motivational patterns observed in sixth-grade science classrooms

JOURNAL OF RESEARCH IN SCIENCE TEACHING VOL. 33, NO. 3, PP. 303-318 (1996)

Motivational Patterns Observed in Sixth-Grade Science Classrooms

Okhee Lee

Department of Teaching and Learning, School of Education, University of Miami, Coral Gables, Florida 33124

Jere Brophy

Department of Teacher Education, College of Education, Michigan State University, East Lansing, Michigan 48824

Abstract

Drawing on theories of student motivation to learn and conceptual change learning in science, this article describes five patterns of student motivation observed in sixth-grade science classrooms: (a) intrinsically motivated to learn science; (b) motivated to learn science; (c) intrinsically motivated but inconsistent; (d) unmotivated and task avoidant; and (e) negatively motivated and task resistant. These motivational patterns were related in theoretically predictable ways with the learning strategies and other behaviors that the students exhibited in the classrooms. The study highlights the value of distinguishing motivation to learn from intrinsic motivation, and of distinguishing general motivational traits from situation-specific motivational states. The study also highlights the importance of considering subject-matter content in classroom motivation. Implications for motivation research and classroom practices are discussed.

Educators interested in subject-matter teaching and learning have emphasized the importance of teaching school subjects for understanding, appreciation, and application of intercon- nected networks of knowledge (Brophy, 1992). Within this context, science educators have stressed the need to teach for conceptual change. These assumptions about optimal curriculum and instruction imply assumptions about students as well. If students are to learn with understanding, and especially if they are to engage in the kind of self-regulated construction of meaning that is implied in the notion of conceptual change, the students must engage in learning activities with certain motivational orientations and respond to them using certain learning strategies. If they operate from undesirable motivational orientations and make undesirable strategy choices, they will not gain the intended benefits from instruction.

In recent years, researchers in both student motivation and conceptual change have stressed the need to integrate learning and cognition with motivation in the classroom. Some have attempted to establish conceptual frameworks for such integration. For instance, Pintrich, Marx, and Boyle (1993) 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). Others have conducted empirical

0 1996 by the National Association for Research in Science Teaching Published by John Wiley & Sons, Inc. CCC 0022-4308/96/030303-16

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research examining the relationship between motivation and learning in science (Anderman & Young, 1994; Lee & Anderson, 1993; Nolen & Haladyna, 1990). Drawing upon concepts from recent theory and research on student motivation and on conceptual change teaching and learning, this study analyzes what is involved in optimal motivational orientations and strategy choices, considers contrasting orientations and choices that are less optimal, and illustrates five patterns observed in an intensive study of sixth-grade students in science classrooms.

Student Motivation to Learn

Brophy (1983, 1987, 1989) outlined a concept of student motivation to learn that integrates issues of motivational operations and learning processes within the context of academic activities in classrooms. He noted that motivation to learn can manifest itself as both a general trait and a situation-specific state:

As a general trait, motivation to learn refers to an enduring disposition to value learning as a worthwhile and satisfying activity, and thus to strive for knowledge and mastery in learning situations. . . . In specific situations, a state of motivation to learn exists when task engagement is guided by the goal or intention of acquiring the knowledge or mastering the skill that the task is designed to teach. (Brophy, 1987, pp. 181-182, original emphasis).

Several aspects of this concept make it particularly applicable to examination of student motivation in classrooms. It emphasizes the importance of situation-specific motivation as dis- tinguished from more general dispositions. Brophy hypothesized that most individuals who display motivation to learn as a general trait are likely to do so because they find learning to be intrinsically rewarding. However, he also noted that the trait of motivation to learn could be manifested by individuals motivated by a duty-bound sense of obligation. In specific situations, both types of individuals would display motivation to learn as a state similar to what others have termed mastery orientation (Dweck, 1986) or task involvement (Nicholls, 1984). Both types of individuals would pursue similar situation-specific learning goals, but the former would do so more out of intrinsic motivation to learn, and the latter would do so more out of a sense of duty or commitment to comply with responsibilities.

Applied to particular situations, the concept distinguishes the state of motivation to learn from intrinsic motivation or interest in the situation (Harter, 1981; Hidi, 1990; Lepper & Hodell, 1989). Considering that most classroom tasks and activities are required rather than optional, the concept of motivation to learn is useful for describing students’ efforts to achieve the goal of content understanding or skill mastery, “whether or not they find a particular task interesting or enjoyable” (Brophy, 1987, p. 182).

