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How to support students’ skills for giving constructive feedback, especially when it is difficult to hear

Being able to deliver feedback to peers is a key management skill and something engineering students report finding difficult, due to the relational and emotional implications. This experiential activity provides students with emotional management strategies and a first, low-stakes opportunity to apply them when both giving feedback and responding to feedback received. This workshop is designed to target the development of the following skills:

• Formulating feedback to be “heard” by others by attending to their emotional response.
• Managing your emotions when receiving and responding to feedback.

There will be refreshments at 9am and 10.30am, followed by another workshop on Supporting students to develop coaching and peer teaching skills and a sandwich lunch at 12pm.

About the trainer

Joelyn de Lima is a scientist & pedagogical advisor at the Ecole Polytechnique Fédérale de Lausanne (EPFL). Trained in the biological sciences, she transitioned to being a discipline-based education researcher. Currently her research and practice are focused on enhancing the higher educational experience for students. Her background has given her a unique blend of perspectives – in terms of culture (She has lived, worked, and taught on 3 continents), theoretical grounding (natural sciences and education), and practice (research & teaching, formal & informal education).

7 Characteristics of Resilient People: Bitesize

Learning and Development bitesize resources are short and high impact; including videos, quick tips guides and interactive bitesize modules. Develop your skills and knowledge quickly, easily, when you need. They complement face to face events and more in-depth online modules.

An introduction to the 8 Wastes (Lean methodology), and how to spot hidden waste in your own processes.

https://youtu.be/Jp5gIwr9xAU

These e-learning modules are available via the InforMEA e-learning platform. Information and guidance on ABS and Nagoya Protocol webpage is available on the University website.

Introduction to Access and Benefit Sharing(ABS)
This course provides an introduction to access and benefit-sharing of genetic resource that originate from overseas.
Sign up on the InforeMEA platform. Further details about the syllabus information are available here.

Introductory Course to the Nagoya Protocol
This course provides an introduction to the major components of the Nagoya Protocol.
Please see the syllabus for further details and sign up on the InforeMEA platform.

If you wish, you can take a quiz at the end of the both courses to assess your learning progress. You are required to answer at least 80% of the assessment questions correctly in order to obtain a course certificate.

Research ethics and research integrity are serious issues. All researchers should consider the ethical context of the research being carried out and be able to justify decisions to the wider academic community.

This session aims to help you get think about the ethical considerations of your research by introducing you to the Department of Engineering ethical review process and investigating some case study scenarios.

This workshop is aimed at breaking the stereotype of an academic essay as a purely scholastic and tedious endeavour, devoid of such assumingly ‘literary’, elements as plot, narrative, denouement, metaphor, hyperbole, sound and rhythm, etc. My own experience shows that most of the guidelines, principles, and attitudes generally associated with the popular literary genre of ‘creative non-fiction’, can be successfully applied to academic writing at its best. This centres on mastering the essential ‘Five Cs’: Clarity, Coherence, Continuity, Concision and Cadence.

This training is provided free of charge to postgraduate researchers, however, the cost of providing the course is £30 per participant.

For Academic Writing Month, academic writers in all disciplines and at any stage of their writing journey are welcome to join us for two hands-on writing workshops being held at the University Library. This session is part workshop in which we discuss academic writing and try out some new techniques, part practical group writing session.

Here's a taste of what to expect at these special events:

• Guidance and advice from experienced academic writers, as they address some common myths and misconceptions about academic writing.
• Tips for staying motivated, tackling large writing projects, and overcoming writer's block.
• Liberate your writing practice by trying out some creative writing exercises.
• Put what you have learned into practice with an hour's group writing time in for the 'Write Here, Write Now' section of the workshop.

This course will show you basic principles and processes for creating accessible documents in Microsoft Word and PowerPoint and PDFs.

• This is the Live Online version of the In Person Face to Face course.

Please Note: It is important that when you book on this course, on your booking confirmation page, click on Add to Calendar to start the process to import the course appointment into your calendar. This contains the link to the MS Teams course meeting under Joining Instructions that you will use to join on the day of the course.

• See Related Courses below to take your skills further

This course will provide a detailed critique of the methods and philosophy of the Null Hypothesis Significance Testing (NHST) approach to statistics which is currently dominant in social and biomedical science. We will contrast NHST with alternatives, especially with Bayesian methods. We will use computer code to demonstrate some issues. However, we will focus on the big picture rather on the implementation of specific procedures.

