The Effectiveness of Application of Moodle Software in Traditional Sports Game Courses

Due to the overemphasis of traditional sports at the expense of other movement domains in physical education (PE) programmes, there is a need to consider what factors might enable or limit PE teachers’ incorporation of some of these other domains that can support student learning. The focus of this article is on one such marginalized domain – alternative environment activities (AEAs). AEAs can afford students a breadth of opportunities for moderate-to-vigorous physical activity in different environments (i.e. land, snow and ice, water, air) and improve environmental awareness and stewardship. This article reports on a comparative investigation of Nova Scotian (Canadian) and Irish PE teachers’ incorporation of AEAs in their PE programmes. To understand what similarities or differences might exist with respect to these PE teachers’ incorporation of AEAs, along with existing enablers and barriers, a self-selected sample of current PE teachers (Nova Scotia = 53; Ireland = 64) completed a 22-item online questionnaire. Descriptive and inferential statistical analyses were employed to conduct comparisons among the two data sets. PE teachers’ understandings of curricular requirements for AEAs were found to be an issue in both Nova Scotia and Ireland. Reported significant differences include: AEA-related professional development participation; most important factors for deciding not to include AEAs; and feelings of school administrative support towards AEA incorporation. Findings also suggest that various issues may be hindering incorporation of AEAs in PE programmes, and that some of these issues do differ based on where the PE programme is situated.

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A Bayesian adjusted plus-minus analysis for the esport Dota 2

Journal of Quantitative Analysis in Sports ◽

10.1515/jqas-2019-0103 ◽

2020 ◽

Vol 16 (4) ◽

pp. 325-341

Author(s):

Nicholas Clark ◽

Brian Macdonald ◽

Ian Kloo

Keyword(s):

Professional Sports ◽

Hierarchical Regression ◽

Sports Analytics ◽

Bayesian Hierarchical ◽

The Past ◽

Score Statistics ◽

Level Statistics ◽

Traditional Sports ◽

Level Information ◽

Individual Player

AbstractAnalytics and professional sports have become linked over the past several years, but little attention has been paid to the growing field of esports within the sports analytics community. We seek to apply an Adjusted Plus Minus (APM) model, an accepted analytic approach used in traditional sports like hockey and basketball, to one particular esports game: Defense of the Ancients 2 (Dota 2). As with traditional sports, we show how APM metrics developed with Bayesian hierarchical regression can be used to quantify individual player contributions to their teams and, ultimately, use this player-level information to predict game outcomes. In particular, we first provide evidence that gold can be used as a continuous proxy for wins to evaluate a team’s performance, and then use a Bayesian APM model to estimate how players contribute to their team’s gold differential. We demonstrate that this APM model outperforms models based on common team-level statistics (often referred to as “box score statistics”). Beyond the specifics of our modeling approach, this paper serves as an example of the potential utility of applying analytical methodologies from traditional sports analytics to esports.

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Current situation and development direction of sports industry in colleges and universities based on euclidean algorithm

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219032 ◽

2021 ◽

pp. 1-7

Author(s):

Shunjiang Ma ◽

Gaicheng Liu ◽

Zhiwu Huang

Keyword(s):

Computer Technology ◽

Colleges And Universities ◽

Status Quo ◽

Euclidean Algorithm ◽

Test Results ◽

Sports Industry ◽

Development Direction ◽

The Status ◽

Traditional Sports ◽

And Function

With the development of sports in colleges and universities, the research on innovation reform of sports industry has been deepened. Therefore, based on the above situation, a study of the status quo and development direction of sports industry in colleges and universities based on the Euclid algorithm is proposed. In the research here, according to the traditional sports industry concept to sum up, and then according to the advantages of computer technology to deal with the relevant data. In order to realize good overlap between data, an application of Euclidean algorithm is proposed. In the test of Euclidean algorithm, the efficiency and function of the algorithm are tested comprehensively, and the test results show that the research is feasible.

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