Transnational settlement is one of the most pervasive phenomena facing most, if not all, countries in the 21st century. Optimising the educational outcomes of immigrant students will ensure successful resettlement for immigrants, and will contribute towards economic prosperity for the host countries. Taking an intercultural approach to transitions in mathematics education, the overall aim of the project is to investigate the mathematics learning experiences of the many thousands of students who move from one culture to another: as international students in search of a ‘better’ school/tertiary education, as family members who support their loved ones’ migration, or as ‘first-generation’ children who move between different cultures continuously as part of their day-to-day lives.
The latest PISA assessment results have extended previous years’ findings that Australia’s rankings amongst the world’s education systems have been propped up by the performance of students with immigrant parents. In PISA 2015, mathematical literacy scores of students from Australian-born families were significantly lower than those attained by first-generation and foreign-born students (Thomson, Wernert, O’Grady & Rodrigues, 2016). These students attend the same school as one another, have the same teachers, have the same in-class opportunities, and are generally treated equally in the (mathematics) education system. Yet, there seems to be a cultural pattern in which students who have grown up moving between Australian and family cultures outperform those who do not make such transitions (Australian-born) or for whom the transitions are new and novel (immigrants).
What common characteristics of these students’ mathematics learning experiences account for their performance and achievement, despite being schooled in the same environments as their native-born peers? How culturally-neutral are these characteristics; in other words, to what extent are these characteristics independent of particular cultural norms or traditions, so that students from other cultural backgrounds might be able to acquire them too?
The paper advances a developmental systems approach to transitions, in which a “system” (e.g., a student) comprises a variety of elements or smaller systems. These elements include cultural experiences such as values and beliefs, psychological experiences such as needs and motivations, as well as biological and social experiences. They work together in mutual constraint, so that each element affects and is affected by other elements (Lerner, 2006). Changes to any element that are sustainable and enduring can lead to transformational change of the entire system (Overton, 2006). Therefore, a shift in students’ abilities in mathematics can be initiated by promoting and maintaining change within their values, attitudes, and motivations.
Objective and research question
This paper reports on one component of the larger project, which is the development of the Valuing Deep Learning (VDL) Questionnaire. The questionnaire framework draws from the Deep Learning Competency Framework (Victorian Department of Education and Early Childhood Development, 2015) of six deep learning competencies of critical thinking, collaboration, communication, creativity, citizenship and character, as well as the ‘What I Find Important (in my mathematics learning)’ questionnaire (Seah & Andersson, 2015). The framework will anchor the research design of the project by investigating the value of deep learning placed by students on each of the six deep learning competencies. In particular, the discussion in this paper responds to a key research question: What are the psychometric properties of the VDL Questionnaire?
References Adams, R. J., Wilson, M., & Wang, W. (1997). The multidimensional random coefficients multinomial logit model. Applied Psychological Measurement, 21(1), 1-23. Cronbach, N. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334. Department of Education and Early Childhood Development (DEECD). (2015). New pedagogies for deep learning. Retrieved from http://fusecontent.education.vic.gov.au/64d291b9-60d0-4afd-9da5-6d0105921af4/8189 deecd new pedagogies program_dl_booklet_lr.pdf Lerner, R. M. (2006). Developmental science, developmental systems, and contemporary theories of human development. In W. Damn & R. M. Lerner (Eds.), Handbook of child psychology (6th ed.) (pp. 1-17). Hoboken, NJ: John Wiley & Sons. Overton, W. F. (2006). Developmental psychology: Philosophy, concepts, methodology. In W. Damn & R. M. Lerner (Eds.) Handbook of Child Psychology (6th ed.) (pp. 18-88). Hoboken, NJ: John Wiley & Sons. Seah, W. T., & Andersson, A. (2015). Valuing diversity in mathematics pedagogy through the volitional nature and alignment of values. In A. Bishop, H. Tan, & T. Barkatsas (Eds.), Diversity in mathematics education: Towards inclusive practices. (pp. 167-183). Switzerland: Springer. Thomson, S., Wernert, N., O’Grady, E., & Rodrigues, S. (2016). TIMSS 2015: A first look at Australia’s results. Camberwell, Australia: Australian Council for Educational Research. Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. Chicago: Meta Press. Wu, M. L., Adams, R. J., & Wilson, M. R. (1998). ACER ConQuest: Generalised Item Response Modelling Software. Camberwell: The Australian Council for Educational Research.
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