This development programme for generalist and specialist administrators draws on the expertise of senior figures in the University and provides up to date information on the various strands and issues of University strategy and governance. It includes development of some key skills and a project activity, and offers a valuable opportunity to network with administrators from the UAS and other departments and institutions.

• You need to meet the selection criteria for the programme and complete an application form for the programme.
• Applications will require approval by your line manager and will then be reviewed and prioritised by School Secretary, Head of Division and Head of Institution, Registrary as appropriate.
• Please see further information about key themes and speakers on the programme brochure.
• Applications typically open in May each year.

As a science researcher, you will need to deal with quite heterogeneous and dirty data. The data may have been collected through different approaches: observation, surveys, interviews, experiments, published printed or online sources, etc. Moreover, the data may have been encoded by different software and persons, and comes to you in different formats (e.g., txt, csv, xlsx, json, etc). Therefore, the data typically needs to be preprocessed before you can make sense of it through statistics and graphical representations. For example, you may need to re-encode the information in a way that is more meaningful to your analysis goals. Also, you may need to re-arrange the data and clean it, removing duplicates and incomplete information. Finally, you may need to apply all these transformations to other similarly structured data, over and over again. Doing this “by hand” is an arduous, time-consuming and error-prone task; so, automatizing these routines is the smart way to go!

In this course, I will teach you how to read, transform and prepare different kinds of data using Python and its popular libraries NumPy and Pandas. We are going to solve several problems (“Missions”) together, of increasing levels of difficulty. Each Mission will introduce you to new data structures (e.g., dictionaries, series, dataframes), methods and attributes, extending your previous knowledge. The content of the course is designed to be to-the-point and focused on practicality. By the end of the course, you should be able to program preprocessing routines that you can apply to your own data. Moreover, you will have an advanced data-handling blueprint to which you can easily add new information and skills over time.

The data we obtain from survey and experimental platforms (for behavioural science) can be very messy and not ready for analysis. For social science researchers, survey data are the most common type of data to deal with. But typically the data are not obtained in a format that permits statistical analyses without first conducting considerable time re-formatting, re-arranging, manipulating columns and rows, de-bugging, re-coding, and linking datasets. In this module students will be introduced to common techniques and tools for preparing and cleaning data ready for analysis to proceed. The module consists of four lab exercises where students make use of real life, large-scale, datasets to obtain practical experience of generating codes and debugging.

Have you received or collected your data (or anticipate doing so!), but are not sure what to do next? This course is designed to equip you with the skills you need to efficiently clean, reformat, and prepare your datasets using Stata. Ideal for social science researchers and analysts who want to use quantitative data for their dissertation or other research project and want to prepare their data efficiently and follow best practices.

Over four interactive sessions, you will master essential techniques for handling missing data, merging and appending datasets, batch processing, and recoding variables. Each session combines concise, focused lectures with practical, hands-on exercises using either your own data or datasets provided by the instructor.

Have you thought about using AI in your research but aren’t sure how to get started? Or are you already using AI and have run into challenges with implementation? Meet the Accelerate Programme's team of AI experts to find the support you need.

The Accelerate Programme's AI clinic is designed to help with challenging software issues a scientist encounters in all phases of the research pipeline when utilising machine learning. This includes issues related to: data collection, implementing privacy and compliance controls, data pipelines, model implementation, hardware/GPU matters, deploying models on the cloud, and packaging & publishing models.

We define a challenging software issue as one that is difficult to find online guidance/tutorials on, or basically one that you have attempted to resolve via multiple approaches but had no success in doing so.

No matter your level of experience with AI, we invite you to book a session and talk to our team to see how we can support you to implement AI in your research.

The clinic is open at any time for support so if you want to get in touch before your session or to book an earlier time, please email accelerate-mle@cst.cam.ac.uk.

An online open meeting for University staff which will focus on key themes from the Vice-Chancellor's 1 October Annual Address, including the University’s People Strategy, Financial Strategy and innovation agenda.

Chair: James Helm, Executive Director of Communications and External Affairs

Panellists

• Professor Deborah Prentice, Vice-Chancellor
• Professor Kamal Munir, Pro-Vice-Chancellor for University Community and Engagement
• Professor Anna Philpott, from 1 October 2024, Pro-Vice-Chancellor for Resources and Operations
• Dr Diarmuid O’Brien, Pro-Vice-Chancellor for Innovation
• Andrea Hudson, Director of HR
• Anthony Odgers, Chief Financial Officer

Questions

You can submit a question for the panel in advance by sending an email to internalcomms@admin.cam.ac.uk. Alternatively, you can ask a question on the day using the Teams Q&A function.

The fundamental-level course is intended for individuals who seek an overall understanding of the AWS Cloud, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS services, security, architecture, pricing, and support. This course also helps you prepare for the AWS Certified Cloud Practitioner exam.

This is a free course, register and sign in for the following dates:

19th July 2021
2nd August 2021
16th August 2021
2nd September 2021
13th September 2021

This free training day hosted by Amazon Web Services (AWS) is a hybrid event, with a choice of attending online using Chime in a web browser, or there are 28 places available to attend at Amazon's offices next to Cambridge railway station.

Please confirm your choice of venue by the end of Wednesday (tomorrow) with one final survey:

AWS Immersion Day: confirm your choice of venue

Are you interested in machine learning, but not sure where to start? Join us for this session with an AWS expert and demystify the basics. Using real-world examples, you’ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can start unlocking new insights and value for your business using machine learning.

This is a free course, register and sign in for the following dates:

22nd July 2021
30th September 2021

In this introductory course, you will learn about AWS products, services, and common solutions. You will learn the fundamentals of identifying AWS services so that you can make informed decisions about IT solutions based on your business requirements.

This is a free course, register and sign in for the following dates:

26th July 2021
9th August 2021
23rd August 2021
6th September 2021

Learn about AWS's strategy and best practices for performing large-scale migrations. Synthesized from AWS's experience of helping hundreds of enterprise customers move to the cloud, you will learn proven techniques that make migrations successful and tools that will accelerate your migration journey to the AWS Cloud.

This is a free course, register and sign in for the following dates:

30th July 2021
23rd September 2021

This short session will provide an understanding of the principles, tools and techniques involved in Process Analysis with a view to improving business process effectiveness and efficiency. Delegates will have the opportunity to practice using the techniques that they learn via exercises designed to be enjoyable and thought provoking.

The Critical Reading course aims to improve students' ability to read critically and evaluate sources, as well as giving helpful tips about productive reading, note taking and providing a checklist of questions to help them with their reading going forward. It is suitable for all students but aimed mostly at undergraduates.

With the increase in AI-generated imagery using models such as Dall-E, Midjourney and Sora and research applications such as AlphaFold, there has been a surge in workflows incorporating models like Stable Diffusion. These models have potential in research applications including drug discovery, weather forecasting, synthetic speech and medical imaging.

The aim of the session will be to equip you with knowledge of how generative AI and diffusion models work and to share an overview of research applications. The workshop will include short talks from researchers already deploying diffusion models in their research.

Much of the workshop content is conceptual and high-level, and by the end of the day participants will have a firm grasp on how diffusion models work. We won’t be coding during the session, but will share code with you for you to work with after the session.

This course will provide an introduction to Docker.

Writing research software in Python presents numerous challenges to reproducibility - what version of Python is being used? What about the versions of PyTorch, Scikit Learn or Numpy? Should we use Conda, or venv, or Poetry to manage dependencies and environments? How can we control randomness? Do I have the right version of Cuda Toolkit? In principle, given the same data, and same algorithms and methodology, we should be able to reproduce the results of any given experiment to within an acceptable degree of error. Dealing with the above questions introduces significant problems to reproducing experiments in machine learning. This workshop will explore the use of Docker to help alleviate almost all of these questions. Furthermore, combining Docker, git and GitHub can be a powerful workflow, helping to minimise your tech stack, and declutter your python development experience.

Please note this course predominantly involves theoretical exploration of video methods, not practical sessions.

This short course provides an introduction to the use of video as a research method within research projects. The use of video in research is not new. However, with technological and societal shifts, researchers frequently turn to video as a way to explore social phenomena. This course explores the proposed affordances of video methods such as claims of neutrality, durability, closeness to data and richness. These claims are also critiqued. We will consider the role of subjectivity in the use of video, the incompleteness and fragility of video data, the social and physical accessibility of devices and platforms as well as the challenge to inclusion associated with a visual method that prioritises the sense of sight. The course will present specific research case studies, associated with videography, video elicitation, content analysis as well as participatory, creative and non-representational approaches. Video methods are, perhaps, conventionally associated with data collection, which will be a substantial focus of the course alongside approaches to analysing video data. Additionally, the course will also consider how video can be used as part of research storytelling. Alongside discussing existing research, the course will provide opportunities for attendees to plan for the use of video methods.