World-Leading PhD Scholarship: Personalised, Adaptive, Language-based Planner for next generation Robotics

A fully-funded PhD scholarship in Computer Science is available for a strong and motivated student wishing to work at the intersection of vision, large-language models, and robotic planning. This prestigious PhD scholarship is awarded by St Leonard’s Postgraduate College at the University of St Andrews and will be supervised by Dr Juan Ye, Dr Alice Toniolo, and Dr Kasim Terzic.

For more information, including how to apply, please see the advert: https://www.st-andrews.ac.uk/study/fees-and-funding/scholarships/scholarships-catalogue/postgraduate-scholarships/world-leading-scholarship-01-computer-science/?

Workshop on Using Video in CS Education

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

Event details

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

SICSA Workshop on Learning Analytics in Education

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/

Event details

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