探究地球科學學習環境的類型及其對學生學習成效的影響(I)

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探究地球科學學習環境的類型及其對學生學習成效的影響

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計畫類別: 個別型計畫

計畫編號: NSC94-2511-S-003-028-

執行期間: 94 年 08 月 01 日至 95 年 07 月 31 日

執行單位: 國立臺灣師範大學地球科學系(所)

計畫主持人: 張俊彥

共同主持人: 蔡今中

計畫參與人員: 蕭建華、李旻憲

報告類型: 精簡報告

報告附件: 出席國際會議研究心得報告及發表論文

處理方式: 本計畫可公開查詢

中 華 民 國 95 年 5 月 15 日

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Preferred Actual Learning

Environment ‘‘Spaces’’ and Earth

Science Outcomes in Taiwan

CHUN-YEN CHANG

Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan

CHIEN-HUA HSIAO

National Si-Hu Senior High School, Changhua County, Taiwan

JAMES P BARUFALDI

Center for Science and Mathematics Education, The University of Texas at Austin, Austin, TX 78726, USA

Received 27 April 2005; revised 4 October 2005; accepted 18 October 2005

DOI 10.1002/sce.20125

Published online 17 February 2006 in Wiley InterScience (www.interscience.wiley.com).

ABSTRACT: This study examines the possibilities of differential impacts on students’

earth science learning outcomes between different preferred – actual learning environment spaces by using a newly developed ESCLEI (Earth Science Classroom Learning Environ-ment InstruEnviron-ment). The instruEnviron-ment emphasizes three simultaneously important classroom components: content, method, and assessment with both student-centered and teacher-centered scales embedded. Findings suggest that preferred – actual space (PASmatch) between

posttreatment perceptions and pretreatment preferences accounted for a more substantial and statistically significant amount of learning outcomes in terms of students’ attitudes to-ward the subject matter with greater than large effect size, concerning practical significance in the actual earth science classroom. These findings suggest that earth science instruction in the secondary schools should bridge the gap between students’ preferred/perceived learning environment with the aim to enhance their learning outcomes. C 2006 Wiley Periodicals,

Inc. Sci Ed 90:420 – 433, 2006

Correspondence to: Chun-Yen Chang; e-mail: changcy@ntnu.edu.tw

Contract grant sponsor: National Science Council (NSC), Republic of China. Contract grant number: NSC 94-2511-S-003-028.

The data presented, the statements made and the views expressed are solely the responsibility of the authors.

C

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INTRODUCTION

Science teaching is conducted primarily in three types of learning environments: class-room, laboratory, and outdoors (Orion et al., 1997). The importance of Science Classroom Learning Environment (SCLE) has been recognized by many researchers and teachers dur-ing the past two decades. The teachdur-ing standard proposed by the recent science education standards in the USA also describes that

As part of challenging students to take responsibility for their learning, teachers involve them in the design and management of the learning environment. (National Research Council, 1996) The specific criteria for a science learning environment will depend on many factors such as the needs of the students and the characteristics of the science program. (National Research Council, 1996)

Many researchers have used various questionnaires to examine students’ preferences and/or perceptions of SCLE; especially those oriented toward a constructivist teaching ap-proach. For example, the widely used Constructivist Learning Environment Survey (CLES) (Kim, Fisher, & Fraser, 1999; Taylor, Dawson, & Fraser, 1995; Taylor & Fraser, 1991) was developed and utilized to enable educators and researchers to determine whether a particular SCLE was consistent with the constructivist pedagogy, including both of “preferred” and “actual” form. There have been an increasingly large number of questionnaires aimed at assessing students’ perceptions of learning environments (Wong, Young, & Fraser, 1997). Most of them were oriented toward the student-centered or openness features of specific learning environments (Fraser & Rentoul, 1980) with the exception of the “Shared Control” subscale of CLES (Taylor et al., 1995) and the “Teacher Support” subscale of WIHIC (Fraser, McRobbie, & Fisher, 1996). Wierstra et al. (2003) constructed the Inventory of the Per-ceived Study Environment (IPSE), which focused on the student-oriented and reproduction-oriented learning environments in a university setting. However, few learning environment questionnaires were designed to measure students’ simultaneous preferences/perceptions of both teacher-centered and student-centered features of learning environments especially in the earth science classroom. Besides, many questionnaires failed to tap students’ pre-ferred – actual spaces (gaps) in association with student-learning outcomes based on the aforementioned student-centered and teacher-centered framework in the secondary science class.

