Tag: conferences

CHI’24 research publications

I attended the prestigious Human-Computer Interaction (HCI) conference CHI’24 at Hawaii, Honolulu in May 2024. While I’m quite familiar with the field of HCI, it was my first time attending the conference because it is much wider than my main area of research (Learning Analytics, AI in education, and Writing Analytics). The sheer scale of the conference (~2K to 3K attendees) and the broad range of topics it covers (check out this full program) is almost impossible to fully grasp!

TLDR; Go to the end for the list of paper from CHI’24.

My personal highlight was the Intelligent Writing Assistants Workshop, which was running for the third time at CHI, organized by a bunch of fun people who are all super keen about researching the use of AI to assist writing. Picture from our workshop below (thanks, Theimo, for the LinkedIn post)

Pictured: Participants of the Intelligent Writing Assistants CHI’24 workshop at the end of the session

The workshop had many mini presentations on the overall theme of Dark Sides: Envisioning, Understanding, and Preventing Harmful Effects of Writing Assistants. I presented my work with Prof. Simon Buckingham Shum on AI-Assisted Writing in Education: Ecosystem Risks and Mitigations, where we examined key factors (in the broader socio-technical ecosystem which are often hidden) that need consideration for implementing AI writing assistants at scale in educational contexts.

This was actually a deep dive into the Ecosystem aspect of a larger piece of work we presented at CHI on A Design Space for Intelligent and Interactive Writing Assistants. The full design space from our full paper mapped the space of intelligent writing assistants reviewing 115 papers from HCI and NLP, with a team of 36 authors, led by Mina Lee.

Figure: Design space for intelligent and interactive writing assistants consisting of five key aspects—task, user, technology, interaction, and ecosystem from our full paper.

An interactive tool is also presented to explore the literature in detail.

I also had a late-breaking work poster presentation on Critical Interaction with AI on Written Assessment (I have a seperate post about it!) where we explored how students engaged with generative AI tools like ChatGPT for their writing tasks, and if they were able to navigate this interaction critically.

A cherished memory to hold on to was also the time I spent with my friend Vanessa, who is currently a Research Fellow at Monash university during this trip in Hawaii. Vanessa and I started our PhD together at th Connected Intelligence Centre at UTS ~8 years ago, and it was really nice to catch up after a long time (along with few others). I had also just visited Monash university’s CoLAM a week before for a talk and meeting fellow Learning Analytics researchers, hosted by her and Roberto. The group do interesting work in Learning Analytics that is worth checking out.

6 years apart… On the left: Vanessa and I in 2018 while attending AIED/ ICLS 2018 in London; On the right: Us while attending CHI in 2024 in Hawaii.

TLDR -> Research publications:

Here are all the papers from the work we presented at CHI’24:

Mina Lee, Katy Ilonka Gero, John Joon Young Chung, Simon Buckingham Shum, Vipul Raheja, Hua Shen, Subhashini Venugopalan, Thiemo Wambsganss, David Zhou, Emad A. Alghamdi, Tal August, Avinash Bhat, Madiha Zahrah Choksi, Senjuti Dutta, Jin L.C. Guo, Md Naimul Hoque, Yewon Kim, Simon Knight, Seyed Parsa Neshaei, Agnia Sergeyuk, Antonette Shibani, Disha Shrivastava, Lila Shroff, Jessi Stark, Sarah Sterman, Sitong Wang, Antoine Bosselut, Daniel Buschek, Joseph Chee Chang, Sherol Chen, Max Kreminski, Joonsuk Park, and Roy Pea, Eugenia H. Rho, Shannon Zejiang Shen, Pao Siangliulue. 2024. A Design Space for Intelligent and Interactive Writing Assistants. In Proceedings
of the CHI Conference on Human Factors in Computing Systems (CHI ’24),
May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 33 pages.
https://doi.org/10.1145/3613904.3642697

Antonette Shibani, Simon Knight, Kirsty Kitto, Ajanie Karunanayake, Simon Buckingham Shum (2024). Untangling Critical Interaction with AI in Students’ Written Assessment. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11-16, 2024, Honolulu, HI, USA. doi.org/10.1145/3613905.3651083

Antonette Shibani & Simon Buckingham Shum (2024). AI-Assisted Writing in Education: Ecosystem Risks and Mitigations. In The Third Workshop on Intelligent and Interactive Writing Assistants @ CHI ’24, Honolulu, HI, USA. https://arxiv.org/abs/2404.10281

London Festival of Learning 2018

I attended the London Festival of Learning this year from June 22nd-30th, which brought together three conferences: the 13th International Conference of the Learning Sciences (ICLS), the Fifth Annual ACM Conference on Learning at Scale (L@S) and the 19th International Conference on Artificial Intelligence in Education (AIED).  It was great to see the convergence of ideas and academics from these three fields that generally work towards enhancing educational practices with technology. I could see overlaps and similarities in the topics of research being studied by these communities, but I also noticed they were divergent in terms of the main foci of their research. The festival was huge with over a 1000 attendees, and also involved edtech companies that wanted to develop evidence-informed products.

