University of Tasmania
Browse

File(s) under permanent embargo

Secondary school students’ directly measured physical activity in school physical education – The expectancy-value theory approach

conference contribution
posted on 2023-05-24, 16:31 authored by Arto Grasten

Schools are an ideal setting for promoting physical activity (PA), because schools can reach a full range of individuals in a population at no additional cost [4]. The expectancy-related beliefs and values have been found to be crucial factors in predicting individuals’ physical education (PE) performance, such as PA [7,8]. However, previous studies [2,7,8] were based on self-reports, and that makes it difficult to accurately assess students’ PA in PE [3,5]. Therefore, exploring the relationships between students’ expectancy beliefs, values, and directly measured PA in PE lessons are of great value for promoting PA in school PE.

Three research questions encapsulated the purpose of present study. The first aim was to examine the relationships between expectancy beliefs, subjective task values, and directly measured PA in PE lessons. The second aim was to investigate gender differences in these variables. The final aim was to analyze prediction of moderate to vigorous PA (MVPA) in PE lessons by expectancy beliefs and task values.

History

Publication title

Proceedings of the 2012 North American Society for the Psychology of Sport and Physical Activity Conference

Pagination

1-4

Department/School

Faculty of Education

Publisher

North American Society for the Psychology of Sport and Physical Activity

Place of publication

USA

Event title

The 2012 North American Society for the Psychology of Sport and Physical Activity Conference

Event Venue

Honolulu, Hawaii

Date of Event (Start Date)

2012-06-07

Date of Event (End Date)

2012-06-09

Repository Status

  • Restricted

Socio-economic Objectives

Evaluation of health outcomes

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC