Young children's motivational beliefs about learning science

Early Childhood Research Quarterly 23 (2008) 378–394

Contents lists available at ScienceDirect

Early Childhood Research Quarterly

Young children’s motivational beliefs about learning science Panayota Mantzicopoulos ∗ , Helen Patrick, Ala Samarapungavan Department of Educational Studies, Purdue University, BRNG, 100 North University Street, Department of Educational Studies, Purdue University, West Lafayette, IN 47907, United States

a r t i c l e

i n f o

Article history: Received 12 February 2007 Received in revised form 11 March 2008 Accepted 11 April 2008 Keywords: Science learning Young children’s motivational beliefs Science self-concept Perceptions of science competence

a b s t r a c t For learning science, motivational beliefs such as confidence in one’s science abilities and liking of science are associated with current and future science achievement, as well as continued interest in science classes and careers. However, there are currently no measures to test young children’s motivational beliefs related to science learning. To meet this need, we developed the Puppet Interview Scales of Competence in and Enjoyment of Science (PISCES). We piloted PISCES with 113 kindergarten children in public schools participating in the Scientific Literacy Project (SLP). Factor analysis supported the multidimensional structure of young children’s self-related beliefs about learning science. PISCES scales measured Science Liking, Science Competence, and Ease of Science Learning. Correlations among PISCES scales and achievement subtests provided evidence of PISCES’s validity. Children’s motivational beliefs varied as a function of length of time spent learning science, with competence beliefs associated positively with science experience. There were no gender differences. © 2008 Elsevier Inc. All rights reserved.

Children’s beliefs about their academic experiences have important implications for their school adjustment and achievement (Dweck, 1998; Harter, 1998; Valentine, DuBois, & Cooper, 2004; Wigfield & Eccles, 2002). Motivational beliefs such as students’ self-competence for, and value or liking of, science are associated with current and future science achievement and continued interest in science classes and careers (Jacobs, Finken, Griffin, & Wright, 1998; Simpkins, Davis-Kean, & Eccles, 2006; Simpson & Oliver, 1990). However, these findings are based on research with older children and adolescents and little is known about young children’s motivational beliefs related to science learning. This is surprising given the importance of science for individuals’ educational success and careers, and for the nation’s future. In order to prepare children adequately for learning science in the upper elementary grades and beyond, and to sustain an enduring interest in learning about science, current research agendas (e.g., Anderson & Helms, 2001; Rennie, Feher, Dierking, & Falk, 2003) call for targeting science literacy in the early school years. Developmentally appropriate, inquiry-based science curricula for young children are needed, in addition to research that examines young children’s learning about science, including their beliefs about their competence and interest in science. This critical research is hampered, however, by the lack of developmentally appropriate and psychometrically robust instruments for measuring young children’s science beliefs. In the present study, we address this need by investigating young children’s beliefs about their competence and skills in science, as well as their liking of science, using a new measure—the Puppet Interview Scales of Competence in and Enjoyment of Science (PISCES). We collected data at two schools participating in the Scientific Literacy Project (SLP; Mantzicopoulos, Patrick, & Samarapungavan, 2005)—a program that integrates science inquiry and literacy activities in line with recommendations by the National Research Council (2000, 2001, 2007). The sample of kindergarten students who participated in this study was ethnically and linguistically diverse and primarily low-income. We examined: (a) the structure of young children’s

∗ Corresponding author. Tel.: +1 765 494 7247; fax: +1 765 496 1228. E-mail address: [email protected] (P. Mantzicopoulos). 0885-2006/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.ecresq.2008.04.001

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

379

beliefs about science learning and (b) evidence of the instrument’s reliability and validity. We then investigated: (c) variations in children’s science-related beliefs as a function of participation in integrated science inquiry and literacy activities and (d) gender differences between boys’ and girls’ early science-related beliefs. 1. Early experience and the development of self-beliefs Young children are intrinsically interested in science. They are curious about the world around them (Gelman, 1990; Piaget, 1967) and about the causes, processes, and mechanisms that underlie biological and physical phenomena (Brown, 1997). This interest is reflected in their everyday conversations; even before they begin formal schooling, young children initiate conversations in the course of daily activities and ask numerous questions about science (Callanan & Jipson, 2001; Fleer & Cahill, 2001; Kallery & Psillos, 2001; Korpan, Bisanz, Bisanz, Boehme, & Lynch, 1997). Despite children’s well-documented natural interest in science, little time is typically allocated to learning science during the early school years, with only 6–13% of instructional time spent on teaching science in grades 1–4 (National Center for Education Statistics, 1997; National Institute of Child Health and Human Development, 2005; Weiss, Pasley, Smith, Banilower, & Heck, 2003). Contributing factors include teachers’ inadequate science content knowledge and a principal focus on language arts that limits the time for other subjects in the early grades (Marx & Harris, 2006). Specifically, fewer than half of elementary teachers have completed the minimum number of recommended science courses (Fulp, 2002) and many elementary school teachers hold significant misconceptions (e.g., Kruger, 1990). This may explain why science is not integrated with other important content areas (i.e., literacy and/or mathematics) and why recommended practices that are developmentally appropriate and engage children in the process of inquiry are even less common (Fulp, 2002). There are concerns that attempts at blending approaches to teaching literacy and science are unsuccessful when teachers, who are less prepared to teach science and more prepared to teach language arts, tip the scale in favor of language arts. When these teachers attempt to integrate science with other activities, they end up teaching very little, if any, science content (Dickinson, Burns, Hagen, & Locker, 1997). Thus, although young children have been described as “natural” scientists (Worth & Grollman, 2003), they are afforded few opportunities for learning not only science concepts and content but also the functions and structure of scientific language, discourse, and processes. At least two lines of research suggest that fostering these opportunities is critical in socializing children to think of science as a meaningful and worthwhile enterprise and to view themselves as literate constituents in the process. Early memory researchers have shown that participation in real-world activities and events underlies the construction of schemas about the nature of these events (DeMarie, Norman, & Abshier, 2000; Hudson, Shapiro, & Sosa, 1995) and is key to the organization and maintenance of a coherent sense of self (Bluck, 2003; Fivush & Haden, 2003). Thus, it is through active engagement with science that children develop concepts of themselves as science learners and participants in the process of science, construct understandings of science as a discipline, and come to view science as interesting and worth pursuing. Similarly, motivation researchers have highlighted the role of experience in the development of self-beliefs (Wigfield et al., 1997). Academic experiences are related to the development of beliefs about school competence in different domains and some researchers have provided evidence for a causal path from experience to beliefs (Chapman & Tunmer, 1997; Wigfield & Karpathian, 1991). For example, research shows that experiences while learning to read, including successes or difficulties encountered during reading, influence children’s enjoyment of reading as well as their views of themselves as competent readers (Aunola, Leskinen, Onatsu-Arvilommi, & Nurmi, 2002; Chapman, Tunmer, & Pronchow, 2000). Additionally, success experiences with mathematics in the early school grades are causally related to the development of children’s positive beliefs of their competence in this domain, and their actual achievement (e.g., Helmke & van Aken, 1995). In the later school years, content-specific competence and value beliefs also predict the choices children make in specific domains, when options are available (Jacobs et al., 1998). Because the evolution of children’s beliefs about a particular subject area is grounded in their experiences within that domain, it is important to ask whether kindergarteners actually have understandings about what science involves. As early as preschool, perhaps both as a result of experiences with print at home and preschool, many children are quite familiar with tasks and activities concerning subjects such as literacy. When asked about the work that they do in literacy centers, preschoolers can differentiate component activities of literacy instruction, such as learning about letters, drawing pictures, writing stories, and naming “ABCs” (Wiltz & Klein, 2001). Literacy is clearly privileged at the beginning of school: the curriculum in the early grades is dominated by a focus on language arts (Duke, 2000; Lanahan, Princiotta, & Enyeart, 2006) and this contributes to children’s greater awareness of literature as a content area. Because science receives substantially less attention than other academic subjects do, young children may not be familiar with what science is, unlike their familiarity with reading. Very limited evidence exists on young children’s views about science as a content area, however. Recent data, based on open-ended interviews conducted in the first month of kindergarten, confirm that only a minority of children ascribe correct content, processes, or activities when asked: “What do you think you’ll learn in science in kindergarten?” (Mantzicopoulos, Patrick, & Samarapungavan, 2007). Even so, children’s perceptions of science evolve over the course of the school year with participation in science activities. Responses to questions later in the year about kindergarten science reflect a growing understanding that science is a content area with its own instructional content, vocabulary, processes, and activities (Mantzicopoulos et al., 2007). In the current study, we also began by asking children to tell us about their experiences with learning science in school. Although this was not a primary goal of the study, it was necessary for validity purposes to establish that children could

380

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

remember what their science lessons involved; this step was intended to strengthen our confidence that children’s responses to the items in PISCES were relevant to their experiences. 2. Structure and organization of young children’s beliefs about learning science In constructing a measure of children’s beliefs about learning science, we were guided by the literature on the structure and organization of children’s self-cognitions. Since the 1980s, theoretical and measurement advances have facilitated research about the structure of self-concept. Over the last two decades, researchers have shown that as early as kindergarten, young children’s self-beliefs are differentiated across several broad cognitive and noncognitive domains. That is, young children’s beliefs vary across domains, such as reading, mathematics, and sports (e.g., Eccles, Wigfield, Harold, & Blumenfeld, 1993; Eder, 1990; Harter & Pike, 1984; Mantzicopoulos, French, & Maller, 2004; Marsh, Craven, & Debus, 1998; Marsh, Ellis, & Craven, 2002; Measelle, Ablow, Cowan, & Cowan, 1998; Strein & Simonson, 1999). Directly relevant to our work, however, are findings associated with Expectancy-Value theory (Eccles et al., 1983; Eccles, 2005). Young children are not only capable of specificity across distinct domains, but can also differentiate their beliefs within each domain. For example, Eccles et al. (1993) reported that first-graders reliably distinguished their beliefs about competence from those about value or liking, within the reading and math domains. More recently, Chapman and coworkers substantiated that 5- and 6-year-old children’s reading self-concepts varied along a three-dimensional structure that included beliefs about reading competence, beliefs about reading difficulty, and enjoyment or liking of reading (Chapman & Tunmer, 1995; Chapman et al., 2000). In conceptualizing the assessment of young children’s motivational beliefs about learning science, we built on this evidence and expected that kindergarteners’ beliefs would be multidimensional. Research discussed in the previous section has shown that young children’s experiences with and engagement in domain-specific learning activities have important implications for the development of self-beliefs involving that domain (e.g., Aunola et al., 2002; Chapman et al., 2000). Consistent with that view, we constructed items that reflected children’s experiences with the science content and activities conducted in the classroom. We were interested in exploring whether children’s beliefs about learning science would also be differentiated across dimensions representing Science Competence and Specific Skills, Science Liking, and Ease of Learning Science, consistent with Eccles et al.’s (1983) Expectancy-Value model, and paralleling the model by Chapman et al. (2000) for reading. 3. Sustained experiences with science, motivational beliefs, and gender differences One suggestion for the negative beliefs that upper elementary children typically have about science as a subject and their competence in it, relative to other academic subjects, is that they have not had sufficient experiences with learning science (Andre, Whigham, Hendrickson, & Chambers, 1999). The limited exposure to science, coupled with the less-thanideal instructional practices discussed earlier (e.g., Fulp, 2002), are barriers to children’s development of rich and meaningful knowledge about the content, processes, and language of science. These barriers compromise children’s attitudes and beliefs about science. Consequently, when children reach the upper elementary grades and encounter science content as part of the required curriculum, they report that science is more difficult than many other school subjects, and that they are better at language arts and math than at science (Andre et al., 1999; Cleaves, 2005). The implications of these findings are daunting. By the upper elementary years, children have developed differentiated views of effort and ability, so that expending greater effort becomes associated with a perception of lesser ability. The capacity to make distinctions between effort and ability influences children’s interpretations of success and failure (Nicholls, 1990). Thus, when children perceive science as a difficult subject that requires more effort, they are more likely to interpret this difficulty as an indication of having low science ability and to think of themselves as not competent at science. To prevent this alarming cycle of negative beliefs, it is necessary to introduce science early, as an ongoing, meaningful, and salient part of the curriculum. Isolated pockets of exposure to science that lack conceptual coherence are not likely to impact the development of knowledge, skills, and/or adaptive motivational beliefs (Worth & Grollman, 2003). Considering that young children are likely to interpret their experiences as involving mastery (Harter, 1998), we expect that early and sustained experience with developmentally appropriate science content will foster positive competence beliefs, as well as perceptions that science is interesting and worth pursuing. Mastery experiences contribute to self-efficacy (Bandura, 1997)—beliefs that are very similar to expectancy or competence beliefs (Eccles, Wigfield, & Schiefele, 1998). Accordingly, as a way of providing additional validity evidence for PISCES, we sought to investigate whether the measure would be sensitive to differences in children’s motivational beliefs as a function of length of participation in integrated science and literacy activities. We asked whether young children who participated in a longer sequence of integrated inquiry and literary science lessons (10 weeks) reported more positive beliefs than did the children who participated in a sequence of lessons for a shorter period (5 weeks). We reasoned that a 10-week sequence of conceptually coherent activities was closer to the goal of having science as an ongoing, meaningful, and salient part of the curriculum. Within this framework, we also explored possible differences between boys’ and girls’ beliefs. Our interest in investigating early gender differences stems from evidence that science is often viewed stereotypically as a domain that males prefer and are more competent at, compared to females (Andre et al., 1999). There is continued concern that women have diminished access to a range of interesting, important, and high-paying careers because they

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

381

do not choose the necessary science courses (Congressional Commission on the Advancement of Women and Minorities in Science, Engineering, and Technology Development, 2000; Eccles, 1994). Thus, central to achieving gender equity is that females perceive themselves to be as competent at science, and to enjoy science as much, as males do. Because there are gender differences in enjoyment, perceived competence, and selection of science classes at college and high school (e.g., American Association of University Women, 1999; Wigfield, Battle, Keller, & Eccles, 2002), researchers must consider students’ self-perceptions for science in earlier grades. Most recent research has found no gender differences in middle grade students’ liking or interest in science (Andre et al., 1999; Shepardson & Pizzini, 1994; Simpkins et al., 2006). However, recent studies have indicated that boys in the middle grades, on average, believe they are more competent or likely to be more successful at science than girls do (Jovanovic & King, 1998; Meece & Jones, 1996). This finding is not unequivocal: Andre and coworkers found a difference for physical science but not life science, and others have reported no gender differences for science (Britner & Pajares, 2006; Simpkins et al., 2006; Slate & Jones, 1998). There is virtually no research that has investigated gender differences about science motivation for younger students. There is some indication though, that differences in science competence beliefs may begin in the early elementary grades. Specifically, Andre et al. (1999) found that among younger students (in grades K-3) girls reported higher levels of competence in life science than in physical science. However, the data were based on single item scales and differences between kindergarteners and older students (e.g., 2nd–3rd graders) were not addressed. Gender differences are present at the beginning of school for beliefs across other academic competence domains such as reading, language, and math, as well as for nonacademic domains such as music, sports, and physical ability (Eccles et al., 1993; Wigfield et al., 1997). Early gender differences in children’s competence beliefs are commonly found along domains that reflect gender-role stereotypes (e.g., Eccles et al., 1993; Jacobs, Lanza, Osgood, Eccles, & Wigfield, 2002; Marsh, Craven, & Debus, 1991, 1998; Pallas, Entwisle, Alexander, & Weinstein, 1990; Wigfield et al., 1997). Specifically, boys tend to evaluate their math-skills and physical ability (e.g., being good at sports, running fast, being strong, playing ball) more favorably than girls do. Conversely, girls rate themselves higher on social competence and certain academic skills that include language arts (e.g., verbal/reading ability), being a good student, and learning things quickly. Whether differential beliefs about science competence and liking are present with boys and girls in kindergarten is a question that merits investigation. In the current study, we contribute to the knowledge base on this issue by exploring possible gender differences in kindergarten students’ beliefs of their competence in, liking, and ease of learning science. 4. Summary of research objectives We use data from a sample of public school kindergarten children to report on the development of PISCES and to describe their science-related motivational beliefs. We begin by documenting that, after participating in science literacy and inquiry activities, young children recognize science as an academic domain and relate it to their experiences. We then examine the dimensionality of PISCES through analysis of the measure’s factor structure, and provide evidence of scale reliability. Next, we include additional validity evidence through correlations between PISCES and external criteria of early academic achievement. These include children’s scores on measures of science achievement, problem solving, and passage comprehension—skills that we expect to be impacted positively by the integrated science inquiry and literacy activities. Finally, we use PISCES to investigate possible differential effects by gender and length of participation in inquiry science. We examine whether boys and girls who participated in a shorter set of integrated science inquiry and literacy activities held different beliefs about their science competence and liking from those of similar children who participated in such activities for a longer period of time. 5. Methods 5.1. Participants This study was conducted in a mid-western, suburban public school district. We collected data from 113 kindergarten children in two different schools who participated in science activities associated with the Scientific Literacy Project (Mantzicopoulos et al., 2005). In School 1, there were 82 children, in four kindergarten classrooms, who were enrolled at the beginning of the science unit; we obtained informed consent for 71 (86.6%) of those children. However, we collected PISCES data for 65 children, because six children moved from the school before the end of the unit, and could not be tested. In School 2, there were 52 children in two kindergarten classrooms, and we obtained informed consent for 49 (94.2%) of them. We collected data for 48 children because one child left the school before the end of the units. School-level data (i.e., school achievement on state mandated tests, race/ethnicity, and free-lunch information), available from the state’s Department of Education website, were examined. The schools were comparable across these characteristics. In addition, we conducted chi-square tests to examine the comparability of the children in the two schools on gender, ethnicity, and free or reduced-cost lunch status. There were no statistically significant differences on these variables. Ethnicity information was as follows: 64 children (56.6%) were Caucasian, 14 (12.4%) were African American, 26 (23%) were Hispanic, and 9 (8%) were classified as Other. There were 68 boys and 45 girls. Free-lunch information was available for 111 of the children, 79 (71.2%) of whom received free or reduced-cost lunch.

382

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

5.2. Context of science lessons: integrated inquiry and literacy activities 5.2.1. Overview of SLP goals and units The premise behind SLP is that early scientific literacy is facilitated in everyday interactive contexts that provide opportunities for cognitively guided learning and adult–child discourse involving concepts of science. Classroom activities are built around science topics (e.g., the living environment, the physical world) and skills (e.g., making and recording observations, matching evidence to predictions) linked to the state academic standards for kindergarten, and are mapped to Science, English/Language Arts, and Mathematics standards. They are also consistent with the National Research Council’s recommendations for science (2000, 2001, 2007) and with current guidelines for developmentally appropriate practice as it applies to science instruction for young children (Chaille & Britain, 2003; NAEYC, 2003; Worth & Grollman, 2003). These underscore the instructional importance of integrated inquiry and literacy activities to address scientifically rich and developmentally appropriate questions that relate to students’ interests and experiences. We focus on integrated instruction that acknowledges disciplinary integrity (Dickinson & Young, 1998; Huntley, 1998; Stoddart, Pinal, Latzke, & Cnaday, 2002) so that SLP literacy and inquiry activities provide a context for the two disciplines to interact and support each other, while each maintains its integrity. The SLP inquiry activities comprise a 3-stage cycle (pre-inquiry, inquiry, and post-inquiry) structured to provide students with opportunities to be active learners (Samarapungavan, Mantzicopoulos, & Patrick, in press). The goals of SLP inquiry units are to help students understand: (a) important science themes or ideas in developmentally appropriate ways and (b) the nature and processes of scientific inquiry. Inquiry topics are selected around key science themes (i.e., growth and development, biological adaptation, life cycles) and address meaningful phenomena for children who can use their knowledge and experiences to ask questions and make predictions about the natural world. They then try to answer those questions by conducting investigations where they observe, record, infer, draw conclusions, and communicate findings. Extension activities within each unit promote conceptual understanding and integrate science, language, as well as math learning. Children use science notebooks to draw pictures, write, and paste digital photos in, and to show later to family members. Along with the science inquiry activities, teachers engage children in interactive science book readings on themes related to the inquiry activities. The reading program is based on informational texts for children and emphasizes dialogic reading strategies (Whitehurst et al., 1999), including questioning strategies consistent with the K–W–L framework (What I know, What I want to learn, What I learned; Ogle, 1986) and with introducing new books to children (Clay, 1991). Through active participation in inquiry and exposure to meaningful content-based reading, children learn not only scientific concepts but also the functions and structure of language as they describe, explain, justify, and summarize. Competence in the use of these language functions is central to the development of scientific knowledge (Halliday, 2006; Norris & Phillips, 2003; Yore & Hand, 2003). 5.2.2. Science activities in the study schools All kindergarten teachers in the two schools volunteered to participate in the project and were enthusiastic throughout the activities. This was confirmed both in informal discussions with the teachers and in individual interviews conducted at the end of the units. During the interviews all teachers told us, that, prior to SLP, science was presented in occasional lessons about topics such as seasons, pumpkins at Halloween, or farm animals. This was because of the heavy focus on literacy. Videotaped data of lessons obtained at baseline, prior to the SLP activities, did not involve science and teachers confirmed that these were typical lessons. Prior to the implementation of activities in both schools, we conducted an after-school workshop with the teachers in each school. In both workshops, we covered the principles of SLP, and provided an overview of SLP activities, readings, and materials for the units. In addition, we discussed a range of instructional and management strategies for teachers, involving use of activity centers, reading non-fiction text and asking higher-order questions, incorporating unit activities within existing classroom routines (e.g., calendar time), eliciting students’ questions, general student-centered strategies, and adapting literacy activities (e.g., writing in notebooks) to individual students’ development. The teachers in both schools taught a series of science lessons associated with the following life science units: living things and life cycle of the butterfly in school 1, and living things followed by marine life in school 2. An SLP graduate student assisted the teachers in the implementation of the activities. All science lessons were videotaped and lasted approximately 60 min, twice a week (for a total of approximately 120 min per week). Key concepts across these life science units, documented in the video-recordings, involved differences between living and nonliving things, habitats and adaptation, animal structures and their function, and life cycles. Activities concurrently addressed concepts involving the nature of science (asking questions, making predictions, conducting observations, and using tools to observe and record findings). Book readings paralleled the themes of the inquiry activities. Children in school 1 spent 5 weeks in SLP pilot activities designed to explore the theme of growth and development through direct observations of the metamorphosis of the monarch butterfly from larva to adult. Readings covered the properties of living things, characteristics of insects, their body structures and adaptation mechanisms, as well as reproduction and their life cycle. Detailed information on these pilot activities and discourse in school 1 classrooms is provided in Samarapungavan et al. (in press). For school 2, we extended the activities into a separate 4-week unit on living things, followed by 6 weeks on the marinelife unit. In the revised living things unit, inquiry activities were based on observations of animals and plants in the children’s

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

383

Table 1 Outline of concepts and activities covered in the living things lessons across the two schools Concept

Inquiry activities and readings

Description

School 1

School 2

The nature of science

Activities

Predictions, observations, recording, using tools (science notebook, ruler, magnifying glass), measurement Tools Scientists Use (Russell, 2003)

X

X

Properties of living things

Activities

Discussion (predictions, observations about living things) Nature walk (observe, identify living things in their natural habitat) Draw a living thing Plants as living things—experiment on plants and discussion on movement Habitats for living things How living things breathe How living things respond to their environment Living Things (Trussell-Cullen, 2001a) Animal, Vegetable, or Mineral? (Trussell-Cullen, 2001b) Living Things Need Food (Pigdon, 2003) Whose Eye Is It? (The Scientific Literacy Project, 2006)

X

Readings

Readings

X X X X X X X X

X X X X X X X

environment. In the marine-life unit, inquiry activities centered on observations of organisms in a saltwater aquarium placed in each classroom for the duration of the unit. Life cycles and reproduction were also addressed through both classroom activities and readings. Although detailed information about the SLP intervention is beyond the scope of this paper, we outline the inquiry themes, readings, and activities in Table 1 for the living things unit to demonstrate both elements common to the two schools and extensions implemented with children in school 2. We show that, despite the overlap between the concepts covered in the activities and readings between the two groups, there were significantly more opportunities for children in school 2 to interact with the content across different contexts, readings, and inquiry activities. 5.3. PISCES 5.3.1. Scale development PISCES is intended for young, pre-literate children who may not possess the linguistic or information processing skills to articulate differentiated self-beliefs within a particular domain such as a science. We thus opted not to rely on open-ended questions (i.e., how good are you in science?) or graded response choices with more than two options (e.g., Likert scale items asking children to choose among several response options). First, open-ended formats depend on the respondent’s verbal expression skills and evidence suggests that young children’s language production skills are less well developed than their receptive language skills (Feagans & Farran, 1993, 1994; Foster, 1990; Kuczaj & Maratsos, 1975). Therefore, young children may fail to respond to open-ended questions about themselves, not because they do not know or comprehend the information, but because they do not yet possess the expressive skills needed to provide self-descriptions (Eder, 1990). Also, graded response formats may tax the cognitive processing abilities of young children, who tend to respond at the extreme points of rating scales, particularly with items referring to social situations and psychological states (Chambers & Johnston, 2002). To work within children’s developmental capabilities, we employed a dichotomous response format that has been shown to be appropriate for assessing young children’s psychological knowledge (e.g., Marsh et al., 2002). To ensure that children understood the options at both end of the continuum, we used bipolar statements (e.g., this child likes reading science books vs. this child does not like to read science books) rather than relying on a “yes/no” response format to questions or statements. A score of 1 was given when children indicated agreement with positive statements (e.g., “I know how to do science”) and a score of 0 was given for agreement with negative statements (e.g., “I don’t know how to do science”). We developed items that comprised descriptive statements referring to children’s typical and familiar experiences during the SLP science activities. This was based on evidence that, when probed specifically about typical and familiar experiences, children can provide a great deal of psychological information about themselves and others (Eder, 1989; Mantzicopoulos & Neuharth-Pritchett, 2003; Measelle et al., 1998). For example, during the SLP cycle of activities, children learned that scientists ask questions and make predictions. In the pre-inquiry stage, they had opportunities to practice making and writing their predictions in their science notebooks. During inquiry, they interacted with the science content (e.g., learning about tools, the characteristics of living things), and recorded their findings. In addition, throughout the intervention, children read science books and participated in discussions about the books. Items developed to assess children’s competence beliefs across these experiences included “I am good at making predictions,” “I know how to use different science tools,” “I know why living things camouflage,” and “I can remember new science words.” Finally, on the basis of evidence that children’s comprehension,

384

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

interest, and engagement are enhanced when descriptive statements are accompanied by concrete materials (Eder, 1990; Miller, 1985; Mize & Ladd, 1988), we developed puppet figures that were used to deliver the bipolar statements. A set of 30 items was administered to children in both schools. The pool of items was derived after: (a) a review of items in self-concept scales for young children (e.g., Chapman & Tunmer, 1995; Harter & Pike, 1984; Marsh et al., 1998, 2002) and (b) classroom observations of the children as they were engaged in science inquiry and reading activities. As noted earlier, items were grouped into the following areas: (a) General Science Competence; (b) Specific Science Knowledge and Skills; (c) Science Liking; and (d) Ease of Science Learning. 5.3.2. Administration format The administration procedures were adapted from work on children’s self-cognitions outlined earlier in this section (i.e., Eder, 1990; Measelle et al., 1998). Specifically, the child was shown a set of five ethnically diverse puppets that matched his/her sex. The examiner explained that the puppets would talk about different things that happen in school and asked the child to choose a puppet (Puppet 1) that was most like him/her. The child named the puppet and the examiner helped him/her write the puppet’s name on a tag that was then attached to the puppet. Then the examiner chose an identical puppet (Puppet 2) from a second set of puppets (out of the child’s view) and said:

The children were given two practice items (Puppet 1: “I like pizza”; Puppet 2: “I don’t like pizza”; Puppet 2: “I like recess in school”; Puppet 1: “I don’t like recess in school”) and asked, after each, “Which puppet thinks the same as you?” Thus, we ensured that children understood the response format before beginning with the PISCES items; additional practice items were given if necessary. Considering that the term “science” may be too abstract for young children, it was important to document that in responding to PISCES children drew on event knowledge grounded in their science-related experiences. Thus, following the presentation of the PISCES practice items we prompted the children to talk about science as follows:

After the children had responded, follow-up prompts were: “Anything else?” or “Is there anything else that you did in science?” No other prompts were used in order to keep the administration time short and avoid taxing children’s attention span. With children in school 1, the examiners made notes of children’s responses but not all responses were recorded verbatim. Our initial plan was to use these questions as prompts for children’s event memories about science during the administration, and we had not considered conducting a narrative analysis of the data. We modified this procedure for children in school 2 so that all examiners recorded children’s responses verbatim. Before presentation of the PISCES items, children were given the following scenario:

