task engagement and conceptual change in middle school science classrooms

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1993 30: 585Am Educ Res JOkhee Lee and Charles W. Anderson

Task Engagement and Conceptual Change in Middle School Science Classrooms

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American Educational Research Journal Fall 1993, Vol 30, No. 3, PP 585-610

Task Engagement and Conceptual Change in Middle School Science Classrooms

Okhee Lee University of Miami

Charles W. Anderson Michigan State University

Science educators have long been concerned that many students fail to engage in academic tasks with the goal of achieving better understanding of science. This study examined two research questions. First, what patterns of students' task engagement emerge as they work on science classroom tasks? Second, how are patterns of students' task engagement related to factors involving their cognition (i.e., knowledge and achievement), motivation (e.g., goals in science class), and affect (i.e., attitudes toward science)? The study involved 12 sixth-grade students in two classrooms where the teachers and instructional materials provided students with extensive support to understand science better. The results indicated that some students recognized the value of science learning and demonstrated high quality of cognitive engagement, whereas others pursued alternative agendas. The results are used to explore two research traditions that offer different explanations for the failure of students' task engagement: (a) cognitive science or conceptual change research and (b) motivation research.

OKHEE LEE is an Assistant Professor in the School of Education at the University of Miami, P.O. Box 248065, Coral Gables, FL 33124. Her specializations are research on teaching, science education, and qualitative research methods.

CHARLES W. ANDERSON is an Associate Professor of Teacher Education in the College of Education at Michigan State University, East Lansing, MI 48824. His specializations are research on teaching, science education, and qualitative research methods.

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Lee and Anderson

E vidence has been mounting for years that our system of science education is not working well. In part, the failures are cognitive: Students fail to un

derstand the content of science classes. National reports on science education indicate slow, consistent declines in student achievement in science subjects since the mid-1960s (Hueftle, Rakow, & Welch, 1983) with a sign of minor recovery in the late 1980s (Mullis & Jenkins, 1988). In addition, comparisons of science achievement among American students and those in other industrialized nations indicate that Americans perform significantly worse than their counterparts (International Association for the Evaluation of Educational Achievement, 1988; Lapointe, Askew, & Mead, 1992).

There is also evidence that our system is failing in a motivational and affective sense. National reports indicate that the proportion of high-school students enrolled in science courses as electives or for science careers has declined steadily since the mid-1960s (Harms & Yager, 1981). Students' attitudes toward science have also indicated negative trends since the mid-1960s (Hueftle, Rakow, & Welch, 1983; Mullis & Jenkins, 1988). Further, students' attitudes toward science deteriorate as they advance in school (Hueftle, Rakow, & Welch, 1983; Mullis & Jenkins, 1988; Simpson & Oliver, 1985).

Observations of science classrooms typically reveal a pattern in which cognitive, motivational, and affective aspects of failure are evident. Students often find classroom tasks to be trivial and boring, or difficult and confusing. The students typically respond with a pattern of behavioral engagement, in which they exert the effort necessary to avoid sanctions for off-task behavior and to earn acceptable grades. However, they fail to engage in deeper cognitive processing that would lead to meaningful understanding (Anderson & Smith, 1987; Blumenfeld & Meece, 1988; Blumenfeld, Mergendoller, & Swarthout, 1987; Doyle, 1983, 1986; Posner, Strike, Hewson, & Gertzog, 1982; Tobin, Butler-Kahle, & Fraser, 1990).

Although the existence and the general pattern of failure are widely recognized, researchers in different traditions differ in their assessments of the causes for this pattern of failure and in their suggestions for improving the situation. Cognitive science and motivation research approaches have largely been concerned with different aspects of classroom learning or motivation (Ames & Ames, 1989; Brown, 1988).

Cognitively oriented researchers, including those in the conceptual change tradition in science education, have focused their attention on the nature of content knowledge, the cognitive demands of academic tasks, and the adequacy of instructional support that accompanies those tasks. They have argued that some tasks are so trivial or so poorly matched to students' knowledge and ability that they afford little opportunity for cognitive engagement or the development of deeper understanding. They have also argued that the instructional support provided in most science classrooms is ineffective. Thus, students who engage tasks in a superficial manner may be responding rationally to a situation that affords them no real opportunity for deeper understanding. Conceptual change researchers' efforts to improve science teaching have generally focused on developing academic tasks and instructional support systems that make it possi-

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ble for students to learn science with understanding (e.g., Anderson & Roth, 1989; Anderson & Smith, 1987; Driver, 1988; Nussbaum & Novick, 1982; Pines & West, 1986; Posner et al., 1982; White & Gunstone, 1992).

Researchers who focus on issues of student motivation argue that many students fail to engage productively in academic tasks for reasons concerning perceptions, beliefs, and affects of the self in relation to those tasks. They suggest that students avoid classroom tasks that require sustained cognitive engagement for various reasons, including feelings of alienation from science or negative attitudes (Cannon & Simpson, 1985; James & Smith, 1985), unproductive goal orientations concerning excessive ego or social involvement at the expense of task involvement (Ames & Archer, 1988; Elliott & Dweck, 1988; Meece, Blu-menfeld, & Hoyle, 1988; Nicholls, 1984; Nolen, 1988; Wentzel, 1989), low self-efficacy (Bandura, 1986; Schunk, 1991), maladaptive causal attributions (Weiner, 1986), conflicting beliefs about the role of ability versus effort in academic performance (Covington & Omelich, 1985), and learned helplessness (Diener & Dweck, 1978, 1980). Thus, motivation researchers' efforts to improve the quality of classroom instruction have tended to address unproductive dispositional and behavioral patterns that interfere with student achievement.

In recent years, researchers in both conceptual change and student motivation have discussed the need to integrate learning/cognition and motivation/ affect in the classroom (Brophy, 1987; Corno & Mandinach, 1983). Some have attempted to establish conceptual frameworks for such integration. For instance, Pintrich, Marx, and Boyle (in press) considered conceptual change learning from a motivational perspective, whereas several conceptual change researchers have considered motivational and affective issues (Strike & Posner, 1983, 1992; West & Pines, 1983; White, 1987). In addition, some researchers have conducted empirical research examining the relationships between motivational orientations and learning strategies or self-regulated learning (Ames & Archer, 1988; Blumenfeld & Meece, 1988; Meece, Blumenfeld, & Hoyle, 1988; Nolen, 1988; Pintrich & De Groot, 1990) or motivational influences on cognition (Graham & Golan, 1991). Despite such recent efforts, the development of conceptual frameworks is still at an early stage, and empirical research has addressed only limited aspects of classroom learning and motivation.

Thus, it is both practically and theoretically important that educators develop a comprehensive understanding of how various cognitive, motivational, and affective factors interact when students decide why, how, and how hard to work on academic tasks in science classrooms. In this study, we attempted to address these questions empirically and in ecologically valid contexts. We therefore sought to observe classrooms where students' academic work provided the potential for learning science with understanding. In these classrooms, we attempted to determine how deeply individual students were engaged in academic tasks, and how cognitive, motivational, and affective factors interacted to influence students' quality of task engagement.

In the present study we examined two research questions. First, what patterns of students' task engagement existed as the students engaged in academic tasks in science classrooms? Second, how were patterns of students' task engage-

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ment related to factors involving the students' cognition (i.e., science knowledge and achievement), motivation (e.g., goals in science class), and affect (e.g., attitudes toward science)? The study involved a small number of students and used descriptive, qualitative research methods. Multiple sources of data were collected through classroom observations; clinical, structured, and informal interviews; and self-report questionnaires. The article concludes with a reexamination of the two research traditions in the light of the findings of this study.

Research Setting and Subjects

Curriculum

The present study was associated with a larger research project, the primary purpose of which was to develop curriculum materials and instructional strategies to promote scientific understanding of matter and its properties and of kinetic molecular theory for sixth-grade science students (Berkheimer, Anderson, & Blakeslee, 1988b; Berkheimer, Anderson, Lee, & Blakeslee, 1988). The curriculum materials included a science book (student text), an activity book including thought questions and hands-on experiments, and teachers' guides for the science book and the activity book. The unit was organized as a series of nine lesson clusters, each consisting of four to six 45-minute lessons.

The curriculum and instructional development was guided by a conceptual change approach to teaching science (Berkheimer, Anderson, & Blakeslee, 1988a; Berkheimer, Anderson, & Spees, 1990). The curriculum materials were based on extensive investigations into students' conceptions and misconceptions about aspects of matter and molecules (Lee, Eichinger, Anderson, Berkheimer, & Blakeslee, 1993). The activities of the unit involved students in describing, explaining, making predictions about, or attempting to control natural phenomena in a variety of contexts.

Teachers and Instruction

The study was conducted in two comparable classrooms from two different schools in the same district. The two participating teachers were recommended as exemplary teachers by their principals and colleagues. Both worked as collaborating teachers in the larger project. During the 3 month duration of the present study, the two teachers implemented instruction consistent with the curricular goals, following the instructional strategies suggested in the teachers' guides. The teachers tried to help their students recognize and resolve conflicts between personal knowledge and canonical scientific knowledge, and they encouraged the students to use scientific knowledge to explain natural phenomena across diverse situations.

As suggested in the teachers' guides, four types of class activities were used extensively in both classrooms: (a) reading and discussing the science book, (b) conducting hands-on experiments, (c) writing about their ideas and experiments in the activity book, and (d) engaging in class discussions of ideas and results. In a typical instructional sequence, students were encouraged to express their prior knowledge about a science topic and compare their ideas with

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canonical scientific ideas. Then they were presented with real-world problems, usually through hands-on experiments, after which they wrote their results and explanations in the activity book. Finally, students engaged in class discussion to present their explanations, exchange ideas, and verify their understanding and explanations. Student grades were determined largely by their performance on tests and quizzes and in the activity book.

Thus, the two classrooms provided a research context to examine student learning and motivation in science classrooms where there were high expectations and where there was extensive support from the teacher and the curriculum materials to help students better understand science. This context differed significantly from most traditional science classrooms or conventional curriculum materials that reward rote learning of vocabulary and technical details, or activity-based programs that are developed from the perspective of scientists without consideration of students' personal knowledge in content domains.

Setting and Students

The study was conducted in two 6th-grade science classrooms in a midwestern urban district with an ethnically mixed student population: 25% African American, 10% Hispanic, 3% Asian, 2% American Indian, and 60% white students. Both classrooms were selected as representing average, regular sixth-grade science classes in the school district in terms of student achievement, behavioral conduct, and other social and cultural aspects.

The study focused on 12 students, 6 from each classroom. The 12 students were identified by their teachers as representing three achievement levels (high, medium, and low) based on their science performance records at the entry to the present middle school and their class performance during a couple of months before the study began. The teachers also considered students' conduct and class participation, gender, and ethnic backgrounds. The 12 students consisted of 4 students from each achievement level; 7 female and 5 male students; and 8 white, 2 Hispanic, and 2 African-American students.

Data Collection and Analysis To examine various aspects of classroom learning and motivation, multiple sources of data were collected. The data analysis involved three main stages (a) informal analyses based on the observers' intuitive reasoning from a thorough reading of data; (b) formal analyses based on coding systems using ratings or frequency counts; and (c) development of summary charts and case studies. Data collection and analysis were completed by two researchers, each of whom collected data primarily in one classroom. The two observers regularly exchanged data sets to check the consistency of data collection procedures. Four types of data were collected and analyzed, as described below.

Task Engagement

Definition. The quality of task engagement is conceived of in terms of students' choice of goals and strategies while engaging in classroom tasks (Brophy, 1983, 1987, 1989; Corno & Mandinach, 1983). In particular, the state of motiva-

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tion to learn science is defined as ' 'students' engagement in classroom tasks with the goal of achieving better understanding of science in specific situations." This definition integrates two distinct conceptual frameworks from existing classroom research: "student motivation to learn" (Brophy, 1983, 1987, 1989; Corno & Rohrkemper, 1985) and conceptual change in science (e.g., Anderson & Roth, 1989; Pines & West, 1986; Posner, Strike, Hewson, & Gertzog, 1982). According to this definition, students who are motivated to learn science engage in science classroom tasks with the goal of achieving scientific understanding as they try to integrate their personal knowledge with scientific knowledge and apply scientific knowledge to describe, explain, predict, and control the world around them.

Measure. Previous research usually relied on self-report questionnaires to assess students' goals and learning strategies in a large sample of students and used quantitative methods (e.g., Ames & Archer, 1988; Meece, Blumenfeld, & Hoyle, 1988; Nolen, 1988; Pintrich & De Groot, 1990; Wentzel, 1989). In contrast, this study employed focused classroom observations and informal interviews with a small number of students and used descriptive, qualitative research methods. This decision was made for two major reasons. First, to examine the quality of students' task engagement, it was deemed necessary to probe into their cognitive and metacognitive processes while the students were actually engaged in classroom tasks in specific situations. Second, research on conceptual change in science suggests that many students do not have a conception of what scientific understanding involves (Nickerson, 1985; Roth, 1986). If so, students' self-reporting of understanding science might not reflect what scientific understanding really is.

To examine the quality of students' task engagement in specific situations, three different categories of behavior were considered. The first category of behavior, self-initiated cognitive engagement, included those situations in which students were observed initiating activities to understand science better without solicitation from the teacher, expanding their thinking beyond the lesson content, and engaging in tasks beyond the requirements or expectations of the classroom. The second category of behavior, cognitive engagement, included those situations in which, within the scope of lesson content and classroom requirements, students demonstrated strategies to achieve scientific understanding as they tried to integrate their personal knowledge with scientific knowledge and apply scientific knowledge to understand the world around them. Finally, behavioral engagement was coded whenever students appeared attentive and involved in class activities. These categories were not considered mutually exclusive or exhaustive. More information on this follows.

Data collection. Based on these three different types of behavior during students' task engagement, guidelines for systematic classroom observations and informal interviews were developed during four major class activities: reading, writing, experimentation, and class discussion. In addition to recording extensive narrative descriptions during class, the observers audiotaped both classroom discourse and informal interviews with target students using two tape-recorders in each classroom. The observers focused on one target student at a time dur-

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ing one of the four class activities. Thus, an observation episode contained detailed descriptions about a target student's behavioral responses and cognitive processes during a designated class activity. Because each activity typically lasted for 10-20 minutes, one lesson produced three or four episodes. To control the influences of certain class activities on students' task engagement, the 12 students were observed across the four types of class activities with equivalent frequency and duration. Also, to control the influences of science content on task engagement, the students were observed at least once during each of the nine lesson clusters in the unit. Eventually, 40 lessons were observed in the two classrooms, resulting in a total of 130 observation episodes (i.e., 10-12 episodes for each of the 12 target students).

Data analysis. To analyze the quality of students' task engagement, the three types of behavior were combined into a coding system. After thorough reading of the observation episodes and the initial data analysis, a seven-level coding system was created. Codes ranged from the highest level of task engagement (Level 1) to the lowest level (Level 7), as shown in Table 1. The observation episode was used as the unit of analysis. For each episode, the quality of task engagement was judged as representing one of the seven levels. For instance, a rating of 2 (or Level 2 task engagement) was given when a target student demonstrated cognitive engagement ("yes" in Table 1) as well as behavioral engagement ("yes") to better understand science, but displayed no self-initiation

Table 1 Coding System for Data Analysis: The Quality of Task Engagement

Observed behavior

Self-initiated cognitive Cognitive Behavioral

Level engagement engagement engagement

1 Yes Yes Yes 2 No Yes Yes 3 No Ambiguity Yes 4 No No Yes 5 No Ambiguity No 6 No No No 7 No No No & disruption

Note. The descriptor "ambiguity" indicates situations when the assessment of cognitive engagement was not clear because of insufficient evidence. This problem often resulted from constraints inherent in classroom settings. For instance, to probe students' cognitive processes, it was desirable for the observer to interact with individual students while they engaged in classroom tasks. However, finding time to talk to individual students during class was not always convenient or possible, especially during whole-class activities. Further, no clear evidence about students' cognitive engagement could be found in the activity book or during class discussion. Such problems of data collection during class were also noted in other studies on classroom learning and motivation (Anderson, Brubaker, Alleman-Brooks, & Duffy, 1985; Tobin, 1986; Winne & Marx, 1982).

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in cognitive engagement ("no"). The agreement between two coders for the 130 observation episodes was 81 %. Disagreements were resolved through discussion by the two coders.

Knowledge and Achievement

Definition. Students' knowledge and achievement in science was defined in conceptual change terms. Students were considered to have understood the science content to the extent that they successfully: (a) integrated their personal knowledge with scientific knowledge and (b) applied scientific knowledge to describe, explain, predict, and control the world around them (e.g., Anderson & Roth, 1989).

Data collection and analysis. Students' knowledge of matter and molecules was examined prior to, during, and after instruction using the curriculum unit (see Lee et al., 1993, for details). Prior to and after instruction, clinical interviews were conducted by two interviewers, one interviewer with each of the six target students in each classroom. The clinical interviews examined students' knowledge of matter and molecules using the following eight science tasks: (a) the nature of matter, (b) three states of matter, (c) expansion and compression of gases, (d) thermal expansion, (e) dissolving, (f) melting and freezing, (g) boiling and evaporation, and (h) condensation. The interviews investigated 19 conceptual issues about aspects of matter and molecules at the macroscopic level (i.e., concerning the nature of substances and their properties) and the molecular level (i.e., concerning molecules and their properties). The extent to which students demonstrated scientific understanding of each of the 19 issues was classified into one of four categories: (a) scientific goal conception, (b) clearly noncanonical response, that is, incompatible with current scientific understanding, (c) mixed response (partially scientific and partially noncanonical), and (d) ambiguous or inconclusive data. The agreement between the two coders for the 19 conceptual issues with the 12 target students was 88%.

Over the period of instruction of the unit, the two observers collected data that were used to evaluate students' success in completing specific classroom tasks. Data sources included informal interviews with target students during and after class, their answers in the activity book and tests, and their conversations with peers and teachers. The extent to which students demonstrated scientific understanding in a specific task situation was assessed as representing one of four categories: (a) success, (b) failure, (c) partial success, and (d) ambiguous or inconclusive data. The agreement between the two coders for 130 observation episodes of the 12 target students was 85%.

Goals in Science Class

Definition. Motivation research indicates that students' behavior in achievement situations is driven by a complex interplay of goals, and that students generally behave so as to achieve their goals (e.g., learning versus performance goals by Dweck & Elliott, 1983; task- versus ego-involved by Maehr & Nicholls, 1980; mastery versus ability-focused by Ames & Ames, 1984). Recent research on goal orientations has identified three forms of goal orientation while students

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engage in classroom tasks: (a) task orientation involves a commitment to learning; (b) ego-social orientation involves a desire to perform better than other students and to please significant others such as the teacher or parents; and (c) work-avoidant orientation involves a desire to minimize effort or do as little as possible (Blumenfeld & Meece, 1988; Maehr, 1984; Meece, Blumenfeld, & Hoyle, 1988; Nicholls, Patashnick, & Nolen, 1985; Nolen, 1988).

One deviation from previous research was made in this study. Because not all students conceived of ' 'learning" or "understanding" in the same way (Nickerson, 1985; Roth, 1986), task orientation was divided into two clusters: understanding and fact acquisition. As a result, four clusters of goals were examined in the study: (a) understanding, (b) fact acquisition, (c) ego-social, and (d) work-avoidant.

Data collection and analysis. Each of the 12 target students' goals in science class was examined using a semistructured interview and a self-report questionnaire prior to and after instruction of the unit. First, to examine whether students recognized what scientific understanding involves, the two interviewers probed the students' perceptions of the nature of science and science learning (e.g., What does science mean to you? Why do you study science?).

Then, the interviewers asked the students to rate a list of 10 goals on a 4-point scale (4 = a lot like me, 1 = not at all like me). Two items concerned understanding as a goal: (a) "I try to make sense of scientifically correct ideas," and (b) "I try to apply scientific knowledge to understand the world." Two items concerned fact acquisition as a goal: (a) "I try to learn science vocabulary and definitions," and (b) "I try to memorize science facts and information." Three items concerned ego-social goals: (a) "I want the others to think I am smart," (b) "It is important to me to do better than other students," and (c) "It is important to me that the teacher thinks I do a good job" (Meece, Blumenfeld, & Hoyle, 1988). Finally, three items concerned work-avoidant goals: (a) "I want to do as little as possible," (b) "I just want to do what I am supposed to do and get it done," and (c) "I want to do things as easily as possible so I do not have to work very hard" (Meece, Blumenfeld, & Hoyle, 1988).

Finally, the interviewers asked the students to select three primary, personal goals from the list and give explanations for their responses. The data were analyzed using ratings and analyses of verbal reports to identify the most salient goals in science class with each student.

Attitudes Toward Science

Students' attitudes toward science involved their interest and enjoyment in learning science. Each of the 12 target students' attitudes was examined using a semistructured interview and a self-report questionnaire prior to and after instruction of the unit. First, the interviewers probed students about their general feelings about science (e.g., What is your favorite subject in school? How do you like science?). Then, the interviewers asked the students to complete an eight-item instrument concerning their interest and enjoyment in learning science on a 4-point scale (4 = strongly agree, 1 = strongly disagree). These items were selected from the Attitudes Toward Science Survey developed for

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the National Assessment of Educational Progress (Hueftle, Rakow, & Welch, 1983; Mullis & Jenkins, 1988). Finally, the interviewers asked the students to explain their responses. The data were analyzed using ratings and analyses of verbal reports.

Results

The results indicated a clear pattern of task engagement for each student over the period of instruction. Four major patterns of task engagement emerged among the 12 students in the study. These patterns indicated different goals and levels of task engagement while the students worked in science classrooms. Further, each pattern of students' task engagement was related to their: (a) science knowledge and achievement, (b) expressed goals in science class, and (c) expressed attitudes toward science, respectively. Thus, the four patterns indicated differences in students' task engagement and various reasons for such differences. The results are summarized in Table 2.

This article uses four case studies of students to illustrate each pattern of task engagement and related factors. The remaining students in the study shared similar characteristics, despite some minor differences, with one of these cases for each pattern. As presented in Table 2, the students from the two classrooms (designated by Teachers A and B) were equally represented across the four patterns.

