be implemented in a Next.js app by calling AI APIs for recommendations or in Python notebooks for offline analysis.

- **Automated Grading:** For certain question types, AI can assist in grading or providing feedback, reducing manual effort. This is particularly useful for large classes, enhancing efficiency.

Given your stack, in a Next.js application, you could integrate AI for real-time analysis, displaying insights directly to instructors. In Python notebooks, you could use libraries like scikit-learn for machine learning tasks, enhancing reports with AI-driven visualizations, such as identifying trends in student engagement over time.

#### Table: Summary of Polling Tool Features and AI Integration

| Aspect | Description | AI Role |
| :---- | :---- | :---- |
| Front-End | User interface for poll creation and response, built with React (Next.js). | AI can suggest question types. |
| Back-End | Processes requests, stores data, uses WebSockets for real-time updates. | AI analyzes responses for insights. |
| Real-Time Communication | Ensures live updates using WebSockets, similar to chat features in Slackbots. | AI flags misconceptions in real-time. |
| Data Analysis | Stores and processes responses for reporting, possible with Python notebooks. | AI provides personalized feedback. |
| Final Analysis Step | Summarizes results, identifies trends, integrates with AI for deeper insights. | AI enhances visualizations, grading. |

This comprehensive analysis ensures a thorough understanding of polling tools, their pedagogical applications, and technical underpinnings, tailored to your aiLab's context and tools.

#### Key Citations

- [Learning Catalytics overview](https://help.pearsoncmg.com/learning_catalytics/instructor/en/Topics/lc_overview.htm)
- [Poll Everywhere](https://www.polleverywhere.com/)
- [Classroom Participation and Polling](https://atg.fas.harvard.edu/classroom-participation-and-polling)
- [Promoting active learning in large classes](https://www.polleverywhere.com/case-studies/lecture-method)
- [Feedback / Polling Tool](https://poorvucenter.yale.edu/strategic-resources-digital-publications/instructional-tools/feedback-polling-tools)s

# Classroom Polling in Higher Education: Enhancing Learning with Interactive Technologies

Classroom polling has emerged as a significant pedagogical tool in higher education, transforming traditional passive lectures into dynamic and interactive learning experiences.1 This method involves educators posing questions to students in real-time, allowing for immediate responses that can enhance engagement, provide valuable feedback, and improve overall learning outcomes.1 The shift from conventional lecture-based teaching to active learning methodologies underscores the importance of strategies that encourage students to become active participants in their education, and polling serves as a powerful means to facilitate this transition.3 Among the various polling tools available, Learning Catalytics and Poll Everywhere stand out as prominent examples widely used in higher education institutions.3 This report will delve into the landscape of classroom polling, explore its diverse pedagogical applications across the humanities and sciences, provide a technical explanation of the underlying mechanisms with a focus on Poll Everywhere, investigate the potential of Artificial Intelligence (AI) to enhance the polling workflow, and consider how these technologies can integrate with existing academic tools.

Classroom polling, at its core, is a method that enables instructors to ask questions and receive instant responses from students during a class session.3 This technology has evolved considerably from the early use of physical clickers to sophisticated web-based and mobile applications accessible on students' personal devices such as smartphones, tablets, and computers.3 This accessibility is a key advantage of modern polling systems, allowing for broad participation without the need for specialized hardware.4 The adoption of polling in higher education addresses several key pedagogical goals. Primarily, it aims to increase student engagement and participation by providing a platform for all students to express their views and interact with the course material in a low-stakes environment.1 It also provides immediate feedback to both instructors, who can gauge student understanding in real-time, and to students, who can see how their responses compare to those of their peers.6 This immediate assessment of comprehension allows instructors to adjust their teaching strategies as needed.1 Furthermore, classroom polling promotes active learning by encouraging students to think critically about the questions posed and to consider different perspectives.1 Many instructors also utilize polling to facilitate peer instruction, a method where students discuss their answers with each other before re-submitting, which has been shown to be particularly effective in engaging students with complex materials.4 Beyond engagement and assessment, polling can also be used for practical purposes such as tracking attendance and participation, providing instructors with data on student involvement.2 While a variety of polling tools exist, including iClicker, Top Hat, Mentimeter, Vevox, and Socrative 3, this report will focus primarily on Learning Catalytics and Poll Everywhere to provide specific examples and technical details.

The integration of polling technologies into the classroom has yielded diverse pedagogical applications across a wide range of disciplines, enhancing the learning experience in both the humanities and the sciences.

In the humanities, polling offers unique opportunities to engage students with subjective and interpretive aspects of the curriculum. For instance, in history courses, instructors can use polls to assess students' prior knowledge about a historical event or to gauge their initial opinions on controversial historical figures.1 Similarly, in literature classes, polls can be employed to explore different interpretations of a text, understand students' perspectives on character motivations, or gather their emotional responses to key plot points.5 Philosophical discussions can also be enriched through polling by asking students to take a stance on ethical dilemmas or philosophical debates, revealing a spectrum of viewpoints within the classroom.5 A particularly effective use of polling in these disciplines is to collect contrasting opinions on a topic, which can then serve as a springboard for passionate in-class discussions.5 Instructors can pose "Where do you stand?" type questions and, after displaying the results, invite students to share their reasoning.5 Beyond facilitating discussions, polling can also be used for more reflective activities. Tools like Poll Everywhere can support reflective journaling by prompting students with questions about their learning experiences.12 Quick quizzes conducted via polls can also serve as effective recaps of lecture material, reinforcing key concepts.1 Furthermore, polling provides a valuable avenue for students to give feedback on lectures, teaching styles, and overall course content, allowing instructors to gain insights into what resonates with students and areas for potential improvement.5 For example, instructors might ask students to rate a lecture or to identify one thing they liked or would like to see improved.5 Even in the realm of political science, polling can be used to gauge student opinions on current events or potential election outcomes, as exemplified by questions about presidential candidates.5

