the need for dyadic data analysis as an emerging method to explore emotional factors

Dyadic data analysis (dda) has been suggested, in the existing literature, to be used to explore interpersonal variables which have long been conventionally investigated in isolation. dda is effective in analyzing procedures that go on among dyads in studies of family relations, partnership, teacher-student affairs, and many other interpersonal relationships. illustrative examples come from psychological, behavioral, and sociological studies that help develop the researcher’s ability to investigate relationship processes, model and test for the effects of actors, partners, and relationships, and control for the statistical inter-dependence which can be conceived between partners. the present paper first reviews the distinctive features of dda and the potential advantages it can have for language studies. also, it shows how longitudinal dda is strongly needed in the investigation of l2 affective variables in the second language acquisition (sla) domain to longitudinally explore the dynamic and developmental nature of language learners’ affective factors. finally, it goes on with making suggestions for a future line of inquiry using this innovative analytic procedure and ends with several conclusive remarks about this analytical framework which is compatible with the complexity of dynamic systems theory (cdst).  

the need for dyadic data analysis as an emerging method to explore emotional factors

dyadic data analysis (dda) has been suggested, in the existing literature, to be used to explore interpersonal variables which have long been conventionally investigated in isolation. dda is effective in analyzing procedures that go on among dyads in studies of family relations, partnership, teacher-student affairs, and many other interpersonal relationships. illustrative examples come from psychological, behavioral, and sociological studies that help develop the researcher’s ability to investigate relationship processes, model and test for the effects of actors, partners, and relationships, and control for the statistical inter-dependence which can be conceived between partners. the present paper first reviews the distinctive features of dda and the potential advantages it can have for language studies. also, it shows how longitudinal dda is strongly needed in the investigation of l2 affective variables in the second language acquisition (sla) domain to longitudinally explore the dynamic and developmental nature of language learners’ affective factors. finally, it goes on with making suggestions for a future line of inquiry using this innovative analytic procedure and ends with several conclusive remarks about this analytical framework which is compatible with the complexity of dynamic systems theory (cdst).