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

385

The examiner then used the two puppets throughout the administration of the scale to facilitate responses to the bipolar items. The procedure involved one puppet making a statement representing the positive end of the continuum for an item (e.g., “Science is easy for me”) followed by a statement from the other puppet representing the negative end of the continuum for the same item (“Science is hard for me”). To control for order effects, the positive statements made by each puppet were counterbalanced so that each puppet made both positive and negative statements. In addition, the order of presentation varied so that each new item was not always presented first by the same puppet. During the administration, the examiner recorded the child’s responses on an answer sheet as the child indicated his/her agreement with one of the puppets. Children’s spontaneous statements during the scale administration were also recorded by the examiner. The total administration time for this scale was approximately 15 min. 5.4. Procedure In the first 2 weeks of school, teachers tested children with two subtests from the Dynamic Indicators of Basic Early Literacy Skills (DIBELS; Good & Kaminski, 2002) assessment. We used these data, in addition to the demographic information, to examine the comparability of the children in the two schools on pre-academic skills before they began the science units. At the conclusion of the SLP unit(s), children in both schools were tested with the PISCES subtests and were asked the two open-ended questions about science. At the same time, children in school 1 were also tested with three subtests from the Woodcock-Johnson III (WJ-III; Woodcock, McGrew, & Mather, 2001) battery. These data provided additional validity information through correlations between scores on the PISCES scales and scores on measures of achievement. Testing took place in two sessions to keep the administration time short and maintain children’s interest and engagement with the tasks. In session 1, we administered the WJ-III Passage Comprehension and Applied Problems subtests, whereas in session 2 we asked the two open-ended questions and administered the PISCES and the WJ-III general science knowledge subtest. The examiners were the first and second author and two graduate students. 5.5. Measures 5.5.1. Dynamic Indicators of Basic Early Literacy Skills (DIBELS; Good & Kaminski, 2002) At the beginning of the school year, school personnel assessed children’s early literacy skills with the two standardized, individually administered subtests of pre-reading and early reading skills. The Initial Sound Fluency (ISF) subtest assesses phonological awareness by asking children to recognize and produce the first sound of words presented in pictorial format and named orally by the examiner. The Letter-Naming Fluency (LNF) subtest assesses children’s knowledge of the names of upper- and lower-case letters as they are presented randomly. Both tests have good reliability; test–retest and alternate form reliabilities ranged from .88 to .91. Predictive validity estimates computed between DIBELS subtests and established measures of academic achievement, such as the Woodcock-Johnson Psychoeducational Battery, are reported to range from .45 to .65 (Good & Kaminski, 2002). 5.5.2. Woodcock–Johnson III Tests of Achievement (WJ-III; Woodcock et al., 2001) Children were tested individually with the Passage Comprehension, Applied Problems, and Science Knowledge subtests of the WJ-III. The Passage Comprehension subtest provides information on the child’s vocabulary and comprehension skills and ability to understand language when it is being read. This subtest requires use of semantic and syntax cues as the child identifies missing information in each question. The Applied Problems subtest assesses children’s understanding of number, mathematical reasoning, as well as the ability to solve quantitative problems. The Science Knowledge subtest assesses general biological and physical science knowledge. These subtests have excellent 1-year retest reliabilities ranging from .84 to .92 for children in the 4- to 7-year-old age range. Correlations of the WJ-III with commonly used achievement measures, reported in the test’s technical manual (McGrew & Woodcock, 2001), support the validity of the test’s subscales. 6. Results 6.1. Children’s narratives about science learning 6.1.1. Coding scheme To establish that children recognized science as an academic subject, we considered the types of children’s responses to the two questions about learning science in school (i.e., “What do you learn in science?” and “What is science?”). The second question was not intended as a prompt for young children’s epistemological beliefs about science, but rather as an additional probe that would provide access to their experiences and event knowledge. Although examiners took detailed notes, we did not implement the verbatim documentation of responses with all children in school 1. Thus, with some responses we did not document whether a list-like record was the child’s exact narrative response to the question or simply brief examiner notes based on that narrative. Nevertheless, 42 narratives from school 1 provided us with sufficient information (including verbatim-noted statements) to develop a coding scheme that we then applied to the verbatim-recorded responses of children in school 2.

386

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

Table 2 Frequency and examples of students’ responses about science by category Category and examples

Number

%

Don’t Know, No Response, or Irrelevant “I don’t know.” or “Can’t remember.”

8

17

School Activities or Events Not Related to Science “I am doing some easy stuff. . .learning money and minus and plus.”

1

2

Science Content not Included in SLP “Seeds!” or “Dinosaurs!” or “The middle of the Earth is called the same as the middle of the egg.”

3

6

31

65

5

10

Science Content Included in SLP “Living things—polar bears, cattails are living. Cars are not living.” “You took pictures of those animals and wrote in journals and did centers. . .you make some experiments.” “Fish excrete and they can use their environment.” “Go on a nature walk.” “Science is when you investigate and learn about stuff.” “Fish, anemone. . .like words that you put on the wall or on paper.” “Fish! They breathe with their gills and anemones eat fish!” “Read science books.” “Color pictures in science book and write. . .the fish tank, fish, anemone.” “Fish, living things, dog - because they breathe. . .excrete, grow, have puppies, feed. . . Learn about nonliving and living things.” Science Content and Affect “Animals, starfish, fish, read books. . .having fun.” “How to make different-colored science so you use red and blue to make a purple color. Science is really fun.”

In the process of developing the coding scheme, and following a review of the responses of children in school 1 to both questions, we found that answers were not independent; children often continued with their comments in response to the second question, or expressed that their first answer addressed the second question also (e.g., “. . .and that’s all;” or “. . .that’s all I know.”). Additionally, in several cases, children’s answer to the same question concurrently referenced interrelated components including SLP content, enjoyment of science, and processes. For example, the answer “We do water and sugar experiments. The water eats the sugar” involves process and content, and “[science] is really fun. It’s hard to do . . . to put warm water and to make science,” addresses enjoyment, ease of learning science, and process. Therefore, we based our coding scheme on the children’s responses to both questions, and coded them across five categories. The coding categories are shown below, along with examples from school 1 children. 1. No response, or “I don’t know,” or “can’t remember.” 2. Descriptions of other school events or activities not related to science: e.g., “[in science we] learn how to sing ABCs” or “School, toys, cars,” or “I just do my homework. . .and go home and do it.” 3. Descriptions of science vocabulary, content, activities, or processes not covered in the SLP curriculum: e.g., “Rain, sun, and clouds,” or “about snacks that are good or bad”, or “being healthy.” 4. Descriptions of vocabulary, content, activities, or processes covered in SLP: e.g., “I learned about butterflies. Instead of chrysalis, people sometimes call it a cocoon,” or “I learned about the magnifying glass. . .when you put it real close you see it big, or “Living things, caterpillar[s]. They get into an egg—a little toy egg [and] when it cracks open it gets into a butterfly,” or “Science is when you investigate.” 5. Affect and value references to science: e.g. “[science] is fun,” or “It’s about something that you like and that you are interested in.” When individual children’s responses addressed several of these components, they were simultaneously coded to reflect this; thus, the coding categories were not mutually exclusive. As we noted, this coding scheme (and the associated school 1 exemplars for each category) was used to code the responses of children in school 2. To ensure that these initial codes accurately captured the content of children’s narratives in the second school, we concurrently searched for discrepant information. The coding for children in school 2 was completed independently by the first and second author on all cases. Inter-rater agreement was 95%. Disagreements were resolved by discussion and consensus. 6.1.2. Results The frequency and percentages of children in school 2 whose comments involved each of the categories, along with examples of their coded narratives, are shown in Table 2. The distribution of answer types was as follows: 9 children either did not respond or did not provide a relevant reference to science. The remaining 39 (81%) children’s narratives referenced science content and activities either from the SLP curriculum (i.e., marine life or living things) or from other sources either in or outside of the classroom (e.g., learning about being healthy, farm animals, the solar system). It is noteworthy that, of the 39 children, only 3 referenced content not covered in SLP. Of the 36 SLP narratives, 9 also included non-SLP information

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

387

Table 3 Pattern matrix for PISCES items

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Items

Science Competence

Science Liking

I know how to do science I know why living things camouflage I can do science I know how to use different science tools I know a lot about different kinds of living things I know a lot about science I can remember new science words I like science I want to know more about science I feel happy when I am learning science I have fun learning science. I like to write in my science notebook I like using different science tools I don’t need help with science Science is easy for me I learn things quickly when we do science I can figure things out in science

.78 .65 .64 .62 .52 .45 .44 −.05 −.10 .07 −.07 .20 .30 −.04 .11 .09 .23

−.02 −.07 −.02 .06 −.05 .07 .06 .82 .70 .68 .49 .48 .48 −.03 .26 −.16 .15

Ease of Science Learning .00 −.04 .01 −.04 .16 .08 .01 −.08 −.01 .05 .14 .08 −.28 .75 .55 .47 .35

Note. Items involved opposing positive and negative statements, however only the positive wording is shown here. The italicized values show the coefficients for items loading on each of the three factors.

(e.g., “Living things, fish, and now farms” [activities about farm animals were not part of SLP]). Although children were not prompted for their enjoyment or liking of science, the science narratives of five children concurrently included statements that science is interesting, valuable or enjoyable. Children’s narratives contained lists of things from content covered in the living things and marine-life units. These lists included content-related vocabulary (e.g., starfish, shells, polar bears, anemone, clownfish, damsel, breathe, excrete, eat, interact, develop, camouflage), factual information (e.g., “fish breathe,” “fish . . . they have bones in them,” or “fish, they live under water”), as well as routine activities that the children engaged in during science (e.g., conducting experiments, recording observations in the science notebook, reading science books). Additional examples are reported in Table 2. 6.2. Structure of children’s motivational beliefs about learning science To explore the dimensionality of the PISCES we used data from the 113 children in both schools who were tested with the measure, and conducted a series of common factor analyses with squared multiple correlations as the communality estimates. We employed oblique (promax) rotations (with principal axis factoring to extract the factors) because we expected the subscales to be intercorrelated. In addition, we compared the oblique solution against an orthogonal (varimax-rotated) solution. To make decisions about the number of factors to retain, we were guided by the literature suggesting the use of several independent criteria, none of which, when used as a single criterion, has been shown to produce satisfactory results (Floyd & Widaman, 1995; Reise, Waller, & Comrey, 2000). We employed the following rules: (a) eigen values of the unrotated factors > 1, (b) Cattell’s scree test, (c) variance accounted by unrotated factors > 5%, (d) factor loadings ≥ .35, (e) internally reliable factors, and (f) factors that yield meaningful psychological constructs. After we identified the factor structure of children’s science-related motivational beliefs, we created scale scores by averaging scores on items with substantial loadings (> or =.35) on each factor. Items with minor factor loadings (<.35) were not considered. We opted to use this method for two reasons: first, factor scores based on all factor loadings of a scale are not easy to replicate across different studies (Hair, Black, Bain, Anderson, & Tatham, 2006). Second, there are virtually no differences between this method and other factor score methods that use factor loadings as weights in the estimation of factor scores (Fava & Velicer, 1992). This was borne out by our data as well. Correlations between the set of averaged scale scores and the sets of factor scores computed using the SPSS version 15 factor-score computation options (e.g., Regression method, Bartlett, Anderson-Rubin) were greater than .95. A three-factor structure met the criteria for an adequate factor analytic solution (eigen values were 5.12, 2.14, and 1.34). The promax rotation of the factors produced a nearly identical solution to that of the varimax rotation. Following these initial procedures, we retained 17 items with factor loadings ≥ .35. This decision was based on the rationale that factor loadings of .35 or greater are acceptable in exploratory factor analysis after factors have been rotated (Nunnally, 1978). We then recomputed the factor analyses on the 17 items. Both varimax and promax rotations produced the same solution that represented a three-factor structure. The factor loadings, after promax rotation, are shown in Table 3. Seven items with factor loadings ≥ .44 loaded on Factor I. Three of these items (“I know a lot about science”, “I know how to do science”, and “I can do science”) were originally grouped under General Science Competence, whereas four items (“I know how to use different science tools”, “I know why living things camouflage”, “I know a lot about different kinds of living

