Gender Inclusion

The first time learners use Bodyswaps, an onboarding sequence familiarises them with the features of the app, takes them through an avatar selection and embodiment activity, and prepares them for the experience to come. 

In the onboarding, learners will: 

• Find out how this training is different from the rest
• Select their avatar
• Discover their virtual journal
• Learn how to navigate and use the tools and settings

The learner is presented with their first scenario. They are tasked with confronting Sam, an employee who exhibits gender-based discrimination against his co-worker, Sophie. The learner's role will involve prompting Sam to reflect on his behaviour and offering constructive feedback to help him improve.

Then, the learner is invited to complete a short, Likert-style, self-reflection survey to indicate how confident they feel about the following key learning points:

• Identifying microaggressions
• Asking questions that encourage self-reflection
• Giving effective feedback

Spotting sexist microaggressions at work involves being attentive to subtle behaviours and comments that demean individuals based on their gender. In this activity, the learner witnesses a meeting between two co-workers - Sam and Sophie, where they discuss a major collaborative project.

The learner’s task is to closely observe their conversation, focusing on Sam's behaviour towards Sophie, in order to identify instances of non-inclusive and sexist behaviour. Each time the learner notices something,  they are asked to click their mouse / controller. However, to encourage thoughtful observation, learners are given 10 clicks to identify 8 instances of non-inclusive behaviour. 

Throughout the conversation, learners witness comments that diminish Sophie’s contributions or capabilities, often disguised as jokes or offhand remarks. They are also primed to notice if Sophie is interrupted more frequently, or spoken over in the meeting, and to be aware of any language that reinforces stereotypes or assumptions about gender roles. For example:

“Sophie: If you’ve had a conversation without me it would be good if you brought me up to speed. 

Sam: Relax love, it was just a coffee...It’s natural that we might discuss elements of the project if we see each other. I mean, if you’re part-time that’s less likely to happen, isn’t it?”

At the end of the activity learners are provided with feedback and have a chance to rewind the scene and rewatch the behaviours they fail to identify.

Sophie has left the meeting. The learner now sits across from Sam in the meeting room and has a chance to speak to him about what they witnessed. 

This scaffolded conversation will involve a total of five quick exchanges with Sam, where the learner chooses what to say by selecting one of three options. One, the most appropriate option, will be an open ended question and an encouragement for Sam to reflect on his behaviour. For example:

1. How are you finding working with Sophie? (The appropriate option)
2. Would you say you have a positive working relationship with Sophie?
3. Why do you think she reacted the way she did? 

The other two choices divert attention from Sam's own conduct. If the learner selects those, Sam will become defensive. The learner will then receive feedback and an opportunity to try again. Progressing the conversation will only be possible once the learner selects the most suitable option.

The learner’s aim is to  avoid accusations and ask meaningful questions that encourage Sam to self-reflect, whilst refraining from offering suggestions. By doing so, he will come to his own conclusion that there was an issue with the way he behaved towards Sophie.

Through this role-playing scenario and guided discussion, learners practise fostering a more reflective and open conversation and basing their feedback on objective observations rather than personal judgments.This will help them build a solid foundation for interacting more respectfully and productively with their colleagues.

Now, the learner is invited to provide feedback on Sam’s behaviour in their own words.  AI analytics pick up keywords which demonstrate that the learner understands how to describe Sam’s behaviour, explain the impact of his actions and suggest what he should do differently next time he interacts with Sophie. 

Learners should aim to use Sam’s name and provide him with precise examples of his misconduct, identifying behaviours such as condescending or dismissive. They should also act with objectivity based on their initial observations and avoid making assumptions about Sophie’s feelings. For example, they could mention that Sophie had to repeat she was working from home on Fridays or that she had to leave the meeting in a hurry.

At the end of the activity, the learner receives feedback about the keywords they used and a chance to reformulate their answer and talk to Sam again, if they wish.

The learner is congratulated on completing the simulation and has a chance to repeat the self-reflection questions from the start of the module, to see how their confidence has changed. 

Note: With soft skills training, it is not unusual to find that learners’ confidence levels actually fall upon completion. This is because people are often overconfident in their ability to communicate or empathise before the training begins. As the experience raises self-awareness, confidence levels may fall in response.

Before the learner leaves the module, they are asked to complete a short survey about their experience. 

This survey is not compulsory, but the data helps us to assess the effectiveness of our product and identify any areas that need improvement. Clients also find it beneficial when assessing ROI. 

They are asked to mark whether they agree or disagree with the following statements, on a 10 point scale: 

• I would recommend this experience to others.
• The experience helped me identify elements I could improve upon.
• I now have a better understanding of how to improve my ability to spot and challenge sexist microaggressions at work.