Evidence map›Paper›PMID 36687994›Full record

ArticleFrontiers in psychology2022

What I know, what I want to know, what I learned: Activating EFL college students' cognitive, behavioral, and emotional engagement through structured feedback in an online environment.

Liqaa Habeb Al-Obaydi, Farzaneh Shakki, Ragad M Tawafak, Marcel Pikhart, Raed Latif Ugla

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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.

Liqaa Habeb Al-ObaydiEnglish Department, College of Education for Human Sciences, University of Diyala, Diyala, Iraq.
Farzaneh ShakkiDepartment of English Language and Literature, Faculty of Humanities and Social Sciences, Golestan University, Gorgan, Iran.
Ragad M TawafakDepartment of Information Technology, Al Buraimi University College, Al Buraimi, Oman.
Marcel PikhartFaculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia.
Raed Latif UglaDepartment of Islamic Studies in English, Al-Imam Al-Adhdham University College, Baghdad, Iraq.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the spread of the COVID-19 pandemic, online classes have received special attention worldwide. Since teachers have a lasting effect on the students, the teacher-student relationship is a pivotal factor in language learning classes. Students will not be engaged in class activities if they are not sufficiently challenged by them or if they do not find them interesting, especially in online classes. From this point of view, motivating, engaging, and testing techniques in online classes are highly important. The present study attempts to demonstrate a correlation between structured feedback and three types of engagement in an online class: cognitive, behavioral, and emotional engagement. The structured feedback, which is used at the end of each lesson lets the students express what they know, what they want to know, and what they learned. The sample of the study consists of 114 EFL third-year college students. The study's findings reveal positive and significant correlations between the three types of engagement; cognitive, behavioral, and emotional, and the use of structured feedback in online classes. In a nutshell, some academic implications and recommendations are provided.

Indexed as

behavioral engagementcognitive engagementemotional engagementonline educationstructured feedback

Identifiers

PMID36687994
PMCPMC9845881

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.