New publication: Untangling Critical Interaction with AI

I’ve had a longstanding interest in exploring how students engage critically with automated feedback and develop their AI literacy. In our LAK22 paper, we argued why it is so important that we develop these skills in learners. There is a heightened necessity in today’s educational landscape for learners in the age of generative AI (Gen AI) to engage with AI critically.

Our upcoming CHI publication investigates the fundamental question: Why do students engage with Gen AI for their writing tasks, and how can they navigate this interaction critically? In our paper, we define in concrete terms and stages how criticality can manifest when students write with ChatGPT support. We draw from theory and examples in empirical data (which are still unbelievably scarce in the literature) to understand and expand the notion of critical interaction with AI.

A pre-print version is available for download on Arxiv [PDF]. Full citation below:

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. Pre-print: https://arxiv.org/abs/2404.06955 

A short video presentation gives the gist of the paper [Follow along with the transcript]

Recognition for Teaching

[Originally posted on LinkedIn]

On Wednesday, I received the ‘2023 Learning and Teaching Citation’ from the Vice-Chancellor of the University of Technology Sydney (UTS) for nurturing well-rounded data science professionals. UTS citations and awards recognise significant and sustained contributions to student learning, student engagement, and the student experience by individuals or teams.



Earlier this week, I also received the ‘Impactful Educator Award‘ in the Partnerships Builder category that recognises educators who build collaboration with external stakeholders into their learning programmes and use elements of innovation to create a demonstrable impact on their students.

I feel deeply honoured and humbled to be recognised for my teaching initiatives and to share the stage with many esteemed educators who are making a positive impact on students. It holds a special place in my heart as a nod to a legacy that I once thought I would not follow. Growing up in a family of educators in India – including both my grandmothers, my mum, and several other relatives – I was taught from a young age how education can uplift individuals and societies. These values were deeply instilled in me, shaping my understanding and appreciation of education, which influenced my research direction. However, interestingly, teaching was never on the cards for me as I trained to be a computer engineer.

The journey from a computer engineer to an educator has been unexpected yet profoundly rewarding for me and comes as a testament to the unpredictable paths our passions can take us. My sincere thanks to colleagues at UTS TD School, mentors, family, and, most importantly, my students, whose enthusiasm and eagerness to learn inspire me. I value every little interaction I’ve had with my students over the last few years, and I hope to have touched some of their lives in a way. I learn from them as much as they learn from me!

The recognition motivates me to continue striving for excellence, innovation, and educational impact. Let’s keep pushing the boundaries of what is possible in education, for the betterment of our students and the future they will create. Thank you once again for this incredible honor. It is a milestone I will cherish deeply, reminding me of the journey so far and the exciting road ahead!

P.S: It was also a lovely memory to share with my family who joined me in the celebration at UTS, and an appreciation for my culture through my attire (a saree, traditionally worn by women in India) 🙂

New Research Publications in Learning Analytics

Three of my journal articles got published recently, two on learning analytics/ writing analytics implementations [Learning Analytics Special Issue in The Internet and Higher Education journal], and one on a text analysis method [Educational Technology Research and Development journal]. that I worked on earlier (many years ago in fact, which just got published!).

Article 1: Educator Perspectives on Learning Analytics in Classroom Practice

The first one is predominantly qualitative in nature, based on instructor interviews of their experiences in using Learning Analytics tools such as the automated Writing feedback tool AcaWriter. It provides a practical account of implementing learning analytics in authentic classroom practice from the voices of educators. Details below:

Abstract: Failing to understand the perspectives of educators, and the constraints under which they work, is a hallmark of many educational technology innovations’ failure to achieve usage in authentic contexts, and sustained adoption. Learning Analytics (LA) is no exception, and there are increasingly recognised policy and implementation challenges in higher education for educators to integrate LA into their teaching. This paper contributes a detailed analysis of interviews with educators who introduced an automated writing feedback tool in their classrooms (triangulated with student and tutor survey data), over the course of a three-year collaboration with researchers, spanning six semesters’ teaching. It explains educators’ motivations, implementation strategies, outcomes, and challenges when using LA in authentic practice. The paper foregrounds the views of educators to support cross-fertilization between LA research and practice, and discusses the importance of cultivating educators’ and students’ agency when introducing novel, student-facing LA tools.

