Most of the frustration experienced by learners is poor, slow or inadequate feedback; the embarrassment of being asked questions in a classroom in front of others, even one-to-one by a human tutor, the fear of asking questions in a classroom or in a Zoom session, as you’d feel stupid, the lack of opportunity to ask for clarification or ask questions in a Zoom lesson, classroom or lecture, the email reply that takes days to come back, that solitary mark A-D and brief comment on a piece of work or general and non-specific comments like ‘needs more clarification’.
The solution is good feedback. Feedback is the lubricating oil of teaching and learning. Feedback accelerates learning. It can therefore reduce the amount of time spent teaching. It motivates and propels learners forward. You need to work hard to keep learners on task, feedback is the spark and stimulus that gets them to the next stage.
Technology can use feedback to propel online learning. We spend so much of our technology time to present linear, media ‘experiences’ that we forget about the locomotive power of feedback. Creating videos, graphics and screeds of text is easy, feedback is personal and hard. Yet there are methods that have emerged from recent technology that make it much easier. We need more focus on technology to deliver feedback as well as media.
There are many forms of feedback; confirmatory, explanatory, consequential, real-time, semantic, media specific, peer-to-peer, reflective, calls to action. It is a powerful aid to learning and should be used to power learners forward.
Right, Correct, Yes, Wrong, Incorrect, No Try again. This feedback simply confirms whether you have succeeded or not.
Hints give snippets of information to nudge learners forward in a task. They are useful in making the learner think deeper about the problem. (Lavbic, Matek & Zrnec, 2017).
Go one step further and explain WHY you got something right or wrong. Note that even when it is right, reinforcing with different wording and extra information and explanations can be useful. A Clark and Mayer (2016) meta-study shows that this is superior to no or corrective feedback.
Feedback can lead to consequences in branched and other forms of simulations. Here you provide remedial or fast-track routing, depending on the response. This can be very sophisticated in adaptive learning where personalisation, through data and AI. uses these techniques.
Feedback in real time is common in VR and real-time simulations and games, where consequences of decisions and actions are immediate as they would be in real life.
You use AI to semantically interpret responses and act upon the meaning. Sentiment analysis has also been used to determine the subjective feelings of the learners to deliver feedback.
7. Media specific
You can choose to provide positive feedback in a specific confirmatory medium, like audio or video, using text or other forms of feedback for negative responses. This strengthens the memory of the positive act and avoids memories of negative responses.
One way to scale feedback is to get one learners to peer review each other. In pairs or groups. There are systems that provide this functionality.
Leaners can be asked to reflect mentally or write a reflective piece, as a forms of self-referential feedback.
10. Call to action
Learner is asked to do something in the real world as a result of their online response. This can be a nudge towards practice and transfer. It may trigger an action in a spaced or retrieval practice system.
Thanks to Connie Malamoud who inspired me to write this blog.