The concept of motivation to learn carries implications about students’ goals and strategies during task engagement. The concept’s definition focuses on students’ goals, but it also carries implications about their learning strategies because of the highly cognitive nature of most academic activities. Students who are motivated to learn are likely to activate cognitive and metacognitive strategies for accomplishing such learning, whereas students who are not motivated to learn are likely to content themselves with strategies for meeting accountability pres- sures with the least possible effort (often completing tasks without learning what the tasks are intended to teach).

In summary, student motivation in the classroom is conceived in terms of students’ choice of goals and strategies during task engagement. In particular, the state of motivation to learn

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exists when students engage in classroom tasks with the goal of understanding the content and activate strategies for developing such understanding. Further, the trait or generalized disposition of motivation to learn exists when students routinely seek to accomplish the intended academic goals, either because they enjoy and take satisfaction in learning or because they feel duty-bound to do so.

Learning Science

According to the conceptual change or constructivist perspective, learning with understanding occurs when learners actively construct and transform their own meanings, rather than passively acquire and accumulate knowledge transmitted to them (e.g., Driver, Akoso, Leach, Mortimer, & Scott, 1994; Posner, Strike, Hewson, & Gertzog, 1982; Toulmin, 1972; Vosniadou & Brewer, 1987). Two major components of scientific understanding emerge in this literature: structural (individual) and functional (social) components. This is summarized in the definition of scientific understanding advanced by Anderson and Roth (1989):

The first of these [criteria] is functional: Students should develop knowledge that is useful for the essential functions of describing, explaining, predicting, and controlling the world around us. The second criterion is structural: Students should develop knowledge that is conceptually coherent and integrated with their personal knowledge of the world, as well as being scientifically accurate. (p. 274, original emphasis)

Structural Component

Perhaps the most important issue in human cognition concerns the role of prior knowledge in learning new knowledge. In a congruent situation, the knowledge structure students bring to the classroom can be linked with formal, scientific knowledge (Pines & West, 1986). When students’ prior knowledge is in conflict with scientific knowledge, however, they cannot simply link the two sources of knowledge. Instead, they need to integrate new, scientific knowledge with their incorrect prior knowledge or misconceptions through a complex process of conceptual change. Through conceptual change, students modify or restructure their previous knowledge, or even completely abandon it, and accept new knowledge that appears counterintuitive. Although the process of conceptual change is difficult for many students, the outcome can be rewarding as they develop a more coherent and richer knowledge of science.

Functional Component

Scientific knowledge serves four basic functions: description, explanation, prediction, and control (Anderson, 1987; Toulmin, 1972). The descriptive function involves activities such as labeling, observation, measurement, classification, and description of objects or natural events. The explanatory function derives from students’ desire to explain how the world around them works. The predictive function also has a basis in everyday actions, as students continuously engage in making predictions about the natural and human worlds. Finally, the control function involves students’ need to control natural events or phenomena through experimental work (not necessarily in laboratory settings). Students who seek to understand how the world around them operates engage in these activities, whether or not they are scientifically literate. Scientific knowledge, however, provides them with conceptual and technical tools that produce power and precision that would not otherwise be possible.

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Motivation to Learn Science

Definition

Integrating the theoretical frameworks of motivation to learn and learning science described earlier, we define a state of motivation to learn science when students engage in science tasks with the goal of achieving a better understanding of science and activate strategies for doing so. While engaging in academic tasks in science classrooms, motivated students use cognitive and metacognitive strategies to integrate personal knowledge with scientific knowledge through conceptual change, and apply scientific knowledge to make sense of the world around them.

The state of motivation to learn in specific task situations has long-term significance. From a motivational perspective, when the state of motivation to learn exists consistently over task situations, it stimulates the development of student motivation to learn science as a generalized disposition (Brophy, 1983, 1989). From a learning perspective, motivated students are likely to accomplish meaningful learning of science. Eventually, these students learn how to learn science independently and become self-regulated learners (Anderson & Roth, 1989).