388

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

Table 4 Correlations between PISCES subscales and achievement subtests PISCES subscale

Academic achievement Science Applied Problems Passage Comprehension

Science Competence

Science Liking

Ease of Science Learning

.34** .41** .27*

.34** .43** .21

.04 .00 −.09

*p < .05; **p < .01.

things”, and “I can remember new science words”) were originally grouped under the Specific Science Knowledge and Skills domain. This factor was labeled Science Competence and accounted for 27% of the variance. Six items with factor loadings ≥ .48, originally thought to reflect children’s liking and enjoyment of science, loaded on Factor II and accounted for an additional 9% of the variance. We labeled this factor Science Liking. Factor III comprised four items with loadings ranging from .35 to .75. Three items, hypothesized to represent the Ease of Learning Science dimension (“I need help with science”, “science is easy for me”, “I learn things quickly when we do science”), loaded on this factor. Additionally, one item (“I can figure things out in science”), originally grouped under General Science Competence, loaded on Factor III. This factor was labeled Ease of Science Learning and accounted for 5% of the variance. 6.3. Reliability of PISCES and descriptive statistics We computed internal consistency reliability coefficients (Cronbach’s alphas) for the three subscale scores, and the full scale. The alpha coefficient for the full scale (17 items) was .84. Alpha coefficients for the three subscales were: .79 (Science Competence), .79 (Science Liking), and .64 (Ease of Science Learning). We computed scale scores by averaging scores on items making up each scale. Mean scores were .78 (Mdn = .86; S.D. = .27), .84 (Mdn = 1.00; S.D. = .26), and .71 (Mdn = .75; S.D. = .31) for Science Competence, Science Liking, and Ease of Science Learning, respectively. The distribution of mean scores on the three subscales was somewhat negatively skewed (skCompetence = −88; skLiking = −1.85; skEase = −39), however these were not outside univariate skewness guidelines for indicating normality (Curran, West, & Finch, 1996). Bivariate correlations indicated positive correlations among the three subscales: Science Competence was correlated with Science Liking (r = .47, p < .001) and Ease of Science Learning (r = .45, p < .001), and there was a trend for Science Liking to be correlated with Ease of Science Learning (r = .18, p = .06). 6.4. Validity evidence We considered two aspects of validity. The first examined the resulting zero-order correlation coefficients between the PISCES subscales with achievement measures collected with 65 children in school 1. The second examined whether children’s responses on the PISCES subscales differed by the extent of their experience with inquiry and literacy activities in the classroom and by gender. 6.4.1. Relationships between children’s responses on the PISCES and achievement This analysis was based on data from children in school 1. The resulting correlations are presented in Table 4. Scores on the Science Competence subscale were associated significantly with all three areas of achievement: Science Knowledge (r = .34, p < .01), Applied Problems (r = .41, p < .01), and Passage Comprehension (r = .27, p < .05). Scores on the Science Liking subscale were associated significantly with performance on the Science Knowledge (r = .34, p < .01) and Applied Problems (r = .43, p < .01), but not Passage Comprehension (r = .21, n.s.), subtests. Scores on the Ease of Science Learning subscale did not correlate significantly with any of the WJ-III subtests. 6.4.2. Gender and length-of-participation differences in children’s science beliefs This analysis involved the examination of differences between children in two schools and therefore it was important to document the groups’ comparability. As noted in the Participants section earlier in the paper, children in the two schools were comparable across several school-level data that included academic achievement and sociodemographic characteristics. In addition, we examined the comparability of early literacy skills across the two groups of children prior to their participation in either the 5-week (Group 1) or the 10-week (Group 2) activities. We used a 2 (Group) × 2 (Gender) MANOVA with the DIBELS scores as outcomes. Data on the DIBELS were available for 104 children. This group was not significantly different from the full group of 113 children on whom data were collected for this study. Both group [F(2, 99) = 3.93, p = .01] and gender [F(2, 99) = 4.83, p = .02] effects were significant but their interaction was not. Examination of the univariate tests for each DIBELS subtest supported that group differences were pronounced in ISF, F(1, 100) = 6.02, p = .02. Children in Group 2 (MISF = 12.85, S.D.ISF = 9.19) had a significantly higher mean for ISF than children in Group 1 (MISF = 9.03, S.D.ISF = 7.24). The univariate effect for Letter-Naming Fluency was not significant. Also, regardless of

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

389

Table 5 Descriptive statistics of PISCES Subscales by length of participation in the science program Group 1

PISCES subscale Science Liking Science Competence Ease of Science Learning

Group 2

M

Madj

S.D.

M

Madj

S.D.

.81 .72 .65

.80 .71 .65

.27 .30 .33

.91 .90 .77

.92 .91 .78

.21 .12 .27

F

p

4.88 14.67 3.67

.03 .00 .06

Note. Group 1 = 5 weeks, Group 2 = 10 weeks.

group, girls outperformed boys on the DIBELS subtests; this difference was primarily attributed to LNF. Girls (MLNF = 14.21, S.D.LNF = 14.70) scored higher than boys (MLNF = 7.31, S.D.LNF = 10.97) on LNF, F(1, 100) = 9.62, p = .002. To control for the difference in early literacy scores, we proceeded with multivariate analysis of covariance (MANCOVA) using the DIBELS subscales as covariates and the three PISCES subscales as the dependent variables. We also examined the correlation between the DIBELS scores and the PISCES subscales and found one small (r = .21, p < .05), yet significant correlation between the DIBELS Letter-Naming Fluency and the PISCES Science Competence subscale. The remaining coefficients were small (rs < .14) and were not statistically significant. Although we did not have a specific hypothesis about classroom differences on the PISCES, we included a nested effect in the model and examined classrooms nested within schools. Thus, the full MANCOVA model controlled for school differences on the DIBELS and examined: (a) the main effects of Group (5 vs. 10 weeks of science) and Gender; (b) the interaction of Gender × Group; and (c) the effects of classrooms nested within each school. Even though the PISCES was administered to 113 children, this analysis was based on 102 children for whom both DIBELS and PISCES scores were available. Again this group of children was not significantly different from the 113 children on any of the characteristics examined in this study. The main effect for gender and the gender by group interaction were not significant. In addition, there were no differences between classrooms in each school. However, a significant multivariate main effect for group was identified in this analysis, F(3,90) = 5.03, p = .003. Results from the follow-up univariate analysis for this effect are presented in Table 5. On average, children in Group 2 had significantly higher perceptions of science competence (Madj = .91) and liking of science (Madj = .92) than children in Group 1 (Madj = .71 and .80 for science competence and liking, respectively). Also, there was a nearly significant trend (p = .058), suggesting that children in Group 2 tended to perceive science as easier than did children in Group 1. 7. Discussion Results from this study provide a number of important findings. First, we addressed a crucial need for research on science learning by showing that PISCES elicits reliable and meaningful information about kindergarteners’ motivational beliefs regarding science. We also extended the research about the specificity of self-related beliefs by identifying that, within the domain of science, the dimensionality of young children’s beliefs is similar to that found for other academic domains. Further, the results showed that children who engaged in integrated science inquiry and literacy activities for a longer time reported higher overall motivational beliefs for science than those who experienced the activities for a shorter time. We found no evidence of gender differences in kindergarteners’ beliefs about learning science. 7.1. Content and dimensionality of young children’s beliefs about learning science Recent evidence confirms that at the beginning of kindergarten few children have knowledge of general or specific events and activities that pertain to science (Mantzicopoulos et al., 2007). Considered in this context, the analysis of narratives supports the notion that, after participation in SLP, children recognized science as an academic domain comprising different but interrelated content and activities. It is noteworthy that, despite not being prompted for their liking of science, a few children spontaneously shared that science is interesting and enjoyable. Although the development of children’s event memories about learning science in kindergarten was not an objective of this study, we ascertained that even with minimal prompting, children recalled different aspects of what their science lessons involved. Children’s reports contained lists of science vocabulary and activities, consistent with research on the development of kindergarten children’s scripts about school (Fivush, 1984; Reifel, 1988; Wiltz & Klein, 2001). This supported the validity of asking children to respond to items about motivational beliefs associated with their science experiences. The factor analytic portion of the study indicated that the a priori specified dimensions—Science Competence, Science Liking, and Ease of Science Learning, were reproduced with our sample. These three factors are consistent with prior empirical evidence about children’s self-concepts in academic domains other than science and with the theoretical frameworks within which our items were developed (e.g., Chapman & Tunmer, 1995; Eccles et al., 1993). Items descriptive of both general and specific beliefs about science competence loaded on the same factor, indicating that children’s specific science-related knowledge and skills (e.g., “I know why living things camouflage”, “I am good at making predictions”) were coordinated with beliefs about their general science competence (e.g., “I am good at learning