Educational research has usually compared or contrasted two different types of instruc-tional methods or learning environments; one is tradiinstruc-tional, as the other is sometimes re-ferred to new, modern, or reform (Chang, 2001, 2002; Chang & Barufaldi, 1999; Chang & Mao, 1999). The modern SCLE is mainly categorized as the constructivist learning environ-ment. It adopts the constructive pedagogy and is “constructive oriented,” “interdisciplinary oriented,” or “student centered.” Students in the constructive setting are encouraged to be ac-tively engaged throughout the learning process with a high degree of self-regulation. Teach-ers in this environment adopt an internal control over the learning process of the classroom. On the other hand, the traditional SCLE is frequently labeled as the objectivism/expository learning environment, which holds the objective pedagogy and is “reproduction oriented,” “subject matter oriented,” or “teacher centered.” Students in this setting learn in reproduc-tive/surface approach and memorizing of facts is stressed. Teachers in this setting adopt an external control over the learning process of the classroom. The stereotypical, traditional image is so prevalent among many science teachers and educators that many people con-sider teacher-centered learning (or reproductive learning) and student-centered learning (or constructive learning) as two contrasting poles of one dimension (Wierstra et al., 2003).

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Nevertheless, some previously conducted studies revealed that constructive learning and reproductive learning were not always negatively correlated and sometimes resulted in a positive correlation (Slaats, Lodewijks, & van der Sanden, 1999; Vermetten, Lodewijks, & Vermunt, 1999).

The need to jointly examine student-centered and teacher-centered components of the learning environment is imperative. Kinchin (2004) pointed out that the tension created between objectivism (the objective teacher-centered pedagogy) and constructivism (the constructive and student-centered pedagogy) represents a real classroom issue to influence teaching and learning. The recent TIMSS (Third International Mathematics and Science Study) 2003 International Science Report (Martin et al., 2004) specifically documented that internationally, the three most predominant activities accounting for 57% of class time were teacher lecture (24%), teacher-guided student practice (19%), and students working on problems on their own (14%) in science classes around the world. Therefore, it appears that the modern science classroom learning environment is often a mixture of divergent pedagogies and diverse students’ orientations or preferences (Chang & Tsai, 2005). van Driel, Bulte, and Verloop (2005) investigated chemistry teachers’ educational ideologies and found that many teachers held both subject-matter oriented beliefs and learner-centered beliefs, indicating that the two learning orientations may not only concurrently exist in teachers’ beliefs but also in students’ preferences of SCLE.

In a previous study, the researchers used a newly developed and validated battery named Earth Science Classroom Learning Environment Instrument (ESCLEI) and found that Taiwanese 10th-grade students seemed to prefer both student-centered and teacher-centered learning environment. A few students even preferred a more teacher-centered ESCLE (Lee & Chang, 2004). Consequently, it might be more important to explore the effects of stu-dents’ preferred-actual learning environment spaces on their earth science learning out-comes with both student-centered and teacher-centered scales highlighted and embedded within curriculum content, pedagogy and assessment in the science classroom. More specif-ically, the rationale for the study is largely grounded in Hunt’s seminar review in 1975 that we would gain more coordinated understanding of differential instructional effects in the classroom if person-environment interaction (fit) were accepted or investigated by re-searchers when conducting educational research (Hunt, 1975). Accordingly, this study tries its best to complement current research that usually explores student-learning outcomes on prior assumptions about what “works best” for students in an experimental situation which generally excludes students’ preferences/perceptions of learning environment in the design.

Furthermore, the authors have found in the most recent study in this series that the teacher-centered instructional approach seems to enhance more positive attitudes of less constructivist-oriented learning preferences students, whereas the student-centered method is more beneficial to more constructivist-oriented learning preferences students on their attitudes toward earth science in a computer-assisted learning environment (Chang & Tsai, 2005). It is therefore hypothesized that student’ preferred – actual ESCLE spaces may also account for some inconclusive research results found in student attitudes and/or science achievement between different teaching strategies or learning environments in the science classroom. Limited research has tried to empirically determine the effects of preferred – actual ESCLE spaces on the learning outcomes in the actual earth science classroom with an experimental design. Therefore, this study took further steps to examine possible differ-ential impacts on students’ learning outcomes between different preferred – actual learning environment spaces by using the newly developed ESCLEI. This instrument emphasizes three simultaneously important classroom components: content, method, and assessment, with both student-centered and teacher-centered scales embedded. More specifically, this

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study, conducted through a quasi-experimental research design, rendered the following research question:

What effects will preferred – actual learning environment spaces have on student earth science learning outcomes (including earth science achievement and attitudes toward earth science) in Taiwan?

