National University of Singapore

Professor Aaron Quigley has been appointed a Visiting Senior Research Fellow in the Smart Systems Institute in the National University of Singapore. As part of his next sabbatical Aaron will spend 6 months in the Creating Unique Technology for Everyone (CUTE) centre in Singapore [Video]. He will be collaborating with researchers there on next generation interfaces, discreet computing and new forms of interaction. The research and lessons learnt will help advance the field of HCI and will be incorporated in future teaching and research here in St Andrews.

Science and Innovation mission to Japan

Sue Kinoshita, Minister Counsellor economic affairs and Professor Quigley

This week Professor Quigley joined a mission to Japan with other academics from the University of Oxford, Edinburgh, UCL and Manchester. The week long event was organised by the UK’s Science and Innovation team in Japan, part of the Foreign and Commonwealth Office. Over five days the delegation visited and presented at seven companies along with three seminars and workshops. Across nine presentations Professor Quigley presented to hundreds of people and introduced some of the Human Computer Interaction research in SACHI, along with research from the AI research group. This mission has the goal to strengthen research collaboration and innovation partnership between the UK and Japan.

During his talks, Aaron provided examples from our engineering doctorate program, our MSc program, work on research interns, PhD students and academics from across Computer Science.

 

Sethu Vijayakumar, Edinburgh University, Sue Kinoshita, Minister Counsellor economic affairs, Professor Aaron Quigley, Seiichi Asano, Senior science Officer and Joesph Robertson, Science & Innovation Officer.

Griff Jones, First Secretary, science innovation & global challenges, Sethu Vijayakumar, Edinburgh University, Sue Kinoshita, Minister Counsellor economic affairs, Professor Aaron Quigley, Seiichi Asano, Senior science Officer and Joesph Robertson, Science & Innovation Officer.

Global Human Computer Interaction at World Usability Day Estonia

Professor Quigley will be a distinguished speaker at the World Usability Day in Tallinn, Estonia this November as part of the ACM DSP. Aaron was appointed to the Distinguished Speaker Program (DSP) of the Association for Computing Machinery (ACM) earlier this year. The DSP brings together international thought leaders from academia, industry, and government.

In Estonia, Aaron will present a talk on Global Human Computer Interaction. This is the study of HCI when considering global challenges, languages, concerns, cultures and different economic drivers. This talk explores new technologies and the next generation of interfaces beyond the desktop, in a global context. The World Usability Day was founded by the User Experience Professionals Association (UXPA) and the theme for 2018 is “Design for Good or Evil”. It brings together UX professionals and the topics range from usability to user experience, and innovative technologies to studies in human computer interaction.

The next big thing or the next big gimmick?

Dr Tom Kelsey will be holding a panel discussion at Computing’s first ever Artificial Intelligence and Machine Learning Live conference on Monday 19th November in London. Through a variety of expert key-notes, end-user case studies, and panel discussions the conference will highlight key developments within AI.

Tom’s panel discussion: The next big thing or the next big gimmick?

Read more about the conference and programme of events at http://events.computing.co.uk/computingai/programme