390

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

science”). These empirical results probably reflect the fact that, for at least most of the kindergarten students in this study, learning specific science concepts and skills targeted in the SLP curriculum constitutes their first introduction to science as an academic domain. Longitudinal research is needed to explore the developmental trajectories that children’s motivational beliefs about science take over time. For example, some researchers have proposed a developmental trajectory in which children’s self-beliefs become hierarchically organized, with sub-sets of beliefs about specific skills nested within beliefs about a general domain (Marsh & Hattie, 1996). Whether this structure also applies to children’s science-related beliefs is an open question, particularly in light of Hattie’s (1992) proposition that the structure and organization of self-beliefs may or may not assume a hierarchical structure for different groups. In the early years, cognitive-developmental considerations would account for limited construct differentiation in children’s motivational beliefs (e.g., Harter, 1998). However, it is also critical to consider the role of context because self-concept development is influenced, at least in part, by children’s experiences in their social environments, including school (Wigfield et al., 1997). Research is needed to examine the extent to which early and consistent participation in science activities facilitates the cognitive differentiation of children’s science competence beliefs into specific sub-domains that may or may not become hierarchically integrated over time. The three PISCES dimensions were related to each other in theoretically meaningful ways. The positive but small-tomoderate-sized correlations of beliefs about the ease of science with both liking of, and competence in, science was similar to those found by Chapman and Tunmer (1995). Thus, young children’s appraisals of their ability or liking of science were not tied closely to how easy science seems, as it is with older children. This is consistent with considerable developmental research showing that young children tend to expect they will improve and be competent and that they can learn difficult tasks with perseverance and effort (Nicholls, 1978, 1979). Science competence beliefs were related positively to liking science; the moderate correlation fell midway between those reported for kindergarten children by Chapman and Tunmer (1995) and by Wigfield et al. (1997). Children responded quite positively on the PISCES items, reporting, on average, that they were good at learning science, that they liked it, and that it was fairly easy. These positive beliefs are typical for students this age, who tend to respond with overly optimistic judgments of their competence (Harter & Pike, 1984; Marsh et al., 2002; Nicholls, 1978, 1979; Parsons & Ruble, 1977). Cognitive-developmental skills as well as early socialization practices have been posited as explanations of this trend (Harter, 1986, 1998). Specifically, changes that include the development of information processing skills, language, as well as memory and perspective-taking abilities, gradually promote greater accuracy in how children evaluate their competence across different areas. In addition, the overwhelmingly positive feedback that preschool children receive for their efforts becomes more specific to children’s individual accomplishments over the elementary school years. Moreover, normative evaluation becomes more salient in the classroom and influences children’s interpretations of their competence across a variety of situations (Stipek & Mac Iver, 1989). Additional psychometric evidence for the adequacy of PISCES is gleaned from the reliability analysis. The internal consistency reliability coefficient for the full 17-item scale was strong (˛ = .84). Reliabilities for the science competence and science liking subscales were very good (˛ = .79) although lower than the reliability for the total scale. This is not unexpected, considering that each subscale consists of fewer items than the total scale. The decision to retain them as distinct measures of beliefs about science competence and liking is supported by a number of reasons including the strength of the reliability coefficient for each subscale, the factor analytic results, and our theoretical framework. Even though the reliability of the Ease of Learning Science subscale was lower than desired, it was consistent with our theoretical model. Therefore, we elected to retain it and investigate its correlations with objective measures. We note that the reliabilities for all three scales compare favorably to others’ results using measures of competence and attitudes for other subjects (reading or literacy, mathematics, music, sports), and for school in general, with students in kindergarten or first grade (Eccles et al., 1993; Harter & Pike, 1984; Valeski & Stipek, 2001).

7.2. Associations between children’s beliefs about learning science and academic achievement Children’s reports on two of the three PISCES subscales (science competence and liking) were associated in meaningful ways with scores on the WJ-III academic achievement subscales. Specifically, scores on science knowledge and applied mathematical problems skills were associated significantly with children’s reports of liking science and believing they are competent at it. Passage comprehension was also related to beliefs of science competence, but the correlation was smaller than for science or math skills. These significant correlations were moderate in size, but noteworthy, considering both the children’s optimistic scores on the PISCES and the broad scope of the WJ-III subtests. These estimates are conservative however, because domain-specific beliefs tend to be stronger predictors of content-specific measures of achievement than more general achievement measures (Schunk, 1990). The early science beliefs-competence relationship would therefore be stronger if early science achievement measures were available. Thus far, because of the lack of content-specific science measures, published early science intervention efforts (e.g., Head Start on Science and Communication Program or HSSC; Klein, Hammrich, Bloom, & Ragins, 2000; the ScienceStart! Program, French, 2004, and Preschool Pathways to Science or PrePS© ; Gelman & Brenneman, 2004) have either not reported efficacy data or have used broad measures of achievement to document outcomes. Specific measures of early science knowledge, competencies, and skills, with well established psychometric properties are critically needed to confirm this with young children, and efforts are currently under way to develop such measures (e.g., Clark-Chiarelli, Gopen, & Challufour, 2007; Samarapungavan et al., in press).

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

391

In contrast to science competence and liking, scores on perceived ease of learning science were not correlated with the achievement measures. This is not consistent with Chapman and Tunmer (1995) who found that early perceptions of reading difficulty had small yet significant correlations with objective measures of reading performance whereas perceptions of reading competence did not. The reverse pattern was found in the present investigation and it’s not clear whether this is due to differences in the item content and/or the content domain (i.e., reading vs. math). With respect to item content, perceptions of reading difficulty (Chapman & Tunmer, 1995) were represented by negatively worded items specific to difficulty in reading (e.g., reading to the whole class, figuring out hard words in a story). The PISCES ease-of science learning items were bipolar and referred to both ease and difficulty in “science,” but not to specific science activities (e.g., asking questions, making observations, using the science notebook). Therefore, additional items that make reference to the difficulty of the latter skills and activities will help clarify whether the early assessment of perceptions of difficulty provides meaningful information about young children’s science-related beliefs. It may also be that the evolution of difficulty perceptions varies by content domain. For example, perceptions of difficulty in reading may develop early, as a result of educational policies and practices that place undue emphasis on the acquisition of reading competencies. Such practices include the salience of normative evaluation (e.g., ongoing DIBELS testing) and draw attention to difficulties encountered by children in the classroom as they are learning to read. This was not the case with the SLP activities (even though the curriculum included reading and writing activities). The differential emphasis afforded to reading and science in the early grades poses important questions for future research about the effects of the instructional context on the co-evolution of content-specific competence and difficulty perceptions.

7.3. Children’s science-related beliefs and experiences with science activities The focus of the present study was on the development of a new measure appropriate for assessing young children’s motivational beliefs about science. However, the opportunity to provide evidence on the extent to which the measure is sensitive to instruction yielded interesting findings that have implications for early science learning. The results of the present study indicate that, when given the opportunity to engage in integrated science inquiry and literacy activities at school, young children do enjoy science, and in general feel competent in learning about it. Of particular importance, those children who engaged in more inquiry and literacy-based science expressed, on average, greater competence and enjoyment of science than those who had less science. This link between the length of time children were involved in science activities and their competency beliefs are particularly promising, and support recommendations from scientists and science educators (e.g., National Research Council, 2000, 2001). Science instruction in the early school years should be an ongoing, salient, systematic and meaningful part of the curriculum if children are to develop, not only the requisite skills and knowledge for careers that involve science and technology, but the interest and feelings of competence that are necessary to sustain continued engagement and achievement, particularly beyond high school. Nevertheless, it is also possible that the findings may reflect differences in children’s interest in the topics covered in the two schools. Even though there was overlap in the science concepts emphasized in the SLP activities across the two schools, the differences in some of the topics covered (e.g., life cycle of the butterfly vs. marine life) may have contributed to the differences in children’s reports on the PISCES. This issue warrants investigation in future research to identify whether some topics are intrinsically more interesting to children than others. Although the results support PISCES as a promising assessment of children’s motivation for science, we note two potential limitations of the study. First, the examiners were not blind to the conditions in the two schools. However, systematic examiner bias was controlled through careful training and by the nature of the PISCES item format that limits subjective examiner judgment. Second, even though the schools were demographically comparable, and we controlled for the effects of early literacy differences on PISCES, other non-measured differences between the groups might have influenced the findings. Thus, it is important to assess the properties of PISCES with additional samples. The inclusion of a comparison group of children who participated only in the regular kindergarten program, without the additional SLP activities, would help document the associations between differential science experiences and children’s PISCES scores.

7.4. Gender and motivational beliefs about science Our findings also provide new and valuable information about the differences in boys’ and girls’ motivational beliefs about science. Despite documented gender differences in competence beliefs by early adolescence (e.g., Jovanovic & King, 1998; Meece & Jones, 1996), there were no gender differences in our kindergarten sample; boys and girls reported feeling equally positive about science and their competence for it. However, all science units involved topics within life science. Given the suggestions that gender differences are greater for physical science (Andre et al., 1999) and that science is a field with diverse disciplinary content, it would be important to continue to explore the origins of gender differences across additional science domains.