METHOD Participants

This study sample consisted of 155 students, grade 10, with a mean age of 16 years in four senior high school classrooms in Taiwan. Approximately equal numbers of boys and girls were present in the sample, with a total of 74 males and 81 females. The study took place at the commencement of the spring semester in March 2004. One earth science teacher who taught the above classes at a public suburban senior high school located in the central region of Taiwan was involved in the study. The participating teacher held an equivalent master’s degree in earth science and had 15 years of experience teaching the subject at the time of the experiment. Two of his classes (n= 77) were randomly assigned to a traditional (teacher-centered) learning environment (TLE) group and two other classes (n= 78) to a mixture (both student- and teacher-centered) learning environment (MLE) group. As a result, two classes with a total of 77 students including 41 females and 36 males were taught by the TLE approach while two classes with a total of 78 students including 40 females and 38 males receiving the MLE scheme.

Different Learning Environments

The MLE in this study is a combination of student-centered and teacher-centered learning environment such as combining whole-class presentation, interactive discussions among the teacher and students, cooperative learning, classroom activities, and mastery assessment plan, etc., which were embedded in both student-centered and teacher-centered components in the earth science class. For example, the teacher-centered element emphasized direct guidance and presentation, occasional demonstrations, and clear explanations of important concepts to the students given by the teacher in the earth science classroom/lab. The student-centered component focused on group activities, cooperative learning, and class discussions between the teacher and the students and among students. In contrast, the TLE concentrated on the teacher-centered component in a regular traditional class. However, it is noted that both MLE and TLE groups were taught 2 h a week and received the same earth science content and assignments. Both groups also had the same learning objectives, i.e. topics and principles introduced in the textbook, and had equal opportunities to practice their learning objectives. Besides, weekly observations of the teacher’s classroom teaching confirmed that the participating teacher not only showed similar interest and commitment in employing both methods proficiently but also presented the domain specific content competently in both classroom environments.

Earth Science Classroom Learning Environment Instrument

The earth science classroom learning environment instrument (ESCLE) was designed to quantitatively measure students’ preferences/perceptions of ESCLEI with the focus on student-centered and teacher-centered components, and to explore related issues with re-spect to earth science teaching and learning (Lee & Chang, 2004). The instrument consists

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of two subscales (student-centered and teacher-centered LEs) with both preferred (odd item number) and actual or perceived (even item number) forms pooled. The following question is a sample item from the ESCLEI:

I have the opportunities to help teachers plan the content and activities of the earth science class.

1. My preferred, anticipated situation is. . . (preferred form) 2. My actual experience was. . . (actual form)

There are two noteworthy advantages in terms of this type of design. It not only helps students to discriminate simultaneously between their preferred and actual ESCLE but also reduces confusion and item repetition that might be experienced if responding in two separated questionnaires. There are 15 items in each subscale (student-centered and teacher-centered subscales), and each item includes both the preferred and actual (or perceived) form; therefore, a total of 60 items was included in the ESCLEI. Each item is scored on a 5-point Likert scale [with responses “almost never” (1), “seldom” (2), “sometimes” (3), “often” (4), to “almost always” (5)] in the questionnaire.

The statements of items cover curriculum content, teaching method, and assessment to determine the ESCLE in practice (Lee & Chang, 2004). Students were asked to what extent they agreed that each item described their preferred/perceived ESCLE. Table 1 illustrates descriptions of subscales and number of items for each subscale. The sample items charac-terizing earth science classroom learning environment with content, teaching method and assessment embedded follows:

1. I have the opportunities to help teachers plan the content and activities of the earth science class

TABLE 1

Descriptions of Subscale and Number of Items for Each Scale of the ESCLEI

Scale Name Description of Subscales No. of Items

P

S Extent to which students preferred the

student-centered classroom-learning environment consistent with the constructivist teaching, learning, and assessment

1, 3, 5, 19, 21, 23, 25, 27, 29, 33, 43, 47, 49, 51, 53

T Extent to which students preferred the

teacher-centered classroom-learning environment consistent with traditional teaching, learning, and assessment 7, 9, 11, 13, 15, 17, 31, 35, 37, 39, 41, 45, 55, 57, 59 A

S Extent to which students perceived the

student-centered classroom-learning environment consistent with constructivist teaching, learning, and assessment

2, 4, 6, 20, 22, 24, 26, 28, 30, 34, 44, 48, 50, 52, 54

T Extent to which students perceived the

teacher-centered classroom-learning environment consistent with traditional teaching, learning, and assessment

8, 10, 12, 14, 16, 18, 32, 36, 38, 40, 42, 46, 56, 58, 60 P: preferred, A: actual, S: student centered, T: teacher centered.

