MétaCan
Menu
Back to cohort
Record W3120907260 · doi:10.37394/23205.2020.19.30

Perceptions of Business Students toward Online Education before and in Transition Period of COVID-19

2021· article· en· W3120907260 on OpenAlexaff
Clare Chua, Nursel Selver Ruzgar

Bibliographic record

VenueWSEAS TRANSACTIONS ON COMPUTERS · 2021
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicPerceptionOnline learningPsychologyTransition (genetics)Period (music)Mathematics educationMedical educationHigher educationMedicineComputer scienceMultimediaPolitical scienceChemistry

Abstract

fetched live from OpenAlex

Covid-19 affects our lifestyles dramatically. It also affects the education styles. Spurred by the Covid19 pandemic, most of the learning in a traditional classroom setting were transferred to online format. This study was designed to assess the students’ perception on the traditional and online learning before Covid-19 pandemic and in transition to the Covid pandemic when all classroom learning is closed and transferred to online based learning. Students were sampled to obtain their general perceptions regarding traditional and online learning. The data were collected via an online survey during October/November 2019 and March/April 2020. Findings indicate that the perceptions of students changed negatively in transition period. A large majority of students agreed before Covid-19, but they disagreed in transition period on the following: online education increases learning levels; students learn more with online courses; zoom is much better than learning in the classroom environment; online courses are easier than traditional courses; I would recommend taking online courses instead of in class courses to a friend or colleague; and I would like to take my other courses in online form. The results show that a sudden change to the system will negatively impact the students and it did not allow time for students to adjust to the change. They are simply not ready to take all the courses online. However, students all agreed the use of technology in classroom increases their engagement and interest in the subject matter

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.600
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.311
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueWSEAS TRANSACTIONS ON COMPUTERSSame topicOnline Learning and AnalyticsFrench-language works237,207