In the sciences, classroom polling plays a crucial role in assessing and reinforcing understanding of often complex and sequential concepts. Instructors in biology, chemistry, and physics can use polls to check students' comprehension of fundamental scientific principles and theories.1 Before conducting a demonstration or experiment, predictive questions can be posed via polls to engage students in the scientific process and encourage them to think critically about potential outcomes.8 Problem-solving skills can also be fostered through polling by presenting scenarios or questions that require students to apply their knowledge to new contexts.16 In laboratory settings, polling tools can be used to gather data in real-time as students conduct experiments, allowing for immediate analysis and discussion of results.1 Image-based questions, where students might be asked to identify a specific structure in a biological diagram or a region on a graph in physics, are another effective application in the sciences.18 To prepare students for exams and reinforce learning, polls can be used for review sessions, allowing instructors to quickly gauge areas where students may need further clarification.1 The peer instruction methodology, which involves posing a question, having students respond individually, then discuss with peers, and respond again, is particularly well-suited to science education and can be effectively implemented using polling tools.8 This approach encourages students to articulate their understanding and learn from their classmates. The versatility of polling in science is further demonstrated by the use of various question types, including sketching chemical structures or drawing arrows to indicate the direction of forces, catering to the visual and interactive nature of scientific learning.18

To understand how classroom polling tools function, it is essential to grasp the underlying technology. Many modern polling systems, including Poll Everywhere, are built upon the client-server model. In this model, a student's device (the client), such as a laptop or smartphone, communicates with the polling platform's infrastructure (the server) to participate in activities.22 The client-server model is a fundamental concept in web applications, where tasks are distributed between the providers of a resource or service (servers) and the service requesters (clients).26 Often, the client and server operate on separate hardware and communicate over a computer network.26 In the context of Poll Everywhere, when an instructor activates a poll, the information about the question and response options is stored on Poll Everywhere's servers. Students, using their client devices, send requests to these servers to access the poll.24 When a student submits a response, their device sends another request to the server containing their answer. The server then processes this request, records the response, and may send back a response to the client, such as confirmation of submission or the display of real-time results.24 This model centralizes the polling logic and data on Poll Everywhere's servers, allowing students to participate from various devices without needing specialized software installed locally.24 The communication between clients and servers in web applications like Poll Everywhere typically occurs using protocols such as Hypertext Transfer Protocol (HTTP) or its secure version, HTTPS.27 HTTP is the foundation of data exchange on the World Wide Web, defining how messages are formatted and transmitted.29 HTTPS adds a layer of security by encrypting the communication, ensuring that data passed between the browser and the server remains private.30 This secure communication is particularly important in educational settings to protect the privacy and integrity of student responses.32

The interaction with Poll Everywhere involves distinct user interfaces for students and instructors. From a student's perspective, accessing polls is typically straightforward. They can join a poll through a web browser by navigating to a specific URL or using a dedicated mobile application.34 In some cases, students might also be able to respond via SMS text messages, providing accessibility for those without smartphones or reliable internet access.40 Once connected to a poll, students encounter various question types depending on how the instructor has designed the activity. These can range from simple multiple-choice questions with predefined answer options to more open-ended formats like text responses, word clouds where student answers collectively form a visual representation, and clickable images where students can indicate a specific area on an uploaded picture.42 After selecting or entering their response, students typically submit it through the interface and may have the option to view real-time results, depending on the instructor's settings.2

From an instructor's viewpoint, Poll Everywhere offers a comprehensive set of tools for creating and managing polls. Instructors can create polls through the Poll Everywhere website or by using integrations with popular presentation software such as PowerPoint, Keynote, and Google Slides.34 These integrations allow for seamless embedding of interactive polls directly within lecture slides, enhancing the flow of presentations.41 When creating a poll, instructors have numerous options for customization. They can choose from a variety of question types, set parameters for whether responses are anonymous or tracked, allow multiple responses from a single student, and even moderate responses to filter out inappropriate content.34 During a class session, instructors can present the polls either directly from the web interface or embedded within their presentation slides.34 Poll Everywhere also provides features for managing courses, including the ability to upload student rosters, organize content into folders, and create assignments that can be graded.2 This integration of course management tools within the polling platform streamlines administrative tasks for educators.50

When a student submits a response through their device, this data needs to be transmitted to Poll Everywhere's servers for processing and analysis. This transmission typically occurs over the internet using web requests, most likely via the secure HTTPS protocol, ensuring that the data is encrypted during transit.52 While the specifics of Poll Everywhere's Application Programming Interfaces (APIs) are not detailed in the provided snippets, APIs generally serve as a crucial component in such systems, allowing different software applications to communicate and exchange data with each other. In this case, the student's device (client) would use Poll Everywhere's API to send the response data to the platform's servers (backend). The platform places a strong emphasis on security and data privacy, employing measures such as encryption to protect user information throughout this transmission process.42 The platform also collects information about the device type and operating system used by the student, which likely helps in optimizing the platform's performance and ensuring broad compatibility across different user environments.52

Once the polling data reaches Poll Everywhere's servers, it is stored securely.42 The platform then offers a range of analysis and reporting features for instructors. In real-time, as students respond to polls, instructors can often see the results displayed visually through charts and graphs, allowing them to immediately gauge the overall understanding of the class.2 Poll Everywhere also provides features for tracking student participation and attendance, often integrated with Learning Management Systems (LMS) like Canvas.2 For polls with correct answers, the platform may offer grading capabilities, allowing instructors to assess student performance.2 Beyond real-time insights, instructors can typically access more detailed reports summarizing the polling data, which can be useful for identifying trends in student understanding and engagement over time.48 Furthermore, Poll Everywhere often allows instructors to export the raw polling data in formats like CSV, which can then be used for further, more advanced analysis using other tools.48 This capability provides instructors with the flexibility to conduct customized analyses tailored to their specific research or pedagogical needs.