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9. Teachers choose useful concepts and knowledge to teach in the earth science class 19. I have the opportunities to do investigations on my own to solve problems in the earth

science class

35. Teachers tell me directly whether my ideas are correct or not

To further understand how ESCLE was preferred and perceived (actual) by the student, the mean scores of students’ responses on the subscales (preferred student-centered, PS; preferred teacher-centered, PT; actual student-centered, AS; and actual teacher-centered, AT) were transformed into the format of (X,Y), i.e., labeled as preferred (PS, PT) and actual (AS, AT), and then plotted on the preferred and actual four quadrant diagram respectively, to display students’ orientations/perceptions of ESCLE as shown in Figure 1. The upper-right quadrant in Figure 1 represents that students prefer (or perceive) both the student-centered and teacher-student-centered ESCLE, labeled as ST. The upper-left quadrant represents that students prefer (or perceive) the teacher-centered ESCLE (T). The lower-right quadrant represents that students prefer (or perceive) the student-centered ESCLE (S), and the lower-left quadrant represents that students prefer (or perceive) neither the student-centered nor the teacher-centered ESCLE (NST). For example, Figure 1a shows that most students preferred the student – centered ESCLE while most perceived their ESCLE as much teacher-centered learning environment as shown in Figure 1b.

The instrument (ESCLEI) was reviewed and validated by a panel of specialists including three university professors and three high school teachers. It was also pilot tested with 167 10th-grade students enrolled in four earth science classes at two senior high schools in April 2003 in Taiwan (Lee & Chang, 2004). The original version of the ESCLEI was further refined after the item analysis techniques based on the results of the pilot study and was again field tested with 1,234 10th-grade students from 34 classes enrolled in a compulsory earth science course at 14 senior high schools in September 2003 in Taiwan. The Cronbach’s alpha of the ESCLEI was estimated to be around 0.88 for the pilot study and was calculated around 0.92 for the field study. The Cronbach’s alpha for each subscale (PS, PT, AS, AT) of the ESCLEI was 0.85, 0.73, 0.80, and 0.69, respectively, in the pilot study and was estimated at 0.87, 0.83, 0.81, and 0.78 in the field study. While the aforementioned

Figure 1. (a) A plot of students’ mean scores on the preferred ESCLEI (n= 155); (b) a plot of students’ mean

scores on the actual ESCLEI (n= 155). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

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Cronbach’s alpha is reported as an index of internal consistency, the mean correlation of a scale with the other scales is used as a convenient index of discriminating validity. The mean correlation of a scale with the other scales ranged from 0.28 to 0.36 for the pilot study (Lee & Chang, 2004) and was estimated between 0.31 and 0.51 for the field study.

Principal components factor analysis of each subscale confirmed the construct valid-ity of the instrument. Most items in each of the subscales had loading on one scale (i.e., student-centered or teacher-centered) both in the pilot study and the field study. Conse-quently, the instrument was found to be a reliable and valid measure for assessing the orientations/perceptions of ESCLE in an actual earth science class. The validity, design, administering, detailed scoring, and analysis of the ESCLEI can also be found in Lee and Chang (2004).

Preferred Actual Spaces (PAS) in Learning Environment

The ESCLEI was administered to the students before and after the intervention to ex-plore and confirm their preferences and perceptions of ESCLE. Participating students’ pretreatment preferences/perceptions of ESCLE were plotted in Figure 1, which shows that most students preferred the student – teacher-centered ESCLE as illustrated in Figure 1a, while most of them actually experienced a teacher-centered ESCLE previously as shown in Figure 1b before the intervention. The results were consistent with our field study with 1,234 10th-grade students, which also suggested that most students prefer both student-centered and teacher-centered ESCLE in the earth science class, yet most of them only experienced teacher-centered learning environment before the intervention.

Unlike conventional “personal-environment fit (PEF)” studies (Diamantes, 2002; Fraser & Fisher, 1983a, 1983b), which generally used the interaction of continuous preferred and actual scores in multiple regression analyses as the measure of PEF, this study derived a two-dimensional numerical Preferred – Actual Spaces (PAS) score for each student by computing the distance between each student’s preferred point (PS, PT) and actual point (AS, AT) plotted in the aforementioned quadrant diagram (see Figures 1a and 1b). Each PAS score was thus calculated by the following equation:

PAS=(PS− AS)2+ (PT − AT)2

The PAS score indicates the distance (gap) between preferred and actual scores on the ESCLEI in a two-dimensional sense. The closer the distance is, the better the classroom environment is matched to the student’s preferences. Accordingly, there are three differ-ent PAS scores for each studdiffer-ent worth to note for the purpose of this study. The pretest PAS (PASpre), the posttest PAS (PASpost), and the matching PAS (PASmatch), which cal-culates the distance between students’ posttest actual point and pretest preferred point. In fact, the PASmatchhas been empirically found more stable than PASpreand PASpost (Hung, 2004), since PASpre only delineates the LE spaces before the intervention, while PASpost will progress or regress on the intervention due to the effects of the intervention on stu-dents’ posttest preferences. Therefore, only PASmatchrepresents the variance between what a student would prefer before the intervention and what the student believes exist in their classroom after the intervention, indicating the extent that the intervention matches the original and unaffected preferences before the intervention.

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Assessments of Earth Science Learning Outcomes

To assess students’ earth science learning outcomes, an inventory, Earth Science Learn-ing Outcomes Inventory (ESLOI), which includes the attitudes toward the earth science inventory (ATESI) (Chang & Mao, 1999) and the earth science achievement test (ESAT) was administered to the participants before and after the intervention. The ESLOI contains two sections with a total of 60 items. The first section is the ATESI (30 items), and the second section is the ESAT with another 30 items.

The attitudes toward earth science inventory (ATESI) consist of 30 items with bipolar disagree/agree statements on a 1 – 5 Likert scale and is intended to investigate students’ attitudes toward earth science with three subscales assessing attitudes toward the earth science subject, attitudes toward learning of earth science, and attitudes toward involvement in earth science activities. Internal reliability was shown to be adequate; the Cronbach’s alpha was estimated to be around 0.90 in previous studies and was calculated at 0.93 with the present sample of this study. The Cronbach’s alpha of the ATESI subscales for attitudes toward the earth science subject, learning earth science, and involvement in earth science activities were 0.82, 0.85, and 0.78, respectively, in previous studies and was estimated at 0.81, 0.84, and 0.81 with present sample of this study.

The earth science achievement test is a 30 question multiple-choice test designed to mea-sure students’ earth science achievement. The researchers compiled the test items selected from a pool of items from the Scholastic Achievement Test (SAT) from 2000 through 2004 based on the content of the earth science textbook used during the class period of interven-tion. The SAT is developed by College Entrance Examination Center (CEEC) of Taiwan and is the most widely used achievement tests for college entrance examination in Taiwan. Thirty test items were selected and equally distributed from unit five through unit seven of the earth science textbook as both the pretest and the posttest. All test items correlate with content from the select units in the textbook.

The content validity of the instruments was reviewed, approved, and verified by a panel of experts including one earth scientist and one earth science teacher of secondary schools. These experts checked the correspondence between textbook content and test items, and confirmed that the substance of the test items is coterminous to important concepts intro-duced in the textbook. Concurrent validity was calculated in a comparison with students’ monthly examination scores and yielded 0.52 and 0.58 for the pretest and posttest, respec-tively. The reliability coefficient was estimated at 0.80 in previous studies and was estimated at 0.65 with present sample of this study, using the Kuder – Richardson formula 20 (KR-20).

Procedure

A nonequivalent control group quasi-experimental design involving four intact classes was adopted (Campbell & Stanley, 1966). Random assignment of individual students to new classes is not likely in the educational system of Taiwan; intact class set is the unit of the experimental design. As alluded to earlier, two intact classes (n= 77) were randomly assigned to the TLE group; two classes (n= 78) were randomly assigned to the MLE group. The ESCLEI and ESLOI were administered to both groups immediately before and after the 3-week intervention.

During the 3-week period, each group received an equal amount of instructional time and was provided with the same instructional materials and assignments. Relevant resources, that is, topics and principles introduced in the TLE and MLE, were made available to students in both groups. The earth science topics taught for the two groups of students during the 3-week period includes the following units in the earth science textbook: Unit Five—Stratigraphy

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and Earth History, Unit Six—Components and Structures of Ocean and Atmosphere, and Unit Seven—Ocean. The following topics are introduced in theses units: sediments, sedi-mentary structures, fossils, geologic time, water cycle, components and structures of ocean and atmosphere, currents and waves, observing ocean, and oceanic geologic geography around Taiwan. Research dealing with classroom-based treatment within a regular school setting usually encounters a variety of difficulties, such as few schools and teachers willing to participate, strict regulations set by the school administration, and random assignment of students to classes. Under these and other limitations, every effort was made to implement different forms of learning environments in the regular earth science classrooms with the aims at deriving reliable PAS scores.

Data Analysis

To understand how the match between preferred and actual learning environment accounts for outcome variance beyond that attributable to the actual learning environment, this study used the following variables as predictors in stepwise multiple regression models to predict students’ learning outcomes (including achievement and attitude):

(1) Pretest scores (2) PASpre (3) PASpost (4) PASmatch

(5) Actual learning environment (including Group, AT, and ST)

Consequently, two regression models using the variables above were constructed to ex-plain the learning outcomes of achievement and attitude separately. For the regression model, both the achievement and attitudes pretest score were included for the regression analysis. Assumptions for the linear regression model were also checked to ensure that they were met in the analysis of regression model for the present study. The measures of each dependent variable were determined to be independent. The histogram of the standardized plot implied no violation of the normality assumption, and the standardized residual plots also indicated that assumptions of the linear regression model are tenable.

To meet contemporary calls for improvement in the interpretation and reporting of quan-titative research in education (Rennie, 1998; Thompson, 1996), this study reports practical significance (effect magnitudes) along with statistical significance test. Measures of associ-ation or how much of the variability in the dependent variable is associated with the variassoci-ation in the independent variable are used for examining proportion of variance such as R2in the regression analysis. Here, the effect size index f2was used since it is more appropriate for multiple regression methods. In accordance with Cohen’s rough categorization (1988, pp. 410 – 414), f2= 0.02 is deemed as a small effect size, f2= 0.15 a medium effect size, and

f2= 0.35 as the large effect size. This kind of data presentation method is quite important in terms of interpreting research results. Researchers have cautioned the insufficiency of using only the result of statistical significance testing in statistical inference (Cohen, 1988; Daniel, 1998; McLean & Ernest, 1998). This is mainly because the computation of statis-tical significance is related to the sample size involved in the analysis. Moreover, it is quite common to observe a statistical significance with a large sample size, even if there was little practical effect actually. Therefore, to protect against statistical significant finding in terms of large sample size for the current study, effect magnitudes were also reported along with statistical significance test.

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RESULTS

Before reporting the results examining the associations between preferred – actual spaces and student earth science learning outcomes, the equivalence of incoming achievement and attitudes among groups must be determined. An ANOVA was computed on the pretest data and found all of them to be not significant ( p= 0.392 for the ESAT and p = 0.833 for the ATESI) between groups. Thus, the groups all started out with approximately the same degree of incoming earth science achievement and attitudes. Besides, given the nested nature of the data, the variances between individual classrooms were examined. The Levene’s tests of the homogeneity of variance indicated that the error variance for each dependent variable is equal across classrooms ( p= 0.13 for the ESAT pretest, p = 0.06 for the ESAT posttest scores; p= 0.66 for the ATESI pretest, p = 0.90 for the ATESI posttest scores). Therefore, data analysis disaggregating to the student level is deemed appropriate for the current study. The descriptive statistics of students’ pretest and adjusted posttest scores on the ESAT and ATESI are summarized in Table 2.

Preferred Actual Spaces in Determining Learning Outcomes

Table 3 shows the results for the stepwise multiple regression model of explaining the achievement outcomes by using achievement pretest score, attitude pretest score, PASpre, PASpost, PASmatch, and actual learning environment. The regression analysis revealed that the pretest scores were the only significant predictors in explaining students’ learning outcomes in achievement (t= 7.12, p < 0.001 for pretest achievement and t = 3.87, p < 0.001 for pretest attitude), R square (R2) equals to .38 with large effect size ( f2= 0.62), suggesting the importance of prior knowledge and attitudes in students’ subsequent learning. It is noted that at the first step of the model, pretest achievement score entered the equation and accounted for 33% of the variance in posttest achievement. At the second step in the

TABLE 2

Descriptive Statistics of Students’ Pretest and Adjusted Posttest Scores on the ESAT and ATESI

