Evidence map›Paper›PMID 41544054›Full record

ArticlePloS one2026

Innovative practice of sustainable digital signal processing education.

Zhibo Xie, Zhongjie Zhu, Yuer Wang, Yongqiang Bai, Ruihua Zhang

Abstract read
In one paragraph

Article in PloS one, 2026. 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

5 authors.

Zhibo XieCollege of Information and Intelligence Engineering, Zhejiang Wanli University, Ningbo, China.ORCID https://orcid.org/0000-0003-2219-4136
Zhongjie ZhuCollege of Information and Intelligence Engineering, Zhejiang Wanli University, Ningbo, China.
Yuer WangCollege of Information and Intelligence Engineering, Zhejiang Wanli University, Ningbo, China.
Yongqiang BaiCollege of Information and Intelligence Engineering, Zhejiang Wanli University, Ningbo, China.
Ruihua ZhangCollege of Information and Intelligence Engineering, Zhejiang Wanli University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Digital Signal Processing (DSP) course serves as a core curriculum for electronic information engineering majors. Traditional DSP instruction predominantly employs a teacher-centered lecture format supplemented by simulation experiments, which fails to engage student interest or foster proactive learning, ultimately resulting in suboptimal educational outcomes. This study integrates the BOPPPS instructional framework with Collaborative Inquiry-Based Learning (CIBL) models while designing simulation-hardware experiments that seamlessly bridge virtual and hardware-based environments. By incorporating Sustainable Development Goals (SDGs)-oriented engineering case studies into Project-Based Learning (PBL) content, this approach effectively stimulates student motivation, cultivates practical skills, and enhances problem-solving capabilities. The effectiveness of these pedagogical innovations is evaluated through academic performance analysis, student surveys, and focused interviews, enabling continuous optimization of teaching plans and content. Research findings demonstrate that integrating SDG-related engineering projects significantly boosts student motivation and professional confidence. Furthermore, the BOPPPS model combined with CIBL effectively improves learning efficiency and specialized competencies among students.

Indexed as

Signal Processing, Computer-AssistedCurriculumHumansMotivationProblem-Based LearningStudents

Identifiers

PMID41544054
PMCPMC12810817

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.