ΑΙhub.org
 

Daphne Koller: Digital learning coming to life – #AAAI2021 invited talk


by
11 March 2021



share this:
online learning graphic

At AAAI 2021, Daphne Koller gave a plenary talk about digital learning. In this presentation she discussed the different motivations for online learning, what we know about effective learning, digital platforms, and using data to improve learning.

AIhub focus issue on quality education

The COVID pandemic has necessitated a transition online for many of our activities, with one of the more significant of these being education. Many academic institutions were unprepared for this transition and, in general, this led to a decline in student satisfaction and achievement. In her talk, Daphne argued that this challenge also presents an unprecedented opportunity to transform the way teaching is delivered.

Balancing increased access and increased engagement

Pre-pandemic, we were seeing a gradual shift towards online learning. In the USA this was partly driven by the fact that the majority of college undergraduates have additional responsibilities to contend with alongside their studies, and having some flexibility in a schedule is desirable. Although online learning can significantly increase access to education, it typically does not have the same level of engagement as face-to-face teaching. This is the main challenge in this space: increasing access without sacrificing student engagement.

shift to online learning graph
Slide from Daphne’s talk. In the USA 74% of college undergraduates are non-traditional students

Daphne also spoke about MOOCs (massive open online courses) and popularity of the AI and machine learning courses offered through Coursera. Since the early days, in 2012, the number of MOOCs on offer has increased rapidly. When people complete a MOOC it is likely to have benefits for their career. However, the completion rate is very low (around 5%).

Research shows that a hybrid approach, where the online format is combined with a small number of meetings with an instructor, can be as effective as a traditionally taught course. It is these hybrid approaches that could unlock the potential of online learning.

How to learn effectively

Daphne identified three key elements that are needed for learning to be effective. Learning should be: active, interactive and collaborative.

She went on to give some examples of how to incorporate these into online learning. The digital format allows for active learning features to be introduced to a lesson quite easily. For instance, by adding polls and quizzes for students to participate in. These provide a quick way informing the teacher how many students have understood the concepts they are trying to convey. This cannot be done so easily in a physical classroom. There is also software for note-taking and annotation that enables students to capture screenshots and add their own notes, and to pull up the relevant section of the video lecture at a later date with a simple click.

active learning examples
Slide from Daphne’s talk showing an example of active learning on a digital platform.

Daphne believes that some of the greatest educational benefits come from collaborative learning. Most classrooms on a University campus are auditoriums, and these do not facilitate collaborative learning. One way to enable collaboration in a physical setting would be to have students sat facing each other on tables of four, like in primary/elementary school. Recreating such a table set-up online is now simple to do. Daphne gave an example where students in a virtual lecture are split into groups (“tables”) of four to eight. They can communicate with each other while the lecture is going on and it doesn’t disrupt the rest of the class. The students can also work together on shared documents and shared whiteboards. This format can really help embolden students to ask questions, as they quickly realise the whole table group is having trouble understanding a concept too, and it gives them the confidence to raise this with the lecturer.

Using data to improve learning

In the final section of her talk, Daphne spoke about data collection and analysis, and how machine learning methods could be used for this. With an online format it is easy to garner a huge amount of data around student engagement. The slide below shows the many different types of data that can be obtained. She was keen to point out that the collection methods do not include invasive gaze tracking, or looking at a student’s video feed.

collecting data in online learning
Slide from Daphne’s talk listing the types of data that can be collected from online learning tools.

This data stream can be used in real-time by an instructor. For example, if the data suggests that class engagement has dropped below a certain level they could run a quiz or a poll, or ask the class a question. There are also prompts that can be sent to students to recommend that they take notes on a particular slide, because other students had taken a note at that point.

Daphne concluded by saying that we have an opportunity to reimagine education. How can we create a learning experience that is both accessible and engaging, and will make students more successful?

Watch the talk in full

You can see this plenary talk, and the Q&A session here.

About Daphne Koller

Daphne Koller is CEO and Founder of insitro, a machine-learning enabled drug discovery company, and the co-founder of the online education platforms Engageli and Coursera. She was previously Professor of Computer Science at Stanford University. Her research interests include representation, inference, learning, and decision making, with a focus on applications to computer vision and computational biology. She has won numerous awards including the 2019 ACM-AAAI Allen Newell Award.



tags: , , ,


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Engineering Out Loud: S13E1 – How many robots can a single human supervise?

  22 Jun 2026
Professor Julie Adams describes the research showing that one person can supervise more than 100 autonomous ground and aerial robots.

Everything, eco-where, AI at once?

Laura Martinez Agudelo builds on her research of visual representations of ecology and digitalisation to explore how "AI eco-imagery" is portrayed.

AI is making journalistic language more repetitive and predictable – and it’s a problem for all of us

  17 Jun 2026
What happens to language when a growing amount of text published in the press, online and on social media is written by machines?
monthly digest

AIhub monthly digest: June 2026 – biodiversity, resource allocation, and color metaphors

  16 Jun 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

AAAI presidential panel – AI agents

  15 Jun 2026
Experts discuss AI agents, one of the topics covered in the AAAI Future of AI Research report.

Interview with AAAI Fellow Tanya Berger-Wolf: AI for ecology, biodiversity, and conservation

  11 Jun 2026
Find out about Tanya work on a foundation model for biology and the insights that this can provide.

Statistical or embodied? Comparing people and LLMs in their processing of color metaphors: an interview with Douglas Guilbeault

  09 Jun 2026
We learn what implications color metaphors and synaesthesia have for human and AI cognition.

The Good Robot podcast: the battle over data centres with Tara Merk

  08 Jun 2026
Eleanor Drage speaks with Tara Merk about how community-owned data centers could transform digital ownership and challenge the dominance of Big Tech.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence