Encouraging Equitable Decision-Making in Academic Technology

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Now is the time for academic technology decision-makers to close the gap between technology decisions and DEI concerns.

Encouraging Equitable Decision-Making in Academic Technology
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In higher education, processes for deciding which academic technologies to procure are often opaque, unclear, and idiosyncratic to everyone involved. The decision-makers for procuring particular tools can range from senior-level administrators to middle-level directors across divisions ranging from academic affairs to student affairs and, of course, to information technology. The decision-makers, in other words, are often removed from the classroom contexts by either a minor or a significant degree.

Meanwhile, technology procurement decisions in higher education have wide-ranging consequences and long-term implications. Rarely are technology procurements in higher education a minimal investment. Most technology procurements involve multiterm evaluation periods and, after that, are often locked into multiyear contracts for usage. On top of all the long timelines for procurement and tool maintenance, mechanisms for collecting student and faculty feedback about particular tools and technologies are often lacking. This means that after a technology contract has been signed and a tool has been procured, there may be minimal opportunities for institutions to reassess based on faculty and student experience.

We also know that technology decisions can have tremendous implications for concerns around access and diversity, equity, and inclusion (DEI). Certain tools and technologies may reinforce systemic biases or actively cause harm to students. Many remote proctoring tools, for example, rely on facial and body recognition, which has known negative impacts on disabled students and students of color.Footnote1 Yet the ability for an institution to quickly break a contract for a harmful tool is complex and time-consuming. With an interpersonal or classroom DEI conflict, the issue can be resolved by individual parties, but if a piece of infrastructure or software is at issue, an institution generally needs much more time to disassociate or end contracts involving that particular tool.

Closing the Gap between IT Decision-Making and DEI Strategy

Given that various hybrid, online, and blended learning experiences are on the horizon for higher education in the 2021 academic year and beyond, now is the time for academic technology decision-makers to do two things to close the gap between technology decisions and DEI concerns:

  1. Create transparency around academic technology procurement workflows
  2. Center DEI principles when making academic technology procurement decisions

The selection of the right technology for student accessibility and academic support is a critical decision and one that can have unintended and long-reaching consequences for the full campus community, from students to faculty to staff. Given that increasingly diverse groups of students will be using academic technologies into the foreseeable future, higher education leaders and faculty have an obligation to make procurement decisions that do not unintentionally exclude students from engaging in their learning experiences.

Situational Decision-Making and Reasoning: Establishing Motivations and Identifying Complexities

Human motivation influences decision-making. Decision-making about technology selection is no different. Keeping this in mind, we've outlined a few reasons that faculty and administrators select certain educational technologies.

Tractability and Compliance. Colleges and universities have legal responsibilities to comply with federal laws about students' privacy, specifically around grading and assessment. For example, the Family Educational Rights and Privacy Act (FERPA) intends to protect student information about grades and assessment. Keeping students' grades and feedback about their academic work secure drives many institutions to adopt solutions that focus on containing grades and class information within campus sign-on ecosystems, such as the learning management system (LMS) and other assessment-based tools (e.g., proctoring software). Many educators have concerns about using the LMS and proctoring software because these kinds of systems are often built with extensive surveillance tools that track students' engagement within the application.Footnote2 Proctoring tools in particular have come under scrutiny, rightfully so, because of their artificial intelligence (AI) features, which can accuse students of cheating even if students are not engaging in dishonest behavior.Footnote3 The ethics of FERPA-compliant tools are thus worth considering, to the extent legally possible, when approaching the acquisition of technology from an equity-based lens.

Operations Maintenance and Productivity. Given the ways in which educational and civic infrastructure have now largely been digitized, colleges and universities may choose to procure technology that fulfills distinct productivity and workforce needs. Most colleges and universities invest, for example, in an "office tools suite," which includes word processing, spreadsheet creation, slide-presentation creation, and file storage. The Google and Microsoft suites are among the most common of these enterprise-level office tools.

