University Research: A Skeptical Perspective by A. Michael Noll

UNIVERSITY RESEARCH: A SKEPTICAL PERSPECTIVE

A. Michael Noll

January 13, 2018

© Copyright 2017 AMN

University research has skeptically made little contribution to the striking advances in communications technology of the last 50 or so years. This is hardly surprising, since most of the advances came from R&D at industrial facilities. The skeptical perspective in this piece is based on my early experience at an industrial research laboratory, in government, and later at a university. My conclusion is that university research is essential mostly for the education and training of students, who then graduate and conduct meaningful research for industry.

Ivory Tower

Ivory Tower sciblog.co.nz

One important example of technological innovation in the communication area is communication satellites. But they were not the result of university research. Bell Labs pioneered satellite communications over a half century ago. In fact, science fiction writer Arthur C. Clarke, as early as 1945, first proposed communication satellites. The Soviets (Sputnik in 1957) developed the first satellite. Then Bell Telephone Laboratories (Echo in 1960 and Telstar in 1962) developed early communication satellites — none of this was university research.

Another technological innovation is the Internet. Was it solely the result of university research? The precursor of today’s Internet was the Arpanet, which utilized packet switching to avoid then costly data service. The Advanced Research Projects Agency (ARPA) of the Federal defense department funded the development of the Arpanet, which was the brainchild of Dr. Larry Roberts, who directed the project at ARPA. Much of the actual development work was done at Bolt, Beranek, and Newman (BBN). Although university people were involved, the Arpanet was not solely the result of university research.

I am not familiar with chemical research and physics, and thus do not know how much practical research has occurred at university facilities. My expertise is in electrical engineering and telecommunications technology. Interesting university research has been done in astrophysics, but little relevance has occurred from this research – it deals with such topics as black holes and distances measured in millions on light years. Decades ago, John McCarthy at his laboratory at Stanford University, and the students he educated did exciting research in artificial intelligence and robotics.

The broader question is what is the purpose and mission of universities, and what is the role of university research? This can become the domain of self-serving opinion. It is a controversial topic with “muddy waters” on its importance depending on personal opinions and perspectives.

Sitting here at my desk with the computer on which I am writing this article, I think of the technology around me. The graphical interface on the computer was invented at the Xerox Palo Alto Research Center (PARC); the mouse was invented at the Stanford Research Institute; researchers at Bell Telephone Laboratories invented the Unix operating system. None of this was university research. Many innovations are the result of discoveries by many researchers at different organizations – credit frequently should be more collectively attributed.

The Federal government through a peer-review process sponsors much university research. The process in seeking support for peer-reviewed research is lengthy and elaborate. It sometimes appears that more thought and effort goes into writing the proposal than the actual conduct of the research. The peer review process assures that the research will be mostly mainstream.

Decades ago, when I worked in Washington and collaborated with the Office of Management and Budget, I wondered whether university research funded by the National Science Foundation was a form of welfare for academics. It was also a reason for being released from teaching a course or two — teaching is real work.

I wonder whether it would be simpler and would result in more innovative groundbreaking research if the university simply supported the research from its endowment and own funds. But these funds would need to be distributed evenly and might not be sufficient to support current levels of research. However, avoiding proposal writing might add efficiency.

University research frequently is more theoretical, not very practical, and long term. It usually is not the kind of proprietary research that leads to breakthroughs and pioneering innovations with practical industrial application. The mission of university research frequently is “new knowledge for its own sake,” as contrasted with industrial research that supports the mission of the industrial firm. It is not the mission of the university to make new products and provide new services.

The best research supports the mission of the sponsoring organization. The mission of a university is education – not providing telecommunication service, space craft, refrigerators, and so forth. Indeed, the major mission of the university should be education. If doctoral students are to be educated and trained, then they need the opportunity to perform some form of research. After they graduate, these doctorial students then frequently go to work at industry performing practical and relevant work. The career path for doctoral students that seems to be most applauded by the faculty is to graduate and work at another university, where their doctoral students then apply to yet another graduate program – not for industry or on practical problems. “Practical” and “relevant” seem to be characterizations to be avoided at many universities.

Research usually tackled practical problems in support of a real-world mission of the sponsor. A good way for a university to be involved in such research is through a separate for-profit research unit. The researchers would not teach nor be tenured – they would be employees. Patents would be obtained, along with other intellectual property. Students and faculty could also work part-time at the research facility. The management of the research unit would evaluate the research. An issue with university research is that the departmental administration does not evaluate it and instead relies on outside peer review.

The “product” of universities is its graduates. Research universities educate and train doctoral students. As graduates these newly minted doctorates go to work in industry performing propriety industrial research and devolvement. The results of this R&D makes their way back to the university, affecting and refining the topics of research done by faculty and current doctoral students. This is a tight loop.