The field of classroom polling is continuously evolving, and the integration of Artificial Intelligence (AI) holds significant potential to further enhance its effectiveness and impact on learning.

One promising application of AI is in assisting instructors with the generation of poll questions.48 AI-powered tools can analyze topics or even uploaded lecture materials to suggest relevant and engaging poll questions, along with potential answer choices.63 This can be particularly beneficial for instructors who may have limited time for content creation or who are looking for fresh and diverse question ideas.63 AI can also help in suggesting a variety of question types, prompting instructors to consider formats beyond traditional multiple-choice, potentially leading to a more comprehensive assessment of student understanding.64 The time-saving aspect of AI-powered question generation is a significant advantage, allowing instructors to quickly create effective polls that can drive meaningful classroom interactions.63

AI also has the potential to revolutionize the real-time analysis of student responses during polling sessions.16 By analyzing student responses as they come in, AI algorithms could identify common misconceptions or areas where a significant portion of the class is struggling.72 This immediate feedback on student understanding would be invaluable for instructors, allowing them to adjust their teaching strategies on the fly.72 For example, if AI detects a widespread misunderstanding of a particular concept, the instructor could revisit that topic or provide additional explanations and resources.75 In large classrooms, where it can be challenging for instructors to manually monitor and interpret student responses in real-time, AI could provide a powerful tool for gaining immediate insights into the collective understanding of the class.72

Beyond real-time analysis, AI can play a crucial role in the advanced analysis of aggregated polling data, uncovering deeper insights into student learning patterns over time.72 AI algorithms could be used to identify trends in student understanding and engagement across multiple polling activities throughout a course.72 Furthermore, AI could potentially uncover correlations between student responses in polls and their performance in other assessments, such as exams, providing a more holistic view of their learning journey.85 There is also the possibility of using AI to generate personalized feedback for students based on their participation and performance in polls, offering tailored guidance and support to enhance their learning.75 By leveraging AI for these advanced analytical tasks, educators can gain a more data-informed understanding of the effectiveness of their teaching and the learning progress of their students.72

Integrating classroom polling tools like Poll Everywhere with existing technology ecosystems can further enhance their utility and streamline workflows.

For instance, Slackbots written in Node.js could be leveraged to provide instructors with notifications about poll activity.87 A bot could be configured to send alerts when a poll has reached a certain number of responses or to provide summaries of the overall results directly within a Slack channel.56 It might also be possible to trigger simple polls or share links to more complex polls directly from Slack using bot commands, making it easier to engage with students or colleagues asynchronously.56 Furthermore, Slack channels could be used as a platform for asynchronous follow-up discussions related to topics raised in polls during a live class session, extending the interactive learning beyond the synchronous environment.5

The team might also consider the potential of using Next.js to build a custom front-end interface for classroom polling.91 While this would require more significant development effort, a custom interface could offer greater control over the user experience and allow for the integration of features specifically tailored to the aiLab's needs.91 This could include a more streamlined design, enhanced accessibility features, or even the integration of custom AI-powered analysis pipelines. While Poll Everywhere may offer its own API for interacting with its platform programmatically, building a custom interface would provide maximum flexibility in terms of features and branding.47

Finally, the aiLab's familiarity with Python notebooks in Google Colab presents a powerful opportunity for advanced data analysis of polling data. Poll Everywhere allows users to export response data in CSV format.48 This exported data can then be easily imported into a Google Colab notebook and analyzed using Python libraries such as Pandas for data manipulation, NumPy for numerical computations, and Matplotlib and Seaborn for creating custom visualizations.95 Within this environment, the team could perform a wide range of analyses, such as identifying trends in student responses over multiple polls, comparing responses across different student groups or courses, and creating visualizations that go beyond the standard options offered by Poll Everywhere.95 Furthermore, the power of Python in Google Colab extends to the integration of AI models from libraries like TensorFlow or PyTorch, allowing for more sophisticated analyses such as sentiment analysis of open-ended responses or the development of predictive models related to student learning outcomes based on their polling participation.95

In conclusion, classroom polling tools like Learning Catalytics and Poll Everywhere offer significant benefits for enhancing student engagement, providing real-time feedback, and assessing understanding in higher education. The integration of AI promises to further amplify the effectiveness of these tools by assisting with question generation, providing immediate insights into student misconceptions, and enabling advanced analysis of learning patterns. By strategically integrating these technologies with existing platforms like Slack, Next.js, and Google Colab, educators can create a more interactive, personalized, and data-informed learning environment that caters to the evolving needs of both instructors and students. The continuous advancements in educational technology and the increasing capabilities of AI suggest a future where interactive polling plays an even more central role in shaping effective and engaging learning experiences.

**Table 1: Conceptual Comparison of Polling Tools**

| Tool Name | Key Features | Primary Pedagogical Uses |
| :---- | :---- | :---- |
| Learning Catalytics | Wide range of question types, team-based learning, peer instruction support | Developing critical thinking, engaging students in active learning, formative assessment |
| Poll Everywhere | Integrates with presentation software, diverse question types, SMS responses | Gauging understanding, gathering opinions, tracking attendance, formative assessment |
| iClicker | Clicker remotes or student app, attendance tracking | Real-time feedback, quick quizzes, large lecture engagement |
| Top Hat | BYOD, integrates with LMS, secure attendance, peer instruction features | Increasing engagement, assessing learning, low-stakes assessments, peer instruction |
| Mentimeter | Word clouds, quizzes, surveys, Q\&A, real-time visualizations | Boosting engagement, assessing knowledge, gathering feedback, interactive presentations |

