Skip to main content
Ottawa 2024
Times are shown in your local time zone GMT

QA and data from exam performance

Workshop

Workshop

10:30 am

26 February 2024

M208

Session Program

HUI MENG ER1
VISHNA DEVI NADARAJAH1
1 International Medical University 



Background 
Learning analytics is a tool for gathering, analysing, and interpreting data related to student’s learning preference, engagement and performance. It can support students’ self-assessment through dashboards that provide real time information about their learning behaviour, progress and performance, as well as personalised recommendations for various aspects of the learning process. These guide the students in identification of areas for improvement, reflection of their learning progress and strategies, leading to realistic goal setting. The technology helps to facilitate the development of self-regulated learning skills among students. 


Why is the topic important for research and / or practice? 
In this workshop, we will introduce the theoretical frameworks and practical tips that guide the design of a learning analytics system. The participants will discuss about stakeholders needs, types and sources of data that are essential to the development of learning analytics based on the contextual needs of the institution. The impact of poor-quality data and ethical issues related to data privacy and confidentiality will be deliberated. 


Workshop format 
Group discussion, break-out small group activity, demonstration of an institutionally developed learner analytics platform and presentation. 


Who Should Participate 
This workshop will be useful for faculty, administrators (student support, academic services, examination office), students, e-learning and IT staff. 


Level of Workshop
Beginner 


Workshop Outcomes 
  1. Identify data that provide insights about students’ learning behaviour, progress and performance 

  2. Discuss the impact of data integrity and ethical issues in implementation of learning analytics 

  3. Discuss the use of learning analytics in developing students’ self-assessment skills 


References (maximum three) 

Saqr, M. (2018). A literature review of empirical research on learning analytics in medical education. International Journal of Health Sciences, 12(2), 80–85. https://pubmed.ncbi.nlm.nih.gov/29599699/ 

Leitner, P., Ebner, M., & Ebner, M. (2019). Learning Analytics Challenges to Overcome in Higher Education Institutions. Utilizing Learning Analytics to Support Study Success, 91–104. https://doi.org/10.1007/978-3-319-64792-0_6 

Bunmi Malau-Aduli1
Tim Wilkinson2, Karen Hauer3, Lambert Schuwirth4, Vishna Devi Nadarajah5 and Richard Hays6
1 School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle
2 University of Otago
3 University of California, San Francisco
4 Flinders University
5 International Medical University
6 James Cook University 



1. Background:
For assessment systems to continually improve efforts in achieving desired aims and fulfilling medical education’s social accountability, quality assurance is indispensable. However, there is lack of agreement among stakeholders regarding definitions of quality and how best to embed ongoing improvements. Such heterogeneity highlights the need for clear, coherent, and plausible definitions of quality with the chosen processes and underlying rationale/evidence in a given context. 


2. Why is the topic important for research and / or practice?
Evaluation of assessment practice and processes often focuses on externally driven quality assurance (QA), such as through accreditation. QA of exams has received more attention than QA of other types of assessment or of programmes of assessment. However, continuous quality improvement has the potential to be more internally driven and collaborative. How best to define quality and how best to develop and implement quality improvement processes has not been well described. It is essential to develop robust, evidence-based assessment processes that are informed by both available evidence and sound theory to guide health professions institutions in developing internal monitoring processes for ongoing improvement of the health professions education they provide. Translation into sustainable assessment practice requires that internal stakeholders are aligned on the purpose of QA. 


3. Workshop format, including participant engagement methods:
This workshop seeks to bring together health professions educators from around the world to learn, share and discuss experiences and best practices in quality assurance and quality improvement of assessment systems. The workshop will facilitate dialogue on the variety of international approaches by presenting literature-informed principles and analysing real-life case studies, derived from the authors/ presenters’ recently published book on quality assurance in health professions education and provide participants with resources to engage in QA of assessment at their institutions. The focus of the workshop will be on sharing practice among the participants and aligning staff development and training with internal and external quality assurance processes for written, performance and workplace-based assessments. 


4. Who should participate?
This workshop is intended for all health professions educators and professional staff who engage in quality assurance of assessment processes and wish to share their experiences and gain insight into how to foster ongoing improvement of their assessment systems. 


5. Level of workshop:
Intermediate and advanced. Familiarity with the quality assurance of assessment paradigm is a pre-requisite for this workshop. 


6. Take-home messages / workshop outcomes / implications for further research or practice:
It is imperative that assessments conducted in health professions education across institutions globally are not only bench-marked against set standards and criteria but also driven by collaborative processes for ongoing improvement. By utilising an improvement-based approach, these criteria and standards can be evaluated to ensure consistent and reliable outcomes across various professional bodies and institutions, regardless of geographical location. 




References (maximum three) 

  •   Malau-Aduli, Bunmi S., Hays, Richard, and van der Vleuten, Cees P.M. (2021) Understanding Assessment in Medical Education through Quality Assurance. Internal Medicine. McGraw Hill Professional, New York, NY, USA. 

  •   Matei, L., & Iwinska, J. (2016). Quality Assurance in Higher Education: A practical handbook. In: Central European University, Yehuda Elkana Center for Higher Education 

  •   Norcini, J., B. Anderson, V. Bollela, V. Burch, M. J. Costa, R. Duvivier, R. Hays, M. F. P. Mackay, T. Roberts, and D. Swanson. (2018). 2018 Consensus Framework for 

Good Assessment. Medical Teacher 40 (11): 1102–1109. doi:10.1080/0142159X.2018.1500016