I have taken a skeptical and controversial tone in this piece. But in the end, what should matter is meaningful research that solves real problems or leads to new knowledge and innovations — not where it is performed. Research should make our lives better through new products and services.

A. Michael Noll

A. Michael Noll

Primary takeaways

  • Digital inequality shows larger impacts on youth academic performance as compared to time spent on screens.

  • Digital skills play a significant role in mediating unstructured online engagement (social media use, playing video games, browsing the web) and youth academic, social, and psychosocial development.

  • Unstructured online engagement and face-to-face social interaction are complementary and continuously interact to create and enhance youth capital outcomes.


A familiar story: concerns of screen time

Today’s discussions of adolescent well-being have coalesced around a clear narrative: teenagers spend too much time online, and their academic performance, mental health, and social lives are deteriorating as a result. A steady stream of academic papers, books, and op-eds, alongside a growing number of policy proposals––school phone bans, age-gated social media use, restrictive screen-time limits––rest on the same underlying claim, aligning with a contemporary, digitized version of the displacement hypothesis:

Screen time, particularly the unstructured, free-time spent on social media, gaming, watching video content, or browsing the web, is said to displace the productive face-to-face activities that build adolescents into capable adults.

The implied and often practiced solution is restriction. In response, this dissertation tested this claim directly, and placed it within the broader context of adolescence.

Across three years, I followed 653 Michigan adolescents from early through late adolescence: in grades 8 or 9 (survey one, 2019) to grades 11 or 12 (survey two, 2022). Notably, these students, studied over time, were part of a broader pooled sample of 5,825 students across the same eighteen highschools. The study window captured the year before and the year after the peak of the COVID-19 pandemic and related lockdown orders, functioning as an unprecedented stress test for theories of adolescent social, academic, and digital life and, importantly, as a benchmark to compare the effects of pandemic-related change and inequality to those effects from screen time alone.

Across four studies of adolescents, consisting of six cross-sectional and longitudinal analyses, findings are not consistent with the displacement narrative, nor the broader concerns about the time youth spend on screens.

Findings are, however, consistent with something the current public and (most) academic discussions have largely overlooked or ignored: the gaps and inequalities that determine whether adolescents can access and use the internet meaningfully in the first place.

What the displacement hypothesis overlooks

Displacement and related research and policy concerning the time young people spend online assumes a “zero-sum” model of adolescent day-to-day time. An hour online is an hour not spent studying, reading, sleeping, or interacting face-to-face (i.e., time spent on more productive or developmentally “better” activity).

Indeed, this makes sense logically. However, as an empirical claim, this model requires time spent online to behave differently from all other ways adolescents allocate time; it must produce uniquely negative outcomes and be inherently harmful across digital contexts, rather than the typical mix of trade-offs corresponding to, and often overlooked among any other social or developmental context.

Yet, online time does not differ from other youth activity. Instead, I find it has a mix of pros, cons, and even some “uniquely digital” benefits which youth utilize for social and academic gains. When I compared unstructured digital media use against traditional face-to-face interaction and activities, both produced similar patterns: some negative associations with academic outcomes, some null, and some positive.

Trade-offs within traditional face-to-face activity (for example, social time with friends and family, or time spent in after-school extracurriculars) are treated as ordinary developmental experiences that must be experienced for the betterment of development. The identical trade-offs involving digital time tend to be overlooked or ignored, and online engagement is perceived as altogether harmful.

A growing body of evidence, including this dissertation, do not support that distinction. Indeed, the developmental context is routinely misread, leaving out the context of the experiences and time spent on digital, as well as face-to-face activities, interactions, existing inequalities, and changes inherent to development. As such, I proposed a novel framework to understand these contexts:

Digital capital exchange

Rather than treating screen time as a unified harm, this dissertation advances an exchange”-based framework, grounded in James Coleman’s theories of youth capital and digital inequality scholarship, particularly following Eszter Hargittai, Jan van Dijk, and Alexander van Deursen (see this list of all dissertation references for full works).

The core proposition is that adolescents’ online engagement is not an alternative to developmental activity but another, albiet modern domain through which young people accumulate and mobilize online resources––particularly digital skills––that work alongside existing social networks and experiences to be exchanged for human capital (measured as: academic achievement, aspirations, STEM interest) and social capital (peer networks, community participation, extracurricular involvement).

Online time is not the mechanism; instead, it is digital skills that I find to be the most vital component in youth capital exchange and enhancement. Unstructured online engagement contributes to online skills; those skills, accumulated and mobilized alongside existing peer, family, and community networks, translate into the outcomes researchers and parents care about, i.e., academic achievement, aspirations, and face-to-face interaction and social networks.