Case 1 0ason): Intrinsically Motivated to Learn Science

Jason demonstrated self-initiated cognitive engagement as well as behavioral engagement in most task situations. On his own initiative, he actively tried to construct scientific knowledge. Further, he seemed to be motivated intrinsically to learn science (Harter, 1981; Lepper & Hodell, 1989; Ryan, Connell, & Deci, 1985), as he found science learning interesting and enjoyable (high frequency of Level 1 task engagement in Table 1).

Jason demonstrated his intrinsic motivation to learn science in various ways. First, Jason was inquisitive about explanations for natural phenomena. For instance, when the teacher explained to the class that evaporation can occur without heating—which conflicts with a prevalent misconception that evaporation requires a heat source—Jason asked the teacher in class: "Can it [water] evaporate when it's below freezing?" In addition, Jason spontaneously tried to make connections between his classroom learning and personal experiences. For instance, when the teacher was explaining that every substance has its own freezing or melting temperature, Jason urged the teacher to explain his question from the previous day: "I asked you a question yesterday and you said you'd know by the end of the day. If you put whiskey in a freezer, why doesn't it freeze?" Jason was persistent in getting answers from the teacher to satisfy his curiosity.

Jason showed enjoyment and interest in learning science. For example, the class engaged in an experiment on "dancing dimes," in which students warmed with their hands a cold bottle with a dime in the opening and observed the dime rattling (i.e., thermal expansion). Noticing the dime starting to rattle,

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Jason talked to himself, "This is neat! I think there is a lot of pressure in it [the bottle]." When asked by the observer to explain the cause of the phenomenon, Jason responded, "The heat from our hands. If it is the room temperature, probably it wouldn't work." While the lesson stressed the connection between heat and molecular motion, Jason expanded his thinking to incorporate pressure and temperate differences.

Knowledge and achievement. Prior to instruction of the unit, Jason had some understanding of kinetic molecular theory (6 scientific conceptions, 6 mixed responses, and 7 noncanonical conceptions). Over the period of instruction, Jason demonstrated consistent success in achieving scientific understanding. When instruction was completed, he successfully developed scientific understanding of kinetic molecular theory (18 scientific conceptions and 1 mixed response). Further, he spontaneously gave elaborate, coherent explanations without being probed by the interviewer. For example, when asked to explain boiling, Jason expanded the question by explaining how boiling, evaporation, and condensation are all related:

Jason: The molecules—well, the heat from the hot plate is heating up the water, and it's making the molecules move faster and they move farther apart, lose attraction. And the molecules, when they move faster, they rise and escape from the surface of the water and evaporate. And when the water vapor hits the cold air, it condenses into water droplets and goes into steam.

Goals. Prior to instruction of the unit, Jason expressed the goal "to use science to understand the world" as his first priority in science class. Jason also had a conception of the nature of science and science learning as useful for explaining natural phenomena:

Jason: Every move you make, like if I just hold this pencil, there is an explanation why I could put the pencil on there. . . there's a reason for it . . . . There is always somewhere, there's science. And science, you know, explains things.

At the conclusion of instruction, Jason emphasized the goal of understanding more strongly than prior to instruction. He commented that "to use science to understand the world" and "to make sense of scientifically correct ideas" were his top two priorities:

Jason: Because that is mainly why I'm in science, just to use science to understand the world, and science stands for everything around us and everything. I think they [the two goals] would almost make a tie, because you have to know correct science and to use science to understand the world.

Further, Jason developed a more definite conception of science and science learning as a way to understand and explain the world around him:

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Table 2 Task Engagement and Related Factors Before, During, and After

Task engagement Knowledge & achievement

Level of Goal task engagement Before During Aft

Pattern 1: Intrinsically motivated to learn science

Scientific Self-initiated understanding cognitive with interest engagement

(Level 1)

Cases: Ken (Teacher A) Jason (Teacher B)

Pattern 2: Motivated to learn science

Scientific Cognitive Little Overall Ove understanding engagement knowledge success succ

(Level 2)

Cases: Sara (Teacher A) Dan (Teacher A) Ann (Teacher B) Maria (Teacher B)

Some Consistent Succ knowledge success



Pattern 3- Task avoidance

Task avoidance

Cases: Lin (Teacher A) Thea (Teacher A) Kim (Teacher B) Sean (Teacher B)

Failure in engagement (Level 6)

Little knowledge

Overall failure

Ove failu

Pattern 4; Active task resistance

Task Disruption resistance (Level 7)

Cases: Nora (Teacher B)

Little knowledge

Consistent failure

Ove failu

Note. One student (Neil, who was with Teacher A) was an exception. The pattern of his task engage 3. In some situations, he demonstrated keen interest and initiative in task engagement (like Pattern and uninvolved (like Pattern 3). He seemed to engage in classroom tasks to satisfy his personal intere sistent across task situations.



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Jason: Earlier I might have counted vocabulary and facts and memorizing facts as a part of using science to understand the world. I don't know. They are different.

/: Does that surprise you? Jason: That does surprise me.

Attitudes. Jason expressed positive attitudes toward science prior to instruction in the unit: "You know science is interesting, to learn a bunch of things about science. I think it's just interesting." After instruction of the unit, Jason expressed more positive attitudes:

Jason: Well, in September, I wasn't in that much of science and I didn't have a lot of interest in it. And now it's January and I've gained an interest in science truthfully.

/.- Why do you think your interest has changed? Jason: Because I've learned a lot more than in September about science.

I got different ideas, explanations, and I've got, I like challenging work.

Case 2 (Sara): Motivated to Learn Science

Sara demonstrated cognitive engagement as well as behavioral engagement with the goal of understanding science. Compared to Jason (Case 1), however, Sara rarely demonstrated evidence of self-initiated cognitive engagement. Instead, her cognitive engagement was confined to the lesson content actually being presented or the class requirements assigned by the teacher (high frequency of Level 2 task engagement in Table 1).

With the support of the curriculum unit and the teacher, Sara displayed various strategies to enhance her scientific understanding. She was among the first to volunteer explanations during class discussions. When confused or faced with learning difficulties, Sara asked the teacher for clarification or assistance. Sara followed the teacher's directions and completed writing explanations in her activity book before class discussions started, instead of waiting for other students to give their answers first. The following examples illustrate how Sara progressed in her understanding of the scientific conception that substances consist of molecules with only empty space between them, as instruction in the unit continued:

Sara: There is water around water molecules.... There is nothing between molecules because molecules are all bunched and close together. (Lesson Cluster 1 on three states of water)

Sara: There is air in between t h e m . . . . Well, something is in between them. There is space between them.. . Air molecules. No, air without molecules... . There is space between the molecules. So, it's really air space. (Lesson Cluster 3 on molecular composition of air)

Sara: There is just space, nothing between the molecules [of a i r ] . . . . It is emply. (Lesson Cluster 4 on compression/expansion of air)

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Knowledge and achievement.When instruction in the unit started, Sara had little scientific knowledge about matter and molecules (noncanonical conceptions for all 19 issues). As instruction continued, Sara demonstrated overall success in achieving scientific understanding, with some occasions of failure. Sara was aware of how she resolved her learning difficulties and came to understand scientific conceptions with the help of the teacher or the textbook:

/.• Was the activity difficult yesterday? Sara: Kind of, kind of hard for me to understand until he [the teacher]

really explained it. /.- Can you understand it now? Sara: Yeah. When you understand it, it is simple because you know

exactly what happens.

Upon completion of instruction, Sara demonstrated adequate scientific understanding of kinetic molecular theory (18 scientific conceptions and 1 mixed response). Although successful, her explanations were not as spontaneous or elaborate as those given by Jason (Case 1). With several complicated tasks involving changes of states of matter (i.e., freezing, melting, evaporation, boiling, and condensation), Sara needed the support of probing questions by the interviewer to produce complete explanations.