Novelty and Originality. Technology changes quickly, which means that many faculty and administrators may be attracted to solutions that reflect the latest developments in hardware or software. Some educational technology may be procured so that a college or university can demonstrate its commitment to adopting the most "cutting-edge" solutions. Many "innovation-driven" missions depend on an infrastructure that supports using new technology largely because it's new. Some faculty and administrators may also want to adopt new technology to be responsive to changes they see in their students' technology experiences or within their own experiences as users and consumers of technology. While novelty for novelty's sake may not be a pedagogically driven reason for technology adoption, it can be a large motivator to demonstrate responsiveness to technology-based trends.

Integration and Exploration: Some college and university decision-makers may adopt technology that better integrates and aligns with specific pedagogical strategies or techniques. For example, e-portfolios have long been popular because they are simultaneously an assessment instrument and an opportunity to showcase work online. E-portfolios can also align well with a variety of teaching styles and can be flexibly adapted to different sets of disciplines and curricula. Other technologies are essential for projects in specific disciplines. For example, geographic information systems (GIS) software is an essential tool to represent geographic and spatial data for scholars and students in geographic and environmental science disciplines. Faculty needs for specialized, discipline-specific data that can be integrated into specific curricula is thus a huge driving factor for procurement.

Alliance and Collaboration. Given that many means of communicating are moving online, colleges and universities may adopt technologies that promote better collaboration between institutional stakeholders. Videoconferencing tools, such as Zoom and Webex, were highly visible during the COVID-19 pandemic as meetings and live conversations moved to remote contexts. Other collaboration tools might be text-based "chat" tools that individuals can use to reach each other either within or outside of real time (popular examples include Slack and Microsoft Teams). Many colleges and universities may be interested in investing in these types of tools, which have the potential to increase interaction and connection.

This wide range of motivations for adopting specific technologies in higher education demonstrates the complexity involved in making a sound technology decision. It is impossible for any tool-procurement decision-maker to accommodate all of these possible motivations. However, given that the responsibility for procuring tools falls largely on a narrow and specific group of administrators, typically in the IT organization, strong communication about these motivations, which may directly overlap with campus DEI initiatives, is needed.

Ideally, administrators would work to gain the broadest insight possible into the various motivations that may be animating decisions to investigate particular tools. Yet IT decision-makers are often not directly part of DEI campus conversations. In fact, technology decisions are often removed from, or seen as operating separately from, campus DEI strategic plans. This means that procurement decision-makers often don't have visibility into DEI concerns and that they may not be able to fully anticipate the potential harm of certain tools and technologies, particularly for students with disabilities and students of color.

Where DEI and Technology Intersect: Recognizing Limitations in Access for Disabled Students

Technology implementation is not neutral, and when supporting students with disabilities and students of color, in particular, we need to be cognizant of the ways in which technology access (or lack thereof) can change students' experiences of engaging with their learning environments.

The numbers of students with disabilities on college/university campuses may be larger than technology leaders think. A survey conducted twenty years ago by the Department of Education National Institute on Disability and Rehabilitation found that of the 1,414 respondents (33 percent with "some college" experience and 15 percent graduated from college or with post-graduate work), 64 percent used some assistive technology. According to Carol P. Kaplan and Emily Shachter, many adults who reach adulthood are never diagnosed with learning disabilities, but the lack of diagnosis is the core issue of barriers to those with learning difficulties. In fact, the Learning Disabilities Association of America found that as many as 60 percent of adults with severe literacy deficits have undiagnosed or untreated learning disabilities. Most recently, a 2019 book by Lynne C. Shea, Linda Hecker, and Adam R. Lalor suggests that learning disabilities—both diagnosed and undiagnosed—are often invisible, and students still choose not to request support via accommodations even if they rely on some form of technology.Footnote4

This high number of undiagnosed or untreated learning disabilities stems from an arduous evaluation and documentation process. That is, if students need access to assistive technology, a psychological evaluation is required from a certified or licensed psychologist or in some cases a physician. This evaluation needs to be documented in order for students to receive campus-supported accommodations. Many students face financial hardships, which may prevent them from visiting such providers and gaining the necessary documentation to support securing accommodations to use assistive technology.

