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Record W4393091421 · doi:10.5296/ijld.v14i1.21712

Online Study during Covid’ 19: What Students Like and Dislike in Online Courses

2024· article· en· W4393091421 on OpenAlex
Moncef Bari, Minh Thi Ai Nguyen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Learning and Development · 2024
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité du Québec à Montréal
FundersUniversité du Québec à Montréal
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Psychology2019-20 coronavirus outbreakOnline learningOnline teachingSociologyMathematics educationComputer scienceMultimediaVirologyMedicine

Abstract

fetched live from OpenAlex

This article presents the results of a research about the students’ likes and dislikes in online courses. The project used surveys to the students of the Dalat University in Vietnam conducted during the fall term of 2021. After analyzing the sample of 708 students, it appears that the main findings are somehow close to many studies conducted at the same time approximately. Mainly, the students like the flexibility of asynchronous courses and the availability of the learning material at any time. They dislike the lack of interaction with the teachers and their classmates. As for online asynchronous courses, students like the possibility of interacting with teachers and classmates (in the case of interactive courses) and the clarity of the schedule. In all cases, the quality of the Internet connection and the power supply appear as a sine qua non condition to any satisfaction supporting any distance studies.Some students have also noted health problems inherent to too long periods sitting in front of screens. This aspect is particularly critical for those who do not have computers and who are forced to work on their smartphones.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.054
GPT teacher head0.470
Teacher spread0.416 · 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