Goals. Before instruction, Sara rated the goal, "to use science to understand the world," after ego-social goals as her primary concerns in science class. She expressed a vague recognition of the value of science as having something to do with the world:

Sara: If you didn't have science, you wouldn't know probably just as much about trees and nature in science.... Science is important because there wouldn't be like nature, and there wouldn't be trees and stuff like that because it helps me live.

After completion of instruction, Sara emphasized the goal of understanding as her first priortiy:

Sara: Because I just feel that it's more important than others [goals] because I'd like to learn more about science than to please my teacher or parents, or to get good grades, or whatever I said before. That's what science is.

Attitudes. Sara expressed positive attitudes toward science prior to instruction. After instruction of the unit, not only did she maintain positive attitudes, she also enjoyed expanding her scientific knowledge: "It's kind of fun to learn about the world, you know, how it works and stuff, 'cause before I didn't know about molecules, I didn't understand it, and it was fun to learn."

Case 3 (Kim): Task Avoidance

Kim was often inattentive or uninvolved in class activities. Further, she avoided engaging in scientific activities in class, even when provided with opportunities

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by the teacher or her peers (high frequency of Levels 5 and 6 task engagement in Table 1).

Kim was a quiet and reserved student; she used various strategies to minimize her effort in completing classroom work. This pattern is illustrated in the following example. While students were working in small groups on a question about evaporation in the activity book, Kim sat quietly with an empty gaze. Suddenly, Kim started talking to a female student in the group. Kim said, "Do you have a black skirt that she can borrow?" (for Kim's friend to attend a school event). The female student responded to Kim, "Come on! We are thinking about science today. Answer the question." Kim stopped talking and looked around her peers or the room. When a male student in the group wrote down an answer in his activity book, Kim looked at his answer and said, "I will put it down. I like it. . . . What are you writing?" Kim copied his answer, even though the male student protested, "We are not supposed to copy." When later asked by the observer, Kim responded that the answer made sense to her, although she could not give an explanation in her own words.

The example above indicated several characteristics of Kim's task engagement. First, she was generally unengaged academically and socially. When she occasionally interacted with her peers, these interactions involved social matters rather than academic issues. Second, her participation in class activities was minimal, even when she was urged by the teacher and by her peers. Third, Kim avoided thinking about science, copying another student's answer, instead of trying to make sense of what was being taught. Finally, she was passive in task engagement; she did not seek help or even avoided help from the teacher and her peers.

Kim generally seemed to be indifferent to learning science in class. During class discussions, Kim often had an empty gaze, looked around the room, focused outside the window, or played with things. Even when the teacher instructed the students to complete the questions in the activity book before engaging in class discussions, Kim usually waited until class discussion started and wrote down answers given by other students. Kim also left some questions in the activity book unanswered.

Knowledge and achievement. Kim began the unit with little scientific knowledge (1 scientific conception, 2 mixed responses, and 16 noncanonical responses), and she generally failed to achieve scientific understanding over the course of instruction. When the unit was completed, Kim's responses during the clinical interview showed relatively little progress (2 scientific conceptions, 7 mixed responses, and 10 noncanonical responses). She maintained many of her misconceptions and failed to give scientific explanations. Further, her explanations were often minimal, and she was unable to elaborate. For example, the interviewer asked her to explain how sugar dissolved in water:

/.- OK. And then what happens? You said something about the water molecules hitting the sugar. Is that right?

Kim: Yeah. /.- OK. Can you tell me more about that?

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Kim: No. /.- So if the water molecules hit the sugar, what happens then? Kim: I don't know.

Goals. Kim expressed all three ego-social goals as her priority in science class. In contrast, Kim did not rate understanding as one of her primary goals. In fact, she gave the lowest rating to the goal "to make sense of scientifically correct ideas" because she felt she was not competent in learning science:

Kim: Because all the work ain't going to be correct. It might be OK, but it isn't all going to be correct all of the time.... Because I know that I ain't better than some of the students in my class. So you can't put 5 [from the scale] when you know that you're not better than some other students.

Further, Kim showed little insight into adults' reasons for valuing science and considering science learning to be important:

/.- Why do you study science? Kim.- So that when you go on next year, so that the teacher, they will

teach it right over mostly. So when you go to the seventh grade next year, you will know more about what they gonna teach.

When instruction was completed, Kim commented that her ideas about science remained "pretty much the same" as those in the beginning of the year.

Attitudes. Kim reported positive attitudes toward science prior to instruction: "Because it [science] helps you learn and I like doing experiments and stuff." After instruction, Kim still expressed positive attitudes.

Case 4 (Nora): Active Task Resistance

Nora was not engaged in classroom tasks either behaviorally or cognitively. Instead, she actively resisted engaging in classroom tasks. Further, she often displayed disruptive behavior and disciplinary problems in class (high frequency of Levels 6 and 7 task engagement in Table 1).

Nora often resisted participating in class activities. For example, while walking around the room, the teacher passed by Nora and reached to pick up her activity book to read the answer for her in class (as the teacher sometimes did for other students). Nora grabbed her activity book, refused to let the teacher read her answer, and hid her book behind her back. Further, Nora often displayed disruptive or undisciplined behavior. She made noise by yawning or coughing loudly, read her answers in class loudly and quickly, and made faces at the teacher and other students. On several occasions, Nora was told by the teacher to change her seat during class or to stay after class because of her misconduct.

Knowledge and achievement. Nora started the unit on molecules with little scientific knowledge (3 mixed responses and 16 noncanonical responses). Over the period of instruction, she consistently failed to understand scientific

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knowledge. When instruction was completed, Nora demonstrated overall failure (7 scientific conceptions, 6 mixed responses, and 6 noncanonical responses). She maintained many of her misconceptions and had difficulty giving scientific explanations.

Goals. Nora expressed ego-social goals as her first priority and a work-avoidant goal as her second in science class. Although Nora seemed to have some understanding of the nature of science and science learning, she actively denied its importance. In fact, she gave the lowest ratings to the understanding goals "to use science to understand the world" and "to make sense of scientifically correct ideas:"

Nora: I don't like learning about the world because when they talk about different states and stuff, because I don't care and stuff. . . . If I get work done, I don't go back and make sure my ideas are correct. If I get them wrong, then they're wrong. I don't like science.

When instruction was completed, Nora still gave the lowest ratings to both goals:

Nora: Because I don't like to understand the world. I don't like to know about things that go on. I don't like to correct my answers and I don't like to go back and look through things 'cause it's boring and I'd rather do other things.... I hate doing work in science.

Attitudes. Prior to instruction of the unit, Nora reported positive attitudes on the questionnaire. However, her attitudes fluctuated depending on contexts. Nora liked some aspects of science, but she did not like the science class because of her personal conflicts with the teacher.

Nora: I don't like the teacher that much.... I don't really like science class.

/.- Is science ever fun? Nora: Sometimes. /.- Yeah? What parts of science are fun for you? Nora: When we do experiments with models and different kinds of

things.

When instruction of the unit was completed, however, Nora expressed negative attitudes:

Nora: Science is boring. In science, you have to be quiet. /.• Other reasons why science is boring? Nora: The work is boring. /.- Can you tell me why your feelings about science class have

changed? Nora: Because in the beginning, I thought school was fun and that sci

ence was fun, too. But now it's boring. The teacher, you know, I don't know, he's weird.