Learning disabilities also remain heavily stigmatized in many cultures and communities and even in some learning environments. In 2000, Myrna Orenstein wrote that individuals who are undiagnosed experience "imprisoned intelligence" while also experiencing shame and embarrassment within their learning experiences.Footnote5 Beyond basic financial barriers to accessing learning disability evaluation, then, many students may never seek evaluation because they may perceive the evaluation and subsequent diagnosis as a reflection of their own personal or familial failings. While educators can support students in their decision to seek out evaluations, the internalized stigma to doing so may be challenging for many students to overcome.

Where DEI and Technology Intersect: Reducing Negative Experiences for Students of Color

Intentional or unintentional racism within the technology diminishes experience for students of color the same way that lack of access diminishes learning for students with disabilities. This is known as techno-racism. The lack of awareness of the inherent bias within much of the coding found in proctoring software and other technologies can significantly contribute to negative outcomes for students of color. Moreover, administrators tasked with making procurement decisions are often unaware of the potential negative consequences embedded within much of the technologies currently available.

For some historical context, many individuals from minority groups mistrust the sciences and technology because of unethical research practices that led to negative outcomes, most notably within Black and Latinx communities.Footnote6 The Tuskegee Experiment is an infamous example of how unethical scientific practice betrayed the trust and endangered the lives of Black men. Between 1932 and 1972, researchers asked 600 Black men, without informed consent, to participate in a study that explored the effects of syphilis, while explaining to participants they were being treated for "bad blood." Researchers did not fully disclose the high risks associated with this study, and they exposed participants to significantly more risk than is ethically acceptable. The lack of transparency and informed consent led to a litany of negative outcomes for participants and their descendants.Footnote7 Beginning in 1946, the US government conducted similar experiments in Guatemala, also resulting in long-lasting health and emotional consequences for the more than 5,000 uninformed and unconsenting participants.Footnote8

While both of these notable historical examples come from the context of the health and medical sciences, their ramifications have ripple effects in educational technology implementations. Specifically, building trust across the institution and offering transparency—about how educational technology solutions will be implemented, when they will be implemented, and who will be impacted by the implementation—are mission-critical.

The strongest attention to students' success with using educational technologies for their learning has been in the context of online education. In particular, researchers have explored the correlation between students' ethnic identities and their retention in online classes. With the exception of Black students, students of color tend to have significantly poorer retention in online classes than their White peers.Footnote9 As Papia Bawa described in a literature review of the research on retention in online learning: "Nuances of cross-cultural communication, coupled with technological impediments, can create untenable learning environments, leading to attrition."Footnote10 These nuances have been identified and analyzed by numerous online learning scholars, particularly through the lens of Culturally Responsive Teaching (CRT), which can improve community, humanize learning experiences, and build empathy.

What could use greater exploration is an understanding of the tools that may shape and impact the interactions within online learning environments. That is, given the rapid adoption of online learning tools during the COVID-19 pandemic, instructors and administrators selecting these tools would be helped by having an awareness of humanizing and culturally responsive teaching approaches that need to be facilitated with digital tools. This could lead to better decision-making about how tools can align with effective instructional practices. It's safe to say that the lines between online and face-to-face learning will continue to blur in the future and that, as a result, the relationship between teaching with technology and teaching in culturally responsive ways will become stronger.

To begin to reduce negative outcomes for students of color, educational technology leaders can connect with their DEI offices to discuss the role that technology has played in the past and areas where DEI intersects with the use of specific technologies on campus. The IT organization and the DEI office may want to work together to produce a commitment to DEI for IT departments. A good example is "IT's Commitment to Diversity, Equity, and Inclusion," developed by the Division of Information Technology at California State University, Fullerton.

