Video Modeling on Shot-Put Acquisition
Video Modeling Variants and Temporal Scheduling Effects on Shot-Put Acquisition
Video modeling is widely used in motor skill instruction, yet its optimal modality and timing within a session remain unclear, particularly for complex athletic tasks. This study compared three video feedback modalities, including video self-modeling, video expert-modeling, and peer-to-peer learning video, administered at three session phases (warm-up, during the learning session, and after the learning session) on shot-put learning outcomes in novice university students. Sport science students aged 19-25 years were assigned to nine experimental groups and one control group in a 3 × 3 between-subjects factorial randomized controlled trial over nine weeks. Physical performance, technical score, selective attention, and episodic memory were assessed at three time points: the predictive session test (week 1), formative session test (week 5), and summative session test (week 9).
Studienübersicht
Status
Bedingungen
Detaillierte Beschreibung
Video modeling is widely used in motor skill instruction, yet the optimal video modality and timing within a training session remain unclear, particularly for complex athletic skills. This study compared three video-based learning modalities, including video self-modeling, video expert-modeling, and peer-to-peer learning video, administered at three different phases of a training session (during the warm-up, during the learning session, or after the learning session) on shot-put learning outcomes in novice university students. A total of 176 university students (122 males and 54 females) participated in the study. Participants were allocated to 10 groups, consisting of one control group and nine experimental groups, with group sizes ranging from 16 to 20 participants. The groups were based on existing administrative classes. The 10 groups were: (1) control group (n = 20); (2) peer-to-peer learning video during warm-up (n = 19); (3) video expert-modeling during warm-up (n = 17); (4) video self-modeling during warm-up (n = 17); (5) peer-to-peer learning video during the learning session (n = 16); (6) video expert-modeling during the learning session (n = 17); (7) video self-modeling during the learning session (n = 17); (8) peer-to-peer learning video after the learning session (n = 19); (9) video expert-modeling after the learning session (n = 17); and (10) video self-modeling after the learning session (n = 17). Shot-put learning outcomes were assessed using physical performance (throwing distance), technical performance score, release velocity, selective attention, and episodic memory. Assessments were conducted at three time points: the predictive session test at week 1, the formative session test at week 5, and the summative session test at week 9.
Studientyp
Einschreibung (Tatsächlich)
Phase
- Unzutreffend
Kontakte und Standorte
Studienorte
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Boulifa
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El Kef, Boulifa, Tunesien, 7100
- Nejmeddine Ouerghi
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-
Teilnahmekriterien
Zulassungskriterien
Studienberechtigtes Alter
Akzeptiert gesunde Freiwillige
Studienberechtigte Geschlechter
Beschreibung
Inclusion Criteria:
- Aged 19-25 years.
- Enrolled as a sport science student.
- No prior competitive experience in shot put.
- Regularly engaged in sports practice for approximately 6 hours per week.
Exclusion Criteria:
- History of musculoskeletal injury affecting upper-limb or trunk function
- Sustaining a neuromuscular or sensorimotor injury during the experimental protocol
- Absence from more than two learning sessions.
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
- Hauptzweck: Sonstiges
- Zuteilung: Zufällig
- Interventionsmodell: Parallele Zuordnung
- Maskierung: Keine (Offenes Etikett)
Waffen und Interventionen
Teilnehmergruppe / Arm |
Intervention / Behandlung |
|---|---|
|
Experimental: Peer-to-peer learning video group during warm-up
Student pairs analyzed their own recorded videos during the warm-up in each learning session over 9 weeks. |
Student pairs analyzed their own recorded videos for 5 minutes at a time that differed according to the condition: during the warm-up phase in each learning session (post-warm-up transition interval), during the learning session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Video expert modeling group during warm-up
Each student viewed an expert-modeling video for 5 minutes during the warm-up phase in each learning session over 9 weeks. |
Students watched a video demonstration of the shot put by an expert during 5-min, at a time that differed according to the condition: during warm-up phase (post-warm-up transition interval), during the session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Video self-modeling group during warm-up
Each student viewed their own video for 5 minutes during the warm-up phase in each learning session over 9 weeks. |
Student pairs analyzed their own recorded videos for 5 minutes at a time that differed according to the condition: during the warm-up phase in each learning session (post-warm-up transition interval), during the learning session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Peer-to-peer learning video group during learning
Student pairs analyzed their own recorded videos during the learning phase in each session over 9 weeks. |