Fable-based Learning: Seminar by Prof Jimmy Lee

Event details

  • When: 21st August 2018 13:30 - 14:30
  • Where: Cole 1.33b
  • Format: Seminar

CUHK + UniMelb = Fable-based Learning + A Tale of Two Cities

Prof Jimmy Lee, Chinese University of Hong Kong

This talk reports on the pedagogical innovation and experience of a joint venture by The Chinese University of Hong Kong (CUHK) and the University of Melbourne (UniMelb) in the development of MOOCs on the computer science subject of “Modeling and Solving Discrete Optimization Problems”.  In a nutshell, the MOOCs feature the Fable-based Learning approach, which is a form of problem-based learning encapsulated in a coherent story plot.  Each video lecture begins with an animation that tells a story based on the Chinese classic “Romance of the Three Kingdoms”, in which the protagonists in the novel encounter a problem requiring technical assistance from the two professors from modern time via a magical tablet bestowed upon them by a fairy god.  The new pedagogy aims at increasing learners’ motivation as well as situating the learners in a coherent learning context.  In addition to scriptwriting, animation production and situating the teaching materials in the story plot, another challenge of the project is the remote distance and potential cultural gap between the two institutions as well as the need to produce all teaching materials in both (Mandarin) Chinese and English to cater for different geographical learning needs.  The MOOCs have been running recurrently on Coursera since 2017.  Some learner statistics and feedbacks will be presented.  The experience and preliminary observations of adopting the online materials in a Flipped Classroom setting at CUHK will also be detailed.

This video at Youtube shows the trailer for the Coursera Course:

Biography:

Jimmy Lee has been on the faculty of The Chinese University of Hong Kong since 1992, where he is currently the Assistant Dean (Education) in the Faculty of Engineering and a Professor in the Department of Computer Science and Engineering.  His major research focuses on constraint satisfaction and optimization with applications in discrete optimization, but he is also involved in investigating ways of improving students’ learning experience via proper use of technologies.  Jimmy is a two-time recipient (2004 and 2015) of the Vice-Chancellor’s Exemplary Teaching Award and most recently the recipient of the University Education Award (2017) at CUHK.

Seminar: SMT, Planning and Snowmen

Event details

  • When: 6th August 2018 11:00 - 12:00
  • Where: Cole 1.33a
  • Series: AI Seminar Series
  • Format: Seminar

Professor Mateu Villaret, from Universitat de Girona is a visiting scholar with the AI group from July 1st until September 30th. Professor Villaret works on algorithms for routing and scheduling with the AI group at St Andrews.

As well as solving practical problems, he also enjoys puzzle games. That is the basis of this talk, about using Planning and SMT to solve the “Snowman” puzzle.

Workshop on Using Video in CS Education

Event details

  • When: 7th August 2018 10:00 - 16:00
  • Where: Gateway Bldg
  • Format: Workshop

The Higher Education Research Group is happy to announce the workshop on using video on Computer Science education on Aug 7th 2018.

Goals

Participants of this full-day workshop will look at the role of video in education in general, and specifically:

* Discussing opportunities and challenges that are specific for use of video in teaching and learning

* Connecting practitioners to share contextual experiences in using video in education

* Discussing curriculum design implications to include the use of technology

* Generating a collection of good practice “tips” and lessons learned for the benefit of those willing to start using video in learning, assessment and feedback, and seek to disseminate them afterwards in a practitioners’ focused publication, e.g. http://collections.plos.org/ten-simple-rules

* Reconciling practice-based with theoretical approaches to construct a vision of the current state-of-the-art learning technologies to then identifying future challenges.

Format

We are very happy to announce that the Director of Computational Foundry at Swansea University, Alan Dix, will give the keynote. He has worked in human–computer interaction research since the mid 1980s, is the author of one of the major international textbooks on Human-Computer Interaction and author of approximately 500 research publications covering topics from formal methods to creativity. In 2013 he produced an HCI MOOC that is now hosted at InteractionDesign.org and the materials reused for flip class teaching. In the same year he walked 1000 miles round the coast of Wales; the outcomes of which have included a case study of the educational use of the data gathered during the walk in the Open Knowledge Foundation book on “Open Data as Open Educational Resources”. The talk will include the use of fine-grained learning analytics of video and related educational resources.

In addition to the invited talk, the workshop will consist of a set of presentations followed by a world-café activity, producing practical tips in using video in education with a focus on assessment and feedback.

Background

Although video has historically played an important part on teaching and learning, only recently video-making and editing technologies have become accessible in an unprecedented way, allowing students to become proficient video “prosumers” (producers and consumers). Further, there are numerous educational gains to be had through these technologies. This interactive workshop explores how can video be used in practice to leverage skills and foster creativity whilst facilitating knowledge acquisition.

Target Audience

The workshop will involve 24 participants, who have experience or an interest in using video in education. While the central topic is video for assessment, we hope to also appeal to practitioners using video in a wider sense (e.g. in lecture capture, MOOCs, video feedback).

In order to register, contact Adriana at agw5@st-andrews.ac.uk, or visit the Eventbrite page:

https://www.eventbrite.com/e/workshop-on-using-video-in-computer-science-education-tickets-48131928895

SICSA Workshop on Learning Analytics in Education

Event details

  • When: 6th August 2018 09:30 - 15:30
  • Where: Gateway Bldg
  • Format: Workshop

The Higher Education Research Group is happy to announce the SICSA-sponsored workshop on learning analytics on Aug 6th 2018.

Goals

The purpose of this SICSA-sponsored workshop is to encourage an evidence-based approach to teaching by leveraging quantitative and qualitative data available to CS schools. Most importantly, we plan to organise a multi-institution study on using machine learning and AI-based techniques on existing data to improve learning outcomes across multiple universities. The workshop will serve to formulate the goals of such a study and forge the necessary collaborations to make this happen.

Format

We are very happy to announce that the chief regulatory adviser at Jisc Technologies Andrew Cormack will give an invited talk about the legal and ethical framework for learning analytics. In addition to the invited talk, the workshop will consist of a set of breakout sessions and a final discussion dedicated to preparing a follow-up study. The breakout sessions will involve discussions about existing quantitative and qualitative data available to educators, how these data influence teaching, what (statistical and other) data procesisng is useful for driving decisions, and which algorithmic approaches could be applied across institutions.

Background

Evidence-based teaching is of particular importance in fast-moving fields like Computer Science, and is therefore of interest to many higher education institutions. We have more data on students and courses than ever before including grades, entry requirements, qualitative and quantitative feedback, and career paths after leaving the university, and as computer scientists we are well equipped to process such data. It is important to measure the positive and negative impact of changes to the delivery (e.g. lecture capture, different lecturers) and content (slides, supporting material, organisation) in order to maintain and hopefully improve learning outcomes over time.

However, measuring how teaching approaches affect learning outcomes can be challenging because of issues such as data protection, small numbers of students, changes in the curriculum, or changes in admission procedures. Measuring differences between institutions is even harder because of differences in course structure, class sizes and marking scales. We believe that computer science techniques such as data mining, machine learning and artificial intelligence will become increasingly important in this field, and would like to set up an ambitious study across several universities based on the findings of this workshop. Such a study is only possible if coordinated well across institutions and this workshop aims to provide the basis for such collaboration.

Target Audience

The workshop will involve 24 academics, mainly from SICSA-affiliated institutions, aiming to foster an exchange of ideas and best practice. While the central topic is CS education, we hope to also appeal to CS academics engaged in data ethics, machine learning, and artificial intelligence (e.g. for processing data in natural text form) because the topic provides an important application of CS, and has great potential for impact.

To register, contact Kasim at kt54@st-andrews.ac.uk, or go to the Eventbrite page:

http://learning-analytics-workshop.eventbrite.com/

Seminar: AI-augmented algorithms — how I learned to stop worrying and love choice

The speaker is Lars Kotthoff, previously a PhD student here, now and Assistant Professor at the University of Wyoming. All welcome.

 

Often, there is more than one way to solve a problem. It could be a different
parameter setting, a different piece of software, or an entirely different
approach. Choosing the best way is usually a difficult task, even for experts.
AI and machine learning allow to leverage performance differences of
algorithms (for a wide definition of “algorithm”) on different problems and
choose the best algorithm for a given problem automatically. In AI itself,
these techniques have redefined the state of the art in several areas and led
to innovative approaches to solving challenging problems.

In this talk, I will give examples of how AI can help to solve challenging
computational problems, what techniques have been applied, and how you can do
the same. I will argue that AI has fundamental implications for software
development, engineering, and computer science in general — stop making
decisions when coding, having more algorithmic choices is better!