Throughout the conferences, I found an emphasis and move towards making more use of human ability and intelligence to augment what artificial intelligence can do for education in many keynotes and talks. This included concepts like giving importance to our internally persuasive voice and the power of negotiation in addition to “datafied” learning, and embracing imperfections from machines by adding in human context. A critical stance on what Artificial Intelligence can and cannot do was seen, with more conversations happening around the ethical use of learner’s data.

(Excuse me for the blurry pictures, I was not in a good spot to take pictures)

In the sessions, I could see a lot of research on developing intelligent tutoring systems, agents, intervention designs and adaptive learning systems for teaching specific skills, and advances made in their techniques. The majority of data comes from online settings i.e, students’ trace data from their usage with such systems. Recently, multi-modal data is getting more attention where sensors and wearables collect data from learner’s physical spaces as well. One best paper award winning work on Teacher-AI hybrid systems showcased the power of mixed-reality systems for real-time classroom orchestration. The cross-over session and the ALLIANCE best paper session showcased interesting research cutting across the three communities; it’s a shame we couldn’t attend both sessions since they ran in parallel.

Simon Knight presented our work on Augmenting Formative Writing Assessment with Learning Analytics: A Design Abstraction Approach at the cross-over session where he explained how we can augment existing good practices with learning analytics, and use design representations for standardizing these learning designs. I presented our poster on studying the revision process in writing in AIED, where I used snapshots of students’ writing data to study their drafting process at certain time intervals. I also participated in the collaborative writing workshop earlier in ICLS where many interesting tools to support writing were discussed. I shared about AcaWriter – a writing analytics tool providing automated feedback on rhetorical moves, developed by the Connected Intelligence Centre, UTS  which is now released open-source.

Overall, it was a great place to learn, network and follow work from related disciplines (with some catching up to do on the presented work, coz we can only be at one place at one time during the parallel sessions). I did feel a bit exhausted a the end of it (maybe I’m better off attending one conference at a time 🙂 ), but I guess that’s natural, and you can’t complain when your brain gets so much to learn in a week!

Preparing for a doctoral consortium

There are many opportunities for doctoral students to participate in a doctoral consortium in the ed-tech research community, amongst others. A Doctoral consortium is usually organized by conferences where graduate students come together to present their work to experts in the field and peers, and get feedback from them. The expert panel might also offer advice on career and other skills. Some conferences also offer Young Researcher’s workshops/ Early Career Workshops which are useful for graduating students and young researchers in the field.

Having attended two doctoral consortium in different conferences, I would recommend PhD students to do it at some point of time.  I found it useful for a number of reasons, so in this post I’m going to list why I think so and how to prepare for a Doctoral consortium – some tips on making the best use of it.

Why participate?

  • Enhancing research skills: It’s a wonderful opportunity to put your thoughts together and think about the big picture of your research. It helps you identify the core ideas of your research and present them succinctly in a limited time. Explaining a potential 60,000 word thesis of your PhD in less than 30 minutes is a great skill to acquire. In some conferences, you might be asked to present a poster explaining your research as well. Also, it is a place where you can actually discuss more about your methodology and design, and not just the results.
  • Expert feedback: It is a great place to get some early feedback (and criticism) on your PhD work and thesis statement. It’s nice to have some extra eyes other than your phd supervisors. You become clear on what your claims can be and what your limitations are. You will be prepared to answer any question and know what to expect as possible questions next time when you present your work to different audiences. Even if you don’t get great advice at all times, you will most likely walk away with a better understanding of what you want to do. And if there’s a certain problem you’re grappling with in your research, you can ask for specific advice.
  • Networking: You meet other PhD Students from closely related fields. Not always do we get a chance to meet students from other universities around the world and know about their research. They are also sailing on the same boat, so it is always good to connect with your peers to get some support, and their feedback on your work. It is also a good opportunity to network with experts in the field and introduce your name in the research community. Who knows, the academic expert you impressed might be the person who gives you a job when you graduate 🙂
  • Financial Support: Most conferences provide some level of financial support for grad students who get accepted to the doctoral consortium. This is especially useful for self-financing students, as it covers registration fees or travel depending on the conference.