392

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

7.5. Implications for future research The finding that young children express greater competence when they are involved in learning science through an ongoing program of integrated inquiry and literacy is of considerable importance. It directly addresses the argument that science must be taught early if children are to develop feelings of competence and enjoyment of science. These beliefs are important precursors of individuals’ continued science learning through high school and beyond, and selection of sciencerelated careers—goals that are valued but not reached by enough people. Our results, showing that the PISCES is a reliable and valid instrument for measuring young children’s beliefs about learning science, will enable additional important issues to be investigated. These include examining differences between science and other academic subjects. Although adolescents tend to view science as more difficult and less interesting than language arts or mathematics (Andre et al., 1999), it is important to know whether experiences with learning science in the early school years alleviate these differences, both in the early grades and much beyond. In summary, having appropriate measures with which to examine motivational beliefs associated with young children’s science learning is a significant first step in fulfilling the challenge of both understanding children’s development of subjectspecific self-related beliefs, and unpacking the ways in which early belief systems contribute to science learning, engagement, and participation in science and technology-related careers. Acknowledgements This research was supported by a grant (#R305K050038) from the U.S. Department of Education, Institute of Education Sciences to the Authors. The opinions expressed are those of the authors and do not represent views of the U.S. Department of Education. Appreciation is expressed to Lisa Duffin, Traci Hemmer, Karleah Harris, Kiana Johnson, Anna Strati, and Sybil Durand for their help in the data collection and preparation of materials for this study. We also greatly appreciate the involvement of the teachers and children in this study. References American Association of University Women. (1999). Gender gaps: Where schools still fail our children. New York: Marlowe & Company. Anderson, R. D., & Helms, J. V. (2001). The ideal of standards and the reality of schools: Needed research. Journal of Research in Science Teaching, 38, 3–16. Andre, T., Whigham, M., Hendrickson, A., & Chambers, S. (1999). Competency beliefs, positive affect, and gender stereotypes of elementary students and their parents about science versus other school subjects. Journal of Research in Science Teaching, 36, 719–747. Aunola, K., Leskinen, E., Onatsu-Arvilommi, T., & Nurmi, J. E. (2002). Three methods for studying developmental change: A case of reading skills and self-concept. British Journal of Educational Psychology, 72, 343–364. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Bluck, S. (2003). Autobiographical memory: Exploring its functions in everyday life. Memory, 11, 113–123. Britner, S. L., & Pajares, F. (2006). Sources of science self-efficacy beliefs of middle school students. Journal of Research in Science Teaching, 43, 485–499. Brown, A. L. (1997). Transforming schools into communities of thinking and learning about serious matters. American Psychologist, 32, 399–413. Callanan, M. A., & Jipson, J. I. (2001). Explanatory conversations and young children’s developing scientific literacy. In K. Crowley, C. D. Schunn, & T. Okada (Eds.), Designing for science: Implications from everyday, classroom, and professional settings (pp. 21–49). Mahwah, NJ: Erlbaum. Congressional Commission on the Advancement of Women and Minorities in Science, Engineering, and Technology Development. (2000). Land of plenty: Diversity as America’s competitive edge in science, engineering, and technology. Retrieved June 11, 2006 from http://www.nsf.gov/pubs/2000/cawmset0409/cawmset 0409.pdf. Chaille, C., & Britain, L. (2003). The young child as a scientist: A constructivist approach to early childhood science education (3rd ed.). MA, Boston: Allyn & Bacon. Chambers, C. T., & Johnston, C. (2002). Developmental differences in children’s use of rating scales. Journal of Pediatric Psychology, 27, 27–36. Chapman, J. W., & Tunmer, W. E. (1995). Development of young children’s reading self-concepts: An examination of emerging subcomponents and their relationship with reading achievement. Journal of Educational Psychology, 87, 154–167. Chapman, J. W., & Tunmer, W. E. (1997). A longitudinal study of beginning reading achievement and reading self-concept. British Journal of Educational Psychology, 67, 279–291. Chapman, J. W., Tunmer, W. E., & Pronchow, J. E. (2000). Early reading-related skills and performance, reading self-concept, and the development of academic self-concept: A longitudinal study. Journal of Educational Psychology, 92, 703–708. Clark-Chiarelli, N., Gopen, J, & Challufour, I. (2007, June). Foundations of science literacy: Physical science in the preschool classroom. Poster presented at the annual conference of the Institute of Education Sciences, Washington, DC. Clay, M. M. (1991). Introducing a new storybook to young readers. The Reading Teacher, 45, 264–273. Cleaves, A. (2005). The formation of science choices in secondary school. International Journal of Science Education, 27, 471–486. Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1, 16–29. DeMarie, D., Norman, A., & Abshier, D. W. (2000). Age and experience influence different verbal and nonverbal measures of children’s scripts for the zoo. Cognitive Development, 15, 241–262. Dickinson, V. L., Burns, J., Hagen, E. R., & Locker, K. M. (1997). Becoming better primary science teachers: A description of our journey. Journal of Science Teacher Education, 8, 295–311. Dickinson, V. L., & Young, T. A. (1998). Elementary science and language arts: Should we blur the boundaries? School Science and Mathematics, 98, 334–339. Duke, N. K. (2000). 3.6 minutes per day: The scarcity of informational texts in first grade. Reading Research Quarterly, 35, 202–224. Dweck, C. S. (1998). The development of early self-conceptions: Their relevance for motivational processes. In J. Heckhausen & C. S. Dweck (Eds.), Motivation and self-regulation across the lifespan (pp. 257–280). New York: Cambridge University Press. Eccles, J. S. (1994). Understanding women’s educational and occupational choices. Psychology of Women Quarterly, 18, 585–609. Eccles, J. S. (2005). Subjective task value and the Eccles et al. model of achievement-related choices. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 105–121). New York: Guilford Press. Eccles, J., Adler, T. F., Futterman, R., Goff, S. B., Kacazala, C. M., Meece, J. L., & Midgley, C. (1983). Expectancies, values and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motivation (pp. 75–146). San Francisco: Freeman. Eccles, J., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993). Age and gender differences in children’s self- and task perceptions during elementary school. Child Development, 64, 830–847.

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

393

Eccles, J. S., Wigfield, A., & Schiefele, U. (1998). Motivation to succeed. In W. Damon (Series Ed.) & N. Eisenberg (Vol. Ed.). Handbook of child psychology: Vol. 3. Social, emotional, and personality development (5th ed., pp. 1017–1095). New York: Wiley. Eder, R. A. (1989). The emergent personologist: The structure and content of 31/2-, 51/2-, and 71/2-year-olds’ concepts of themselves and other persons. Child Development, 60, 1218–1228. Eder, R. A. (1990). Uncovering young children’s psychological selves: Individual and developmental differences. Child Development, 61, 849–863. Fava, J. L., & Velicer, W. F. (1992). An empirical comparison of factor, image, component, and scale scores. Multivariate Behavioral Research, 27, 301–322. Feagans, L. V., & Farran, D. C. (1993). How demonstrated comprehension can get muddled in production. In R. A. Pierce & M. A. Black (Eds.), Life-span development: A diversity reader (pp. 47–59). Kendall/Hunt. Feagans, L. V., & Farran, D. C. (1994). The effects of daycare intervention in the preschool years on the narrative skills of poverty children in kindergarten. International Journal of Behavioral Development, 17, 503–523. Fivush, R. (1984). Learning about school: The development of kindergartners’ school scripts. Child Development, 55, 1697–1709. Fivush, R., & Haden, C. A. (2003). Autobiographical memory and the construction of a narrative self: Developmental and cultural perspectives. NJ: Erlbaum. Fleer, M., & Cahill, A. (2001). I want to know. . .? Learning about science. Australian Early Childhood Association Research in Practice Series, 8(1) (ERIC Document Reproduction Service No. ED458983) Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7, 286–299. Foster, S. H. (1990). The communicative competence of young children. London: Longman. French, L. (2004). Science as the center of a coherent, integrated early childhood curriculum. Early Childhood Research Quarterly, 19, 138–149. Fulp, S. L. (2002). 2000 National survey of science and mathematics education: Status of elementary school science teaching. Retrieved November 24, 2003 from http://www.2000survey.horizon-research.com/reports/elem science.php. Gelman, R. (1990). First principles organize attention to and learning about relevant data: Number and the animate–inanimate distinction as examples. Cognitive Science, 14, 79–106. Gelman, R., & Brenneman, K. (2004). Science learning pathways for young children. Early Childhood Research Quarterly, 19, 150–158. Good, R. H., & Kaminski, R. A. (Eds.) (2002). Dynamic Indicators of Basic Early Literacy Skills (6th ed.). Eugene, OR: Institute for the Development of Educational Achievement. Retrieved June 2, 2006 from http://www.dibels.uoregon.edu/. Hair, J. F., Black, W. C., Bain, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). New Jersey: Pearson. Halliday, M. A. K. (2006). The language of science. In J. J. Webster (Ed.), The collected works of M. A. K. Halliday. New York: Continuum. Harter, S. (1986). Processes underlying the construction, maintenance, and enhancement of self-concept in children. In S. Suls & A. Greenwald (Eds.), Psychological perspectives of the self (pp. 136–182). Hillsdale, NJ: Erlbaum. Harter, S. (1998). The development of self-representations. In W. Damon (Series Ed.) & N. Eisenberg (Vol. Ed.). Handbook of child psychology: Vol. 3. Social, emotional, and personality development (5th ed., pp. 553–617). New York: Wiley. Harter, S., & Pike, R. (1984). The pictorial scale of perceived competence and social acceptance. Child Development, 55, 1969–1982. Hattie, J. (1992). Self-concept. NJ, Hillsdale: Erlbaum. Helmke, A., & van Aken, M. A. G. (1995). The causal ordering of academic achievement and self-concept of ability during elementary school: A longitudinal study. Journal of Educational Psychology, 87, 624–637. Hudson, J. A., Shapiro, L. R., & Sosa, B. B. (1995). Planning in the real world: Preschool children’s scripts and plans for familiar events. Child Development, 66, 984–998. Huntley, M. A. (1998). Design and implementation of a framework for defining integrated mathematics and science instruction. School Science and Mathematics, 98, 320–327. Jacobs, J. E., Finken, L. L., Griffin, N. L., & Wright, J. D. (1998). The career plans of science-talented rural adolescent girls. American Educational Research Journal, 35, 681–704. Jacobs, J. E., Lanza, S., Osgood, D. W., Eccles, J. S., & Wigfield, A. (2002). Changes in children’s self-competence and values: Gender and domain differences across grades one through twelve. Child Development, 73, 509–527. Jovanovic, J., & King, S. S. (1998). Boys and girls in the performance-based science classroom: Who’s doing the performing? American Educational Research Journal, 35, 477–496. Kallery, M., & Psillos, D. (2001). Pre-school teachers’ content knowledge in science: Their understanding of elementary science concepts and of issues raised by children’s questions. International Journal of Early Years Education, 9(3), 165–179. Klein, E. R., Hammrich, P. L., Bloom, S., & Ragins, A. (2000). Language development and science inquiry: The Head Start on Science and Communication program. Early Childhood Research and Practice, 2, 1–22. Korpan, C. A., Bisanz, G. L., Bisanz, J., Boehme, C., & Lynch, M. A. (1997). What did you learn outside of school today? Using structured interviews to document home and community activities related to science and technology. Science Education, 81, 651–662. Kruger, C. (1990). Some primary teachers’ ideas about energy. Physics Education, 25, 86–91. Kuczaj, S. A., II, & Maratsos, M. P. (1975). What children can say before they will. Merrill-Palmer Quarterly, 21, 89–111. Lanahan, L., Princiotta, D., & Enyeart, C. (2006). Instructional focus in first grade: Issue brief (National Center for Education Statistics Rep. No. NCES 2006-056). Retrieved October 28, 2006 from: http://www.nces.ed.gov/pubs2006/2006056.pdf. Mantzicopoulos, P., & Neuharth-Pritchett, S. (2003). Development and validation of a measure to assess Head Start children’s appraisals of teacher support. Journal of School Psychology, 41, 431–451. Mantzicopoulos, P., French, B. F., & Maller, S. J. (2004). Factor structure of the pictorial scale of perceived competence and social acceptance with two pre-elementary samples. Child Development, 75, 1214–1228. Mantzicopoulos, P., Patrick, H., & Samarapungavan, A. (2005). The Scientific Literacy Project: Enhancing young children’s scientific literacy through reading and inquiry-centered adult–child dialog. Unpublished manuscript. Mantzicopoulos, P., Patrick, H., & Samarapungavan, A. (2007, June). Kindergarten children becoming science learners. Poster presented at the annual conference of the Institute of Education Sciences, Washington, DC. Marsh, H. W., & Hattie, J. (1996). Theoretical perspectives on the structure of self-concept. In B. A. Bracken (Ed.), Handbook of self-concept (pp. 38–90). New York: John Wiley & Sons. Marsh, H. W., Craven, R. G., & Debus, R. (1991). Self-concepts of young children 5 to 8 years of age: Measurement and multidimensional structure. Journal of Educational Psychology, 83, 377–392. Marsh, H. W., Craven, R. G., & Debus, R. (1998). Structure, stability, and development of young children’s self-concepts: A multicohort–multioccasion study. Child Development, 69, 1030–1053. Marsh, H. W., Ellis, L. A., & Craven, R. G. (2002). How do preschool children feel about themselves? Unraveling measurement and multidimensional selfconcept structure. Child Development, 38, 376–393. Marx, R. W., & Harris, C. J. (2006). No Child Left Behind and science education: Opportunities, challenges, and risks. Elementary School Journal, 106, 467–477. McGrew, K. S., & Woodcock, R. W. (2001). Technical manual: Woodcock-Johnson III. Itasca, IL: Riverside. Measelle, J. R., Ablow, J. C., Cowan, P. A., & Cowan, C. P. (1998). Assessing young children’s views of their academic, social, and emotional lives: An evaluation of the self-perceptions scales of the Berkeley Puppet Interview. Child Development, 69, 1556–1576. Meece, J. L., & Jones, M. G. (1996). Gender differences in motivation and strategy use in science: Are girls rote learners? Journal of Research in Science Teaching, 33, 393–406. Miller, P. H. (1985). Children’s reasoning about the causes of human behavior. Journal of Experimental Child Psychology, 39, 343–362.