Keywords: learning analytics; writing analytics; participatory research; design research; implementation; educator

Citation and article link: Antonette Shibani, Simon Knight and Simon Buckingham Shum (2020). Educator Perspectives on Learning Analytics in Classroom Practice [Author manuscript]. The Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2020.100730. [Publisher’s free download link valid until 8 May 2020].

Article 2: Implementing Learning Analytics for Learning Impact: Taking Tools to Task

The second one led by Simon Knight provides a broader framing for how we define impact in learning analytics. It defines a model addressing the key challenges in LA implementations based on our writing analytics example. Details below:

Abstract: Learning analytics has the potential to impact student learning, at scale. Embedded in that claim are a set of assumptions and tensions around the nature of scale, impact on student learning, and the scope of infrastructure encompassed by ‘learning analytics’ as a socio-technical field. Drawing on our design experience of developing learning analytics and inducting others into its use, we present a model that we have used to address five key challenges we have encountered. In developing this model, we recommend: A focus on impact on learning through augmentation of existing practice; the centrality of tasks in implementing learning analytics for impact on learning; the commensurate centrality of learning in evaluating learning analytics; inclusion of co-design approaches in implementing learning analytics across sites; and an attention to both social and technical infrastructure.

Keywords: learning analytics, implementation, educational technology, learning design

Citation and article link:  Simon Knight, Andrew Gibson and Antonette Shibani (2020). Implementing Learning Analytics for Learning Impact: Taking Tools to Task. The Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2020.100729.

Article 3: Identifying patterns in students’ scientific argumentation: content analysis through text mining using LDA

The third one led by Wanli Xing discusses the use of Latent Dirichlet Allocation, a text mining method to study argumentation patterns in student writing (in an unsupervised way). Details below:

Abstract: Constructing scientific arguments is an important practice for students because it helps them to make sense of data using scientific knowledge and within the conceptual and experimental boundaries of an investigation. In this study, we used a text mining method called Latent Dirichlet Allocation (LDA) to identify underlying patterns in students written scientific arguments about a complex scientific phenomenon called Albedo Effect. We further examined how identified patterns compare to existing frameworks related to explaining evidence to support claims and attributing sources of uncertainty. LDA was applied to electronically stored arguments written by 2472 students and concerning how decreases in sea ice affect global temperatures. The results indicated that each content topic identified in the explanations by the LDA— “data only,” “reasoning only,” “data and reasoning combined,” “wrong reasoning types,” and “restatement of the claim”—could be interpreted using the claim–evidence–reasoning framework. Similarly, each topic identified in the students’ uncertainty attributions— “self-evaluations,” “personal sources related to knowledge and experience,” and “scientific sources related to reasoning and data”—could be interpreted using the taxonomy of uncertainty attribution. These results indicate that LDA can serve as a tool for content analysis that can discover semantic patterns in students’ scientific argumentation in particular science domains and facilitate teachers’ providing help to students.

Keywords: text mining, latent dirichlet allocation, educational data mining, scientific argumentation

Citation and article link:  Wanli Xing, Hee-Sun Lee and Antonette Shibani (2020). Identifying patterns in students’ scientific argumentation: content analysis through text mining using Latent Dirichlet Allocation. Educational Technology Research and Development. https://doi.org/10.1007/s11423-020-09761-w.

