# Research Notes: *After the Ban*

Updated September 9, 2026.

## Purpose and status

This file records the evidence and interpretive boundaries behind the digital companion to Micah J. Miner's practitioner feature, *After the Ban: What District Leaders Must Put on the Next Agenda*.

The companion is not a research report. Its classroom sequences are illustrative and report no classroom result, district outcome, dissertation finding, or causal effect. The page extends Miner's published conceptual framework and a practitioner argument about leadership follow-through after a device-policy decision.

## Central claim

A device restriction can protect attention and improve the conditions for learning. It does not determine what students will do with the reclaimed time, whether students retain needed supports, when an approved AI tool enters a task, or what evidence district leaders will review. Those are separate instructional and leadership decisions.

## Evidence boundaries used on the page

### Illinois Public Act 104-0657

The law requires each Illinois school board, on or before the beginning of the 2027-2028 school year, to adopt and implement a policy that prohibits student use of wireless communication devices during school time, subject to statutory exceptions. The definition excludes devices a district or teacher directly issues, provides, or requires a student to possess and use for educational purposes. The companion therefore distinguishes personal-device policy from governance of district-issued educational technology.

The page does not summarize every provision. Districts should read the enacted text and applicable guidance when developing policy.

### Beland and Murphy (2016)

The authors used a difference-in-differences strategy with school policy data and England's National Pupil Database. They found increased examination performance after schools adopted phone bans, with effects driven by previously lower-achieving students.

The study concerns four English cities, earlier mobile-phone conditions, and a policy environment that predates generative AI. It supports the claim that restrictions can help some students in some contexts. It does not establish what a present-day U.S. district should teach after adopting a restriction.

### Goodyear et al. (2025), SMART Schools

The cross-sectional observational study included 30 English secondary schools and 1,227 students. The authors reported no evidence that restrictive school phone policies were associated with better adolescent mental wellbeing or lower overall phone and social-media use. Lower in-school phone and social-media use did not translate into lower use across the full day.

Because the design compared schools that already differed, it cannot estimate what would happen if a particular school changed its policy. The page avoids describing the findings as a universal prediction or a causal test of policy change.

### Hatfield (2024), Pew Research Center

Pew's analysis reports that 72% of U.S. public high school teachers surveyed in fall 2023 considered student distraction by cellphones a major problem in their classroom. The page uses this as evidence of teachers' reported experience, not as evidence that any specific restriction improves learning.

### Kapur (2016)

Kapur's framework distinguishes immediate performance from learning and includes the category of unproductive success: successful task performance without the intended learning. The companion uses this distinction to question whether a polished product makes an individual student's reasoning visible. It does not claim that any featured assessment has been experimentally tested.

### Miner (2026)

Miner's published conceptual article defines pedagogical friction across noetic, rhetorical, existential, and infrastructural dimensions. The companion renders these as understanding, voice, agency, and conditions for a leadership audience. This is an application of the framework, not a dissertation finding.

## APA-style references

Beland, L.-P., & Murphy, R. (2016). Ill communication: Technology, distraction & student performance. *Labour Economics, 41*, 61-76. https://doi.org/10.1016/j.labeco.2016.04.004

Goodyear, V. A., Randhawa, A., Adab, P., Al-Janabi, H., Fenton, S., Jones, K., Michail, M., Morrison, B., Patterson, P., Quinlan, J., Sitch, A., Twardochleb, R., Wade, M., & Pallan, M. (2025). School phone policies and their association with mental wellbeing, phone use, and social media use (SMART Schools): A cross-sectional observational study. *The Lancet Regional Health – Europe, 51*, Article 101211. https://doi.org/10.1016/j.lanepe.2025.101211

Hatfield, J. (2024, June 12). *72% of U.S. high school teachers say cellphone distraction is a major problem in the classroom*. Pew Research Center. https://www.pewresearch.org/short-reads/2024/06/12/72-percent-of-us-high-school-teachers-say-cellphone-distraction-is-a-major-problem-in-the-classroom/

Kapur, M. (2016). Examining productive failure, productive success, unproductive failure, and unproductive success in learning. *Educational Psychologist, 51*(2), 289-299. https://doi.org/10.1080/00461520.2016.1155457

Miner, M. J. (2026). When the output looks like learning: Tertiary algorithmicity, unproductive success, and the case for pedagogical friction in K-12 schools. *i.e.: inquiry in education, 18*(1), Article 4. https://digitalcommons.nl.edu/ie/vol18/iss1/4/

Wireless Communication Device Policy, Ill. Pub. Act 104-0657, 105 Ill. Comp. Stat. 5/10-20.88 (2026). https://ilga.gov/Legislation/PublicActs/View/104-0657

## Privacy and implementation

- The agenda builder runs entirely in the page.
- Entries are not transmitted or stored.
- The companion includes no analytics or tracking scripts.
- The page does not request student, staff, or participant information.
- The subject examples are illustrative extensions of the article's assessment sequence.