Based on my experience and the advice I’ve heard, here are some tips to make the best use of your time at the Doctoral Consortium:

  • Pick the right time to go – Best to go when you have conceptualized your research and done some work, so that you don’t go as an empty slate. The experts want to see what you have thought through so they can give you advice. Also don’t go too late (for example when you are almost submitting your thesis) by which time you can’t make any more changes to your research and thesis.
  • Make a proper submission – Most doctoral consortium require students to make formal submissions which include a short paper describing the research, supporting documents like a letter of support from the supervisor, and sometimes your own statement and CV. They usually look for sharp minds who can benefit from the discussion and contribute to the research community, so make sure you follow the mentioned format while submitting your application with well-written documents.
  • Practise and be ready to explain your research – You are usually provided a limited time to present (15-20 mins), and given that you are attempting to present your whole thesis in this time slot, practise well in advance to highlight the key aspects. Even better if you can present to your local peers and get their advice earlier. Sometimes, we tend to run through some ideas quickly without noticing that they need more emphasis or highlight less important aspects more, which your peers can notice for you.
  • Go prepared with your questions & answers: It is always nice to be prepared with questions to ask advice from experts. If there’s a particular problem you’re grappling with in your research, make sure you point that out and ask for suggestions. This helps you get focused attention on that problem rather than spend a lot of time on other minor things you are  not very interested in. If you want feedback from a specific expert, you can try mentioning that too. Be prepared to face tough questions and criticism on your research work (a good rehearsal before your phd defence). Also, if your peer’s work is previously made available, take some time to read about their research so you can contribute to the discussion and add value with your feedback.

LAK 2018 in Sydney

This post is on the exciting week of the Learning Analytics and Knowledge Conference LAK 2018, held in Sydney. LAK is a prestigious conference dedicated for sharing work in Learning Analytics across the globe. LAK coming down under was something we were looking forward to for quite some time. LAK is in fact the very first international conference I’ve ever attended (back in 2015), so it is always extra special 🙂

I started off with a Writing Analytics workshop, which we organized in Day 1 of LAK. We used a Jupyter notebook which runs Python code to demonstrate the application of text analysis for writing feedback and the pedagogic constructs behind designing such applications for learning analytics. Our aim was to bridge the gap between pedagogic contexts and the technical infrastructure (analytics) by crafting meaningful feedback for students on their writing, and to do so by developing writing analytics literacy. The participants were quite engaged in this hands on approach and we had good discussion on the implications of such Writing Analytics techniques.

The next day, I participated in the Doctoral Consortium, which is a whole day workshop where doctoral students present their work, discuss and receive feedback on their work from experts and other students. To know more about a Doctoral Consortium, read this. My doctoral consortium paper published in the companion proceedings is available here:

The new workshop for school practitioners was of interest to many educators working in K-12 learning analytics applications, and the Hackathon continues to be of wide interest. After the pre-conference events, the main conference officially started with the first keynote by Prof. David Williamson Shaffer on ‘The Importance of Meaning: Going Beyond Mixed Methods to Turn Big Data into Real Understanding’. David talked about how data is not scarce anymore, and to analyze such a sheer volume of data for learning, how we have to go beyond traditional quantitative and qualitative approaches. He gave examples of logical fallacies where statistics is likely to be misused while interpreting the concepts in learning, and introduced the notion of quantitative ethnography which can close the interpretive gap between the model and the data.

If you want to hear the full talk, all the keynotes are available along with the slides here: https://latte-analytics.sydney.edu.au/keynotes/ 

In general, there was great interest in the development of theories around designing dashboards, discussing how to and how not to develop dashboards for students.

Aligning learning analytics with learning design was increasingly emphasized. The demo paper which I presented that day exemplifying this in a Writing Analytics context is here (bonus pic with the supervisors):

The second day of the main conference (aptly on International women’s day) started with Prof. Christina Conati’s keynote on user adaptive visualizations, where she talked about adaptive interactions.

She showed how visualizations can be personalized for users by building user models based on eye tracking features.