**Table 2: Use Cases of Polling in Humanities and Sciences**

| Discipline | Example Polling Question or Activity | Pedagogical Goal |
| :---- | :---- | :---- |
| History | "Who do you think was the most influential figure in the French Revolution?" | Assessing prior knowledge, sparking discussion |
| Literature | "In *Hamlet*, do you believe Claudius is genuinely remorseful?" | Exploring interpretations, encouraging critical thinking |
| Philosophy | "Do you agree with the statement 'The ends justify the means'?" | Gathering stances on ethical dilemmas, facilitating debate |
| Biology | (Image of a cell) "Identify the mitochondria." | Checking understanding of biological structures |
| Chemistry | "What are the stoichiometric coefficients for the following reaction: A \+ 2B → C?" | Assessing understanding of chemical equations |
| Physics | "If a ball is thrown upwards, what is the direction of its acceleration at the highest point?" | Checking understanding of fundamental physics concepts |

**Table 3: Poll Everywhere Question Types**

| Question Type | Description | Potential Use Cases |
| :---- | :---- | :---- |
| Multiple Choice | Ask a question with predetermined answer options. | Quick knowledge checks, gathering opinions, formative assessment |
| Open-Ended | Allow participants to submit free-form text responses. | Brainstorming, collecting qualitative feedback, asking for explanations |
| Word Cloud | Display submitted words visually, with more frequent words appearing larger. | Gathering initial thoughts on a topic, identifying key concepts |
| Clickable Image | Upload an image and allow participants to click on specific areas. | Identifying parts of a diagram, pinpointing locations on a map, interactive exercises |
| Ranking | Ask participants to rank predetermined answer options in order of preference. | Prioritizing items, understanding preferences, gauging importance |
| Q\&A | Allow participants to submit questions, which can then be upvoted or downvoted. | Facilitating question and answer sessions, identifying key areas of confusion |
| Survey | Create a series of questions with different activity types. | Collecting comprehensive feedback, conducting pre- or post-assessments |
| Competition | A series of multiple-choice questions with a leaderboard. | Gamifying learning, encouraging quick recall, assessing knowledge in a fun way |
| True/False | Pose a statement and ask participants to indicate if it is true or false. | Quick checks of understanding, identifying misconceptions |
| Numeric Rating | Ask participants to rate something on a numerical scale. | Gathering feedback on satisfaction, assessing levels of understanding or agreement |
| Donut Chart | Display responses as segments of a donut chart. | Visualizing proportions of responses for single-select questions |
| Column Chart | Display responses as vertical bars. | Comparing frequencies of responses across different categories |
| Bar Chart | Display responses as horizontal bars. | Comparing frequencies of responses across different categories |
| Scatter Plot | Display responses as points on a graph. | Exploring relationships between two variables (if data is collected accordingly) |
| Map | Allow participants to drop pins on a map. | Gathering geographic information, identifying locations |
| Spotlight | Display open-ended responses one at a time. | Focusing on individual responses, facilitating a sequential sharing of ideas |
| Cluster | Group similar open-ended responses together visually. | Identifying common themes and patterns in qualitative data |
| Image Upload | Allow participants to upload images. | Sharing visual examples, completing drawing activities |

