Rasch measures for sports, drama and music student self-views based on Gardner intelligences

Document Type

Book Chapter


Nova Science Publishers


Faculty of Education and Arts


School of Education / Fogarty Learning Centre




Edries, A. , & Waugh, R. F. (2010). Rasch measures for sports, drama and music student self-views based on Gardner intelligences. In Russell F. Waugh (Eds.). Specialized Rasch Measures Applied at the Forefront of Education (pp. 25-49). Hauppauge, New York: Nova Science Publishers, Inc. Available here.


A co-educational Independent Australian Islamic College has three campuses which cater for migrant students from war-torn countries and others with culturally and linguistically, diverse backgrounds. This paper is part of a larger study to identify the strengths and interests of Islamic students, across eight of Gardner’s intelligence domains, as perceived by the students, so that the College could better meet the needs of these students. This study is important for the Islamic College because it is hoped that the study will lead to the provision of opportunities for students to increase their confidence, self-esteem and motivation, and to achieve better in academic and non-academic areas. Student self-views were based on three aspects: (1) Things I really like; (2) Things I enjoy; and (3) Things I prefer, with items answered in two perspectives What I would like to do and What I actually do. This paper reports a Rasch analysis of student self-views based on three Gardner Intelligences: Sports, Drama and Music (N=321). All 12 items fitted the measurement model for Sports Self-Views, 9 out of 12 items for Drama Self-Views and all 12 items for Music. For all items, students found it easier to say what they would like to do than to actually do it. The item-trait interaction chi-squares are respectively: x2 =69.56, df=48, p=0.02; x2 =43.39, df=36, p=0.41and x2 = 52.85, df = 48, p= 0.29 showing no significant interaction between student measures and item difficulties along the scale, thus supporting uni-dimensional scales. The Person Separation Indices are respectively 0.88, 0.89 and 0.88 with standard errors of about 0.10 logits showing acceptable separation of measures compared to errors, and improvements could be made by adding more items to all measures.