2019 Year in review

Welcome 2020! A new year is the perfect time to reflect on the past year, so I wanted to take a step back and think about it. 2019 was one of the most successful years for me professionally (and personally) with a range of experiences and productive outcomes. Quite a few achievements I’m really proud of happened this year. This post is mostly a note for myself to remind me of all those 🙂

I started the year on a positive note – I allocated quality time for me to do some coding for a novel graph analysis method I developed for writing analytics. Recovering from my laptop loss from the previous year (noting how important backing up your work is), I redid it from scratch, and made a version better than what I had last time. Coding up those interactive automated revision graphs was probably the first successful outcome in the year for me.

My biggest achievement this year was completing my PhD from the Connected Intelligence Centre. Even at the start of the year, I hadn’t started writing my thesis and I was still finishing up data analysis. Even when I started writing my thesis in February, I was unsure if I could complete it before the August deadline. The main chapter seemed like a monster job since most of the analysis had to be done newly and I hadn’t written it up before. The best decision I made at that point was to start off with this hard chapter instead of the starting or the easier ones, where I had already written stuff (like a lit review or an introduction). A pat on the back – I stuck with the deadline of completing it before I flew out to LAK19 in March- it was quite intense, both emotionally and physically taxing, but I made it! I emailed the first version of this chapter with an overall skeleton of the thesis to my supervisors when I was on a bus home – I was literally making use of every minute I had before flying out to the conference.

My participation in LAK19 was quite a success. I’ve written a whole post on it before, so I’m not gonna dive into details. But I presented a full paper and got some amazing comments, facilitated a workshop (almost solo since my co-organizers couldn’t make it at the last minute) and joined the SoLAR executive committee. I had received the ACM-Women in Computing Scholarship to attend this conference.

While I was writing the rest of my thesis, I applied for a Lectureship at UTS Faculty of Transdisciplinary Innovation and got it! I decided to go for this one over postdoctoral research positions to stay long term in academia. Searching and applying for jobs are such an ordeal and my skills were dusty; I’m super glad mine went smoothly since it was the only job I applied for, and the timing worked out perfectly.

I had to start the lectureship in July, which pushed my thesis submission deadline a month earlier. I couldn’t take a break after thesis submission, so I took a small break after sending out the full draft of my thesis to my internal reviewers in June. I went home to India for 2 weeks, which just flew by. I worked super hard to submit the final thesis after my return, to the point where I didn’t really want to take another look at it anymore! Finally, I submitted my thesis on the 25th of July, 2019.

I started lecturing right from the first month of me joining the Faculty of Transdisciplinary Innovation. It was pretty hard, truth be told, as I was trying to juggle between a few different things. First time teaching a subject from preparation to delivery, handling student queries, the admin, the mentoring, managing difficult students – it was a handful. I even dropped my plans to take part in the 3MT competition coz my schedule was so tight.

In the meantime, the reviews for my thesis came back. I passed with flying colours and the reviews were extremely positive, with appreciation of it being one of the best theses the reviewers had reviewed! Both reviewers accepted the thesis for publication without any changes. I did make some minor changes for final publication based on their comments and my degree was conferred on the 12th of November 2019.

I also got a few invitations (both internal and external to my university) to take part in events, which went really great. I was invited as a panel speaker at Intel, Sydney where we discussed ‘Artificial Intelligence Today for Our Tomorrow‘ with some great minds. I co-organised a workshop with our Faculty staff on Data in September for the Festival of Learning Design. I gave a short talk at UTS TeachMeet “The Future Starts Now“ in October,  hosted by the School of International Studies and Education, UTS – Video of Highlights here. I visited the Centre for Research in Assessment and Digital Learning (CRADLE) at Deakin University, Melbourne in October to participate as an invited delegate at the “Advancing research in student feedback literacy” international symposium – had good conversations and set plans to move the research forward in our upcoming work.

I received the Future Women Leaders Conference Award and visited Monash for two days in November for the conference, where there were a series of workshops and talks supporting future women leaders in academia from engineering and IT. I also created from scratch and published a podcast (Episode 3 of SoLAR Spotlight) that month – lots of learning happened in putting it together, from preparation to editing. I do have regrets in turning down some good opportunities that came my way, just because I was not having enough hours in a day to manage everything. But I guess it is a part of growing as an academic, since you prioritize and decide what is more important, and try to achieve work-life balance. In the end of November, I co-organized a workshop at ALASI. That was the end of work-related events in 2019, but the best was yet to come.

