Surveillance in Online Classrooms

When referring to online education, many educators and administrators worry about the value of online learning and having less oversight of students, thereby rationalizing the use of surveillance tools to enhance online teaching (Armstrong & Hamilton, 2015; Sabrina et al., 2022; UAF CTL Staff, 2020;). Meanwhile, ed-tech companies capitalize on this perceived need for educational security by marketing surveillance tools as essential for maintaining academic integrity (surveillance as control) and educational retention (surveillance as care) (Casella, 2010, pp. 73–76; Harwell, 2020). Since the COVID-19 pandemic, ed-tech companies specializing in anti-cheating software have drastically increased sales (Harwell, 2020). In this model, however, ed-tech companies provide the software to the institution with the arrangement that the faculty will implement the tool in the online classroom. Those educators, therefore, assume the responsibility for extending control and care with little knowledge of the capabilities of the application or the surplus benefits that the university or company receives (Casella, 2010, pp. 73–76). Ed-tech companies make these tools appealing to instructors by promoting their analytics and automation to “busy teachers” (Peterson, 2020).

Often administrators and information technology (IT) staff make contractual agreements with big ed-tech companies without including the faculty governance process. Ed-tech staff teach faculty how to use the tools through tutorials and workshops, but administrators have provided little institutional space to discuss the ethics of using such applications during assessments or the impacts that the tools have on student and faculty rights (Cohn, 2021; Paris et al., 2021). Although the COVID-19 pandemic did not create the conditions to allow for this type of corporate overreach into online classrooms, the increased use of surveillance applications during this period did exacerbate already existing divisions and hierarchies across the university (Cohn, 2021; Kelley, 2021a). The ranked structure of workers within campus communities has created conditions that often deter conversations between the staff selecting and administering the technology and the faculty using the technology (Cohn, 2021). Additionally, the values of university IT and ed-tech departments often align more closely with the corporate strategies of tech companies, amplifying social inequalities by transferring racist and sexist biases into product design and not consistently prioritizing privacy (Anderson, 2019; Dubrofsky & Magnet, 2015; Noble, 2013).

During the COVID-19 pandemic, some campus administrators and ed-tech companies explained that using these surveillance applications marked good teaching practices and contributed to positive institutional “cultures” revolving around data (U.S. Department of Education, 2012, p. 46). Since 2012, the US Department of Education has viewed the benefits of surveillance through data analytics and suggested that the “higher education sector[s] should increase the use of educational data mining and learning analytics to improve student learning” (U.S. Department of Education, 2012, p. 46). It recommended that “educators should develop a culture of using data for making instructional decisions” (2012, p. 46). More recently, a teaching centre also encouraged its faculty to use analytics so that they could detect “disengaged behaviors and take actions to intervene before missed classes and failed assignments lead to students failing or dropping classes” (Center for Transformative Teaching, n.d.). Instructure, the parent company of the popular LMS known as Canvas, advertised its reports as “data insights for student success,” explaining that, “without face-to-face interaction, it can be difficult to know if students are engaged and on track to achieve target academic outcomes” (Instructure, n.d.). According to these entities, using data in online teaching equates to better learning practices.

In practice, students and watch groups have communicated concerns about data security when using ed-tech applications such as analytics, automated grading, proctoring, and cameras within online learning spaces. Students have indicated that they do not always know when and how they are being monitored by the instructor since they do not have easy access to the same records (Romano, 2021). Additionally, users have questioned the use of biometrics by proctoring services to determine student behaviour in terms of cheating. These tools record students while taking an exam, reporting on body movements perceived as irregular by monitoring their eyes, sounds, browser activity, and the presence of other people in the room (Kelley & Oliver, 2020; Nast, 2020). These systems also use personal information to confirm the identities of students with “facial recognition” technologies and “personally identifiable information,” much of which is protected by the Family Educational Rights and Privacy Act (Kelley & Oliver, 2020). Students have also raised concerns about how their data is used by these corporations, which collect information such as IP addresses and browser histories without a clear accounting of how they keep that data safe from increasing cyberattacks or whether they make profits using student information and labour (Kelley & Oliver, 2020; Retta, 2020; Wang, 2021). Professionals who encourage the use of proctoring services or require students to turn on cameras assume that learners engage with academic work in solitary spaces, with strong internet connections, while not accounting for housing conditions or the diversity of students’ learning needs (Finders & Muñoz, 2021; Woldeab & Brothen, 2021). Many of these requirements do not match the educational realities of the students who traditionally take online courses (Chick & Hassel, 2009, p. 201).