Student pairs analyzed their own recorded videos for 5 minutes at a time that differed according to the condition: during the warm-up phase in each learning session (post-warm-up transition interval), during the learning session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Video expert modeling group during learning
Each student viewed an expert-modeling video for 5 minutes during the learning phase in each session over 9 weeks. |
Students watched a video demonstration of the shot put by an expert during 5-min, at a time that differed according to the condition: during warm-up phase (post-warm-up transition interval), during the session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Video self-modeling group during learning
Each student viewed their own video for 5 minutes during the learning phase in each session over 9 weeks. |
Student pairs analyzed their own recorded videos for 5 minutes at a time that differed according to the condition: during the warm-up phase in each learning session (post-warm-up transition interval), during the learning session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Peer-to-peer learning video group after learning
Student pairs analyzed their own recorded videos after the learning phase in each session over 9 weeks. |
Student pairs analyzed their own recorded videos for 5 minutes at a time that differed according to the condition: during the warm-up phase in each learning session (post-warm-up transition interval), during the learning session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Video expert modeling group after learning
Each student viewed an expert-modeling video for 5 minutes after the learning phase in each session over 9 weeks. |
Students watched a video demonstration of the shot put by an expert during 5-min, at a time that differed according to the condition: during warm-up phase (post-warm-up transition interval), during the session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Experimental: Video self-modeling group after learning
Each student viewed their own video for 5 minutes after the learning phase in each session over 9 weeks. |
Student pairs analyzed their own recorded videos for 5 minutes at a time that differed according to the condition: during the warm-up phase in each learning session (post-warm-up transition interval), during the learning session (the final shot-put simulation exercise), or after the learning session (the cool-down phase). |
|
Aktiver Komparator: Control group
Participants in the control group maintained their normal learning activities in physical education. |
The same shot-put learning program was implemented without the use of video-based learning. |
Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Shot-put throwing distance (m)
Zeitfenster: Week 1, Week 5, and Week 9
|
The distance of the shot-put throw, measured in meters. The best performance across three trials at each assessment was used for analysis |
Week 1, Week 5, and Week 9
|
|
Shot-put technical execution score
Zeitfenster: Week 1, Week 5, and Week 9
|
Technical execution was assessed by two independent raters using a standardized evaluation grid covering five phases of the throw: preparation, push, inclination, extension, and follow-through. Each phase was rated on a three-point scale (1 = not achieved, 2 = partially achieved, 3 = fully achieved), yielding a total score ranging from 5 to 15 points. The mean score across the three trials at each assessment was used for analysis |
Week 1, Week 5, and Week 9
|
|
Shot-put release velocity (m/s)
Zeitfenster: Week 1, Week 5, and Week 9
|
Shot release velocity, expressed in m/s, was determined from video recordings using Kinovea motion analysis software |
Week 1, Week 5, and Week 9
|
Sekundäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Go/No-Go response time (ms)
Zeitfenster: Week 1, Week 5, and Week 9
|
Response time during Go trials was recorded in milliseconds using the Go/No-Go task administered through the CogniFit online cognitive assessment platform. |
Week 1, Week 5, and Week 9
|
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Go/No-Go inhibitory control accuracy (%)
Zeitfenster: Week 1, Week 5, and Week 9
|
Inhibitory control was assessed using the Go/No-Go task. Accuracy during No-Go trials was recorded as the percentage of correct responses using the CogniFit online cognitive assessment platform. |
Week 1, Week 5, and Week 9
|
|
d2 attention test performance
Zeitfenster: Week 1, Week 5, and Week 9
|
The d2 attention test was used to assess selective attention by requiring participants to identify target stimuli among distracting stimuli within a limited time. The percentage of correct responses and the total time required to complete the task, measured in milliseconds, were recorded at each assessment. |
Week 1, Week 5, and Week 9
|
Mitarbeiter und Ermittler
Ermittler
- Hauptermittler: Nejmeddine Ouerghi, Research Unit "Sport Sciences, Health and Movement"(UR22JS01) High Institute of Sport and Physical Education of Kef, University of Jendouba, 7100 Kef, Tunisia.
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn (Tatsächlich)
Primärer Abschluss (Tatsächlich)
Studienabschluss (Tatsächlich)
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Tatsächlich)
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Schlüsselwörter
Zusätzliche relevante MeSH-Bedingungen
Andere Studien-ID-Nummern
- NJ_MB_Video_Modeling
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