Coordinating projects using AI-aided systematic screening with ASReview.
Unlock the power of AI-aided systematic reviews and transform your organization’s research process with our hands-on, expert-led course.
Coordinating projects using AI-aided systematic screening with ASReview.
Unlock the power of AI-aided systematic reviews and transform your organization’s research process with our hands-on, expert-led course.
The scientific output of the world doubles every nine years. In this tsunami of new knowledge, imagine the enormous challenge of updating a medical guideline, developing evidence-based treatments, creating unbiased policy recommendations, or scouting for new technologies. There’s not enough time to read everything! Attempts to synthesize state-of-the-art research findings in a particular scientific field therefore are under severe strain; the exponential growth in papers means screening an increasingly larger body of work – resulting in costly, or error-prone work that is often abandoned prematurely. Nevertheless, systematic reviews are pivotal for scholars, clinicians, policymakers, journalists, and, ultimately, the general public. The rapidly evolving field of Artificial Intelligence (AI) has allowed the development of AI-aided pipelines that assist in finding relevant texts for such search tasks. A well-established approach to increase the efficiency of text screening is screening prioritization via active learning: an interaction between a human screener and a machine learning model which constantly learns from the human and proposes the most likely relevant paper to the human. This method can reduce the number of papers to screen by up to 95%(!) and is easily integrated in popular, active learning text screening software. Our course prepares the participants for coördinatingprojects which are carried out in the open-source software ASReview.
In addition to the standard course format, we offer an optional module that emphasizes networking and co-creation opportunities with the core developers of ASReview. By joining the discussions during the weekly stand-up meetings, participants can connect with the experts behind the software and actively contribute to its ongoing development. Thereby, participants can engage in the development process by sharing insights, experiences, and ideas, contributing to the improvement and evolution of ASReview. This will result in a deeper understanding of ASReview’s features, functionalities, and the underlying technology through direct interaction with the development team.
The primary goal of this course is to equip participants with the knowledge and skills required to coördinateAI-aided screening projects using ASReview within their organizations. The course accommodates individual learning objectives and projects, ensuring that upon completion, participants will be able to:
Upon successful completion of the course, participants will be awarded with a microcredential qualification of 84 hours. A microcredential is a globally recognized qualification granted to learners after completing a standalone educational unit. This qualification serves as a mark of quality both within and outside educational institutions, demonstrating the knowledge, skills, and competencies developed through the course. The European Commission encourages countries to pilot flexible learning pathways through microcredentials for lifelong learning. In response, the microcredential initiative has been launched at Utrecht University
Upon completing the course and its assignments, learners will receive a digital certificate in the form of an EduBadge. This badge contains information about the level, scope, and learning outcomes of the course. It is easily stored, shared, and presented as evidence of acquired competencies. For instance, participants can display their EduBadge on LinkedIn. The earned EduBadge is recorded in a national registry, allowing learners to accumulate and potentially stack credentials toward a more comprehensive continuing education package.
This course is designed for project coordinators, data scientists, information specialists, PhD supervisors and PIs of bigger projects, and others who wish to coördinateAI-aided systematic reviews. Prior experience with traditional systematic reviews is expected and we assume basic knowlegde of ASReview obtained via, for example, the summer school course or self-study.
Because we want to stimulate interaction and collaboration, the maximum number of participants is ~10.
The first edition will start 05-10-2023.
ASReview Community Room – Located in the old University Library – Entrance at the Drift 27 – Room 0.21 – Utrecht, The Netherlands.
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Task | Description | Optional |
Meeting 1
(8 hours) |
Meet & greet the other participants + explain the set-up of the course + lecture on the steps of systematic reviewing and where AI-aided screening fits in + differences between software packages + intro on active learning | Meet the core developers and information experts
Join the discussions during the weekly stand-up |
Self-study
(6 hours) |
Read literature + watch instruction videos + exercise in using ASReview LAB | Try out ASReview LAB with your own dataset |
Meeting 2
(2 hours) |
Q&A about exercises+ technical lecture on the active learning model | Join the discussions during the weekly stand-up |
Self-study
(6 hours) |
Exercises in using ASReview-datatools, the simulation mode with the WebApp and Makita | Option to work on location
Join the discussions during the weekly stand-up |
Assessment 1 | Hand in the answers to the questions in the exercises |
Task | Description | Optional |
Meeting 3
(2 hour) |
Lecture on responsible use of AI in systematic reviewing, reproducibility and FAIR data principles | Join the discussions during the weekly stand-up |
Self-study
(4 hours) |
Exercise about reproducing results via the asreview project file (using the ASReview Python API in Jupyter Notebook) | Option to work on location
Join the discussions during the weekly stand-up |
Assessment 2 | Hand in answers to the exercise |
Task | Description | Optional |
Meeting 4
(2 hours) |
Lecture on open-source workflows + how to create a reproducible workflow via Github + contributing roles | Join the discussions during the weekly stand-up |
Self-study
(20 hours) |
Contribute to open-source software (ASReview) | Option to work on location, work on your PRs together and receive instant feedback from the engineers. |
Assessment 3 (6 hours) | Create at least two Pull Requests |
Task | Description | Optional |
Meeting 5
(2 hours) |
Meeting to discuss how to implement AI-aided screening in organizations + lecture on how to create a journey map | Join the discussions during the weekly stand-up |
Self-study
(20 hours) |
Create a screening protocol to be used in your own organization + work on a journey map | Option to work on the exercises on location
Join the discussions during the weekly stand-up |
Assessment 4 | Hand in the journey map and screening protocol |
Task | Description | Optional |
Meeting 6
Users Meeting (2 hours) |
Join a Users Meeting and present findings from part 4 |
Standard fee: €4500,00
Fee for scientists or (semi) government: €3500,00
This expert-led course will provide you with the necessary knowledge and skills to supervise AI-aided screening projects within your organization. The course includes a globally recognized EduBadge upon completion. Invest in your career and stay ahead in your field. Register now!
For more information about the course or to register, please email asreview@uu.nl expressing your interest in participating. Due to the interactive nature of the course, we have a maximum limit of 10 participants per cycle.
Please note that obtaining the EU credits for this course requires some administrative work. Upon registration, you will be provided with detailed information on the necessary steps and documentation to ensure a smooth process for obtaining your credits.