Measure

Students’ motivation to learn science is measured by focusing on the quality of task engagement in science classroom tasks. Brophy (1987) stated that “Measures of student motivation to learn must reflect the quality of student engagement in academic activities” (p. 183. original emphasis). The complexity and difficulty of measuring student engagement in academic tasks has baffled researchers in classroom learning and motivation alike. Newmann (1992, p. 13) proposed that levels of engagement must be estimated or inferred from indirect indicators in terms of behavioral responses (e.g., amount of participation), cognitive processes (e.g., intensity of concentration), and interest (e.g., curiosity or enthusiasm). The quality of task engagement in this study considered three aspects of task engagement: (a) observable, behavioral responses; (b) covert, cognitive responses activated during learning; and (c) intrinsic motivation or interest. These three aspects were not considered to be mutually exclusive or exhaustive.

Behavioral engagement included observable signs of attention or time on a task. Although behavioral indicators have been used as measures of classroom motivation (e.g., Brophy, Rohrkemper, Rashid, & Goldberger, 1983; Tobin, 1986), critics claim that measures of cogni- rive engagement are more valid and precise. They argue that students may be going through the motions of a task without being cognitively engaged in it, so measures of the quality of cognitive processes are needed to distinguish this difference (Anderson, Brubaker, Alleman- Brooks, & Duffy, 1985; Blumenfeld & Meece, 1988; Peterson, Swing, Stark, & Waas, 1984; Wittrock, 1986). In particular, the concept of motivation to learn emphasizes “the quality of students’ cognitive engagement in the activity-the degree to which they approach the activity purposefully and respond to it thoughtfully” (Brophy & Merrick, 1987, p. 11, original emphasis).

The quality of task engagement also involves intrinsic motivation or interest. In this study, intrinsic motivation and interest are used synonymously; as Deci and Ryan (1991) suggested, “intrinsically motivated behaviors are those the person undertakes out of interest” (p. 241). Interest is also closely related to curiosity (see the summary in Tobias, 1994). Key indicators of intrinsic motivation to learn include “initiation” in task engagement (Corn0 & Rohrkemper, 1985), “choice” among alternatives (Ryan, Connell, & Deci, 1985), and “flow” (Csikszent- mihalyi & Nakamura, 1989).


In the present study, a measure of motivation to learn science was established by considering these three aspects of task engagement, specifically in the context of science content (see Method for details). Students who are motivated to learn science display a high quality of task engagement in science classrooms. In terms of behavioral engagement, they pay attention to lessons and are actively involved in class activities. These students also activate cognitive and metacognitive strategies to achieve the goal of understanding science in specific task situations. In addition, students who are intrinsically motivated to learn science demonstrate interest, curiosity, and enjoyment in learning science.

In contrast, students who are not motivated to learn science display a low quality of task engagement in science classrooms. They engage in classroom tasks with alternative goals, rather than the goal of understanding science. Some may try to appear capable while meeting the minimum classroom requirements (i.e., completion of assigned work). Others may try to avoid task engagement, such as mindlessly answering questions or copying others’ answers. In addition to these ego-involvement and task-avoidance goals (e.g., Meece, Blumenfeld, & Hoyle, 1988; Nolen & Haladyna, 1990), still others may actively resist engaging in academic tasks or school activities (Wehlage, 1991).

These distinctions in the level of task engagement were incorporated into a set of guidelines for observing and informally interviewing students. The application of the instrument in two sixth-grade science classrooms resulted in the identification of five distinct patterns of student motivation and strategy use.

Method

Research Setting and Subjects

Curriculum.

The case studies of the two sixth-grade science classrooms were related to a larger project that involved developing curriculum materials and instructional strategies to promote sixth- grade students’ understanding of kinetic molecular theory (Berkheimer, Anderson, & Blakeslee, 1988b; Berkheimer, Anderson, Lee, & Blakeslee, 1988). Curriculum development was guided by a conceptual change approach in science (Berkheimer, Anderson, & Blakeslee, 1988a; Berkhemier, Anderson, & Spees, 1990). The materials were based on extensive investigations into students’ conceptions and misconceptions about aspects of matter and molecules (Lee & Anderson, 1993; Lee, Eichinger, Anderson, Berkheimer, & Blakeslee, 1993). The activities involved students in describing, explaining, making predictions, or attempting to control natural phenomena in various contexts.

The curriculum materials included a science book (student text), an activity book, and accompanying teachers’ guides. The curriculum unit was organized as a series of nine lesson clusters, each consisting of four to six 45-min lessons over the course of 12 weeks. Topics included: (a) the nature of matter; (b) three states of matter; (c) molecular composition of air; (d) expansion and compression of gases; (e) thermal expansion; ( f ) dissolving; (g) melting and freezing; (h) boiling and evaporation; and (i) condensation.