Encouraging Reflective Technology Decision-Making

Decisions about technology are often made with specific goals in mind. In other words, decisions about the use of technology and its application within an institution may be transactional in nature. Specifically, technologies may be meeting the criteria for goals and objectives within a greater strategic plan but may be misaligned with the practices of students and faculty. Self-reflection, a significant aspect of leadership, can support best outcomes for making decisions related to the selection of academic technology while also keeping goals in mind.

According to Sarah J. Donovan and her colleagues, "Self-reflective decision making requires decision makers to consciously and continuously reflect on themselves and the situation."Footnote11 Moreover, as Michael Reynolds has noted, leaders benefit from "a commitment to questioning assumptions and taken-for-granteds embodied in both theory and professional practice."Footnote12 This is also true of decision-making in higher education. Leaders responsible for making influential decisions about technology and the role that technology will play in the experiences of faculty and students will benefit from a self-reflective exploration of the theoretical and practical applications of academic technology.

The following are some questions that technology decision-makers may want to consider:

  • Who ultimately benefits from this decision?
  • How similar is this proposed technology to the technology we are currently using?
  • What is the most equitable way to implement this technology adoption?
  • If we made this change today, right now, what would that look like?

Faculty decision-makers may want to consider the following questions:

  • Historically, what is my personal relationship with academic technology?
  • How have I viewed the use of technology? Is the adoption of technology for the purpose of true access for all students, or is the implementation of technology more for compliance?
  • How might such views influence the learning of students within my courses?

Identifying a Heuristic

To center the procurement of tools that keep DEI and accessibility principles in mind, we need to develop academic technology decision-making heuristics that focus on these principles. Many heuristics are targeted either toward faculty members making individual educational technology decisions for their class or toward a collective of faculty and IT staff making these decisions.Footnote13 Where we aim to intervene in this conversation is in developing a heuristic that brings together faculty, IT staff, and the DEI office for choosing educational technology tools to make education more equitable and accessible.

Table 1 shows equity-minded decision-making characteristics used in DEI contexts but often overlooked in academic technology procurement. We created this table as a general guide for higher education leaders to explore, discuss, and support the use of academic technology across an institution. The first column is a list of characteristics that can support a more equity-minded thought process. The second column is a list of considerations that can expand decision-makers' thinking about the technology and its potential applications in the learning environment. The third column lists action steps that a decision-maker can take for improving any academic technology procurement that may already be under way.

We anticipate that this table can be used in the following ways:

  1. As a conversation-starter within IT divisions when new technology procurements are considered
  2. As a tool to bridge conversations between IT divisions and DEI offices when collaborating on academic technology procurements that impact teaching and learning
  3. As a heuristic or rubric for technology pilots in higher education institutions
  4. As a tool for personal reflection on how past decisions have been made and what qualities might be needed to adjust for future decision-making

Table 1. Equitable Decision-Making for Academic Technology Procurement

Equity-Minded Decision-Making Characteristics Considerations Prior to Taking Action DEI Action Steps

Awareness: A healthy understanding of historical disparities of technology and its uses

  • Adopting technology through strength-based and needs-based perspectives
  • Include DEI officers in dialogue to understand currently unknown consequences of the technology adopted previously.

Understanding: The comprehension of boundaries and limitations of the technology

  • Compassionate action versus indifferent response
  • Meaningful dialogue
  • Do your research.
  • Understand the pitfalls and unintended consequences of technology prior to the investment.

Orientation: The identification of origin for technology adoption

  • Clarity and transparency for all stakeholders about why technology was procured
  • Create a checklist for the adoption of technology.
  • Include various stakeholders in the selection process.

Commitment: The level of dedication applied to the implementation of the technology

  • Identifying if technology is integrated into the capital project of an institution
  • Create a mission statement or pledge to support effective decision-making surrounding technology implementation.
  • Be transparent.

