Evidence map›Paper›PMID 38524564›Full record

ArticleHeliyon2024

Enhancing legibility in educational settings: Optimizing projection illuminance for varied indoor ambient illuminance.

Zhengyin Gu, Xinle Bao, Ying Zhu, Saiwei Song, Wei Gao, Chunyan Kang, Qijun Wang, Duming Wang, Yu Tian

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Zhengyin GuDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Xinle BaoDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Ying ZhuDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Saiwei SongDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Wei GaoDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Chunyan KangDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Qijun WangDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Duming WangDepartment of Psychology, Zhejiang Sci-Tech University, Zhejiang, China.
Yu TianNational Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Projectors are common display devices in the educational setting. However, dim projector lightbulbs or well-lit classrooms may cause blurriness in the projected image. To determine the optimal projection light under different ambient light conditions, the conjoint effects of projection illuminance and ambient illuminance on the legibility of projection images indoors were investigated. Participants (N = 96) were randomly assigned to one of six indoor ambient light conditions (0, 40, 80, 120, 160, and 200 lx) and performed a visual search task under several projection illuminance conditions (200, 250, 300, 350, and 400 lx). The accuracy and correct response time on the task were collected to evaluate the participants' visual performance to represent legibility. The optimal projection illuminance (high visual accuracy and fast reaction) was 400 lx (944 ANSI lumen) under all ambient light conditions. To avoid low legibility (accuracy<0.6) and maintain acceptable legibility (accuracy>0.7), the projection illuminance should be increased as the indoor ambient light increases.

Indexed as

Indoor ambient illuminanceLegibilityProjecting apparatusProjection illuminance

Identifiers

PMID38524564
PMCPMC10957382

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.