Data. The Non-Verbals of the Online World

In the virtual classroom, we work without many of the luxuries that face to face teachers are given. Individuals in the same space can gauge and innately understand each other. In these face to face interactions, you can use your emotional intelligence to guide the situation and build proper frameworks for learning. A teacher’s ability to correctly read the body language of their class and students will have a higher chance of success. It can be assumed that students will not generally be forthcoming with what they need and they may also not have the vocabulary to describe what it is they need. With body cues, they don't have to.

In the virtual space, however, we largely rely on alternative forms of communication and data. These various forms of communication (email, phone call, instant messaging) leave us with a large chunk of what is being said staying invisible. To also note, these alternative forms of communication do sometimes offer up different non-verbal clues that require a different perspective and sometimes extra professional development to uncover. We must, therefore, rely on non-traditional strategies and clues to fill in these non-traditional narratives. This means that data plays a critical role in helping us understand and intervene in the virtual classroom. I wrote a piece earlier regarding the how we can use data to determine engagement in an online school. In this blog, I want to focus more on the barriers to entry and why it is vital for teachers to learn how to use data.

Barriers to Entry

As Thomas Redman notes in a Havard Business Review article, most people fear data. It can be overwhelming. Analytics, data drive practice, new technologies, visualization, mathematics… All these words trigger certain feelings in people. Even worse, what happens if I make a prediction with the data and I am wrong? Or what happens if I can’t use the tools to build a narrative with the data? When people are afraid they won’t share important information and they won’t take risks. Maybe worse, they will take risks that may not be backed by data. In order to make significant improvements to a school, the school must collect and use data effectively (ACER 2012). This means combating the natural reflex people may have when you say the word data.

The culture needs to also not penalize mistakes that individuals make, people want to generally avoid the costs of failure until the cost becomes minimal.

To combat fear, organisations need to create a culture where learning is central to the work. The more people are open to learning about data-driven practices, the more they will gain confidence implementing it into their practice. The culture needs to also not penalize mistakes that individuals make, people want to generally avoid the costs of failure until the cost becomes minimal. Learning happens when people make mistakes. If mistake making is suppressed, learning will be suppressed. Without the fear of making a mistake hanging over them, individuals will be more likely to try new ideas and initiatives, a key element in innovative schools and organisations.


The knowledge gap between expert teachers and others needs to also be bridged. Professional development opportunities need to be available for teachers to upskill and gain confidence in their abilities to improve the way they use data. In a paper by the Grattan Institute (2015), they reported that student evaluation and assessment as a key area teachers wanted additional professional development. Without valuing and giving people the opportunity to learn, your workforce will stagnate.

In fear, individuals will look also at leadership. Leadership teams need to stress that data-driven practices are here to stay. They must also understand the importance and the inevitability that data will be used for decision making in many aspects of 21st-century work. With a clear mandate and a clear way to upskill teachers, the rest should follow. If the Leadership is afraid of data-driven practices than the staff will have no incentive to take the first step.

The next barrier to entry is apathy. People may not feel like the data is worthwhile. They may not feel like it is part of their role to work with the data. They may not see the benefit from learning this new technology in their practice.

One way to alleviate this is to use technology that is easy and straightforward. Not everyone has an interest in data. Not everyone wants to be an expert. The more we can reduce the technological barriers and the more we can show teachers the benefits, the more likely data will be used. This type of thinking about introducing new technology is similar in all types of uptake.

Another way to combat this apathy is to make it easy to access the data. If the data is locked away for only a certain team to work with, it signals to the rest of the staff that it isn’t for them. The data must be available for individuals to ponder and build their own narrative and form their own conclusions.

The Non-Verbal of Online Learning

With a lack of non-verbal signals in online learning, we need new ways to gather similar clues about student learning and engagement. As Patrick Griffin (2014) says, data is what we can observe what a student does, makes, says, and writes. In the online space we can gather what students say, make, and write. We need other information to gather what a student is doing, more specifically what cues can we use to translate non-verbal signals and how this relates to teaching and learning. 

Data are the non-verbals of online learning. Data does not lie.

This is where data becomes critical. Data are the non-verbal of online learning. Data does not lie. This includes:

  1. Time spent on an activity
  2. Login frequency
  3. Session times
  4. Reattempts and revisits to activities
  5. Reflections on tasks

Proper analysis will show you the progress of your students, their engagement level, and the effectiveness of your learning program. This is especially true when you are not next to the student.

By using data and the alternative communication channels we spoke about above (email, phone call, instant messaging, etc), teachers can build data-driven narratives around their students. It also alleviates the disadvantages of not being in the same physical space as the students, a huge issue for virtual schools.

In some instances, the data is better at telling you what is happening with a student than our own judgement at a moment in time (sometimes we are not always on our game!). We all have our own bias and we may interpret the same situation much differently. With data and various visualization techniques, the bias may still be present but the data does not lie. The methods of gathering the data is not as variable as just looking at non-verbal cues. With non-verbal cues, it is largely dependent on my ability to be tuned-in to that moment. Data does not need me to be on, it does it’s thing and when I have the opportunity and the right frame of mind I can analyse it.

Data is not just for virtual schools. Traditional teaching now relies on data as the integration of technology into many learning programs becomes the new normal. With more data, we will become more dependent on our abilities to use this data. If you don’t use data, you are falling behind and fast.

ACER. 2012. The Tool Incorporates Material Developed by ACER in Collaboration with the Queensland Department of Education.

Goss, P., Hunter, J. 2015. Targeted Teaching: How better use of data can improve student learning. Grattan Institute.

Griffin, P. 2014. Assessment for Teaching.