1. Characterizing Cognitive Styles: James Anderson Perceive elements as a part of a total picture Do best on verbal tasks Learn material which has social/human content Performance influenced by authorizing figures’ confidence or doubt Style conflicts with traditional school environment Perceive elements as discrete from their background Do best on analytic tasks Learn material that is inanimate and impersonal more easily Performance not greatly affected by opinions of others Style matches up with most school environments Field-Dependent, Relational/Holistic, Affective Field-Independent, Analytic, Non-Affective Cognitive style and multicultural populations. Journal of Teacher Education, 39, 1, 2-9

2. Populations Exhibiting These Cognitive Styles: James Anderson American-Indians Mexican-Americans African-Americans Vietnamese-Americans Puerto Rican-Americans Chinese-Americans Japanese-Americans Many Euro-American females Euro-Americans (primarily, males) Minorities with high degree of acculturation Field-Dependent, Relational/Holistic, Affective Field-Independent, Analytic, Non-Affective Cognitive style and multicultural populations. Journal of Teacher Education, 39, 1, 2-9

3. Characterizing Cognitive Styles: Sherry Turkle and Seymour Papert Enjoy working with information in context (conceptual framework) Like to arrange and rearrange well-known materials to form theories Prefer to have relationship with or understanding of subjects of inquiry Often need to “visualize” information Prefer to collaborate Enjoy manipulating abstract symbols Develop theories by manipulating symbols based-on a set of predefined rules Prefer to study material separate from self Do not need to “visualize” information Enjoy working alone Concrete/Bricolage (Levi-Strauss)Canonical/Formal Epistemological pluralism: styles and voices within the computer culture. Signs:Journal of Women in Culture and Society, 16, 1, 128-157 1990.

4. How Women Practice Science Sue Rosser:Women’s Way of Knowing Use of precise gender neutral language to describe data and theories. Critique of observations, conclusions drawn, and theories generated differing from those drawn by the traditional scientist from the same observations. Awareness of other biases such as those of race, class, sexual preference, and religious affiliation which may permeate theories and conclusions drawn from experimental observations. Development of theories that are relational, interdependent, and multicausal rather than hierarchical, reductionistic, and dualistic. Female Friendly Science: Applying Women’s Studies Methods and Theories to Attract Students. By Sue Rosser, Pergamon Press. Women’s Ways of Knowing, By Mary Field Belenkey, Blythe McVicker Clinchy, Nancy Rule Goldberger, and Jill Mattuck Tarule.