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Record W3137245932 · doi:10.5539/jel.v10n2p159

Views of Sports Sciences Students About Distance Education During Covid-19: SWOT Analysis

2021· article· en· W3137245932 on OpenAlexvenueno aff
Didem Gülçin Kaya

Bibliographic record

VenueJournal of Education and Learning · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSWOT analysisDistance educationPsychologySocializationContent analysisMedical educationMathematics educationHigher educationStrengths and weaknessesProcess (computing)Sports sciencePedagogySociologyComputer scienceSocial scienceSocial psychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

This study is aimed to examine the views of the students of the Faculty of Sports Sciences on distance education with SWOT analysis and to evaluate the current circumstance. The phenomenology design was used in the study. The research group consisted of 62 students studying at Afyon Kocatepe University Faculty of Sport Sciences located in a town in the Aegean region in Turkey. In collecting the data, the personal information form created by the researchers and the semi-structured interview form was used, and the data obtained were analyzed by content analysis and descriptive analysis technique. As a result of the findings, it was seen that the views of the students studying in the field of sports sciences on the strengths of distance education provided the best conditions in the Covid-19 process, gained experience in synchronous-online courses and the online system, and to reinforce the knowledge by making use of projects and assignments. Views on the weaknesses of distance education were expressed as the inability of every student to benefit from the right to education under equal conditions, difficulties in accessing the internet, and lack of materials. Besides, the views on the opportunities of distance education were determined as good management of the process, planning the applied courses face-to-face, that is, choosing the hybrid system, motivating the students for the assignments and projects, and making up compensatory programs applied to solve the problems. Socialization of students, unsuitable working environment, anxiety, and negative views of the society towards the education system were recorded as threats and dangers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.396
Teacher spread0.332 · 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.

Study designQualitative
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

Citations1
Published2021
Admission routes1
Has abstractyes

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