You will be provided with a reference and some statements. Please determine whether each statement is 'supported', 'unsupported', or 'unknown' with respect to the reference. Please note:
First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
If the reference is valid, for a given statement: if the facts or data it contains can be found entirely or partially within the reference, it is considered 'supported' (data accepts rounding); if all facts and data in the statement cannot be found in the reference, it is considered 'unsupported'.

You should return the result in a JSON list format, where each item in the list contains the statement's index and the judgment result, for example:
[
    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

Below are the reference and statements:
<reference>
Research on the Application of Artificial Intelligence Video Feedback System in College Basketball Shooting Teaching

Objective: To test the effect of the artificial intelligence video feedback system in the basketball shooting teaching in Colleges and universities. Methods: 24 male basketball players from XX University were randomly divided into experimental group (n=12) and control group (n=12). The experimental group and the control group were given shooting learning for 8 weeks. During each teaching period, the experimental group was intervened with 10-minute video feedback system, while the control group was not intervened. Results: After the experiment, the shooting percentage and the performance of action skill evaluation of the experimental group were significantly higher than those before the experiment (p=0. 0320.05). After the experiment, the experimental group in the fixed-point shot and jump shot shooting percentage and action skill evaluation results were significantly higher than the control group (p=0. 026<0.05). Conclusion: The application of artificial intelligence video feedback system in college basketball shooting teaching is helpful to: Students can get the action points of shooting technique more richly and intuitively; Help students quickly establish the technical action model and spatial thinking concept of shooting; The correction and consolidation of shooting techniques are more personalized and timely.

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Proceedings
ICCSMT
ICCSMT 2020
2020 International Conference on Computer Science and Management Technology (ICCSMT)
Research on the Application of Artificial Intelligence Video Feedback System in College Basketball Shooting Teaching
Year: 2020, Pages: 144-148
DOI Bookmark:
10.1109/ICCSMT51754.2020.00035
Authors
Jianjian Lin
,
University of International Relations,Beijing,China,100091

Lihong Sun
,
Shandong University of Finance and Economics,Shandong,China,250014

Jie Song
,
Beijing University of Agriculture,Beijing,China,102206
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Abstract
Objective: To test the effect of the artificial intelligence video feedback system in the basketball shooting teaching in Colleges and universities. Methods: 24 male basketball players from XX University were randomly divided into experimental group (n=12) and control group (n=12). The experimental group and the control group were given shooting learning for 8 weeks. During each teaching period, the experimental group was intervened with 10-minute video feedback system, while the control group was not intervened. Results: After the experiment, the shooting percentage and the performance of action skill evaluation of the experimental group were significantly higher than those before the experiment (p=0. 032<0.05). After the experiment, the control group in the fixed-point shot and jump shot shooting percentage and action skill evaluation results were higher than before the experiment (p=0.158>0.05). After the experiment, the experimental group in the fixed-point shot and jump shot shooting percentage and action skill evaluation results were significantly higher than the control group (p=0. 026<0.05). Conclusion: The application of artificial intelligence video feedback system in college basketball shooting teaching is helpful to: Students can get the action points of shooting technique more richly and intuitively; Help students quickly establish the technical action model and spatial thinking concept of shooting; The correction and consolidation of shooting techniques are more personalized and timely.
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</reference>

<statements>
1. In a college basketball study, male players were randomized to experimental (AI video feedback, n=12) and control (n=12) groups over 8 weeks, the experimental group receiving 10-minute video-feedback interventions per session; outcomes were shooting percentage and expert action-skill evaluation.
2. College basketball (AI video feedback): the experimental group improved significantly (p = 0.032 < 0.05) and significantly exceeded controls on fixed-point and jump shots (p = 0.026 < 0.05); control-group gains were non-significant (p = 0.158).
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.