Qbot Services Help Students Reach Their Full Potential
Enhance remote learning by creating a teaching and learning community and personalising the student experience using world-first AI infused technology.
QBot is Transforming how Students Learn, Interact and Collaborate
For forward-thinking education institutions, these tools have limitless potential – from improving student engagement, to achieving better learning outcomes.
QBot FAQ’s for educators and course administrators
Who will/should answer @QBot answers?
Everyone in the Team can help by contributing answers. With the default configuration of QBot, the user who asked the question OR the educator can select the correct response.
Where should students post their question @QBot? In the Lesson Channel itself or under the Questions tab?
In the channel > Post Tabs
What happens if a student posts questions in the wrong Lesson Channel?
We should always ask students to post their questions in the right channel, however the knowledge base is common across the module, so it doesn’t really matter.
What can lecturers and students do if they detect a potentially wrong/poor answer paired to a @QBot question?
When a student detects a wrong/poor answer, they can select ‘tag admin’. The student can also provide a new answer. When the student selects ‘tag admin’; the lecturer has the opportunity to provide a new answer.
How can we manage the wide range of questions that students may post, e.g., course admin questions, or even random/odd questions, e.g., “Where should I go for lunch?”
With origins in data mining, artificial intelligence, and educational technology, learning analytics focuses on the collection and measurement of The lecturer is not expected to answer questions that are ‘off topic’ however they may consider using these questions as an opportunity to develop a personality for their bot.
What happens when someone forgets to tag QBot when he/she posts questions? How can lecturers and students respond in such cases?
In this case, QBot can always be tagged in a reply. Then, QBot will recognise the first post as a question.
Can students answer @QBot questions posted by their peers?
Yes – and they should be encouraged to do so by lecturers.
How does QBot know which educator to send a student’s question to?
QBot has access to the student’s information and uses AI to detect which educator should be sent the question.
Would the lecturer be able to edit the “good answer” given by students to make it “ideal answer”?
The educator can’t edit a student’s answer, but can comment and supply the correct answer, based on the student’s answer.
Will educators be able to tell which students attempted to answer a single question posted to QBot even though the lecturer may only select one as the correct answer?
Yes, the educator can see all responses to a question.
What about when questions are asked in different ways?
QBot is based on natural language processing. The question does not need to be exact to get a response. For QBot to return a response, the confidence score needs to be above a certain threshold. You can view the confidence score with each of QBot’s responses.
How can I get extra help with using QBot?
Just tag @QBot and then ‘help’ in the relevant team and QBot will provide further information. QBot automatically provides further help if a user incorrectly tags QBot as well.