Inequality in Education
Student activists are drawing attention to issues of inequality in educational systems faced by low income, first-generation, black, indigenous, and students of colour. Unsurprisingly, bias held in the real-world transfers to the virtual one (Lopez, 2019). As virtual learning is becoming more commonplace in K-12 and higher education, instructors must take a hard look to ensure the technology they’re using serves the needs of all.
Within the classroom context, negative attitudes can be seen and felt from the instructor to a particular student, as well as between students. This phenomenon is commonly known as implicit bias. The impact holds real and lasting consequences for students on the receiving end of bias, even if unintentional. In the study The Influence of Racial Embodiment on Racial Bias in Immersive Virtual Environments, implicit bias is defined as how “people’s attitudes and behaviours towards others are consequently influenced by […] categorization, even when people are unaware of this influence” (Groom et al., 2009). If a student faces discrimination or microaggressions while trying to participate in class, it can reduce the individual’s engagement and motivation.
Shift to “Zoom University”
During the 2020-21 school year, many schools had to use video conferencing. This transition to “Zoom University” as the Internet playfully called it, highlighted the wide technological discrepancy between students. Structural issues, such as reliable internet connectivity and high-speed internet, varied as students attended virtual synchronous courses across the world. Video conferencing software versioning created a new set of potential bias conditions. Only some students can use certain software features, such as virtual backgrounds. Many students, not wanting to reveal the conditions of their home, turn off cameras. Even with only names showing, instructors can uphold implicit bias behaviour for first names, despite believing themselves unbiased (Conaway & Bethune, 2015).
Students who turn on their cameras invite internalized judgement. It can be based on a variety of factors such as their location, age, race, sex, gender identity and expression, and physical appearance. Additional factors such as a general room condition, other family members being visible and multiple other observable features can further judgment. The level of language proficiency, accent, and dialect could also create potential issues when students use a microphone to vocally contribute to the class discussion. Implicit bias held by instructors may “contribute to racial disparities in educational outcomes both at the interpersonal and the aggregate levels” causing students to become less attentive to the course materials and learning activities (Chin et al., 2020).
Meeting online at fixed times also reduces opportunities for casual interpersonal connection, which would strengthen relationships between students and instructors to combat prejudices. These combined issues contribute to a lack of community, felt by both the instructor and students.
Issue of Student Engagement
Educators are faced with the struggle to improve student engagement, while creating a more equitable learning environment. Although implicit biases of instructors and students cannot be resolved through technology or pedagogy, they can be mitigated through the intentional design of an XR classroom and educational activities. Utilizing these methods, educators can control more about their learning environment and how they interact with their students. Add in real-time data capabilities of XR (see AI and Data Analytics below), and you have a combination of technology for educators to enhance engagement while removing many of the distractions.
Structuring an XR classroom experience to reduce bias and increase student engagement
Many schools, universities, and individual students cannot afford the latest technology, including XR headsets. Designing an XR experience to work on devices students already own, such as laptops, can overcome significant financial barriers and increase the ability of instructors to offer an XR experience within their classroom, virtual or in-person. In a hybrid class, where some students are there physically while others are attending online, the XR experience can bridge the technological gap to host all students together in a virtual space.
If an instructor intends to reduce implicit bias, one of the key factors is the look and characteristics of avatars. The Commons XR created a homogenous genderless avatar so all students appear physically the same. The purple body colour of each genderless avatar does not elicit the same implicit bias response as avatars with realistic human virtual bodies (Peck et al., 2013). Thus, the avatar removes any assumed bias related to the student’s skin colour, body composition, or sexual orientation.
With every student appearing physically the same within the virtual classroom, instructors can focus exclusively on academic contributions to class activities. The purpose is not to erase “identities or categories themselves but, rather, dismantl[e] structures that selectively impose vulnerabilities upon certain bodies” (Cho et al., 2013). The intentional avatar design in an XR environment can reduce distractions about appearance and allow both instructors and students to concentrate on the academic material.
Another tool to reduce bias is to allow students anonymity within the XR experience, especially if students are using text-based chat or voice-to-chat technology, rather than voice, to communicate. Sharing thoughts and opinions can be intimidating in class, especially if a sense of community or safety has not yet been established. Instructors can approach this from different perspectives:
- To create an entirely anonymous experience, where students are assigned an Anonymous ID (AID), with their avatar to sign into the virtual classroom. Student logins can be shuffled for each individual class experience, so students don’t reuse the same AID.
- To build opportunities for anonymous polling and/or discussions within the lesson plan.
Teaching tools, (e.g., interactive 3D models or post-it notes on a virtual whiteboard) should be exciting learning opportunities for students, as long there is no fear of judgement from their classmates. Dengel and Mägdefrau (2018) presented how effective “design of the immersive EVE (educational virtual environments) can strengthen the positive effect of cognitive factors on learning activities”.
Providing students with the opportunity to anonymously contribute to the class discussion can significantly increase their willingness to share. Anonymity also helps instructors better understand the class’ learning and knowledge retention. Of course, with anonymity, there is a risk of students making off-topic comments without fear of retaliation. Establishing class guidelines or agreements at the start of an XR experience about behaviour, language, and consequences is highly encouraged.
AI and Data Analytics
Data points based on avatar movement, such as eye motion and time spent interacting with 3D models of learning objects, can be incredibly helpful to instructors. Instead of manually noticing certain students lose focus during a large class lesson, data analytics can provide deeper insights on engagement, both real-time and post class. AI integration can rapidly analyze data points to provide instructors with information about the behaviour of their students on an individualized basis within the XR environment. Knowing if a student has not moved or interacted with learning objects in x amount of time can prompt the instructor to check in with that particular student to get them involved with the learning activity.
Using avatars with an AID and purple body colour reduces the possibility for an AI system to be trained with biased data based on skin colour or gender, resulting in algorithmic discrimination (Buolamwini and Gebru, 2018). Without being able to make judgements or assumptions about which student is not following directions or making a specific contribution to class discussion, an instructor can grade the student based on their work in the class.
XR platforms should be built with student accessibility in mind from the start. There are many aspects of accessibility, such as compatibility with screen readers, e.g., Jaws and Voiceover, which has historically been overlooked. In an ideal world, 3D interactive objects should have alternative text specific to the lesson, with the option to be read aloud when selected. Students should be able to access all tools and commands exclusively with a keyboard, in addition to clicking with a mouse. A “follow along with the instructor” mode should be optional, for students who may have trouble navigating the XR experience on their own. Embedded videos should have closed captions. The colour contrast of the entire experience and objects should be tested to ensure it passes AAA WCAG 2.0 standards. It is critical that XR platforms meet the needs of all users to reduce barriers to learning and access.
Structurally reducing implicit bias within an XR experience can help students engage with course materials even further to achieve the desired learning outcomes. It is important to realize that tools to accomplish this are in conjunction with the visual and teaching capabilities of teachers today, not instead of them. Combining the best abilities of teachers with a tool to combat implicit bias is a win-win for the classroom. Add to that the ability to provide analytical data to point out potential engagement issues within the classroom and anonymity capabilities to provide for more diverse conversations and the potential for meaningful engagement in the class increases dramatically.
For more Insights on XR in education, you can visit our Education category page within our Insights and case studies library.