Pretest Scores Adjusted Posttest Scores

TLE MLE TLE MLE

Dependent Variables Mean (SD) Mean (SD) Mean (SD) Mean (SD)

Achievement 16.82 (2.88) 17.26 (3.44) 20.11 (4.08) 20.75 (3.15)

Attitudes 3.55 (0.45) 3.57 (0.49) 3.60 (0.45) 3.73 (0.44)

TABLE 3

Stepwise Regression Model Testing the Predictors of Students’ Achievement

Dependent Variable Predicting Variables B S.E. β t p Value

Achievement Ach. pretest 0.56 0.08 0.48 7.12** 0.000

Att. pretest 2.05 0.53 0.26 3.87** 0.000

Constant 3.67 1.89 1.91 0.054

Note: R2= 0.392; adjust R2= 0.384. ∗∗ p < 0.001.

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TABLE 4

Stepwise Regression Model Testing the Predictors of Students’ Attitudes

Dependent Variable Predicting Variables B S.E. β t p Value

Attitude Att. pretest 0.74 0.05 0.78 14.82** 0.000

PASmatch −0.09 0.04 −0.108 −2.07* 0.040

Constant 1.13 0.18 6.29 0.000

Note: R2= 0.591; adjust R2= 0.586.p < 0.05,∗∗p < 0.01.

regression, pretest attitude entered the equation, adding an incremental R2change of almost 5% to the model.

A similar stepwise multiple regression analysis was conducted on student attitude out-comes, illustrated in Table 4. Results showed an adjusted R square (R2)= 0.586,

F(2, 152)= 109.832, p < 0.001. Hence, about 59% of the outcome variance may be

ac-counted for by the following variables: attitude pretest scores and PASmatch. The regression analysis also revealed that only the pretest attitude and PASmatch could significantly ex-plain students’ learning outcomes in attitude (t = 14.82, p < 0.001 for pretest attitude and

t = −2.07, p < 0.04 for PASmatch) with greater than large effect size ( f2= 1.42), suggest-ing the importance of prior attitudes, and preferred – actual space (in a reverse manner) in students’ subsequent attitudes toward the subject matter. It is noted that at the first step of the model, pretest attitude entered the equation and accounted for 57% of the variance in posttest attitude. At the second step in the regression, PASmatchentered the equation, adding an incremental R2 change of 2% to the model. According to the regression model, it is plausible to find that student (attitude) pretest score was a significant variable in predicting their attitude outcomes. More importantly, student PASmatchcould also determine student attitude outcomes (t = −2.07, p < 0.04). The result suggested that the closer the learning environment matched students’ pretreatment preferences of LE, the more likely the students developed a more positive attitude toward earth science.

DISCUSSION AND IMPLICATIONS

The objective of this study was to determine whether preferred – actual space accounts for outcome variance beyond that explained by actual learning environment. The results indicated that although preferred – actual space is not related to achievement, but is both statistically and practically associated with attitudes toward the subject when actual learning environment is controlled. These findings substantiated, to some extent, some latest findings from a previous study in this series (Chang & Tsai, 2005), in which the researchers found that students’ preferences of learning environment significantly interacted with the treatments merely on student attitudes toward the subject matter (but not on their achievement). The teacher-centered instructional approach seemed to enhance more positive attitudes of less constructivist-oriented learning preferences students, whereas the student-centered method was more beneficial to more constructivist-oriented learning preferences students on their attitudes toward earth science in a computer-assisted learning environment. This experi-mental study further extended the aforementioned findings with a congruent – incongruent learning environment design and also confirmed the effectiveness of preferred – actual learn-ing environment spaces mainly in the affective learnlearn-ing outcomes, i.e., in student attitudes toward the subject matter. It indicates that the improvement of the congruence between an

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individual student’s actual and preferred learning environment should play a more important role in planning and designing individualizing instruction in the earth science classroom. Besides, the enhancement of student attitudes toward earth science through bridging pre-ferred – actual spaces is significant both statistically and practically as a result of current study.