Openness: The ability to lack restriction when exploring reasons to implement or reject technology

  • Development of growth mindset for IT leaders
  • Establishment of innovation with purpose
  • Identification of leadership values associated with technology implementation
  • Develop an appreciation for new ideas, discussions, and experiences with technology and its uses.

Collaboration: Working together to achieve intended outcomes

  • Making informed decisions
  • Increasing buy-in or buy out
  • Consider the following when collaborating with stakeholders: What is more important, information giving or information gathering?

Actualization: Understanding the reality of technology for the stakeholders

  • Understanding the full potential of the relationship between stakeholders and technology selection
  • Start small and think big.
  • What is the most meaningful potential outcome(s) for faculty members and students when using thetechnology under consideration?

Next Steps

Centering DEI in academic technology decision-making goes beyond just picking tools; it must also include deliberate strategies for building awareness among all students and faculty. For example, many colleges and universities invest in tools that support a wide variety of students, but not all students and faculty may have knowledge of particular tools or understand how tools may best meet their needs.

Knowing that many students may not have formal accommodations for disabilities, faculty and staff alike should be aware of the accessibility features built into and accessible within everyday hardware and software. By understanding the range of accessibility features available within an existing tool suite, faculty and staff can point students to the resources that they might need to be successful in their learning experiences, regardless of their disclosure and documentation of disability. For that reason, before making a decision on a specific technology, administrators can review many of the no-cost technology options that are currently available (e.g., phone and computer apps) and any other technology that is readily available and applicable for students who may need the support but will not be able to access such services through official campus channels.

For example, most mainstream laptops, desktops, and mobile phones include accessibility tools, such as speech-to-text applications and color contrast modifiers that could impact viewing and use. Many students use a diverse array of software for their learning, and accessibility features may also be built into commonly used applications such as the institutionally supported LMS and office productivity tool suites. Yet not all students and faculty may be aware that these features exist and may not know how these features can help them and support their learning. Academic technology offices should partner with disability and accessibility centers to provide resources and workshop opportunities to understand these available features. Doing so could also mean working with peer and academic resource centers or peer learning centers to ensure that students can help other students understand these tools at their disposal.

A common misunderstanding of educational technology is that it is used enthusiastically and primarily by "early adopters" or by those who are "tech-savvy." However, technologies of all kinds, digital or not, are simply part of our learning environments, and we can help students realize how these technologies may enhance—or, in some cases, detract from—their lived experiences. In other words, we cannot assume that simply procuring tools means that faculty and students will understand how those tools work and how they matter. Awareness-building and deliberate training opportunities will be ways to drive adoption and also to allow for fuller and more meaningful conversations about technology usage on campus.

Making decisions about academic technology involves a complex tapestry of considerations. The process demands openness, decision-making skills, compassion, and an equity mindset. It also requires individuals to make long-range decisions while using the current contextual and practical experiences of students, faculty, and staff. By doing so, we can create an environment of equitable decision-making in academic technology.


