Task:
Continued engagement in data-based inquiry influences the organisation’s culture over time. Discuss 3-5 practical examples (that have not been mentioned in this module) of ways educational leaders can build a data rich culture. Links to examples (e.g. photos, websites, articles) should be included.
MINIMUM 700 WORDS
SAMPLE IS GIVEN BELOW. I NEED PRACTICAL EXAMPLES.
In higher education, and specifically within medical schools, there are a number of ways for educational leaders to build a data rich culture, including:
- Break down information silos
- Invest in technology and tools to make data accessible to staff
- Collecting student feedback, engaging student buy-in
- Set expectations that data will underpin continuous improvement
Firstly, information silos are a problem in education, particularly higher education, as fields of expertise are often distinct and research tends to stay within the field. For example, educational researchers as well as library and information science researchers publish research on student achievement, but these are published in separate education and information science journals, and researchers are not necessarily aware of what has been discovered elsewhere (Stefl-Mabry & Radlick, 2016). This is also the case when journals published in countries like the United States and Australia feature far fewer articles by international researchers, and potentially useful data about ‘the way things are done’ in education elsewhere remain unseen by most educators (Tight, 2014). In my case this even occurs inside the medical school. It is laborious and time-consuming for myself, leading the law and ethics program, to find out how students are doing in other aspects of their degree, and almost impossible for me to track international students’ progress, or Indigenous students’ progress. There is very little communication or sharing of data between theme leads and administration, and very little expectation that we would even consider having those data-driven discussions to improve the student experience. There is also very little time for academics to achieve this thoughtfully.
My next suggestion is related, and that is investing in technology and tools to make this data more accessible. We still use excel spreadsheets and a very old custom-built database to store and communicate data. Attached is an image depicting students’ marks in some of their short-answer questions for one exam. The way multiple choice question results are presented is even more difficult to interpret, image also attached. If a student makes an appointment to see us for feedback, we need to look up their student number, and the question numbers on the exams that relate to our theme, and then highlight them in the spreadsheet to try to see which MCQ they got wrong (and we can’t see which incorrect answer they chose), or which SAQ they struggled with more. Our school is desperately in need of a modern, user-friendly way to collect, store and disseminate data on student performance to better inform the feedback we provide to students, who are very keen to track their progress and understand this data also. There seem to be so many programs and apps to collect and publish performance data (Exam Soft is often mentioned in the tertiary setting, but see links to other examples below) but many are focused on primary to high school, and widespread use of these programs and apps are yet to reach higher education. Students of this generation must feel that they get to university and go backward, because it’s been my observation (as a member of Gen Y myself) that our use of technology in higher education has not kept up with schools.
One thing the school has made a concerted effort to do, is to collect data from students. We are undertaking a curriculum review and recently had more than 250 students respond to quantitative and qualitative questions about the degree; how useful they thought each course was, what worked or didn’t work, what should be kept, what should be changed, etc. This will help us to justify any changes we make to the course. However, there is a risk of medical students being over-surveyed, and the school has strict guidelines about how to collect information from students and in what ways, for what purposes. Most student feedback is collected anecdotally, or through the standard SET/SEC (student evaluation of teaching/course) surveys delivered by the university, which typically have very low response rates. Yet again, feedback ends up in several different places, which makes it difficult to track. Instead, it is most often shared anecdotally, casually between staff.
Ultimately, what would benefit this situation is leadership in creating a data culture. What appears to be lacking is the expectation that data will underpin continuous improvement. I recently made significant changes to the assessment program for my theme, based on feedback and research and planning, and I went to committee prepared to explain and defend my decisions, and was not even asked. This could lead to a situation where academics could make unjustified changes to their course, or alternately, they can keep their course in a format that might not be so well-received by students because no one is looking critically at the data or asking those academics to justify why they do things the way that they do. This can lead to a stagnant program for students, and continues this disconnect between the data that is available to us and the changes we could be making to improve student outcomes.
While this might sound fairly negative, it is difficult as a young person to enter a very well-established environment that has not changed in a long time. I think leadership on data is lacking, and am looking forward to investigating this further in my work in the coming years, to be part of the change that I want to see.
Notes on looking at the examples:
The top row in both tables is the question number. Below that is the total amount of marks available. In MCQs this is followed by the pass mark, and the placement of the correct answer in red (A-E represented as 1-5). A 1 means the student got it correct, and a 0 means incorrect. In the SAQ example, the pass mark is in red this time, with students’ marks below. There are no student numbers or identifying information in these examples, but this provides a good insight into why constantly striving to improve data and create a data culture are important.
Examples of data tracking (these are examples only, I am sure there are more!)
Exam Soft. Retrieved from https://examsoft.com.
Gradexpert. Retrieved from https://www.gradexpert.com.au.
i-Ready. Retrieved from http://i-readycentral.com/ideas/track-student-goals-with-progress-logs-and-data-chats/.
Lane, M. (2016). 10 Data Tracking Apps You Can Use in Your Class Tomorrow. Retrieved from http://www.gpb.org/blogs/education-matters/2016/12/13/10-data-tracking-apps-you-can-use-your-class-tomorrow.
Student Tracker. Retrieved from https://www.studenttracker.com.au/features-2
Other References:
Stefl-Mabry, J. & Radlick, M.S. (2016). Breaking down information silos: sharing decades of library research with educational researchers. Proceedings of the American Educational Research Association, Washington DC. Retreived from https://www.researchgate.net/publication/299462704_Breaking_down_Information_silos_Sharing_decades_of_school_library_research_with_educational_researchers.
Tight, M. (2014). Working in separate silos? What citation pattersn reveal about higher education research internationally. Higher Education, 68(3), 379-395. Retrieved from https://link.springer.com/article/10.1007/s10734-014-9718-0.
1151 words
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