During spring 2020 remote instruction, internet connectivity and hardware/software problems interfered with course participation for large shares of undergraduates¶

Claim · All claims
Evidence · 2 studies (3 entries) · 2 associational r2 · q2–q3
Currency · newest study 2021 · checked against its sources 2026-10-19 (automated, 3 of 3 entries) · not reviewed by a person

Subclaims¶

q2 i? 44% of surveyed students reported internet connectivity issues serious enough to interfere with attending or participating in their courses at least occasionally, with 16% experiencing them often or very often; 23% reported hardware or software problems at least occasionally (8% often or very often). → Means 2021

q3 i? Internet connectivity issues interfered with course attendance or participation at least occasionally for 44 percent of students, with 16 percent experiencing them often or very often. → Means 2020

q3 i? Almost a quarter of students (23 percent) experienced hardware or software problems serious enough to impact participation at least occasionally. → Means 2020 (2)

Evidence¶

Means 2021¶

Means, B., Peters, V., Neisler, J., Wiley, K., & Grifths, R. (2021). Lessons from remote learning during COVID-19. Digital Promise. https://doi.org/10.51388/20.500.12265/116

q2 · i? · associational · r2

National probability-based KnowledgePanel survey of undergraduates whose in-person courses went fully remote in spring 2020; final sample of 1,008. The survey found "44% of students" faced connectivity issues interfering at least occasionally, and separately almost a quarter (23%) reported hardware or software problems at least occasionally.

"Internet connectivity issues were serious enough to interfere with students’ ability to attend or participate in their courses at least occasionally for 44% of students, with 16% of students reporting that they experienced such problems often or very often."

Means 2020¶

Means, B., and Neisler, J., with Langer Research Associates. (2020). Suddenly Online: A National Survey of Undergraduates During the COVID-19 Pandemic. San Mateo, CA: Digital Promise. https://digitalpromise.dspacedirect.org/items/32aee7c4-5363-4d50-bc9c-a338e7dfac7e. doi:10.51388/20.500.12265/98

q3 · i? · associational · r2

Structured-response survey items asked students how often connectivity problems interfered with course participation. Ninety-five percent accessed courses via home internet; videoconferencing's high bandwidth demands are given as context.

"Internet connectivity issues were serious enough to interfere with students’ ability to attend or participate in their course at least occasionally for 44 percent of students, with 16 percent of students experiencing such problems often or very often."

Means 2020 (2)¶

Means, B., and Neisler, J., with Langer Research Associates. (2020). Suddenly Online: A National Survey of Undergraduates During the COVID-19 Pandemic. San Mateo, CA: Digital Promise. https://digitalpromise.dspacedirect.org/items/32aee7c4-5363-4d50-bc9c-a338e7dfac7e. doi:10.51388/20.500.12265/98

q3 · i? · associational · r2

Structured-response survey item on hardware/software problem frequency; ten percent of students shared their access device and three percent used a college-provided device.

"Almost a quarter of students (23 percent) experienced hardware or software problems serious enough to impact their ability to attend or participate in their course at least occasionally."

Studies bearing on this claim¶

Does a learner's device, connectivity and technical support predict whether they can take part in technology-delivered learning and assessment? This table gathers the studies behind this claim and the 10 narrower claims that bear on it: 12 distinct studies (5 associational, 2 causal, 2 review, 2 qualitative, 1 theoretical), q1–q3, 0 of 12 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Discussion¶

Learner Variables¶

• Access — predictor: learners who differ on it differ in outcomes

Related Claims¶

• Higher education digital divides are acute at MSIs, HBCUs, and TCUs, which have stark capability deficits in hardware, software, and broadband — related
• Nearly half of STEM students experienced internet connectivity problems that interfered with course participation after the COVID shift to remote instruction — a narrower finding that bears on this claim
• Technology access problems during the COVID shift were more prevalent among minoritized students and students from lower-income households — related
• Hispanic and low-income students reported more challenges and technology problems after the shift online than non-Hispanic White and higher-income peers; rural students did not differ — related
• Immediately after closure, New York charter students lacked adequate devices (44.4% on average) more often than adequate internet access (27.0%), while teachers were almost universally equipped — related
• Motivation, internet connectivity, and hardware/software problems were widespread challenges in remote STEM courses — possibly the same claim (merge candidate)
• An estimated one-third of students fail to learn because of psychosocial problems that interfere with engagement in instruction — related
• Teachers' technology use increased during COVID-19 remote learning, but infrastructure and device barriers hindered effective integration — related
• Technical issues (login scanning, internet connectivity, projector setup, and glitches) frustrated students and created a significant barrier to playlist implementation — related
• In informal virtual programs, technology access was the first and most significant barrier to participating in Hero Elementary — related
• AI in adult education risks reinforcing existing inequalities via the digital divide, particularly for rural, low-income, and marginalized learners — related
• Students identified weaknesses in the AI feedback model: lack of real-time feedback, software/economic access barriers, and occasional incorrect or inconsistent outputs — related
• Infrastructure and access constraints were reported in 18 of 54 studies (33%) as the second higher-order technical limitation category — related
• Teachers identify attendance, unreliable devices, prior academic gaps, and COVID-related disruption as compounding contextual barriers to persistence — related
• Distributing hardware without capable software produced no measurable effect on mathematics or language scores in a large randomized evaluation, as the article reports citing Cristia et al. — related
• Lack of study space and financial issues are associated with higher test anxiety in online exams, and reliable technology with lower — related
• Learners used products outside class despite infrastructure limits: 65% of surveyed students reported doing software work outside class while mobile access was largely unavailable — related
• Community college students hold concrete quality criteria for edtech, including evidence of claims, accessibility, and peer and faculty connection — related
• Student anxiety under remote proctoring is mixed: some students report reduced anxiety from home comfort and no travel, while others face anxiety from connectivity issues and fear of wrongful accusations — related
• Technical difficulties were the most frequently reported implementation limitation, mentioned in ten of the thirteen studies — related
• Most Digital Café participants had home Internet but no one to help with everyday computer learning needs — related
• Digital access among adults on the margins is not a one-time event but an ongoing, contingent accomplishment requiring an assemblage of resources — related
• Emergency federal funding narrowed the digital access divide during the pandemic but did not close the digital use divide — related
• Participants who accessed the report card site with mobile devices had more difficulty using it — related
• Student access to devices and internet rose from about 60 percent in March 2020 to at least 98 percent by March 2021 — related
• Infrastructure barriers — limited internet speed, connectivity problems and lack of technical support — hinder effective AI use in nursing education institutions — related