The results of the regression analyses showed that only prior knowledge and attitude played important roles in students’ posttreatment achievement with large effect size. Since student posttreatment achievement might necessitate students’ prior achievement and atti-tudes, therefore these factors consequently have major roles in determining student posttreat-ment achieveposttreat-ment. The quantitative data analysis further provides affirmative recognition of students’ prior experiences in their subsequent learning, reflecting an Ausubelian view of learning. However, for the posttreatment attitudes measure, only the preattitude and PASmatch (the extent that the intervention matches the original and unaffected LE preferences of stu-dents before the intervention) came into play, which jointly could significantly predict the posttreatment attitudes toward the subject matter with greater than large effect size. These findings suggest that students’ preattitude and learning environment spaces (congruence) could enable students to develop more positive attitudes toward earth science subject. Ap-proximately 59% of the variation in these students’ posttreatment attitude outcome was attributable to differences in their pre-existing attitudes and post/prelearning environment congruence. These data indicate that these variables might serve as important inputs in student attitude toward the subject matter. These findings also suggest that earth science instruction in the secondary schools should not only emphasize the improvement of student attitude toward the subject but also bridge the gap between students’ preferred/perceived learning environment with the aim to enhance their attitudes toward earth science. Students receiving a more congruent learning environment would be provided with the opportunity to increase their affective variables toward earth science. Accordingly, the decreased spaces between pre-preferred/postperceived learning environments might help students, to some extent, to further improve their attitudes.

Previous research on person-environment fit suggested that actual – preferred congruence was important in predicting student achievement (Fraser & Fisher, 1983a, 1983b). This study added experimental results to the growing empirical base, yet only in the affective learning outcomes. The discrepancy may arise from student culture background and characteristics. Past research in cultural analysis and social psychology has suggested that Americans tend to value uniqueness while East Asians tend to value ordinariness and see themselves as similar to others, these individual views of themselves in turn may shape their own self-perception (Heine & Lehman, 1997; Kim & Markus, 1999; Markus & Kitayama, 1991) and their preferences of leaning environment. The ordinariness and conformity views (such as obedience to the teachers) are the most important virtues in Chinese culture and are deeply affected by Confucius. As a result, Taiwanese students are generally quiet and passive learners, and like listening to teachers instead of enjoying self-learning (Chang & Mao, 1999) due to the aforementioned cultural influences. Besides, the traditional teacher-centered learning environment has prevailed in the science classrooms for many years and students in Taiwan were not quite familiar with the innovative student – teacher-balanced learning environment. Consequently, students’ attitudes toward the subject might be more easily improved than their traditional achievement through decreasing the spaces between pre-preferred/postperceived learning environments.

The practical implication of the aforementioned research result for teachers and science educators is that individual students’ attitudes can be enhanced by altering the earth science classroom learning environment in ways which make it more congruent with that preferred by students. Furthermore, classroom-learning environment should put more emphasis on

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individualizing instruction to improve the match between an individual student’s actual and preferred environment. However, students’ cultural background and characteristics should be taken into account when cultivating or devising specific leaning environments in the secondary school. Teachers should also recognize that students learn in different way and at different rates within different cultural backgrounds, therefore, the construction of ESCLE should take all of these differences into consideration.

In conclusion, teachers could employ the instruments and data analysis methods proposed in the study to provide meaningful information about their classrooms and a tangible basis for instructional improvement. It is noted, however, that the use of Euclidean distance to measure the preferred – actual spaces does not indicate the locus of the two points (pre-ferred and perceived learning environment). Additional research with larger sample exam-ining the locus of the aforementioned points in addition to the PAS might be informative in understanding the context of the student’s interpretations of the learning environment. Future replication studies concerning differential effects of various learning environments on student-learning outcomes including higher order thinking skills might also be needed to further substantiate and extend the findings. In addition, more evidence is needed by conducting studies employing longer treatments, larger samples, and more learning envi-ronments or from studies that draw on qualitative data collection methods. Some of these issues are currently being addressed in secondary schools in Taiwan.

The authors gratefully acknowledge the assistance of Sophia Wang and Jing-Wen Hsu. The authors would also like to thank the students, teachers, and the principal (Huei-Deng Tsai) of the National Si-Hu Senior High School of Changhua County of Taiwan, who were involved in the series of the learning environment studies.

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數據

Figure 1. (a) A plot of students’ mean scores on the preferred ESCLEI (n = 155); (b) a plot of students’ mean

Figure 1.

(a) A plot of students’ mean scores on the preferred ESCLEI (n = 155); (b) a plot of students’ mean p.7
Table 3 shows the results for the stepwise multiple regression model of explaining the achievement outcomes by using achievement pretest score, attitude pretest score, PAS pre , PAS post , PAS match , and actual learning environment

Table 3

shows the results for the stepwise multiple regression model of explaining the achievement outcomes by using achievement pretest score, attitude pretest score, PAS pre , PAS post , PAS match , and actual learning environment p.11

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