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Record W4366771853 · doi:10.47119/ijrp1001231420234698

MOVES AND GROOVES: STUDENTS’ ENGAGEMENT IN USING TIKTOK AS PLATFORM IN ENHANCING STUDENTS’ DANCE SKILLS

2023· article· en· W4366771853 on OpenAlexaboutno aff
NORMAN M. TAGBO

Bibliographic record

VenueInternational Journal of Research Publications · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Methods and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsDanceEntertainmentPsychologyQuarter (Canadian coin)Simple random sampleMedical educationPreferenceStudent engagementSocial mediaMathematics educationMedicineGeographyVisual artsComputer sciencePopulationEnvironmental healthMathematics

Abstract

fetched live from OpenAlex

The researcher identified the respondents demographic profile such as age, sex and gender. Meanwhile, it also determined the respondents engagement with TikTok platform in terms of entertainment, inspiration, self-expression, trend updates and social benefit. Also, this study investigated the level of students dance skills in terms of performance and grades. The performance includes the physical and technical skills of the students. Lastly, it analyzed if there is a significant relationship between students demographic profile and dance skills and between students engagement in TikTok platform and dance skills. Furthermore, the researcher utilized a validated self-made questionnaire. The respondents were the Grade 12 senior high school students of Atimonan 1 District (4th Congressional District) of DepEd – Division of Quezon who are officially enrolled in the School Year 2022-2023. There are 234 students who serves as the respondents of the study as a result of the Slovins formula. Specifically, there are 217 students from Atimonan National Comprehensive High School and 17 students from Malusak National High School who were selected through simple random sampling. The data gathering procedure was implemented on 2nd Quarter of the School Year 2022-2023. In this study, it was found out that majority of the respondents are 17 years old and female. Most of the gender preference of the respondents is feminine. The level of engagement in Tiktok App as a social media platform in terms of entertainment, inspiration and trend updates is highly engaged. On the other hand, the respondents level of engagement in Tiktok platform in terms of self-expression and social benefit is engaged. The level of students skills as to dance performance in physical skill is “fully meets expectations” as to posture and coordination. They got “meets expectations” on flexibility. For technical skills, the level of students competencies as to dance performance in technical skill is “meets expectations” on dynamics, and “fully meets expectations” on spatial and timing. There is no significant relationship exist between the level of dance skills of the students and their profile. Physical skills of the respondents were significantly correlated with their engagement in Tiktok platform in terms of entertainment, inspiration and social benefit. However, no correlations exist between the students engagement in Tiktok platform as to self-expression and trend update and the development of their physical skills.

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)0.014
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.279
GPT teacher head0.625
Teacher spread0.346 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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