Students’ Understanding of Human Nature: An Analogical Approach R. BROCK FROST AND ERIC AMSEL Weber State University Introduction University students enter psychology classes with an intuitive theory about the nature of the discipline (Amsel et al., 2005). This intuitive theory (called Folk Psychology) is an inherently unscientific account of behavior in terms of conscious mental states (D’Andrade, 1987). Folk Psychology is inconsistent with Scientific Psychology, which is an account of behavior based on the influence of genetic, biological, cognitive, and sociocultural forces. Amsel et al. (2005) found that Psychology students more strongly distinguish between the two theories than do others, embracing the tenets of Scientific Psychology without rejecting those of Folk Psychology. They propose that the two forms of explanation conceptually coexist. Following up on the previous work, the present study explores how Psychology and other students think about how human beings are like animals (i.e., great apes) and machines (i.e., computers). In Scientific Psychology such commonalties are based more on relational analogies than literal similarities. For example, beyond any literal similarity, human beings, like computers, are thought to compute, store, and retrieve information. Similarly, humans, like animals, are thought to evolve species-specific behavior which may not be literally similar. It was hypothesized that compared to others, Psychology students would be more likely to judge commonalities between humans, animals, and machines based on relational analogies than literal similarities. Abstract Psychology, Science and Humanities students were interviewed to assess their judgments of how human beings, animals (great apes), and machines (computers) were alike. Science students were more likely than others to judge that human beings and animals were similar, but Psychology students were more likely to justify their judgments with relational analogies than literal similarities. References Amsel, E., Anderson, C., & Corbin, P. (April, 2005). Conceptual change in psychology majors’ understanding of the discipline. Poster presented at RMPA, Phoenix AZ. Carey, S. (2000). Science education asconceptual change. Journal of Applied Developmental Psychology, 21, D'Andrade, R. G. (1987). A folk model of the mind. In D. Holland and N. Quinn (Eds.) Cultural Models in Language and Though (pp ). Cambridge UK: Cambridge University Press. Gentner, D. & Wolff, P. (2000). Metaphor and knowledge change. In E. Dietrich & A. Markman (Eds.), Cognitive dynamics: Conceptual change in humans and machines (pp ). Mahwah, NJ: Lawrence Erlbaum Associates. Nersessian, N. J. (1989). Conceptual change in science and in science education. Synthèse, 80, Methods Participants Students were initially screened to assess their academic background. Those with appropriate backgrounds were then contacted and offered $5.00 to participate in the study. The sample consisted of 30 (15M and 15F) seniors or juniors who were majoring in Psychology (N=10), Natural Science (N=10; 3 Physics, 3 Microbiology, and 4 Zoology), or Arts and Humanities (N=10; 8 English, 1 History, and 1 Communication). Interview Participants’ judgments and justifications of the similarity of humans and animals and humans and machines were assessed in an interview format. The interview began with general questions regarding the similarity between humans and animals or machines. Other questions were also posed, but only the results from the general questions are reported. Participants were asked, “To what extent are human beings similar to animals (e.g., great apes)/machines (e.g., computers)?” Participants recorded their ratings on a 7-point scale, anchored by Not at all Similar (1), A Little Similar (2), Somewhat Alike (3) Moderately Similar (4), A Good Deal Alike (5), Very Alike (6), Identical (7). Participants were probed about their ratings of entity similarity with follow-up questions such as, “Why do you say that they are _________?”, “What makes them ______?”, and “What exactly are you saying is alike about humans and _______?” The probes were designed to elicit justifications for participants’ similarity ratings. The justifications were coded as literal similarity (elements of one entity are also found in the other) or relational analogy (relations between elements in one entity are also found in another) based on Gentner & Woolf (2000). An intermediate code was also established for cases with elements of each justification (partial analogy). There were two orders of presenting the interview. Half the participants in each group were first posed questions addressing human/animal similarities and the other half were posed questions addressing human/machine similarities. Results Justifications were coded on an interval scale, with Literal Similarity coded as 1, Partial Analogy as 2, and Relational Analogy as 3 (see Table 1). Inter-rater reliability based on all the responses of 30% of the participants was 96%. Two analyses tested the prediction that Psychology students would be more likely than others to judge commonalities between entities based on relational analogies. The first analysis was a 3 (Groups) by 2 (Entities) ANCOVA on similarity ratings with sex and order as covariates. There was a main Groups effect which approached significance, F(2,25)=3.17, p=.059. Science students (M=4.77) judged greater overall similarity between entities than did Humanities students (M=3.43), with Psychology students (M=3.95) no different from the other groups. The main effect was modulated by a Groups by Entity interaction effect which also approached significance, F(2,25)=2.85, p=.076. As shown in Table 2, Science students judged greater similarity than Humanities and Psychology students in the Animal condition, F(2,25)=6.58, p<.01, but there was no Groups difference in the Machine condition, F(2,25)=.33, ns. The second analysis was a 3 (Groups) by 2 (Entity) ANCOVA on justification responses with sex and order as covariates. There was a main Group effect, F(2,25)=6.75, p<.01. Psychology students (M=2.10) had higher justification responses than did Humanities students (M=1.31), with Science students (M=1.89) no different from the other groups. There was a significant Group by Entity interaction effect, F(2,25)= 6.31, p<.01 (see Table 3). Psychology students had higher justification responses than Humanities and Science students in the Animal condition, F(2,25)=10.94, p<.001. Psychology and Science students had higher justifications responses compared to Humanities students, in the Machine Condition, an effect which approached significance F(2,25)=3.03, p=.066 Discussion It was predicted that compared to others, Psychology students would be more likely to judge commonalities between humans, animals, and machines based on relational analogies than literal similarities. The prediction was confirmed most strongly for Human/Animal comparisons. Although, compared to Science students, Psychology students judged less similarity between Animals and Humans, they justified their similarity judgments with relational analogies more so than others. Such a pattern may reflect Amsel et al.’s (2005) claim that Psychology majors continue to hold onto the tenets of Folk psychology, with its assumption of the uniqueness of human beings, despite adopting those of Scientific psychology with its relationally-based continuity between human beings, animals, and computers. We are continuing to collect data freshmen and sophomores motivated to major in Psychology to confirm this analysis. We predict that would- be psychology majors will be less inclined than advanced Psychology students to judge humans and animals as similar and justify their judgments with relational analogies. Table 1: Justifications of Similarity Ratings 1. Literal Similarity a. Animals and humans are both bipedal, have hands. b. Humans and computers don’t work the way they are supposed to. 2. Partial Analogy a. Both humans and computers solve problems, a machine uses a set....mechanism while a human just tries different stuff b. Both have gone through evolution, have opposable thumbs, and similar social systems. 3. Relational Analogy a. The brain is compartmentalized, different areas do different stuff, kinda like computer programs. b. Humans and apes have anatomical structures with similar functions. Figure 2: Similarity Ratings by Groups and Entity Identical Not at all Similar Literal Similarity Relational Analogy Figure 3: Justifications by Groups and Entity