I went to India in December for my long-awaited wedding with my sweetheart. It was a big fat south Indian wedding, so lots of prep and stress, but loads of fun! Here’s a picture from the wedding 🙂

LAK 2019 in Tempe, Arizona

I attended the Learning Analytics and Knowledge Conference LAK this year in the midst of my tight thesis writing schedule, and did not regret it 🙂 This 9th International LAK (4-8 Mar, 2019) was held in Tempe, Arizona which meant a flight travel of 15 hours + transit from Sydney one way; I survived, thankfully.

First of all, I was excited to have been awarded a scholarship from ACM-W that supports Women in Computing for conference travel. And super excited to have received it for LAK which competes with journals in publishing some of the most influential work in educational technology.

I kicked off LAK2019 with the full day Writing Analytics workshop I chaired on Advances in Writing Analytics: Mapping the state of the field. While the other workshop organizers could not make it that day which was unfortunate, I’m thankful for the support from UTS CIC colleagues and the participants for helping to run a successful workshop. This fourth workshop in the series of Writing Analytics workshops in LAK had great participation and discussions. We saw interesting presentations on writing analytics from various speakers, and tried a demo version of AcaWriter to see the tool in action – check out tweets with #WaLAK19 and #LAK19. We brainstormed utopian and dystopian visions of how writing analytics in 2030 would look like, and discussed ways to get to a desirable future from where we are now. The potential formation of a Special Interest Group on Writing Analytics (SIGWA) was discussed to facilitate a community of researchers in the area. Notes from the workshop are shared here.

In the main conference, I presented our full research paper, co-authored by Dr. Simon Knight and Prof. Simon Buckingham Shum on Contextualizable Learning Analytics Design: A Generic Model and Writing Analytics Evaluations. We emphasized the need for flexible Learning Analytics Applications that can provide contextualized support, and demonstrated the CLAD model with our example.

I recommend watching the key note recordings from LAK’19, which are added in the SOLAR youtube channel. I would have loved to go into more detail to highlight some of the interesting work across LAK, but my notes for this conference are shorter than my usual notes since I’m now back to thesis writing and frantically managing time 😂. I did come across exciting work and meet lots of interesting people, most of whom I followed-up (I think!), so hope there would be new collaborations! I also officially joined the Society of Learning Analytics (SOLAR) executive committee as the elected student member. Thrilled and looking forward to serving on the committee!


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!

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.

 

The changing face of learning and how to adapt to it

This post is based on my notes from Prof. Roger Säljö‘s talk at a Sydney Ideas event, hosted by the University of Sydney. I was undecided at first about attending this talk since it was held on a Valentine’s day evening, but I’m really glad I did 🙂 In his intriguing talk, Prof. Roger shared how the nature of knowledge and learning have changed in our current digital societies compared to previous traditional forms, and how educators should respond to it.

We’ve almost always been finding ways to preserve and communicate knowledge, from scripts and stone age symbols to modern digital libraries. That’s how we learn, grow and improve the society we live in. The Game of Thrones quote about its library town ‘Citadel’ is something I could immediately relate to:

Source: https://scatteredquotes.com/without-us-men-little-better-dogs/

While all societies need to reproduce knowledge for the next generations (like how its been done for ages), the conditions for reproducing the cultural memory is quite different in modern, digital societies. The size and complexity of such knowledge have grown tremendously in modern societies due to technology, which is why it is important to prioritize the skills and knowledge for learning. What is of value for students to learn in the new digital world and what skills they need should be considered. There could be two strategies for thinking about this:

  1. We can preserve what has been done (back-to-basics movement in education)
  2. Or we can think about what might be productive for the future

I’m more inclined towards working for a productive future, considering the new changes (by preserving the traditional elements that are essential, of course).