Teachers and Instruction.

The study was conducted in two comparable classrooms from two schools in a midwestern urban district with an ethnically mixed student population. The two teachers were recommended

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as exemplary by their principals and colleagues. They implemented instruction consistent with the curricular goals and followed instructional strategies suggested in the teachers’ guides. To help students learn science through conceptual change, the teachers highlighted common student misconceptions as opposed to scientific conceptions, and tried to help the students recog- nize and resolve conflicts between personal knowledge and scientific knowledge. Using various situations of natural phenomena, the teachers also encouraged their students to apply scientific knowledge to understand and explain these phenomena across diverse contexts.

Four class activities suggested in the teachers’ guides were used extensively in both classrooms: (a) reading and discussing the science book, (b) conducting hands-on experiments, (c) writing ideas and experiments in an activity book, and (d) engaging in class discussions of ideas and results of experiments. In a typical instructional sequence, students were first encouraged to express their prior knowledge about the topic and to compare their ideas with scientific conceptions. Students were then presented with real-world problems, usually through hands-on experiments accompanied by the writing of results and explanations in their activity books. Finally, students engaged in class discussion to present their explanations, exchange ideas, and verify answers. Grades were determined largely by performance on tests, quizzes, and the activity book.

Although it was highly effective, instruction in both classrooms had shortcomings. Two of these were inherent in the social context of classrooms: pacing and accountability. Both teachers kept on schedule to complete the unit as planned and advanced the entire class at the same time, rather than vary the pacing according to students’ needs. Also, the teachers did not hold the students accountable for really thinking about science and not just finishing the assigned work. Even when some students did not complete tasks, the teachers did not closely monitor their performance and provide adequate feedback to enable them to identify and correct learning difficulties.

The two classrooms provided unique contexts for studying student motivation to learn science. There were high expectations and extensive support by the teachers and curriculum materials to help students understand what they were learning according to a conceptual change or constructivist perspective. Although it was highly effective, the instruction in both classrooms was far from ideal. Given these classroom contexts, would students take advantage of the opportunity and become motivated to learn science? (A similar issue was raised by Blumenfeld, 1992, and Pintrich et al., 1993).

Students.

Observation focused on 12 students, 6 from each classroom, who were identified by their teachers as representing three achievement levels (high, medium, and low). The selection was based on an overall assessment of students’ science records (i.e., standardized test scores and elementary science grades) 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 from each achievement level; 7 girls and 5 boys; 8 white, 2 Hispanic, and 2 African-American students.

Data Collection and Analysis

Data collection and analysis were completed by two researchers. Each worked primarily in one classroom, but they regularly compared data sets to check the consistency of data collection procedures as a reliability check.


Measure.

The measure considered three aspects of task engagement. The first aspect, behavioral engagement, included apparent attention, involvement in class activities, reaction to distraction. persistence in task engagement, and the nature of interactions with others. The second aspect, cognitive engagement, included students’ awareness of learning difficulty or confusion, recogni- tion of misconceptions or conceptual conflicts, effort to relate the science task to prior knowledge or a similar task done before, and attempt to apply science knowledge in describing and explaining the phenomenon in the task. Finally, interest or intrinsic motivation indicated enthusiasm in learning science, self-initiation in task engagement without solicitation from the teacher, choice in academic activities among alternatives, interest or curiosity in learning beyond the lesson content, and engagement in tasks beyond the requirements or expectations of the classroom.

Data Collection.

Guidelines were developed for systematic classroom observations and informal interviews with target students to assess the quality of task engagement in a specific task situation. Using the guidelines, the observers focused on one target student at a time during each of the four major class activities: reading, writing, experimentation, and class discussion. When using these guidelines to develop case study materials, the two researchers would not only observe students but interview them informally about their learning processes, understanding of science content, and interest or curiosity in specific task situations. The questions concerning students’ understanding of science content had been formulated based on lesson objectives in the cumcu- lum guidelines. Classroom observations were recorded in field notes, and informal interviews were audiotaped and transcribed.

Thus, an observation episode contained detailed descriptions of one target student’s behavioral responses, cognitive processes, and interest during a designated class activity. Since each activity typically lasted 10-20 min, one lesson produced three or four episodes. To keep the influences of class activities on motivation consistent among the 12 students, they were observed across the four activities with equivalent frequency and duration. Also, to keep the influences of science content consistent, the students were observed at least once during each of the nine lesson clusters. Eventually, 40 lessons were observed in the two classrooms, resulting in a total of 130 observation episodes (10-12 for each target student).