This digital capital framework treats online and in-person contexts as complementary rather than antagonistic, and it situates adolescents’ digital lives within the structural conditions––connectivity quality, device reliability, autonomy of use––that determine whether exchange can occur at all.


Methods (in brief)

Paper-and-pencil surveys were administered to students in classrooms at two time-points: spring 2019 (N=2,876) and spring 2022 (N=2,949), across the same eighteen predominantly rural Michigan schools, grades 8–12. Official, nationally-ranked standardized reading, writing, and math test scores (PSAT 8/9, PSAT 10, SAT; College Board) were then anonymously linked to students’ survey responses with the help of participating districts.

Cross-sectional path analyses modeled pooled and wave-specific samples (pooled N=5,825); two-wave cross-lagged panel models tested reciprocal, longitudinal relationships on the 653 students who completed both surveys. Multi-group analyses of the cross-lagged panel models compared relationships between girls (N=345) and boys (N=308). All longitudinal models included time-invariant socioeconomic covariates as well as time-varying covariates to reduce omitted-variable bias.

Key findings: an overview

To summarize, to the best of my ability, eight chapters across 376 pages, I present two primary findings:

First: digital inequality predicted larger and more consistent declines in human capital than screen time did.

Unreliable home internet and technology maintenance problems––experiencing and/or dealing with broken or outdated devices and software, restrictive school-issued hardware, issues with connecting to or maintaining internet access––decreased youth GPA and standardized test achievement. And, these effect sizes were substantially larger than any negative direct effect from unstructured digital media use.

Across all four empirical studies, digital inequality emerged as the most substantial predictor of academic and developmental decline.

Second: digital skills mediated the relationship between online time and adolescent academic and social outcomes.

Unstructured digital media use, particularly online gaming and web browsing, predicted higher internet and social media skills for adolescents, which in turn predicted stronger academic achievement and self-efficacy (human capital), and social interaction and extracurricular participation (social capital). The positive indirect effect of screen time through skills offset or exceeded any small negative direct effects across several outcomes (supporting our existing peer-reviewed work: Hales & Hampton, 2025, and which you can read more about here).

These exchange processes were amplified when peer and family networks were modeled alongside digital skills, consistent with the premise that online and offline contexts operate together rather than in competition. The effect was not universal: social media skills amplified rather than offset a negative association with consistency of interest, one of the two subscales of grit. The exchange framework describes a contextual and conditional, domain-specific mechanism, not a blanket defense of time spent online.

Implications

If digital inequality, and not screen time, is the primary predictor of adolescent academic and developmental decline, and still warrants concern regarding access quality and experience even with the broader adoption of digital devices across the United States, the current policy emphasis on restriction is pointed at the wrong target. The evidence supports a different set of priorities.

Stable, reliable home (fast) broadband should be treated as an educational prerequisite rather than a consumer amenity. Unreliable connectivity exerted larger downward pressure on human capital than any measure of screen time, and that pressure intensified during the pandemic-era reliance on digital infrastructure. Technology maintenance, device repair, replacement, technical support, and the flexibility to install software and explore the web autonomously, matters as much as initial access, and school-issued devices that restrict autonomous use appear to hinder skill accumulation rather than support it.

Restrictive parental mediation of internet use was negatively associated with grit and self-efficacy at magnitudes comparable to the positive contributions of face-to-face activity. This challenges the assumption that digital restriction functions protectively. Instructive mediation, teaching adolescents to verify information, navigate platforms critically, and mobilize online resources toward meaningful ends, is the posture the data supports.

Finally, the technical skill-building that occurs through gaming, self-directed exploration, and deep web use is skill-building, not wasted time. Closing the persistent gender gap in these domains likely requires legitimizing technical play for girls, rather than restricting it for everyone.

None of the above is an argument that screen time is benign. It is an argument that screen time is the wrong focus, particularly when studied mostly in isolation. Context matters substantially, whether that is time spent on other activities during adolescence, the period of adolescence itself, digital inequality, resources gained from such online use, and how all such factors interact. The factor that predicts whether a given adolescent can convert online engagement into capital outcomes is structural: access, infrastructure, skills, and the autonomy to use them. These factors are distributed unevenly, and its uneven distribution, not hours logged, is what separates adolescents who thrive from those who fall behind.

The full dissertation is available through Michigan State University’s ProQuest archive, or see the embedded full-text PDF below. I’m happy to share papers, preprints, or the underlying framework with anyone interested and working in this area––don’t hesitate to reach out via my contact form. Thanks for reading.

University Research: A Skeptical Perspective by A. Michael Noll