  1. For example, see Mitchell Clark, "Students of Color Are Getting Flagged to Their Teachers Because Testing Software Can't See Them," The Verge, April 8, 2021; Shea Swauger, "Our Bodies Encoded: Algorithmic Test Proctoring in Higher Education," Hybrid Pedagogy, April 2, 2020. Jump back to footnote 1 in the text.
  2. For the K-12 context, see Priya C. Kumar, Jessica Vitak, Marshini Chetty, and Tamara L. Clegg, "The Platformization of the Classroom: Teachers as Surveillant Consumers,"Surveillance & Society 17, no. 1/2 (2019). For the higher education context, see Sharon Slade and Paul Prinsloo, "Learning Analytics: Ethical Issues and Dilemmas," American Behavioral Scientist 57, no. 10 (2013). Jump back to footnote 2 in the text.
  3. Jeffrey R. Young, "Pushback Is Growing against Automated Proctoring Services, but So Is Their Use," EdSurge, November 13, 2020; Jason Kelley, "A Long Overdue Reckoning for Online Proctoring Companies May Finally Be Here," Electronic Frontier Foundation (website), June 22, 2021. Jump back to footnote 3 in the text.
  4. Dawn Carlson and Nat Ehrlich, Assistive Technology and Information Technology Use and Need for Persons with Disabilities in the United States, 2001 (Washington, DC: US Department of Education, National Institute on Disability and Rehabilitation Research, August 2005); Carol P. Kaplan and Emily Shachter, "Adults with Undiagnosed Learning Disabilities: Practical Considerations," Families in Society: The Journal of Contemporary Social Services 72, no. 4 (1991); "Your Chances of Knowing Someone with a Learning Disability Are Very Good: Did You Know?" Learning Disabilities Association of America (website), accessed September 10, 2021; Lynne C. Shea, Linda Hecker, and Adam R. Lalor, From Disability to Diversity: College Success for Students with Learning Disabilities, ADHD, and Autism Spectrum Disorder (Sterling, VA: Stylus Publishing, 2019). Jump back to footnote 4 in the text.
  5. Myrna Orenstein, "Picking Up the Clues: Understanding Undiagnosed Learning Disabilities, Shame, and Imprisoned Intelligence," Journal of College Student Psychotherapy 15, no. 2 (2002). Jump back to footnote 5 in the text.
  6. Institute of Medicine, Committee on Quality of Health Care in America, Crossing the Quality Chasm: A New Health System for the 21st Century (Washington, DC: National Academies Press, 2001). Jump back to footnote 6 in the text.
  7. Darcell P. Scharff et al., "More Than Tuskegee: Understanding Mistrust about Research Participation," Journal of Health Care for the Poor and Underserved 21, no. 3 (August 2010). Jump back to footnote 7 in the text.
  8. Michael A. Rodriguez and Robert García, "First, Do No Harm: The US Sexually Transmitted Disease Experiments in Guatemala," American Journal of Public Health 103, no. 12 (December 2013). Jump back to footnote 8 in the text.
  9. Pedro A. Willging and Scott D. Johnson, "Factors That Influence Students' Decision to Drop Out of Online Courses," Journal of Asynchronous Learning Networks 13, no. 3 (2009), p. 125; Youngju Lee and Jaeho Choi, "A Review of Online Course Dropout Research: Implications for Practice and Future Research," Educational Technology Research and Development 59 (2011); Jump back to footnote 9 in the text.
  10. Papia Bawa, "Retention in Online Courses: Exploring Issues and Solutions—A Literature Review," SAGE Open 6, no. 1 (2016). Jump back to footnote 10 in the text.
  11. Sarah J. Donovan, C. Dominik Güss, and Dag Naslund, "Improving Dynamic Decision Making through Training and Self-Reflection," Judgment and Decision Making 10, no. 4 (July 2015), p. 285. Jump back to footnote 11 in the text.
  12. Michael Reynolds, "Critical Reflection and Management Education: Rehabilitating Less Hierarchical Approaches," Journal of Management Education 23, no. 5 (October 1999). p. 538. Jump back to footnote 12 in the text.
  13. Michelle D. Miller, "How to Make Smart Choices about Tech for Your Course," Chronicle of Higher Education, August 26, 2019; Lauren Anstey and Gavan Watson, "A Rubric for Evaluating E-Learning Tools in Higher Education," EDUCAUSE Review, September 10, 2018. Jump back to footnote 13 in the text.

Courtney Plotts is National Chair of the Council for At Risk Student Education and Professional Standards.

Jenae Cohn is Director of Academic Technology at California State University, Sacramento.

© 2021 Courtney Plotts and Jenae Cohn. The text of this work is licensed under a Creative Commons BY-NC-SA 4.0 International License.