Data Analysis.

To produce scores representing the quality of students’ task engagement, the three aspects of behavior were combined via a coding system (Table 1). The observation episode was used as the unit of analysis. After a thorough reading of each observation episode, coders assigned one of seven levels of task engagement, ranging from the highest (Level 1) to the lowest level (Level 7). For example, a rating of 2 (Level 2 task engagement) was assigned to an observation episode in which a target student demonstrated cognitive engagement (Yes) and behavioral engagement (Yes) but not interest or intrinsic motivation (No). The agreement between the two coders was 81 %. Disagreements were resolved through discussion.

Results

Although students’ levels of task engagement varied across situations, each student demonstrated a clear overall pattern of motivation. Table 2 presents the ratings of the level of task

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Table I Coding System for Data Analysis: Level of Task Engagement

Cognitive Behavioral Rating Interest engagement engagement

Level 1 Yes Yes Yes Level 2 No Yes Yes Level 3 No Ambiguity Yes Level 4 No No Yes Level 5 No Ambiguity No Level 6 No No No Level 7 No No No and disruption

Nore. The descriptor ambiguiry in Levels 3 and 5 indicates situations when the assessment of cognitive engagement was not clear because of insufficient evidence. This problem was often due to 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 et al., 1985; Tobin, 1986).

engagement for each student, including the number of observation episodes and the mode, mean, and standard deviation of rating scores. The students from the two classrooms were designated by Teacher A or B.

As shown in Table 2, five patterns of classroom motivation were identified, and the 12 students from the two classrooms were equally represented across the patterns. A case of each pattern is presented to illustrate the different goals and levels of task engagement across these patterns (Table 3).

Pattern I : Intrinsically Motivated to Learn Science

Jason was one of two students classified as demonstrating intrinsic motivation to learn science across task situations. Often on his own initiative, he actively tried to construct scientific knowledge (high frequency of Level 1 task engagement in Table 2).

Jason was inquisitive and curious about explaining natural phenomena. In his effort to explain novel events that had not been discussed in class, he expanded the lesson content to relate it to his prior knowledge or personal experience. For instance, students engaged in hands- on experimentation to test the presence of carbon dioxide in exhaled air in human breath versus normal air in the environment. The students breathed into bromothymol blue solution and observed the solution changing from blue into yellow (as a result of the increased amount of carbon dioxide). After the experiment, Jason asked the teacher whether it would be possible to change yellow back to the original blue. This question extended the lesson content, leading to class discussion about the molecular bondage between a liquid (solution) and a gas (carbon dioxide). Jason applied the activity to the idea of plants absorbing carbon dioxide and emitting oxygen. He told the observer that he would leave the yellow solution under a plant in the room. He stayed for a couple of minutes after the class period to test his theory of the rate of color change.


Table 2 Ratings of the Level of Task Engagement (Number of observation episodes, and mode, meun, and standard deviation of rating scores)

Student n Mode(s) M SD

Pattern I Ken (Teacher A) Jason (Teacher B)

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

Neil (Teacher A)

Lin (Tcacher A) Thea (Teacher A) Kim (Teacher B) Sean (Teacher B)

Nora (Teacher B)

Pattern 2

Pattern 3

Pattern 4

Pattern 5

10 10

10

I I I I I I 12

I I

Level 1 Level I

Level 2 Level 2 Level 2 Level 2

Levels I and 6

Level 6 Levels 4 and 6 Levels 5 and 6 Levels 4 and 6

Levels 6 and 7

1.52 I .27

2.63 2.51 2.28 2.56

2.64

4.70 4.63 4.38 4.41

5.77

.53

.40

.81

.69

.60

.82

2.17

I .37 1.80 1.62 1.83

I S O

Jason usually paid close attention to the class content and pointed out mistakes, ambi- guities, or places for further elaboration in the curriculum unit or the teacher’s explanations. Jason sometimes posed challenging questions to the teacher and engaged in debates until he convinced the teacher of his ideas or was convinced by the teacher’s explanations. Jason contributed to class discussions by proposing alternative or novel ideas, and demonstrated leadership in small-group work. Because he was frequently at a pace ahead of the rest of the class, he used this extra time to help other students, check and elaborate his answers in the activity book, or pursue his interest and curiosity in the activity.