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Conclusions

This study has led us to reconsider some of the implicit assumptions that have typically been shared by conceptual change and motivation researchers. Within both traditions, researchers have typically regarded academic tasks as defined by teachers and curriculum materials while treating students' task engagement as primarily a quantitative variable: Cognitive, motivational, and affective factors of students were thought to influence their reasons for working and how much effort they put into a particular task. The efforts of the students in this study, however, were qualitatively as well as quantitatively different. Although they were taught by the same teachers using the same curriculum materials, the students understood and experienced the academic tasks differently. In effect, the nature of the tasks themselves was the product of interaction between the students' agendas and understandings and those of the teachers and curriculum materials.

The teachers and the curriculum materials in these classrooms attempted to engage students in academic work that was substantially different from most school work. In particular, they sought to engage students in two kinds of activities: (a) making intellectual connections, that is, comparing students' understanding of the world with scientists' understanding (in this case, matter and phenomena involving changes in matter) and seeking to integrate the two, and (b) using scientific concepts and theories as intellectual tools to interpret and explain the world. These are important intellectual activities; they are essential if students are to understand the nature and the power of scientific knowledge. They are also, however, cognitively complex and culturally embedded activities. It appears, for example, that young children and adults in many oral cultures rarely if ever treat ideas as objects of thought to be consciously manipulated and evaluated (e.g., Egan, 1987; Kuhn, Amsel, & O'Laughlin, 1988).

Thus, meaningful learning of science is not only effortful, it also requires different kinds of reasoning from that normally expected of children in or out of school. Of the four students whose case studies are presented in this article, only Jason gave evidence that he regularly engaged in these kinds of reasoning before the unit began. The class reinforced his identification with the culture of science and the goal of scientific understanding.

The teachers and curriculum materials used a wide variety of strategies to encourage students' engagement in scientific activities and to scaffold successful learning of science. For Sara and students like her, these teaching strategies were successful. In trying to comply with her teacher's expectations, Sara found herself engaged in making intellectual connections and using scientific concepts. She eventually came to value these activities and appreciate scientific understanding.

For Kim and Nora and other students like them, on the other hand, the experience of science class was quite different. Kim and Nora each came to class with personal agendas that left little room for attempting to make intellectual connections or use scientific knowledge. They were not simply lazy or unwilling to work. Nora's resistance to her teacher, for example, arguably took at least as much effort as Jason's and Sara's pursuit of scientific understanding.

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Kim and Nora also realized that, compared to themselves, students like Jason and Sara were more successful in science class, and they were willing to follow their teachers' lead in attaching the label ' 'understanding" to that differential success. There was little evidence, however, that Kim or Nora ever really appreciated what students like Jason and Sara were doing to achieve "understanding" or why Jason and Sara believed that those intellectual activities were worthy of their time and effort. Though they were side by side in the same classrooms, Jason, Sara, Kim, and Nora understood and experienced the activities of the science classroom in very different ways.

Implications Although we cannot make generalizations about science curriculum and instruction from a study that focused on only 12 students in two classrooms (Yin, 1988), the case studies of the students lead us to consider some limitations in theoretical frameworks that have traditionally guided conceptual change research and motivation research. The study also points out some of the practical limitations of science instruction programs and strategies like those used in these two classrooms.

In seeking to understand students' difficulties in learning science and to design instruction that helps students learn successfully, conceptual change researchers have focused on cognitive barriers to scientific understanding: They have sought to understand students' conceptions and implicit theories about the world and how they connect or conflict with canonical scientific theories. In the process, conceptual change researchers have paid less attention to motivational and affective factors, including personal agendas and orientations that students bring with them to science classes. For students like Jason and Sara who came to class with personal agendas compatible with the researchers' goal of understanding science, the focus of conceptual change research seems appropriate: Cognitive barriers really were the most important barriers to their understanding of science. The case studies of Kim and Nora, however, point out important limitations in conceptual change research and in instructional programs based on it. In failing to pay adequate attention to motivational and affective issues, conceptual change research neglected the most important barriers to Kim's and Nora's science learning. Thus, the results of this study pose a challenge for cognitively oriented researchers and curriculum developers: They must develop analytical tools and instructional programs that recognize the importance of students' agendas and commitments, as well as their conceptions and learning processes.

This study also expands the knowledge base of motivation research, which has addressed various motivational and affective concerns in an effort to improve the quality of students' task engagement. One limitation of previous motivation research involves its failure to consider cognitive qualities of classroom work (Blumenfeld, Mergendoller, & Swarthout, 1987). The nature of students' task engagement is a function of curriculum materials and instructional programs as much as the students themselves. For example, the curriculum and instruction in this study seemed to have greatest impact on students like Sara,

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who were willing to expend effort but needed support. Without adequate support, they might have expended their effort for less valued outcomes, as is often the case in conventional classrooms. Thus, the curriculum and instruction provided a classroom context that accounted for the nature of students' task engagement.

Further, previous motivation research does not fully explore the interplay between students' personal agendas and the goals or values of the science curriculum, the teacher, and the school. Each student was faced with the task of reconciling his or her personal agendas with the goals of the curriculum, the teacher, and the school. Further, each student needed to maintain his or her own sense of dignity and self-worth. They engaged in a sustained and often unconscious process of negotiation, identification, or denial in the class (Steele, 1992; Wehlage, 1987, 1991). Some students whose goals were initially close to those of the teachers were successful in achieving this reconciliation. For others, however, the discrepancy was so great that adopting the teachers' goals would threaten their self-worth. These students developed coping strategies that enabled them to pursue personal agendas and protect self-worth while avoiding the worst consequence of school failure. Thus, an important challenge for motivation researchers is to develop deeper and richer analyses of the complex processes that lead toward or away from students' effort within the dynamic inteplay of the curriculum, the teacher, and students in science classrooms.

We wish to conclude with two observations about the implications of this study for science curriculum and instruction. The instructional program used in this study (Berkheimer et al., 1988, 1988b) was based on careful analyses of students' conceptions of matter and molecules; it was innovative in its treatment of science content but largely traditional in its approaches to classroom organization and management. The available evidence indicates that almost all students understood the content of this unit better than students in classes using a more traditional unit (Lee et al., 1993). However, the results of this study suggest two important limitations in this instructional program that will require greater attention for all students to achieve meaningful understanding of science.

The first of these limitations has to do with patterns of communication among students about their scientific reasoning. Although the students in these classrooms worked together during hands-on activities, classroom discussions were dominated by teacher-student communication, and the teachers were the primary evaluators of students' academic work. Thus, students like Kim and Nora were able to "get by," meeting their teachers' minimal standards without being challenged to reconcile their reasoning about science with the quite different reasoning of many of their classmates. The results support many current researchers' proposals to develop approaches to classroom teaching that emphasize collaborative work and sustained communication among students concerning their reasoning about subject-matter content (e.g. Cobb, Wood, Yackel, & McNeal, 1992; Palincsar, Anderson, & David, 1993; Resnick, 1987).

The second limitation in the instructional program concerns its lack of attention to issues of race, culture, and social class. Of the four students described in detail in this article, Jason, Sara, and Kim were white; Nora was Mexican

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American. Of the 12 target students in this study, the six most successful in understanding the science content were all white. Of the six less successful students, two were white, two were African American, and two were Mexican American.

