Evidence map›Paper›PMID 35487051›Full record

ArticleEvaluation and program planning2022

Preference analysis on the online learning attributes among senior high school students during the COVID-19 pandemic: A conjoint analysis approach.

Ardvin Kester S Ong, Yogi Tri Prasetyo, Thanatorn Chuenyindee, Michael Nayat Young, Bonifacio T Doma, Dennis G Caballes, Raffy S Centeno, Anthony S Morfe, Christine S Bautista

Abstract read
In one paragraph

Article in Evaluation and program planning, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

9 authors.

Ardvin Kester S OngSchool of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines, 658 Muralla St., Intramuros, Manila 1002, Philippines. Electronic address: aksong@mapua.edu.ph.
Yogi Tri PrasetyoSchool of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines, 658 Muralla St., Intramuros, Manila 1002, Philippines. Electronic address: ytprasetyo@mapua.edu.ph.
Thanatorn ChuenyindeeSchool of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines, 658 Muralla St., Intramuros, Manila 1002, Philippines; School of Graduate Studies, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila 1002, Philippines; Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand. Electronic address: thanatorn_chu@rtaf.mi.th.
Michael Nayat YoungSchool of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines, 658 Muralla St., Intramuros, Manila 1002, Philippines. Electronic address: mnyoung@mapua.edu.ph.
Bonifacio T DomaSchool of Chemical, Biological, and Materials Engineering and Sciences, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila 1002, Philippines. Electronic address: btdoma@mapua.edu.ph.
Dennis G CaballesGraduate Program School of Teacher Education, The National Teachers College, Philippines, 629 Nepomuceno St, Quiapo, Manila, 1001 Metro, Manila, Philippines. Electronic address: dg.caballes@ntc.edu.ph.
Raffy S CentenoHigh School Department, Malayan Colleges Mindanao, Philippines, Gen. Douglas MacArthur Hwy, Talomo, Davao City 8000, Davao del Sur, Philippines. Electronic address: rscenteno@mcm.edu.ph.
Anthony S MorfeCollege of Arts and Sciences, Malayan Colleges Laguna, Philippines, Pulo-Diezmo Road, Cabuyao, 4025 Laguna, Philippines. Electronic address: asmorfe@mcl.edu.ph.
Christine S BautistaCollege of Engineering and Architecture, University of Nueva Caceres, Philippines. J. Hernandez Ave, Naga, Camarines Sur, Philippines. Electronic address: christine.bautista@unc.edu.ph.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has resulted in the shift from face-to-face to fully online learning. The purpose of this study was to evaluate the preference of senior high school students on online learning attributes during the COVID-19 pandemic by utilizing a conjoint analysis approach. Six attributes which consist of delivery type, assigned tasks, evaluation, virtual laboratory, interface layout, and delivery platform were simultaneously analyzed through orthogonal design. A total of 1189 senior high school students were collected via purposive sampling approach through the social media platform. The respondents voluntarily participated and answered 29 stimuli with 2 holdouts generated by using SPSS 25 utilizing a 7-point Likert scale. The results indicated that evaluation was found to be the most significant attribute and followed by virtual laboratory, delivery type, and delivery platform. Interestingly, multiple choice evaluation, not requiring virtual laboratories, mixed delivery type (synchronous with recorded lectures), and MS Teams as delivery platform were considered as the keys for the preference. This study is the first study that utilized a conjoint approach to analyze the senior high school students' preference on the online learning attributes during the COVID-19 pandemic. Finally, the conjoint approach can be applied and extended to evaluate the online learning attributes globally by utilizing the attributes and design created in this study.

Indexed as

COVID-19Education, DistanceHumansPandemicsProgram EvaluationSARS-CoV-2StudentsConjoint analysisCOVID-19Online LearningStudents’ Preference

Identifiers

PMID35487051
PMCPMC9023093

What OpenQuestion holds

Textmetadata
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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.