Jason expanded class activities to connect to his science experiences outside class. For instance, students were engaged in hands-on experimentation on dissolving, using sugar as an example. Jason commented in class that he was currently growing sugar crystals on a paper clip at home after having watched the activity on a television science program.

Partern 2: Motivated to Learn Science

Sara was one of four students who demonstrated cognitive engagement with the goal of understanding science, but without the evidence of intrinsic motivation or self-initiation seen in Pattern 1 students. Sara’s cognitive engagement was confined to the lesson content or the class requirements assigned by the teacher (high frequency of Level 2 task engagement in Table 2).

With the support of the curriculum unit and the teacher, Sara displayed various strategies to enhance her scientific understanding. In the process of undergoing conceptual change, Sara recognized conceptual conflicts and tried to modify misconceptions into scientific conceptions. When confused or faced with learning difficulties, she expressed to the teacher in class, “I don’t understand what you just said,” and asked for clarification or further explanation. The teacher, in turn, provided feedback to correct her confusions, assist with learning difficulties, elaborate on her answers, or promote further understanding.

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Table 3 Patterns of Student Motivation in Science Classrooms

Motivational patterns Goal Level of task engagement

Pattern 1 Intrinsically motivated Scientific understanding Interest and cognitive en-

to learn science with interest gagement (Level I ) Pattern 2

Motivated to learn science

Pattern 3 Intrinsically motivated,

but inconsistent

Pattern 4 Not motivated to learn

science Pattern 5

Negatively motivated

Scientific understanding Cognitive engagement (Level 2)

Satisfaction of interest Interest or failure in engagement (Levels 1 and 6)

Task avoidance Failure in engagement (Level 6)

Task resistance Disruption (Level 7)

For instance, a question in the activity book asked students to explain in molecular terms how ice melts. Sara completed her explanation in her activity book before class discussion started, instead of waiting for other students to give their answers first. During class discussion, Sara was among the first to raise her hand and volunteer her answer in class. She provided an explanation in terms of molecular arrangement and movement during changes of state: “The molecules are moving farther apart and vibrating in their place, and then they move into another pattern.” The teacher probed her reasoning, “Moving farther apart and vibrating in place sound opposite to me. In which state do molecules vibrate?” Sara did not respond to the teacher and appeared confused. Later she revised the answer: “The molecules are moving farther apart and moving faster, and then they move into another pattern. Molecules break out of their rigid puttern when ice changes into water” (italics indicates changes in the revised answer).

Sara was attentive in class and actively involved in class activities. She sometimes used a pencil or her finger to point in the textbook as she followed reading aloud in class. She reread sections of the textbook which the class had just finished reading aloud. Sara closely followed the teacher’s directions and completed tasks on time or slightly ahead of the rest of the class.

Pattern 3: Intrinsically Motivated, but Inconsistent

Neil was the only student who fit this motivational pattern. He sometimes engaged in classroom tasks to satisfy his personal interest in learning science, but his interest was inconsistent. In some situations, he demonstrated keen interest and initiative; in other situations, he was inattentive and uninvolved. The quality of Neil’s task engagement depended on his interest, rather than on the goal of understanding science (combination of Levels 1 and 6 in Table 2).

Neil had no hesitation in expressing his opinions of tasks or activities. He told the observer that he liked the topic of evaporation: “The water evaporation, that was fun. Like when we turn the water into water vapor and back into the water again.” He also told the observer why he liked the experiment on condensation: “1 think this is my favorite one . . . because it is fun, like trying to build the solar thing [a solar still].” In contrast, he noted that some tasks or activities


were “not fun.” He told the observer, “I like the experiment, but I don’t like writing in the [activity] book.” Despite the teacher’s continual reminders to the class to complete the questions, Neil left some portions of his activity book unfinished.

Pattern 4: Unmotivated to Learn Science-Task Avoidance

Kim was one of four students who were often inattentive or uninvolved. Further, she avoided engaging in scientific activities, even when provided with opportunities by the teacher or her peers (high frequency of Level 6 in Table 2).

Kim was a quiet and reserved student who used various strategies to minimize her effort in completing work. Even after instruction, she displayed basic misconceptions and relied on commonsense explanations. For instance, a question in the activity book was, “Will a towel dry out faster in humid air or in dry air? Explain why.” By this point, the class had discussed water vapor and evaporation on several occasions. Kim wrote her answer in the activity book: “Dry air, ’cause there won’t be no more humid air to get on the towel.” The observer (0) probed her response:

0: We were talking about evaporation in your class today. What do you mean when we say the air is humid?

