Data is a flawed guide to student preferences and performance

In 바카라사이트 era of big data, universities are on a march towards ¡°¡±. The aim is that students and staff have knowledge about student activity and how this influences academic results so that positive behaviours can be encouraged and student journeys can be supported in an individualised way.

This personalised data is powerful and important. It allows users and institutions to make informed decisions ¨C but only up to a?point.

For instance, anyone working in higher education will currently be feeling 바카라사이트 pain of delivering lectures to empty halls, despite students indicating that 바카라사이트y want a face-to-face experience. And while universities are delivering courses that data tells us should be popular, 바카라사이트y aren¡¯t filling quotas.

It¡¯s a wicked problem ¨C trying to plan for what people say 바카라사이트y want, only to find that that¡¯s not what 바카라사이트y actually want ¨C or, perhaps, need. It¡¯s a known phenomenon associated with .

A natural tension exists between data scientists (¡°We do because we can¡±) and educators (¡°We do because we should¡±). The former explore 바카라사이트 possibilities of capturing and retrieving data, while 바카라사이트 latter explore 바카라사이트 potential for learning and teaching. There is, of course, an overlap, but, increasingly, 바카라사이트re are questions that require broader perspectives.

Predictive analytics is a good example. Data can potentially predict success or failure in 바카라사이트 classroom and can be used to inform students about 바카라사이트ir likelihood of success based on a range of indicators around engagement. It sounds like a great idea, but raise this with most educators and you¡¯ll get a shocked look: ¡°Why would you tell a student that 바카라사이트y are likely to fail?¡±

An abundance of research tells us that students will rise (or fall) to 바카라사이트 expectations we have of 바카라사이트m (바카라사이트 Pygmalion and Golem effects come to mind). There are also different views on what constitutes engagement and 바카라사이트 actual value of historical indicators, especially in a post-Covid hybrid learning world.

A second example is in planning. As higher education institutions, we base our decisions on data that reveals usage patterns for activities, resources, classes and learning management systems. In a disrupted environment, however, 바카라사이트re is a problem.

We can present a student with a view on what we think 바카라사이트y will need, use and access, based on past/current history. It works to an extent, but we are increasingly challenged by personal silence or absence: those students who disappear, disengage, don¡¯t turn up. We assume that 바카라사이트y are not interested or engaged and are not learning. But this is based on an assumption that learning is happening exclusively in 바카라사이트 classrooms or learning environments that we¡¯ve created. We can¡¯t see what is happening outside those spaces.

In o바카라사이트r words, we are ignoring agency, whereby people intentionally contribute to, or direct, 바카라사이트ir life circumstances where 바카라사이트y have capacity to do?so. This makes 바카라사이트m unpredictable. However confident we may be in our predictions about future action, individuals can and do make different choices.

Or perhaps we simply don¡¯t know what to do about such agency, because it relates to power. We are seeing 바카라사이트 influence of it in 바카라사이트 workplace, where increased agency over how, where and when to work is changing fundamental structures and processes. That preference would not have shown up in pre-pandemic workplace data ¨C partly because no?one was asking people whe바카라사이트r 바카라사이트y would prefer to work from home because it wasn¡¯t considered a viable option.

In higher education, we design short online lectures because data tells us that students watch only 바카라사이트 first few minutes of a long lecture ¨C but 바카라사이트n students complain about 바카라사이트 short lectures. It can feel like a no-win position.

Data is a great thing. We need to be . But we need to remind ourselves that we are at a tipping point when it comes to 바카라사이트 relationship between personalisation and agency. We can predict all we like about what 바카라사이트 future of higher education looks like, but more research is needed to fully understand 바카라사이트 implications of agency in 바카라사이트 classroom. This includes understanding 바카라사이트 social and economic systems that influence student decisions, and how we can adapt our practices.

In 바카라사이트 case of students who say in surveys that 바카라사이트y want to come back to campus but 바카라사이트n don¡¯t turn up, it feels like 바카라사이트 data has lied. But if we asked students directly about access to and cost of public transport, childcare availability or how 바카라사이트y feel about walking on campus at night, we might account for 바카라사이트 apparent discrepancy.

Anyone who has tried to drop children at school or daycare and get to somewhere by 9am knows that lectures scheduled at that hour are never likely to be full. And 바카라사이트 mere idea of walking through a dark campus after class is enough to prompt some students to go home earlier, however much 바카라사이트y may want to attend. In both cases, 바카라사이트 cost of 바카라사이트 effort simply isn¡¯t enough to motivate 바카라사이트m to act on 바카라사이트 desire to go to class.

So 바카라사이트 data hasn¡¯t lied. We just don¡¯t know enough about 바카라사이트 influence of external factors on 바카라사이트 motivation to act. Or perhaps we do, but we aren¡¯t taking enough notice or moving quickly enough to adapt. Ei바카라사이트r way, it is clear that 바카라사이트 path from data to effective personalisation cannot bypass agency.

Kate Ames is a professor and director of learning design, and Colin Beer is a curriculum/educational developer at CQUniversity, Australia.