Visualization in general was another key topic which gathered growing interest in the LAK community, along with other topics like Discourse analysis and Writing Analytics, many of them moving towards more near real-time applications.

I attended the SOLAR executive meeting for the first time to see what’s happening around SOLAR. It felt great to be part of a very welcoming community of researchers and practitioners. That’s where they announced this:

We also celebrated Women’s day:

It was quite an eventful day ending with the conference banquet in a Sydney harbour cruise.

The final keynote on the last day touched upon a number of criticisms around learning analytics and how we can progress the field further taking into account the key aims of learning analytics.

Multi modal learning analytics, MOOCS, Ethics and Policies, Theories, Self-regulated learning and Co-designing with stakeholders are other areas which continued to be discussed throughout the conference.

And then to wrap it up, happy hour!

To read all the interesting papers from LAK, follow this link.

For more tweets from the awesome LAK community, check #LAK18, #LAK2018, @lak2018syd

Note: Initially created as a private post for my own reference notes, this post was later made publicly available from 23 May 2018.

 

ICCE 2017 in New Zealand

Last month I attended the 25th International Conference on Computers in Education ICCE 2017 at Christchurch, New Zealand, organised by the Asia-Pacific Society for Computers in Education (APSCE). It was the first time I attended this conference, although I have heard of it previously when I was working in NIE, Singapore. Overall, it was a great experience, and I could see different sub-fields under ‘Computers in Education’ coming together. Being a slightly more extensive field than learning analytics, it helped widen my knowledge beyond my current expertise.

I found the keynote speeches and talks very exciting, and I was tweeting some of my key take-home messages with   tag. Personalized and adaptive learning, learner models and how we can empower learners with technology were some key topics discussed in the keynotes and invited talks:

Emerging technical solutions and capabilities shared in the paper and poster sessions, especially on Virtual Reality, Augmented Reality, Mobile and Sensor technologies were widening the horizon of technologies used in the field of education. New applications of gaming technology used for teaching in many levels of education were quite interesting. Combining multiple forms and modes of data (multimodal data) was another emerging topic in collaborative learning, personalized learning and language education.

The overarching theme of pedagogy and learning were emphasized and questioned along the way, when some talks were focussed more on technology than its appropriate usage in educational settings. I believe that this topic is widely discussed these days in many areas where technology is used for education: an emphasis to go back to the basic aim of improving education, working alongside teachers, with technology as only a helping factor.

In particular, we had fruitful discussions within the Learning Analytics (LA) community on testing the effectiveness of LA applications, providing actionable insights for learners and teachers, creating standards for LA and data ethics issues.

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I presented a full paper on the “Design and implementation of a pedagogic intervention using Writing Analytics”, where I shared work done with our colleagues at UTS Connected Intelligence Centre (UTS CIC) on exemplifying authentic classroom integration of learning analytics applications. It was well-received and provoked discussion on supporting students in their pedagogic contexts with the right kinds of feedback using analytics.

I also presented a doctoral consortium paper on “Combining automated and peer feedback for effective learning design in Writing practices” based on my main doctoral research idea, where we had discussions on how an embedded human component can add to automated analytic capabilities. I received the APSCE Merit Scholarship of USD500 to help me attend the conference, which is quite special as it is my first external scholarship/award during my PhD😊 I’m also thankful for the VC’s conference fund from UTS and the constant support from my lab UTS CIC at all levels (mentorship and financial support to attend conferences – I attended ALASI at Brisbane just the week before attending this one).

APSCE Merit scholarship_Shibani

 

In general, I could see a good mix of senior and young researchers from the Asia-Pacific region sharing their work enthusiastically and networking with peers from different communities of the broader educational research field. I caught up with some old friends and met some new interesting people too 😊 The hosts of the conference were amazing and everything was well-organized. We were given an introduction to the local culture with a lot of tidbits and entertainment along the way. I noticed a lot of photos being taken both by official photographers as well as the delegates to capture special moments (Is it just me who observed this? I’m super happy anyway to see those pics). The conference banquet dinner and the celebrations for the 25th anniversary of the conference need a special mention, as the past APSCE presidents were paid tribute. Also, watching the traditional Haka being performed during the banquet was a whole new experience. It was definitely a very well-organized conference, with every detail thought of and paid attention to; credits to the local organizing committee. Plus, New Zealand was so beautiful and I got to see some lovely places like these after the conference:

Lake Tekapo
Lake Tekapo

Mount Cook
Mount Cook, New Zealand