Kim: We got a lot of water in it, in the air.

Kim: It means, uh, it’s changing to the air. . . . Water will break up, water will go into the air, change into 0: When you use the word evaporate, what do you mean by that?

the air. 0: So it will change into the air?

0: So, water will become air? Is that what you mean? Kim: Yeah.

Kim: Yeah.

Kim was often unengaged academically and socially. She rarely volunteered to give her explanations in class discussion. When called on by the teacher to encourage her participation, Kim made feeble attempts or responded, “I don’t know.” When she occasionally interacted with her peers in small-group work, these interactions were social rather than academic. Kim readily accepted other students’ ideas and copied their answers, instead of trying to make sense of what was being taught.

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

Pattern 5: Negatively Motivated-Task Resistance

Nora was the only student who fit this pattern. She was not engaged in classroom tasks either behaviorally or cognitively. Further, she actively resisted engaging in these tasks and often displayed disruptive behavior (high frequency of Level 7).

Nora was often inattentive in class and avoided task engagement. For instance, when called on by the teacher during class discussion to give her answer about dissolving sugar, Nora provided an elaborate, scientific explanation. It turned out, however, that she copied the answer from the textbook. On two other occasions, when called on by the teacher she gave answers for

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questions that had already been discussed. She started reading her answer in her activity book, then stopped and asked her neighbor, “Which question am I supposed to answer?’

Nora actively resisted participating in class activities. For example, when the teacher was explaining water cycle in class, one girl (Maria of Pattern 2 motivation) expressed confusion and asked the teacher for clarification. As the teacher tried to help Maria with her learning difficulty, Nora looked at Maria and sarcastically commented, “Just believe it, Maria.” On another occasion, while walking around the room, the teacher passed by Nora and reached to pick up her activity book to read her answer (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.

Nora displayed disruptive behavior in class. She often made noise by yawning or coughing loudly, read her answers loudly and quickly, and made faces at other students. She even made faces at the teacher behind his back while he was writing on the board. On several occasions, Nora was told to change her seat or to stay after class because of her misconduct.

In summary, students exhibiting different patterns of motivation engaged in science tasks with different goals and levels of task engagement. The students of Patterns 1 and 2 seemed motivated to learn science, although they differed in terms of the presence or absence of intrinsic motivation. Other students settled for outcomes short of understanding, such as satisfying personal interests that were inconsistent across situations (Pattern 3), avoiding engagement in classroom tasks (Pattern 4), or actively resisting task engagement (Pattern 5).

Discussion and Implications

Motivation research has examined an array of cognitive processes in classroom settings, including issues of motivational operations, learning processes, and the demands of academic tasks. Because student motivation exists within the context of subject-matter content, it is important to consider the nature of subject-matter learning when conceptualizing and measuring classroom motivation. This was done in the present case studies of middle-school science classrooms. Five patterns of motivation emerged, indicating different goals and levels of task engagement.

Students of both Patterns 1 and 2 displayed a generalized disposition toward motivation to learn science, although with different orientations. Pattern 1 students were intrinsically motivated to learn science. In contrast, Pattern 2 students did not demonstrate intrinsic interest or enjoyment; instead, they seemed motivated by a duty-bound sense of obligation or commitment to understanding academic content and mastering skills (Brophy, 1987, 1989).

The distinction between motivation to learn and intrinsic motivation was further noted between Patterns 2 and 3 (Brophy, 1987, 1989; Ryan et al., 1985). Motivation to learn does not necessarily imply intrinsic interest in learning the content or enjoyment of the process of learning it (Pattern 2). Likewise, intrinsic motivation does not necessarily involve students’ adoption of the goal of understanding the content and willingness to expand effort to achieve the goal (Pattern 3).

The Pattern 3 student provided evidence that intrinsic motivation can be task specific, rather than generalized across a subject area. This student’s intrinsic motivation varied from task to task even within the same unit on matter and molecules. Motivation research often conceives of intrinsic motivation as a generalized disposition or trait in a subject area (Eccles et al., 1989; Gottfried, 1985) or in the classroom (Harter, 1981). However, the results suggest that intrinsic motivation is often a situation-specific state, rather than a generalized disposition or trait.