394

P. Mantzicopoulos et al. / Early Childhood Research Quarterly 23 (2008) 378–394

Mize, J., & Ladd, G. W. (1988). Predicting preschoolers’ peer behavior and status from their interpersonal strategies: A comparison of verbal and enactive responses to hypothetical social dilemmas. Developmental Psychology, 24, 782–788. National Association for the Education of Young Children. (2003). Early Childhood Curriculum, Assessment, and Program Evaluation. Retrieved December 20, 2003 from: http://www.naeyc.org/resources/position statements/pscape.asp. National Research Council. (2000). Inquiry and the national science education standards: A guide for teaching and learning. Washington, DC: National Academy Press. National Research Council. (2001). Eager to learn: Educating our preschoolers. Washington, DC: National Academy Press. National Research Council. (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academy Press. National Center for Education Statistics (1997). Time spent teaching core academic subject in elementary schools: Comparisons across community, school teacher, and student characteristics (NCES 97-923). Washington, DC: U.S. Department of Education. Retrieved, November 28, 2003 from http://www.nces.ed.gov/pubsearch/pubsinfo.asp?pubid=97293. National Institute of Child Health and Human Development-Early Child Care Research Network. (2005). A day in third grade: A large-scale study of classroom quality and teacher and student behavior. Elementary School Journal, 105, 305–323. Nicholls, J. G. (1978). The development of the concepts of effort and ability, perceptions of academic attainment, and the understanding that difficult tasks require more ability. Child Development, 49, 800–814. Nicholls, J. G. (1979). Development of perception of own attainment and causal attributions for success and failure in reading. Journal of Educational Psychology, 71, 94–99. Nicholls, J. G. (1990). What is ability and why are we mindful of it? A developmental perspective. In R. J. Sternberg & J. Kolligian Jr. (Eds.), Competence considered (pp. 11–40). New Haven, CT: Yale University Press. Norris, S. P., & Phillips, L. M. (2003). How literacy in its fundamental sense is central to scientific literacy. Science Education, 87, 224–240. Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill. Ogle, D. M. (1986). K–W–L: A teaching model that develops active reading of expository text. The Reading Teacher, 39, 564–570. Pallas, A. M., Entwisle, D. R., Alexander, K. L., & Weinstein, P. (1990). Social structure and the development of self-esteem in young children. Social Psychology Quarterly, 53(4), 302–315. Parsons, J. E., & Ruble, D. N. (1977). The development of achievement-related expectancies. Child Development, 48, 1075–1079. Piaget, J. (1967). The language and thought of the child. New York: The Humanities Press. Pigdon, K. (2003). Living things need food. Washington, DC: National Geographic Society. Reifel, S. (1988). Children’s thinking about their early education experiences. Theory into Practice, 27, 62–66. Reise, S. P., Waller, N. G., & Comrey, A. L. (2000). Factor analysis and scale revision. Psychological Assessment, 12, 287–297. Rennie, L. J., Feher, E., Dierking, L. D., & Falk, J. H. (2003). Toward an agenda for advancing research on science learning in out of school settings. Journal of Research in Science Teaching, 40, 112–120. Russell, S. (2003). Tools scientists use. Washington, DC: National Geographic Society. Samarapungavan, A., Mantzicopoulos, P., & Patrick, H. (in press). Learning science through inquiry in kindergarten. Science Education, doi:10.1002/sce.20275. Schunk, D. H. (1990). Self-concept and school achievement. In C. Rogers & P. Kutnick (Eds.), The social psychology of the primary school (pp. 70–91). London: Routledge. Shepardson, D. P., & Pizzini, E. L. (1994). Gender, achievement, and perception toward science activities. School Science and Mathematics, 94, 188–193. Simpkins, S. D., Davis-Kean, P. E., & Eccles, J. S. (2006). Math and science motivation: A longitudinal examination of the links between choices and beliefs. Developmental Psychology, 42, 70–83. Simpson, R. D., & Oliver, J. S. (1990). A summary of major influences on attitude toward and achievement in science among adolescent students. Science Education, 74, 1–18. Slate, J. R., & Jones, C. H. (1998). Fourth and fifth grade students’ attitudes toward science: Science motivation and science importance as a function of grade level, gender, and race. Research in the Schools, 5, 27–32. Stipek, D. J., & Mac Iver, D. (1989). Developmental change in children’s assessment of intellectual competence. Child Development, 60, 521–538. Stoddart, T., Pinal, A., Latzke, M., & Cnaday, D. (2002). Integrating inquiry science and language development for English language learners. Journal of Research in Science Teaching, 39, 664–687. Strein, W., & Simonson, T. (1999). Kindergartners’ self-perceptions: Theoretical and measurement issues. Measurement and Evaluation in Counseling and Development, 32, 31–42. The Scientific Literacy Project. (2006). Whose eye is it? The Scientific Literacy Project. Trussell-Cullen, A. (2001a). Living Things. Carlsbad, CA: Dominie Press. Trussell-Cullen, A. (2001b). Animal, Vegetable, or Mineral? Carlsbad, CA: Dominie Press. Valentine, J. C., DuBois, D. L., & Cooper, H. (2004). The relation between self-beliefs and academic achievement. Educational Psychologist, 39, 111–133. Valeski, T. N., & Stipek, D. J. (2001). Young children’s feelings about school. Child Development, 72, 1198–1213. Weiss, I. R., Pasley, J. D., Smith, P. S., Banilower, E. R., & Heck, D. J. (2003). A study of k-12 mathematics and science education in the United States. Chapel Hill, NC: Horizon Research. Retrieved from http://www.horizon-research.com/insidetheclassroom/reports/looking/. Whitehurst, G. J., Zevenbergen, A. A., Crone, D. A., Shultz, M. D., Velting, O. N., & Fischel, J. E. (1999). Outcomes of an emergent literacy intervention from Head Start through second grade. Journal of Educational Psychology, 91, 261–272. Wigfield, A., & Eccles, J. S. (2002). The development of competence beliefs, expectancies for success, and achievement values from childhood through adolescence. In A. Wigfield & J. S. Eccles (Eds.), Development of achievement motivation (pp. 91–120). San Diego: Academic Press. Wigfield, A., & Karpathian, M. (1991). Who am I and what can I do? Children’s self-concepts and motivation in achievement situations. Educational Psychologist, 26, 233–261. Wigfield, A., Eccles, J. S., Yoon, K. S., Harold, R. D., Arbreton, A. J. A., Freedman-Doan, C., et al. (1997). Change in children’s competence beliefs and subjective task values across the elementary school years: A 3-year study. Journal of Educational Psychology, 89, 451–469. Wigfield, A., Battle, A., Keller, L. B., & Eccles, J. S. (2002). Sex differences in motivation, self-concept, career aspiration, and career choice: Implications for cognitive development. In A. McGillicuddy-De Lisi & R. De Lisi (Eds.), Biology, society, and behavior: The development of sex differences in cognition (pp. 93–124). Westport, CT: Ablex. Wiltz, N. W., & Klein, E. L. (2001). “What do you do in child care?”—Children’s perceptions of high and low quality classrooms. Early Childhood Research Quarterly, 16, 209–236. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). Woodcock-Johnson III tests of achievement. Itasca, IL: Riverside Publishing. Worth, K., & Grollman, S. (2003). Worms, shadows, and whirlpools: Science in the early childhood classroom. Washington, DC: National Association for the Education of Young Children. Yore, L. D., & Hand, B. M. (2003). Examining the literacy component of science literacy: 25 years of language arts and science research. International Journal of Science Education, 25, 689–725.