#### **Works cited**

1. How Online Polling Enhances Classroom Participation \- TheySaid, accessed April 4, 2025, [https://www.theysaid.io/blog/online-polling-enhances-classroom-participation?916a5ddd\_page=20](https://www.theysaid.io/blog/online-polling-enhances-classroom-participation?916a5ddd_page=20)
2. Student Engagement for Higher Education | Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/how-it-works-higher-ed](https://www.polleverywhere.com/how-it-works-higher-ed)
3. Classroom Polling \- Center for Teaching Innovation \- Cornell University, accessed April 4, 2025, [https://teaching.cornell.edu/learning-technologies/assessment-tools/classroom-polling](https://teaching.cornell.edu/learning-technologies/assessment-tools/classroom-polling)
4. Teaching Resources \- Instructional Technologies \- Student Response Systems, accessed April 4, 2025, [https://citl.indiana.edu/teaching-resources/instructional-technologies/student-response-systems/index.html](https://citl.indiana.edu/teaching-resources/instructional-technologies/student-response-systems/index.html)
5. Engaging Strategies: Polling | Queens College, CUNY, accessed April 4, 2025, [https://www.qc.cuny.edu/cetll/engaging-strategies-polling/](https://www.qc.cuny.edu/cetll/engaging-strategies-polling/)
6. The Benefits of Using an Interactive Response System in Education \- IQBoard.net, accessed April 4, 2025, [https://www.iqboard.net/blog/The-Benefits-of-Using-an-Interactive-Response-System-in-Education](https://www.iqboard.net/blog/The-Benefits-of-Using-an-Interactive-Response-System-in-Education)
7. Classroom Response System A Classroom Technology, accessed April 4, 2025, [https://www.cmu.edu/teaching/resources/Teaching/TechnologyTools/Clickers-generalinfo.pdf](https://www.cmu.edu/teaching/resources/Teaching/TechnologyTools/Clickers-generalinfo.pdf)
8. Polling: Overview \- Center for Teaching and Learning \- Washington University, accessed April 4, 2025, [https://ctl.wustl.edu/resources/polling-overview/](https://ctl.wustl.edu/resources/polling-overview/)
9. Student and Classroom Response System \- Mentimeter, accessed April 4, 2025, [https://www.mentimeter.com/education/classroom-lessons](https://www.mentimeter.com/education/classroom-lessons)
10. What are Classroom Response Systems and what are the best CRS tools? \- Vevox, accessed April 4, 2025, [https://www.vevox.com/blog/what-are-classroom-response-systems](https://www.vevox.com/blog/what-are-classroom-response-systems)
11. Types of Polling Questions \- Center for Teaching and Learning \- Washington University, accessed April 4, 2025, [https://ctl.wustl.edu/resources/polling-activities-and-questions/](https://ctl.wustl.edu/resources/polling-activities-and-questions/)
12. Poll Your Way to Success: Using Poll Everywhere to Enhance Student Reflection and Learning \- Higher Ed and Technology: Academics at Chapman, accessed April 4, 2025, [https://blogs.chapman.edu/academics/2023/03/06/poll-your-way-to-success/](https://blogs.chapman.edu/academics/2023/03/06/poll-your-way-to-success/)
13. Top 5 classroom polling tools to engage students | The Jotform Blog, accessed April 4, 2025, [https://www.jotform.com/blog/classroom-polling/](https://www.jotform.com/blog/classroom-polling/)
14. Feedback / Polling Tools | Poorvu Center for Teaching and Learning \- Yale University, accessed April 4, 2025, [https://poorvucenter.yale.edu/strategic-resources-digital-publications/instructional-tools/feedback-polling-tools](https://poorvucenter.yale.edu/strategic-resources-digital-publications/instructional-tools/feedback-polling-tools)
15. Measuring public opinion: lesson overview (article) \- Khan Academy, accessed April 4, 2025, [https://www.khanacademy.org/humanities/ap-us-government-and-politics/american-political-ideologies-and-beliefs/measuring-public-opinion/a/lesson-summary-measuring-public-opinion](https://www.khanacademy.org/humanities/ap-us-government-and-politics/american-political-ideologies-and-beliefs/measuring-public-opinion/a/lesson-summary-measuring-public-opinion)
16. Developing Poll Questions to Engage and Assess Student Thinking in Science and Engineering Courses \- Columbia Center for Teaching and Learning, accessed April 4, 2025, [https://ctl.columbia.edu/resources-and-technology/resources/poll-questions-stem/](https://ctl.columbia.edu/resources-and-technology/resources/poll-questions-stem/)
17. The ins and outs of Polling @ McGill | Office of Science Education, accessed April 4, 2025, [https://www.mcgill.ca/ose/channels/news/ins-and-outs-polling-mcgill-297049](https://www.mcgill.ca/ose/channels/news/ins-and-outs-polling-mcgill-297049)
18. Learning Catalytics in College \- YouTube, accessed April 4, 2025, [https://www.youtube.com/watch?v=G0GsqAWDqFM](https://www.youtube.com/watch?v=G0GsqAWDqFM)
19. Teaching Tools \- Polling \- CNDLS \- Georgetown University, accessed April 4, 2025, [https://cndls.georgetown.edu/resources/tools/polling/](https://cndls.georgetown.edu/resources/tools/polling/)
20. Polling & Clickers | The Derek Bok Center for Teaching and Learning \- Harvard University, accessed April 4, 2025, [https://bokcenter.harvard.edu/polling-clickers](https://bokcenter.harvard.edu/polling-clickers)
21. Learning Catalytics Question Types \- YouTube, accessed April 4, 2025, [https://www.youtube.com/watch?v=cYXU1ej4elk](https://www.youtube.com/watch?v=cYXU1ej4elk)
22. Lesson 2 The client-server model \- Teach Computing, accessed April 4, 2025, [https://teachcomputing.org/curriculum/key-stage-4/networks/the-client-server-model](https://teachcomputing.org/curriculum/key-stage-4/networks/the-client-server-model)
23. The Client Server Model Improving Technology Management | Mindsight, accessed April 4, 2025, [https://gomindsight.com/insights/blog/client-server-model-improves-tech-management/](https://gomindsight.com/insights/blog/client-server-model-improves-tech-management/)
