Bibliometric Mapping of AI-Supported Social Presence in Online Learning Environments: Trends, Collaboration, and Thematic Directions
This bibliometric analysis of 59 empirical studies reveals a post-2020 surge in AI-supported social presence research within online learning, highlighting a primary focus on engagement and instructional design while identifying a critical need for greater international collaboration and deeper exploration of ethical concerns.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine the world of online learning as a giant, bustling digital town square. In a real town square, you can see people's faces, hear their laughter, and feel the energy of the crowd. That feeling of connection is called "Social Presence." It's what makes you feel like you aren't just staring at a screen alone, but are part of a real community.
However, in the digital town square, that feeling is often missing. It can feel cold and lonely. Recently, people have started trying to fix this by bringing in Artificial Intelligence (AI)—like friendly robot helpers or chatbots—to act as the "glue" that brings people together.
This paper is like a mapmaker's report. Instead of drawing a map of streets, the authors (a team of researchers from the Philippines) drew a map of the ideas and people working on this problem. They looked at 59 specific research studies (like looking at 59 different blueprints) to see where the field is going.
Here is what their map reveals, broken down into simple stories:
1. The "Explosion" of Interest
For a long time (before 2020), very few people were drawing blueprints for AI in this specific area. It was quiet. But then, 2020 happened (the year the world went online for school and work). Suddenly, the interest skyrocketed.
- The Analogy: Think of it like a small campfire that was barely flickering. In 2020, someone threw a bucket of gasoline on it, and now it's a roaring bonfire. The number of studies jumped from just a handful a year to over a dozen recently.
2. The "Islands" of Researchers
The researchers looked at who is writing these papers. They found that while many people are working on this, they are mostly working in small, isolated groups.
- The Analogy: Imagine a group of people trying to build a bridge across a river. Most of them are building their own tiny, separate piers on their own islands. They are talking to their neighbors on the same island, but they aren't really shaking hands with the people on the other islands.
- The Reality: The US and Brazil are building the biggest piers (they have the most studies), but the bridges connecting these countries are very weak. There isn't enough teamwork between different nations or universities.
3. The Four Main "Neighborhoods" of Ideas
When the authors grouped the studies by what they were talking about, they found four main "neighborhoods" or themes:
- The "Engagement" Neighborhood: This is the biggest area. It's all about how to keep students interested and not bored while learning online.
- The "AI Tools" Neighborhood: This is where people talk about the robots themselves—chatbots and smart tutors that try to talk like humans.
- The "Teaching Style" Neighborhood: This focuses on how teachers should change their lessons to fit the online world.
- The "Ethics" Neighborhood: This is a very small, quiet corner of the map. It deals with tricky questions like: Is the AI fair? Can we trust it? The authors noted that while this is important, not many people are exploring it yet.
4. The "Star" Blueprints
The paper also looked at which specific studies were the most famous (the most "cited").
- The Analogy: If these studies were songs, these are the "greatest hits" that everyone keeps playing.
- The Reality: The most popular studies are mostly about how to make students feel connected using the "Community of Inquiry" framework (a fancy way of saying "let's make sure everyone feels like they belong"). They also found studies that use AI to predict if a student is paying attention or if they are about to get bored.
5. What's Missing?
The map shows that while we are getting better at building the "pods" (the AI tools) and the "rooms" (the online classes), we are still missing the "handshakes."
- The Gap: We don't have enough big teams working together across borders.
- The Gap: We aren't asking enough hard questions about whether these AI tools are fair or trustworthy.
- The Gap: The research is a bit scattered. It's like everyone is building a different kind of Lego brick, but no one has figured out how to snap them all together into one giant, perfect castle yet.
The Bottom Line
This paper is a snapshot of a field that is growing fast but still a bit messy. We have a lot of energy and many new ideas about using AI to make online learning feel more human. However, to build a truly great digital town square, researchers need to stop working in their own little bubbles and start building bridges to each other, while also making sure the AI they build is safe and fair for everyone.
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