Active Listening in the Workplace - AI Roleplay

The scenario and AI colleague in this Active Listening at Work roleplay can be customised in BSGO for a unique and personalised experience:

• Learner role – what occupation and position will the learner roleplay in this conversation?
• Colleague avatar - choose between Faye and Jeremy to match your scenario
• Topic of conversation – what does the AI colleague want to discuss with the learner?
• Avatar’s background – to liven their personality!
• Avatar’s current mood – how will the AI colleague behave when the learner first talks to them?
• Transcript submission – you can toggle to choose if learners must submit their transcript for instructor review

You can also edit technical details like the activity title, description, and instructions for the learner, based on how you tailor the scenario.

Upon entering the simulator, learners will see the customised instructions in a text pop-up for guidance on what to expect and their goals during the conversation. Then, they’ll meet the virtual colleague and practice putting their active listening skills into action.

The conversation flows back and forth with exchanges between the AI-powered virtual colleague and the learner. Once the AI colleague has said their piece, the learner then has an opportunity to respond in their own words, then their colleague replies, and so on. The AI’s responses dynamically adapt to progress the conversation based on the learner’s input.

If the learner navigates the conversation with a keen ear and thoughtful answers, they’ll elicit positive responses from their colleague and constructively progress the conversation, eventually reaching a stage where their teammate feels heard, their worries ease, and they’re more open to the learner’s thoughts.

Oppositely, giving judgemental, dismissive, or self-centred responses may devolve the conversation into hurt feelings and annoyance, before the AI character eventually withdraws from speaking openly to the learner any further.

Once the conversation comes to a natural conclusion, the learner can view AI-powered, personalised feedback on their performance. 

When the learner’s conversation with the AI character concludes, a pop-up panel offers LLM-generated insight about their active listening skills. Short text summaries explain where they excelled and where they could improve in future, using examples from their transcript.

Learner performance is measured based on these key verbal and non-verbal active listening skills: 

• Paraphrasing and summarising – reflecting back what their colleague shared with them to demonstrate understanding.
• Empathy – using empathetic and validating statements that show caring and recognition of their colleague’s emotions.
• Open questions and clarification – seeking to open up the conversation and gain a better grasp of what the other side is thinking and feeling.
• Eye contact – making frequent, but not excessive, eye contact to convey engagement and empathy.
• Body language – adopting a relaxed, open posture that creates a calm and welcoming aura.

The learner can also view the full conversation transcript in this pop-up panel, for further self-reflection of where they excelled and where they went wrong.