Rasch measures for Inter-Personal and Intra-Personal Student Self-Views Based on Gardner Intelligences

Document Type

Book Chapter

Publisher

Nova Science Publishers

Faculty

Faculty of Education and Arts

School

School of Education / Fogarty Learning Centre

RAS ID

10293

Comments

Edries, A. , & Waugh, R. F. (2010). Rasch measures for Inter-Personal and Intra-Personal Student Self-Views Based on Gardner Intelligences. In Russell F. Waugh (Eds.). Applications of Rasch Measurement in Education (pp. 37-62). Hauppauge, New York: Nova Science Publishers. Available here.

Abstract

The Australian Islamic College is a co-educational Islamic Independent school with 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 two Gardner Intelligences: inter-personal and intra-personal (N=321). Only 8 out 12 items fitted the measurement model for inter-personal self-views and 10 out of 12 items for intra-personal self-views. 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 =38.77, df=32, p=0.19; and x2 = 57.65, df = 40, p= 0.03 showing no significant interaction between student measures and item difficulties along the scale, thus supporting uni-dimensional scales. The Person Separation Indices are respectively 0.78, and 0.85 with standard errors of about 0.09 logits showing acceptable separation of measures compared to errors, and improvements could be made by adding more items to all measures.

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