In combination, Patterns 1, 2, and 3 illustrated the importance of distinguishing between

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motivation to learn and intrinsic motivation, either as a state or as a generalized disposition. The results indicated differences between a generalized disposition of intrinsic motivation to learn science (Pattern l), a generalized disposition of motivation to learn that appeared to stem from a sense of duty to fulfill the student role (Pattern 2), and a situation-specific state of intrinsic motivation that did not include motivation to leam (Pattern 3).

Finally, the findings indicated that some students lacked motivation to leam science. They displayed various patterns, including inconsistency of interest across task situations (Pattern 3), apathy and indifference to learning science (Pattern 4), and disruptive behavior and disciplinary problems (Pattern 5).

The study was based on the conception and measure of classroom motivation that integrated student motivation and learning in science classrooms. Specifically, the conception of motivation to learn science incorporated motivation to learn and conceptual change learning in science. While explicating the conception of motivation to learn science, the study also pointed out differences from related motivation constructs or theories, including goal orientations and intrinsic motivation or interest. Further research is needed to clarify major differences as well as similarities among these constructs (Pintrich, 1992).

The study differed from previous motivation research in a methodologic sense. While previous research usually relied on self-report questionnaires with a large sample of students using quantitative methods, this study employed intensive classroom observations and informal interviews with a small number of students using descriptive, qualitative methods. Although we can only cautiously make generalizations based on this small sample, the case studies seem to be coherent with theoretical constructs (Yin, 1994). Also, the findings provide rich information about different patterns of classroom motivation. Motivation research has recently attempted to broaden its methodologic perspectives, including classroom observations, interviews, narra- tives, and case study methods (see the discussion in Blumenfeld, 1992; Corno, 1992). Further research using different research methods will produce findings to expand and validate the knowledge base of classroom motivation.

The findings suggested the importance of considering subject-matter content in classroom motivation, which has not been well developed in motivation research (Blumenfeld, 1992). Indeed, the definition of motivation to learn depends on the definition of learning in a subject area in the first place. This study conceptualized and operationalized subject-specific motivation, using the case of science. Comparable approaches could be taken in other subject areas based on what is known about learning in their respective areas. This knowledge base will indicate commonalities as well as differences in student motivation across subject areas.

The findings point to the need to consider student motivation within the classroom contexts of curriculum, instruction, and teachers (also see Blumenfeld & Meece, 1988; Blumenfeld, Mergendoller, & Swarthout, 1987; Lee & Anderson, 1993; Marshall, 1987, 1988). Specifically, motivational and affective aspects of a conceptual change or constructivist approach to cumcu- lum development and instructional programs deserve attention (Blumenfeld, 1992; Pintrich et al., 1993). For instance, would Pattern 2 students be motivated to leam without the extent of instructional support by the curriculum and the teachers observed in these two classrooms? Without such support, might they have expended their effort for less valued outcomes, as is often the case in more traditional science classrooms that focus on technical details and vocabu- lary? On the other hand, why did students of Patterns 4 and 5 not take advantage of the opportunities to learn science with understanding in their classrooms? What classroom contexts would be needed to help these students become motivated to learn science?

It is disturbing that half of the 12 students in the study were not motivated to learn science in the two classrooms, even though the curriculum and the teachers provided extensive support

316 LEE AND BROPHY

and high expectations for scientific understanding. Wide variations of motivational patterns in the study suggest that the nature of classroom motivation is a function of many factors, including subject-matter content, curriculum materials, instructional programs, academic tasks, and teachers, as much as students themselves. Thus, instructional programs or teachers address their intervention strategies more specifically in response to the characteristics of individual students.

This article was based on work supported by the National Science Foundation under Grant MDR-855-0336. Any opinions, findings, conclusions, or recommendations in this publication are those of the authors and do not necessarily reflect the position, policy, or endorsement of the funding agency. The authors acknowledge the generous support of Glenn Berkheimer and Charles Anderson, principal investi- gators of the NSF-funded project. This study was presented at the annual meeting of the American Educational Research Association, Chicago, April, 1991. A version of the study by Okhee Lee and Charles W. Anderson appeared in American Educational Research Journal (1993). Any table or portions of tables published herein appear with the permission of the American Educational Research Association.

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Received April 7, 1995 Accepted July 18, 1995

motivational patterns observed in sixth-grade science classrooms

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