Many students have pointed out the social inequalities that surveillance technologies have entrenched in online classrooms. Students have complained that conditions such as lighting and working in semi-public and public spaces have made the proctoring software trigger warnings for the instructors to review for cheating (Claburn, 2021). Students have also indicated that these technologies do not account for bodily and cultural diversity, including skin tone, habits of movement, modes of dress, and disability (Claburn, 2021; Harwell, 2020; Hill, 2021; Retta, 2020). Other students have claimed that these systems cause additional stress since reporting systems that measure engagement based on clicks and page timers often produce false readings by recording erroneous data and that proctoring services require uncomfortable physical conditions. These students along with their peers have resisted these new norms by using petitions and social media critiques that have encouraged some faculty members and administrators to reconsider their use of surveillance tools (Harwell, 2020; Hill, 2021; Kelley, 2021c; Rader, 2021; Retta, 2020; Singer, 2021; York, 2021).

Surveillance and Feminist Pedagogy

Student voices along with some instructional advocates should not be the only opposition to the misuse of surveillance and quantitative tools in higher education. When COVID-19 forced many educators to transfer their curricula to the digital modality, many administrators and learning centres encouraged faculty to use digital tools focusing on top-down approaches to their online courses that could measure learning through surveillance tools (Juhasz et al., 2020, p. 1). Through this system, the content delivery for many emergency remote courses mimicked MOOCs that provided information through a single-direction method of delivery. This design did not account for students’ individual learning needs or life experiences that influence learning. While encouraging top-down approaches and surveillance tools that automate and quantify assessment, administrators overlooked the work of feminist educators who had been using active learning strategies in distance learning courses for more than a decade (FemTechNet White Paper Committee, 2013, pp. 2, 4; Chick & Hassel, 2009, p. 197). Feminist educators have pointed out the inequities often entrenched by surveillance applications. These strategies counter the feminist aims of creating supportive learning environments and do not capture the complexities of the learning process (FemTechNet, 2020; Romano, 2021).

Feminist pedagogy does not align with the use of surveillance and quantitative methods that focus on a solitary collection point and neglect the holistic student experience (FemTechNet White Paper Committee, 2013, pp. 2, 4). Instead, feminist educators resist surveillance assessments by implementing active learning activities and authentic assessments while instilling community building that emphasizes care and trust among students (Wexler, 2015). Feminist educators continuously attempt to divest power from the educator and to empower the student to collaborate within digital learning spaces (Bond, 2019; Romero-Hall, 2021). They encourage active learning and collaborative activities that use three-directional modes of communication, such as instructor-to-student, student-to- instructor, and peer-to-peer (Chick & Hassel, 2009; Sharoni, 2020). These instructors encourage participation by providing students with options for how and when to engage content (FemTechNet White Paper Committee, 2013, p. 1). They encourage students to learn from mistakes by assessing the process of learning by doing and self-reflection rather than by proctored tests (Sharoni, 2020; Stommel, 2017). Using flexible methods such as asynchronous activities allow instructors to measure engagement outside camera participation and clicks while respecting students’ boundaries and privacy (Juhasz et al., 2020). Feminist educators also provide opportunities for students to learn from multiple perspectives and refer to knowledge vested outside the academy to move beyond top-down learning approaches less assessable by numerical data (Chick & Hassel, 2009; Sharoni, 2020; Stephens & Maclaren 2022).

On this current trajectory, surveillance and analytical tools will continue to expand online, creating questions about ethical and privacy practices. Educators cannot continue to ignore the problem or even refuse to use all ed-tech tools. Instead, they need to learn how to use various technological tools and actively question the role of technology applications in teaching (Chick & Hassel, 2009, p. 197). Understanding the terms of service, and how the application is integrated into the LMS, will better equip the instructor to determine the ethical implications of using the tool. Also, educators should research the company’s website and read reviews to understand who developed the technology and its intention. Instructors should communicate with students about the need to protect themselves on the web, point to the terms of service of using a tool, and discuss any requirements for additional accounts. Instructors should come up with alternative learning experiences that give students flexibility and choice to decide when and how to use a technical tool. If using reports or analytics, instructors should walk students through the analytics at the beginning of the class and provide them the reports that they use in graded assessments (Doersch et al., 2022).

Educators and designers should encourage each other to understand what the LMS reports measure and the original intention of those reporting systems. Additionally, they need to use “feminist objectivity” or supplementary assessments such as self-reflections to examine which other conditions and narratives about the data best represent the student’s experience (D’Ignazio and Klein., 2020, p. 83). These techniques allow educators to embrace “embodiment” with data by including descriptions and viewpoints that capture the work and experiences that the numerical information represents (D’Ignazio and Klein, 2020, pp. 76–77, 83, 95). When able, feminist educators, especially those with academic freedom, should confront administrators’ misconceptions that data-driven reports provide a neutral and full picture of students’ learning, seek explanations from technology staff regarding the application’s privacy and terms of use, and push back on claims that these tools provide best examples of teaching in workshops, committees, and faculty meetings.

Feminist educators need to adapt their practices continuously in an increasingly digital landscape and resist surveillance approaches in online courses. As administrators encourage the use of more corporate ed-tech tools as online teaching best practices for “control” and “care,” educators should extend their understanding of surveillance beyond analytical interventions. Instead, an essential component of feminist pedagogy will include thinking about how these tools affect the security and equity of students within the social and cultural structures of the digital classroom. Student complaints resulting from monitoring errors indicate that educational surveillance technology does not always present an accurate depiction of their experiences.

Many students and some faculty members have also indicated concerns about privacy and data security and question the ethics of allowing companies to collect student data. The misuse or unintentional use of many of these tools causes tensions while heightening inequalities among students within online classrooms. Surveillance tools, such as analytics, do not account for the personal interactions and experiences between teachers and students during the learning process and constrict the definition of learning to meet standardized objectives that can be measured via data. Instead of implementing summative assessments that require proctoring technologies, measuring attendance and engagement via analytics, and providing participation grades through automated processes or video engagements, online instructors should embrace feminist teaching tenets refined specifically for the online modality.

Key Takeaways

• Ed-tech companies sell surveillance tools to universities for faculty implementation in online courses under the guise of increasing integrity and retention efforts with little faculty governance.
• Critiques of the impact of surveillance on students’ well-being and security in the classroom have become more prevalent among students, watch groups, and some educators.
• Instead of placing the burden of protest on students, instructors should de-emphasize the use of data and surveillance in their classrooms.
• Feminist educators should design student-centred learning experiences specifically for online courses that encourage active engagement and integrate technological components to build caring digital communities.

Notes

1. 1  Thank you to Kailen Mitchell, Rachel Tabor, Sophie Tanen, and Ainsley Anderson, who helped to gather primary sources and format references.

2. 2  When using the term “feminism,” I refer to intersectional feminisms. Elizabeth Losh and Jacqueline Wernimont define intersectional feminism as “acknowledg[ing] the interactions of multiple power structures (including race, sexuality, class, and ability)” (Losh et al., 2018, p. xi).

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