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The changing face:

So what has actually changed over the years? Why should we think through these for education NOW? Education has been evolving all the time: from scribal schools over 5000 years ago meant for systematic training of the human mind, to the still relevant act of ‘studying’ which was once a social revolution.  Symbolic technologies are well developed to share a common understanding with all people of the world. In particular, Writing is a literacy that’s probably not dying anytime soon, although its forms may have changed. Text is still the main source of knowledge and is used everyday in many forms including emails, messages, and social media posts. The concepts of schooling have remained stable, although its focus on reproduction (not creativity) and individual as a source of knowledge are changing in recent times.

However, the biggest changes to our society are brought by technology, which has digitized the world. In addition to the growing amount of knowledge in the form of digital data, the conditions of learning have also changed tremendously. A lot of cognitive functions have been externalized and cognitive habits transformed. For instance, we make use of computer software to perform spelling/grammar checks in our everyday writing and even for simple arithmetic calculations (we should probably try to do mental calculations once in a while so that we don’t always need a calculator for 451 * 23). We are dependent on apps for cognitive tasks like remembering and problem solving. Children are starting to learn writing by typing using keyboards, and are moving from passive media consumption to active forms of interaction. We are able to master complex tasks, without understanding the basic steps involved.  There are statistical packages for use today which can help us come up with solutions for highly complex tasks with few lines of code without understanding the sequential steps it involves. Advanced technologies act as a black-box, which cannot be unpacked for education in the classroom: one example from my research context is a machine learning scoring algorithm that doesn’t disclose the features used for calculating these scores of students in a writing task.

Technological changes have made minds hybrid with thinking detours and collaboration with artifacts, which no longer nurture a concentrated mind. The way we look for information has also changed completely with search engines. Google has become our go-to place to seek any information we want, and is available for anyone. There is increased internet use in young children, even on their own. This places huge emphasis on coming up with strategies like restrictions and parental guidance for responsible internet usage by children, and opens a whole new dimension of security. We cannot control the learning trajectory of children from 2 years to 11 years as before, since we don’t know what they learn externally out of class (indirect curriculum). Schools can have no control on external tools and knowledge as it is hard to restrict access to computers at home. One can just hope that such external knowledge children gain is for the good, and guide them to distinguish it from other non desirable content on the internet.

Because the future is digital and there’s no coming back, our duty is to adapt to it the best we can. For this, Prof. Roger emphasizes that the metaphors of learning should shift to respond to the changing environment. Learning should be more performative (rather than reproductive) and focus on learning as design. Learners should be encouraged to participate in and contribute to communities and collective practices, and no longer consider knowledge as an individual asset. With the human mind, interactions with symbolic technologies and communications with people should be relational. Technologies and artificial intelligence should be used with care in education, keeping in mind that “Education is not production, it is not a smoothly running machine”. For young teachers to cope with the advances, they have to learn how to marry the resources to the ambitions of the school, while understanding that technology changes the nature of education, but does not solve the problem. The education system will also have to change assessments to assess the skills that matter the most in the future. While the advances have a role to play in improving learning (E.g. virtual environments where students can experience near reality complex environments), they should also have co-ordination with the teacher to get user perspectives. And for people to accept it more broadly, there should be steps taken to ensure digital literacy. Further, the knowledge, value and skills of an individual should be connected to what technology has to offer. Such design of transparent technology to respond to the natural repertoire of uses will be more relevant for education in the future.

To learn more about Prof. Roger’s work, visit: www.lincs.gu.se

 

 

 

 

 

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

Hello again!

After a long inactive period of about two years, I’m finally bringing my blog back to life. Yayy!!!
I will be blogging on topics related to learning analytics, text and writing analytics, learning technologies, educational research and probably more general research topics that are useful for fellow PhD students.

Note: I’ve tried to import my previous blog on the Dalmooc course, but there are a few errors in importing the pictures. You can still view the original posts at http://shibanila.blogspot.com.au/

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