Nora was not articulate about reasons for disliking her teacher, and we saw no evidence of overt discrimination or unfair treatment on the part of the teacher. The persistent pattern of interaction between Nora and her white male teacher might have originated in part from crosscultural miscommunication and misunderstanding (Delpit, 1988; Heath, 1983; Michaels, 1991). Similarly, the larger pattern of results indicates that the instructional program failed to address some critical barriers to scientific understanding for members of traditionally underrepresented groups. The results suggest the need to consider social, cultural, and racial issues in science teaching and learning (Contreras & Lee, 1990; Pugh, 1990; Rosebery, Warren, & Conant, 1990). These issues include the active resistance of some students to the mainstream culture of the scientific community (Ogbu, 1987; Steele, 1986).

In conclusion, distinct patterns of task engagement among the 12 students in two similar classrooms in this study illustrate how difficult it is to help all students learn science with understanding. The results point to complex interactions among cognitive qualities of academic tasks, students' knowledge and achievement, and students' motivational and affective orientations in science classrooms. Further, the results help expand the existing knowledge base for designing curriculum materials and instructional programs that take into consideration the dynamic interplay of students' personal agendas with the goals and values of the science curriculum, the teacher, and the school. Eventually, the success of science teaching may depend on the establishment of a kind of ' 'social bonding" in which both teachers and the curriculum accommodate students' agendas, needs, and sociocultural backgrounds in such a way as to lead the students into identifying the goals of science class as their own.

Notes

This work is sponsored in part by the Institute for Research on Teaching, College of Education, Michigan State University. The Institute for Research on Teaching is funded from a variety of federal, state, and private sources including the United States Department of Education and Michigan State University. This material is based on work supported by the National Science Foundation under Grant No. MDR-855-0336. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author and do not necessarily reflect the position, policy, or endorsement of the funding agencies.

The authors acknowledge the comments of Drs. Glenn Berkheimer, Linda Anderson, and Evelyn Oka of Michigan State University.

References

Ames, C, & Ames, R. (1984). Systems of student and teacher motivation: Toward a qualitative definition. Journal of Educational Psychology, 76, 535-556.

Ames C, & Archer, J. (1988). Achievement goals in the classroom: Student learning strategies and motivation processes. Journal of Educational Psychology, 80, 260-267.

Ames, R., & Ames, C. (1989). Introduction. In C. Ames & R. Ames (Eds.), Research on motivation in education. Vol. 3: Goals and cognitions (pp. 1-10). San Diego: Academic Press.

606




Anderson, C. W., & Roth, K. J. (1989). Teaching meaningful and self-regulated learning of science. In J. Brophy (Ed.), Teaching for meaningful understanding and self-regulated learning (pp. 265-309). Greenwich, CN: JAI Press.

Anderson, C. W., & Smith, E. L. (1987). Teaching science. In V. KoeWer (Ed.), The educator's handbook: A research perspective (pp. 84-111). New York: Longman.

Anderson, L. M., Brubaker, N., Alleman-Brooks, J., & Duffy, G. (1985). A qualitative study of seatwork in first-grade classrooms. The Elementary SchoolJournal, 86(2). 123-139.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

Berkheimer, G. D., Anderson, C. W., & Blakeslee, T. D. (1988a). Using a new model of curriculum development to write a matter and molecules teaching unit (Research Series No. 196). East Lansing, MI: Michigan State University, Institute for Research on Teaching.

Berkheimer, G. D., Anderson, C. W., & Blakeslee, T. D. (1988b). Matter and molecules teacher's guide: Activity book (Occasional Paper No. 122). East Lansing, MI: Michigan State University, Institute for Research on Teaching.

Berkheimer, G. D., Anderson C. W., Lee, O., & Blakeslee, T. D. (1988). Matter and molecules teacher's guide: Science book (Occasional Paper No. 121). East Lansing, MI: Michigan State University, Institute for Research on Teaching.

Berkheimer, G. D., Anderson, C. W., & Spees, S. T. (1990). Using conceptual change research to reason about curriculum (Research Series No. 195). East Lansing, MI: Michigan State University, Institute for Research on Teaching.

Blumenfeld, P. C, & Meece, J. L. (1988). Task factors, teacher behavior, and students' involvement and use of learning strategies in science. The Elementary School fournal, 88(5)y 235-250.

Blumenfeld, P. C, Mergendoller, J. R., & Swarthout, D. W. (1987). Task as a heuristic for understanding student learning and motivation, Journal of Curriculum Studies, 19(2), 135-148.

Brophy, J. (1983). Conceptualizing student motivation. Educational Psychologist, 18, 200-215.

Brophy, J. (1987). Socializing student motivation to learn. In M. L. Maehr & D. A. Kleiber (Eds.), Advances in motivation and achievement: Vol. 1 (pp. 181-210). Greenwich, CT: JAI Press.

Brophy, J. (1989). Synthesis of research on strategies for motivating students to learn. Educational Leadership, 45(2), 40-48.

Brown, A. (1988). Motivation to learn and understand: On taking charge of one's own learning. Cognition and Instruction, 5, 311-321.

Cannon, R. K., Jr., & Simpson, R. D. (1985). Relationships among attitude, motivation, and achievement of ability grouped, seventh-grade life science students. Science Education, 69, 121-138.

Cobb, P., Wood, T., Yackel, E., & McNeal, B. (1992). Characteristics of classroom mathematics traditions: An interactional analysis. American Educational Research fournal, 29(5), 573-604.

Contreras, A., & Lee, O. (1990). Differential treatment of students by middle school science teachers: Unintended cultural bias. Science Education, 25, 433-444.

Corno, L., & Mandinach, E. B. (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 18(2), 88-108.

Corno, L., & Rohrkemper, M. M. (1985). The intrinsic motivation to learn in classrooms. C. Ames & R. Ames (Eds.), Research on motivation in education: Vol. 2. The classroom milieu (pp. 53-90). Orlando, FL: Academic Press.

Covington, M. V., & Omelich, C. L. (1985). Ability and effort valuation among failure-avoiding and failure-accepting students, fournal of Educational Psychology, 77, 446-459.

607



Lee and Anderson

Delpit, L. (1988). The silence dialogue: Power and pedagogy in educating other people's children. Harvard Educational Review, 55(3), 280-296.

Diener, C. I., & Dweck, C. S. (1978). An analysis of learned helplessness: Continuous changes in performance, strategy, and achievement cognitions following failure. Journal of Personality and Social Psychology, 36, 451-462.

Diener, C. I., & Dweck, C. S. (1980). An analysis of learned helplessness II: The processing of success. Journal of Personality and Social Psychology, 39, 940-952.

Doyle, W. (1983). Academic work. Review of Educational Research, 53, 159-199. Doyle, W. (1986). Content representation in teachers' definitions of academic work. Jour

nal of Curriculum Studies, 18, 365-379. Driver, R. (1988). Theory into practice I: A constructivist approach to curriculum develop

ment. In P. Fensham (Ed.), Development and dilemmas in science education (pp. 133-149). Basingstoke, England: Falmer Press.

Dweck, C. S., & Elliott, E. S. (1983). Achievement motivation. In E. M. Hetherington (Ed.), Socialization, personality, and social development (pp. 643-691). New York: Wiley.

Egan, K. (1987). Literacy and the oral foundations of education. Harvard Educational Review, 57(4), 445-472.

Elliott, E. S., & Dweck, C. S. (1988). Goals: An approach to motivation and achievement. Journal of Personality and Social Psychology, 54(1), 5-12.

Fensham, P. J. (1985). Science for all: A reflective essay. Journal of Curriculum Studies, 17(4), 415-435.

Graham, S., & Golan, S. (1991). Motivational influences on cognition: Task involvement, ego involvement, and depth of information processing. Journal of Educational Psychology, 83, 187-194.

Harms, N. C, & Yager, R. E. (1981). What research says to the teacher: Vol. 3- Washington, DC: National Science Teachers' Association.

Harter, S. (1981). A new self-report scale of intrinsic versus extrinsic orientation in the classroom: Motivational components. Developmental Psychology, 3, 300-312.

Heath, S. B. (1983). Ways with words: Language, life and work in communities and classrooms. New York: Cambridge University Press.

Hueftle, S. J., Rakow, S. J., & Welch, W. W. (1983). Images of science: A summary of results from the 1981-82 National Assessment of Science. Minneapolis: Minnesota Research and Evaluation Center, University of Minnesota.

International Association for the Evaluation of Educational Achievement. (1988). Science achievement in seventeen countries: A preliminary report. New York: Pergamon.

James, R. K., & Smith, S. (1985). Alienation of students from science in grades 4-12. Science Education, 69, 39-45.

Kuhn, D., Amsel, E., & O'Loughlin, M. (1988). The development of scientific thinking skills. New York: Academic Press.

Lapointe, A. E., Askew, J. M., & Mead, N. A. (1992). Learning science. Princeton, NJ: Educational Testing Service.

Lee, O., Eichinger, D. C, Anderson, C. W., Berkheimer, G. D., & Blakeslee, T. D. (1993). Changing middle school students' conceptions of matter and molecules. Journal of Research in Science Teaching, 30(3), 249-270.

Lepper, M. R., & Hodell, M. (1989). Intrinsic motivation in the classroom. In C. Ames & R. Ames (Eds.), Research on motivation in education: Vol. 3' Goals and cognitions (pp. 73-105). San Diego, CA: Academic Press.

Maehr, M. L. (1984). Meaning and motivation: Toward a theory of personal investment. In R. Ames & C. Ames (Eds.), Research on motivation in education: Vol. 1. Student motivation (pp. 115-144). Orlando, FL: Academic Press.

Maehr, M. L., & Nicholls, J. G. (1980). Culture and achievement motivation: A second look. In N. Warren (Ed.), Studies in cross-cultural psychology: Vol. 2 (pp. 221-267).

608




New York: Academic Press. Meece, J. L., Blumenfeld, P. C, & Hoyle, R. H. (1988). Student's goal orientations and

cognitive engagement in classroom activities. Journal of Educational Psychology, 80, 514-523.

Michaels, S. (1991). Hearing the connections in children's oral and written discourse. In C. Mitchell and K. Weiler (Eds.), Rewriting literacy: Culture and the discourse of the other (pp. 103-122). New York: Bergin & Garvey.

Mullis, I., & Jenkins, L. (1988). The science report card: Elements of risk and recovery. Trends and achievement based on the 1986 National Assessment. Princeton, NJ: Education Testing Service.

Nicholls, J. G. (1984). Conceptions of ability and achievement motivation: A theory and its implication for education. In S. Paris, G. Olsen, & H. Stevenson (Eds.), Learning and motivation in the classroom (pp. 211-237). Hillsdale, NJ: Lawrence Erlbaum Associates.

Nicholls, J. G., Patashnick, M., & Nolen, S. B. (1985). Adolescents' theories of education. Journal of Educational Psychology, 77, 683-692.

Nickerson, R. S. (1985). Understanding. American Journal of Education, 93(2), 201-239. Nolen, S. B. (1988). Reasons for studying: Motivational orientations and study strategies.

Cognition and Instruction, 5, 269-287. Nussbaum, J., & Novick, S. (1982). Alternative frameworks, conceptual conflict and ac

commodation: Toward a principled teaching strategy. Instructional Science, 11, 183-200.

Ogbu, J. U. (1987). Variability in minority school performance: A problem in search of an explanation. Anthropology and Education Quarterly, 18, 312-334.

Palincsar, A. S., Anderson, C, & David, Y. (1993). Pursuing scientific literacy in the middle grades through collaborative problem solving. Elementary School Journal, 93(5), 643-658.

Pines, A. L., & West, L. H. T. (1986). Conceptual understanding and science learning: An interpretation of research within a source-of-knowledge framework. Science Education, 70, 583-604.

Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33-40.

Pintrich, P. R., Marx, R. W., & Boyle, R. (in press). Conceptual change and student motivation in the classroom context. In A. Pace (Ed.), Beyond prior knowledge: Issues in text processing and conceptual change. Norwood, NJ: Ablex Publishing.

Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66, 211-227.

Pugh, S. (1990). Introducing multicultural science teaching to a secondary school. Secondary School Review, 71, 313-335.

Resnick, L. B. (1987). Learning in school and out. Educational Researcher, 16(9), 13-20. Rosebery, A. A., Warren, B., & Conant, F. B. (1990). Appropriate scientific discourse:

Findings from language minority classrooms. Newton, MA: Bolt, Benarek, and Newman, Inc.

Roth, K. J. (1986). Conceptual change learning and student processing of science texts (Research Series 167). East Lansing, MI: Institute for Research on Teaching, Michigan State University.

Ryan, R. M., Connell, J. P, & Deci, E. L. (1985). A motivational analysis of self-determination and self-regulation in education. In C. Ames & R. Ames (Eds.), Research on motivation in education: Vol. 2. The classroom milieu (pp. 13-51). Orlando, FL: Academic Press.

Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational Psychologist,

609



Lee and Anderson

26(3), 207-232. Simpson, R. D., & Oliver, J. S. (1985). Attitude toward science and achievement motiva

tion profiles of male and female science students in grades six through ten. Science Education, 69, 511-526.

Steele, C. M. (1992). Race and the schooling of black Americans. The Atlantic Monthly, 269(4), 68-78.

Strike, K. A., & Posner, P. J. (1983). On rationality and learning: A reply to West and Pines. Science Education, 67(1), 41-43.

Strike, K. A., & Posner, P. J. (1992). A revisionist theory of conceptual change. In R. A. Duschl & R.J. Hamilton (Eds.), Philosophy of science, cognitive psychology, and educational theory and practice (pp. 147'-176). Albany, NY: State University of New York Press.

Tobin, K. (1986). Student task involvement and achievement in process-oriented science activities. Science Education, 7(9(1), 61-72.

Tobin, K., Butler-Kahle, J., & Fraser, B.J. (1990). Windows into science classrooms: Problems associated with higher-level cognitive learning. Bristol, PA: Falmer Press.

Wehlage, G. (1987). A program model for at-risk high school students. Educational Leadership, 44(6), 70-73.

Wehlage, G. (1991). School reform for at-risk students. Equity and Excellence, 25(1), 15-24.

Weiner, B. (1986). An attribution theory of motivation and emotion. New York: Springer-Verlag.

Wentzel, K. R. (1989). Adolescent classroom goals, standards for performance, and academic achievement: An interactionist perspective, fournal of Educational Psychology, 81, 131-142.

West, L. H. T., & Pines, A. L. (1983). How "rational" is rationality? Science Education, 67(1), 37-39.

White, R. T. (1987, April). The future of research on cognitive structure and conceptual change. Paper presented at the Annual Meeting of the American Educational Research Association, Washington, DC.

White, R., & Gunstone, R. (1992). Probing understanding. Bristol, PA: Falmer Press. Winne, P. H., & Marx, R. W. (1992). Students' and teachers' views of thinking processes

for classroom learning. The Elementary School Journal, 82, 493-518. Yin, R. K. (1989). Case study research: Design and methods. (Applied Social Research

Methods Series, Vol. 5). Newbury Park, CA: Sage Publications.

Received September 14, 1991 Revision received August 10, 1992

Accepted September 28, 1992 Final revision received January 8, 1993

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task engagement and conceptual change in middle school science classrooms

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