24. Client-Server Network: Understanding, Functions, and Services \- FS.com, accessed April 4, 2025, [https://www.fs.com/blog/a-guide-to-understanding-clientserver-network-6976.html](https://www.fs.com/blog/a-guide-to-understanding-clientserver-network-6976.html)
25. What is a Client-Server Application? How It Works & Use Cases | V2 Cloud, accessed April 4, 2025, [https://v2cloud.com/glossary/client-server-application](https://v2cloud.com/glossary/client-server-application)
26. Client–server model \- Wikipedia, accessed April 4, 2025, [https://en.wikipedia.org/wiki/Client%E2%80%93server\_model](https://en.wikipedia.org/wiki/Client%E2%80%93server_model)
27. www.cloudflare.com, accessed April 4, 2025, [https://www.cloudflare.com/learning/ddos/glossary/hypertext-transfer-protocol-http/\#:\~:text=The%20Hypertext%20Transfer%20Protocol%20(HTTP,of%20the%20network%20protocol%20stack.](https://www.cloudflare.com/learning/ddos/glossary/hypertext-transfer-protocol-http/#:~:text=The%20Hypertext%20Transfer%20Protocol%20\(HTTP,of%20the%20network%20protocol%20stack.)
28. What is HTTP? | Cloudflare, accessed April 4, 2025, [https://www.cloudflare.com/learning/ddos/glossary/hypertext-transfer-protocol-http/](https://www.cloudflare.com/learning/ddos/glossary/hypertext-transfer-protocol-http/)
29. An overview of HTTP \- MDN Web Docs, accessed April 4, 2025, [https://developer.mozilla.org/en-US/docs/Web/HTTP/Overview](https://developer.mozilla.org/en-US/docs/Web/HTTP/Overview)
30. www.cloudflare.com, accessed April 4, 2025, [https://www.cloudflare.com/learning/ssl/what-is-https/\#:\~:text=HTTPS%20uses%20an%20encryption%20protocol,an%20asymmetric%20public%20key%20infrastructure.](https://www.cloudflare.com/learning/ssl/what-is-https/#:~:text=HTTPS%20uses%20an%20encryption%20protocol,an%20asymmetric%20public%20key%20infrastructure.)
31. What is HTTPS? How it Works and Why It's So Important | UpGuard, accessed April 4, 2025, [https://www.upguard.com/blog/what-is-https](https://www.upguard.com/blog/what-is-https)
32. HTTP vs HTTPS \- Difference Between Transfer Protocols \- AWS, accessed April 4, 2025, [https://aws.amazon.com/compare/the-difference-between-https-and-http/](https://aws.amazon.com/compare/the-difference-between-https-and-http/)
33. What is HTTPS? Its meaning, what it does, and how it works \- One.com Web hosting, accessed April 4, 2025, [https://www.one.com/en/website-security/what-is-https](https://www.one.com/en/website-security/what-is-https)
34. Poll Everywhere FAQs \- The Center for Teaching and Learning \- UNC Charlotte, accessed April 4, 2025, [https://teaching.charlotte.edu/academic-technologies/student-response-system/poll-everywhere-faqs/](https://teaching.charlotte.edu/academic-technologies/student-response-system/poll-everywhere-faqs/)
35. Poll Everywhere: Overview | Discover Instructional Tools \- Canvas @ Yale, accessed April 4, 2025, [https://help.canvas.yale.edu/a/1334907-poll-everywhere-overview](https://help.canvas.yale.edu/a/1334907-poll-everywhere-overview)
36. Polling (Poll Everywhere) \- University of Rochester, accessed April 4, 2025, [https://tech.rochester.edu/services/polling-poll-everywhere/](https://tech.rochester.edu/services/polling-poll-everywhere/)
37. Poll Everywhere for K-12 Education, accessed April 4, 2025, [https://www.polleverywhere.com/k12-student-response-system](https://www.polleverywhere.com/k12-student-response-system)
38. Poll Everywhere Student Guide | Instructional and Information Technology Services (IITS), accessed April 4, 2025, [https://www.csusm.edu/iits/services/ats/idesign/canvas/guides/polleverywhere\_studentguide/index.html](https://www.csusm.edu/iits/services/ats/idesign/canvas/guides/polleverywhere_studentguide/index.html)
39. How do I log into the Poll Everywhere app as a student? | Integrated Tools, accessed April 4, 2025, [https://lts-help.its.virginia.edu/m/integrated-tools/l/1770420-how-do-i-log-into-the-poll-everywhere-app-as-a-student](https://lts-help.its.virginia.edu/m/integrated-tools/l/1770420-how-do-i-log-into-the-poll-everywhere-app-as-a-student)
40. Poll Everywhere Tutorials: \- Center for Teaching and Learning, accessed April 4, 2025, [https://ctl.wustl.edu/polleverywhere-students/](https://ctl.wustl.edu/polleverywhere-students/)
41. Poll Everywhere \- Academic Technology for FAS \- Harvard University, accessed April 4, 2025, [https://atg.fas.harvard.edu/poll-everywhere](https://atg.fas.harvard.edu/poll-everywhere)
42. Poll Everywhere: Engage your audience, accessed April 4, 2025, [https://www.polleverywhere.com/](https://www.polleverywhere.com/)
43. Activity gallery \- Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/gallery](https://www.polleverywhere.com/gallery)
44. Poll Everywhere \- CTE Resources \- Boston College, accessed April 4, 2025, [https://cteresources.bc.edu/documentation/poll-everywhere/](https://cteresources.bc.edu/documentation/poll-everywhere/)
45. Poll Everywhere \- The Office of Technology \- Washington State University, accessed April 4, 2025, [https://tech.medicine.wsu.edu/technology/poll-everywhere/](https://tech.medicine.wsu.edu/technology/poll-everywhere/)
46. Poll Everywhere Applications and Integrations, accessed April 4, 2025, [https://www.polleverywhere.com/app](https://www.polleverywhere.com/app)
47. The essential Admin guide \- Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/poll-everywhere-admin-guide.pdf?hsLang=en](https://www.polleverywhere.com/poll-everywhere-admin-guide.pdf?hsLang=en)
48. Pricing Plans \- Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/plans](https://www.polleverywhere.com/plans)
49. New in Poll Everywhere: Course Management Interface \- Research, Teaching, & Learning, accessed April 4, 2025, [https://rtl.berkeley.edu/new-poll-everywhere-course-management-interface](https://rtl.berkeley.edu/new-poll-everywhere-course-management-interface)
50. Getting Started with Course Management \- Poll Everywhere, accessed April 4, 2025, [https://support.polleverywhere.com/hc/en-us/articles/27578588765339-Getting-Started-with-Course-Management](https://support.polleverywhere.com/hc/en-us/articles/27578588765339-Getting-Started-with-Course-Management)
51. Introducing the new Course Management Interface for Poll Everywhere, accessed April 4, 2025, [https://rtl.berkeley.edu/news/introducing-new-course-management-interface-poll-everywhere](https://rtl.berkeley.edu/news/introducing-new-course-management-interface-poll-everywhere)
52. Privacy policy | Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/privacy-policy](https://www.polleverywhere.com/privacy-policy)
53. Security | Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/security](https://www.polleverywhere.com/security)
54. Data Privacy Framework and GDPR Compliance Policy \- Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/data-privacy-framework](https://www.polleverywhere.com/data-privacy-framework)
55. Poll Everywhere | HMS IT \- Harvard University, accessed April 4, 2025, [https://it.hms.harvard.edu/service/poll-everywhere](https://it.hms.harvard.edu/service/poll-everywhere)
56. Poll Everywhere | Slack Marketplace, accessed April 4, 2025, [https://slack.com/marketplace/ABEM7C9LP-poll-everywhere](https://slack.com/marketplace/ABEM7C9LP-poll-everywhere)
57. Reporting | Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/features/reports](https://www.polleverywhere.com/features/reports)
58. Features | Poll Everywhere, accessed April 4, 2025, [https://www.polleverywhere.com/videos/features](https://www.polleverywhere.com/videos/features)
59. Customizing your poll chart, accessed April 4, 2025, [https://www.polleverywhere.com/videos/tutorials/customizing-poll-chart](https://www.polleverywhere.com/videos/tutorials/customizing-poll-chart)
60. Poll Everywhere launches Attendance Management feature to automate attendance tracking and boost student performance., accessed April 4, 2025, [https://blog.polleverywhere.com/poll-everywhere-launches-attendance-management](https://blog.polleverywhere.com/poll-everywhere-launches-attendance-management)
61. Introducing Course Management: Redefining Classroom Administration, accessed April 4, 2025, [https://blog.polleverywhere.com/introducing-course-management-redefining-classroom-administration](https://blog.polleverywhere.com/introducing-course-management-redefining-classroom-administration)
62. Download Learning Catalytics scores and results \- help.pearsoncmg.com, accessed April 4, 2025, [https://help.pearsoncmg.com/learning\_catalytics/instructor/en/Content/Topics/grading\_scoring/lc\_scores\_download.htm](https://help.pearsoncmg.com/learning_catalytics/instructor/en/Content/Topics/grading_scoring/lc_scores_download.htm)
63. Create Powerful Polls in an Instant with AI, accessed April 4, 2025, [https://blog.polleverywhere.com/create-powerful-polls-in-an-instant-with-ai](https://blog.polleverywhere.com/create-powerful-polls-in-an-instant-with-ai)
64. Transform Presentations with AI Poll Questions Generator \- Wooclap, accessed April 4, 2025, [https://www.wooclap.com/en/blog/crafting-engaging-polls-with-ai/](https://www.wooclap.com/en/blog/crafting-engaging-polls-with-ai/)
65. AI Social Media Poll Questions Generator \- Narrato, accessed April 4, 2025, [https://narrato.io/ai/ai-social-media-poll-questions-generator/](https://narrato.io/ai/ai-social-media-poll-questions-generator/)
66. How to Use AI to Create Engaging Quick Polls, accessed April 4, 2025, [https://support.engageli.com/hc/en-us/articles/26976330680347-How-to-Use-AI-to-Create-Engaging-Quick-Polls](https://support.engageli.com/hc/en-us/articles/26976330680347-How-to-Use-AI-to-Create-Engaging-Quick-Polls)
67. The Best AI Assessment Tools for Teachers \- Atomic Blog, accessed April 4, 2025, [https://blog.atomicjolt.com/the-best-ai-assessment-tools-for-teachers/](https://blog.atomicjolt.com/the-best-ai-assessment-tools-for-teachers/)
68. How AI Question Generators Spark Deeper Learning in 2024? \- Hurix Digital, accessed April 4, 2025, [https://www.hurix.com/blogs/how-ai-question-generators-spark-deeper-learning/](https://www.hurix.com/blogs/how-ai-question-generators-spark-deeper-learning/)
69. AI-Powered Survey Question Generator Online \- Metaforms AI Blog, accessed April 4, 2025, [https://metaforms.ai/blog/ai-powered-survey-question-generator-online](https://metaforms.ai/blog/ai-powered-survey-question-generator-online)
70. Top Hat Ace | Top Hat, accessed April 4, 2025, [https://tophat.com/features/ace-ai/](https://tophat.com/features/ace-ai/)
71. QuestionWell: AI-Powered Teaching Tools | Enhance Educators' Efficiency, accessed April 4, 2025, [https://questionwell.org/](https://questionwell.org/)
72. Learning analytics and insights from AI | by Artificial Intelligence \+ \- Medium, accessed April 4, 2025, [https://aiplusinfo.medium.com/learning-analytics-and-insights-from-ai-4ca2bb011e3f](https://aiplusinfo.medium.com/learning-analytics-and-insights-from-ai-4ca2bb011e3f)
73. AI Trends in Real-Time Analytics: What You Need to Know \- MicroStrategy, accessed April 4, 2025, [https://www.strategysoftware.com/pl/blog/ai-trends-in-real-time-analytics-what-you-need-to-know](https://www.strategysoftware.com/pl/blog/ai-trends-in-real-time-analytics-what-you-need-to-know)
74. AI for Data Analytics | Google Cloud, accessed April 4, 2025, [https://cloud.google.com/use-cases/ai-data-analytics](https://cloud.google.com/use-cases/ai-data-analytics)
75. 2024 Trends: AI-Powered Learning Analytics \- eLearning Industry, accessed April 4, 2025, [https://elearningindustry.com/2024-trends-ai-powered-learning-analytics](https://elearningindustry.com/2024-trends-ai-powered-learning-analytics)
76. Detecting and Correcting Misconceptions with Lifelike Avatars in 3D Learning Environments \- The IntelliMedia Group, accessed April 4, 2025, [https://intellimedia.ncsu.edu/wp-content/uploads/sites/42/cpu-aied-99.pdf](https://intellimedia.ncsu.edu/wp-content/uploads/sites/42/cpu-aied-99.pdf)
77. Get your students actively involved with Online polling in the classroom \- TheySaid, accessed April 4, 2025, [https://www.theysaid.io/blog/online-polling-enhances-classroom-participation?916a5ddd\_page=23](https://www.theysaid.io/blog/online-polling-enhances-classroom-participation?916a5ddd_page=23)
78. Leveraging Classroom Polling and Artificial Intelligence to Enhance Learner Engagement and Metacognition in a First-Year Anatomy and Physiology Course \- ResearchGate, accessed April 4, 2025, [https://www.researchgate.net/publication/385696558\_Leveraging\_Classroom\_Polling\_and\_Artificial\_Intelligence\_to\_Enhance\_Learner\_Engagement\_and\_Metacognition\_in\_a\_First-Year\_Anatomy\_and\_Physiology\_Course](https://www.researchgate.net/publication/385696558_Leveraging_Classroom_Polling_and_Artificial_Intelligence_to_Enhance_Learner_Engagement_and_Metacognition_in_a_First-Year_Anatomy_and_Physiology_Course)
79. The Ultimate Guide to AI in Education: Benefits, Challenges, & Real-World Uses, accessed April 4, 2025, [https://www.powerschool.com/blog/ai-in-education/](https://www.powerschool.com/blog/ai-in-education/)
80. Student Voice \- Text Analysis for Education, accessed April 4, 2025, [https://www.studentvoice.ai/](https://www.studentvoice.ai/)
81. How Schools Can Leverage AI for Student Feedback Collection and Analysis, accessed April 4, 2025, [https://zenphi.com/students-feedback-collection-ai/](https://zenphi.com/students-feedback-collection-ai/)
82. Student Generative AI Survey 2025 | HEPI, accessed April 4, 2025, [https://www.hepi.ac.uk/wp-content/uploads/2025/02/HEPI-Kortext-Student-Generative-AI-Survey-2025.pdf](https://www.hepi.ac.uk/wp-content/uploads/2025/02/HEPI-Kortext-Student-Generative-AI-Survey-2025.pdf)
83. Survey: College students enjoy using generative AI tutor \- Inside Higher Ed, accessed April 4, 2025, [https://www.insidehighered.com/news/student-success/academic-life/2025/01/22/survey-college-students-enjoy-using-generative-ai](https://www.insidehighered.com/news/student-success/academic-life/2025/01/22/survey-college-students-enjoy-using-generative-ai)
84. Leveraging AI for Survey Analysis: A Comprehensive Guide from Sprig, accessed April 4, 2025, [https://sprig.com/blog/leveraging-ai-for-survey-analysis](https://sprig.com/blog/leveraging-ai-for-survey-analysis)
85. Analyzing click data with AI: implications for student performance prediction and learning assessment \- Frontiers, accessed April 4, 2025, [https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2024.1421479/full](https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2024.1421479/full)
86. Data-Driven Teaching: AI for Pre- and Post-Class Surveys, accessed April 4, 2025, [https://mitsloanedtech.mit.edu/ai/teach/data-driven-teaching-ai-for-pre-and-post-class-surveys/](https://mitsloanedtech.mit.edu/ai/teach/data-driven-teaching-ai-for-pre-and-post-class-surveys/)
87. Simple Poll | Slack Marketplace, accessed April 4, 2025, [https://slack.com/marketplace/A0HFW7MR6-simple-poll](https://slack.com/marketplace/A0HFW7MR6-simple-poll)
88. Slack bot Integrations | Automated Workflows with Latenode, accessed April 4, 2025, [https://latenode.com/integrations/slack-bot?4b77e0b0\_page=1&820bb7f0\_page=4](https://latenode.com/integrations/slack-bot?4b77e0b0_page=1&820bb7f0_page=4)
89. Slack Integrations, create a Slack Bot and automate workflow \- Konnectify, accessed April 4, 2025, [https://www.konnectify.co/blogs/slack-integrations-create-a-slack-bot-and-automate-workflows](https://www.konnectify.co/blogs/slack-integrations-create-a-slack-bot-and-automate-workflows)
90. How to create a poll in Slack: 4 easy methods | Zapier, accessed April 4, 2025, [https://zapier.com/blog/how-to-create-a-poll-in-slack/](https://zapier.com/blog/how-to-create-a-poll-in-slack/)
91. Build a Beautiful, Scalable Real-Time Voting App with Next.js 14, Upstash (2024) \- YouTube, accessed April 4, 2025, [https://www.youtube.com/watch?v=zWRBobemogk](https://www.youtube.com/watch?v=zWRBobemogk)
92. Build a Q\&A and Polls platform with Nextjs, Supabase, Kinde, Prisma | Part 2/2 \- YouTube, accessed April 4, 2025, [https://www.youtube.com/watch?v=PhzhjlK0URI](https://www.youtube.com/watch?v=PhzhjlK0URI)
93. How I Built & Deployed a Real-time Polling App in 30 Minutes | by Sunith | Medium, accessed April 4, 2025, [https://medium.com/@sunithvs/how-i-built-a-quick-polling-app-during-lunch-break-a64217555a5e](https://medium.com/@sunithvs/how-i-built-a-quick-polling-app-during-lunch-break-a64217555a5e)
94. STREAM VOD: Building a Poll Site in NextJS Part 1 \- YouTube, accessed April 4, 2025, [https://www.youtube.com/watch?v=jX7nTj05SYs](https://www.youtube.com/watch?v=jX7nTj05SYs)
95. Analyze Survey Data with Python for Beginners | Pandas \- YouTube, accessed April 4, 2025, [https://m.youtube.com/watch?v=B-lliwc0ZMk\&pp=ygULI2RhdGFzdXJ2ZXk%3D](https://m.youtube.com/watch?v=B-lliwc0ZMk&pp=ygULI2RhdGFzdXJ2ZXk%3D)
96. Analyzing Categorical Data from the General Social Survey in Python \- YouTube, accessed April 4, 2025, [https://m.youtube.com/watch?v=fOZvR7Y3-l8\&pp=ygULI2RhdGFzdXJ2ZXk%3D](https://m.youtube.com/watch?v=fOZvR7Y3-l8&pp=ygULI2RhdGFzdXJ2ZXk%3D)
97. How to Analyze Survey Data with Python for Beginners \- Dataquest, accessed April 4, 2025, [https://www.dataquest.io/blog/how-to-analyze-survey-data-python-beginner/](https://www.dataquest.io/blog/how-to-analyze-survey-data-python-beginner/)
98. Get Started Analyzing Survey Data with SQL & Python \- DataCamp, accessed April 4, 2025, [https://www.datacamp.com/code-along/get-started-analyzing-survey-data-with-sql-and-python](https://www.datacamp.com/code-along/get-started-analyzing-survey-data-with-sql-and-python)