Article Cite This: J. Chem. Educ. XXXX, XXX, XXX−XXX
pubs.acs.org/jchemeduc
Developing High School Students’ Self-Efficacy and Perceptions about Inquiry and Laboratory Skills through Argument-Driven Inquiry Guluzar Eymur* Department of Child Care and Youth Services, Giresun University, Giresun 28200, Turkey ABSTRACT: The present study investigated how students’ self-efficacy changed after participation in four lab investigations that were designed on the basis of a new laboratory instructional strategy, namely, argument-driven inquiry (ADI). The study was conducted with 64 10th grade students from two intact classes in a public high school in the northeast of Turkey. One class was randomly assigned as an experimental group, and the other as a comparison group, and data were collected to allow for a comparison of students’ self-efficacy across treatment conditions. Both experimental and control groups had the same chemistry courses and laboratories. However, the experimental group conducted laboratory activities that were designed using the ADI instructional model, and the control group performed traditional laboratory instruction. The Students Perceptions in Chemistry Evaluation (SPiCE) Instrument was used to measure students’ perceptions of their own inquiry skills (self-efficacy) and attitudes about various aspects of chemistry. Additionally, the Interest in Science Pursuits Instrument was used to evaluate whether students’ interest in pursuing science endeavors changed after their laboratory experience. The results indicate that the ADI instructional model improves students’ perceptions about self-efficacy, inquiry skills, and lab skills as compared to traditional laboratory instruction. However, the findings showed that there was no significant difference between the experimental and the control group concerning students’ attitudes toward chemistry. With regard to students’ interest in pursuing science endeavors, there was also no significant difference between the experimental and the control groups. KEYWORDS: High School/Introductory Chemistry, Inquiry-Based/Discovery Learning, Chemical Education Research, Laboratory Instruction FEATURE: Chemical Education Research
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INTRODUCTION Researchers have shown that learning interest can encourage learners to learn and to put more effort into learning.1 Unfortunately, current trends suggest that interest in science in middle schools is declining.2 Research studies have shown that engagement with science courses and the pursuit of careers related to science have decreased in recent decades.3 The most common reason for this low interest is related to students’ perceptions of their scientific abilities.4 The evaluations of science knowledge and inquiry skills affect students’ perceptions of their scientific abilities. Furthermore, their perceptions predict their achievement in science4 and influence their future careers.5 Science tests during middle school evaluate students’ performance and show their abilities in scientific fields. This time is very important for students in terms of scientific career choices.6 Thus, their perceptions are also crucial. However, the present evaluations generally assess scientific knowledge, not inquiry skills.7 There is no doubt that interest plays a crucial role in students’ learning of science and that it may influence students’ decisions to take certain science elective courses or pursue a career in science. Research has also shown that there is a relationship between self-efficacy and interest in science.8 Bandura defined self-ef f icacy as people’s beliefs in their capabilities to produce given attainments.9 Bandura affirmed that one’s beliefs shape one’s behavior and persistence in this domain.9 This affects a person’s effort and succethat means © XXXX American Chemical Society and Division of Chemical Education, Inc.
higher self-efficacy comes higher interest and effort. A great deal of research has shown that self-efficacy has a strong, positive influence on achievement.10−12 Self-efficacy predicts intellectual performance better than skills alone, and it explicitly affects academic achievement and anticipates future achievement better than past performance.13−17 As Bandura stated, selfefficacy beliefs are also conducive to performance because they affect motivation, thought processes, and behavior.9 Changes in self-efficacy may lead to changes in performance. For example, different beliefs in self-efficacy may change outcomes whether these beliefs are held by two individuals with the same skills or by one individual in two different situations.9 Also, if students’ perceptions of their scientific abilities are negative, then their self-efficacy and interest in science decrease. This will also affect students’ science engagement in the future.18 If we affect students’ success and perceptions in a positive manner, we can increase their self-efficacy and interest in science. The self-efficacy research in chemical education has mainly addressed single or pre- and postimplementations of selfefficacy assessment instruments.19−22 Also, too little research has investigated changes in self-efficacy throughout a semester.23,24 There are very few studies about self-efficacy and laboratory applications in chemistry education.25,26 This Received: December 5, 2017 Revised: March 23, 2018
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DOI: 10.1021/acs.jchemed.7b00934 J. Chem. Educ. XXXX, XXX, XXX−XXX
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Table 1. Steps of ADI Instructional Model and Purposes Step Identification of task and the research question Development of a method; collection and analysis of data Generation of a tentative argument Argumentation session Composition of an investigation report Double-blind group peer review Revision of investigation reports
Purpose Attract students’ attention; activate students’ previous knowledge Give a chance to students to design and practice an investigation; provide an opportunity to students to decide what type of data they need and how to collect it Give an opportunity to students to develop a tentative argument that includes a claim, evidence, and justification of evidence Make students discuss and share their ideas; give a chance to students to get feedback about their argument Make students learn how to craft written argument Give a chance to students to understand a good quality investigation report; provide an opportunity to students to get feedback from their peers Make students revise and improve their writing
by using more authentic and educative laboratory activities. Additionally, the social conditions of the ADI instructional model give students an opportunity to become active participants in science processes. Walker et al. stated that the components of the ADI instructional model (the development of an argument, the discussion of findings, and scientific writing) encourage students to participate and feel successful.29 We also think that in this kind of approach, one in which students have the opportunity to conduct authentic scientific research with their friends and get feedback from their peers about their performance, students are able to increase their selfefficacy and in return increase their interest in science. This idea is rooted in the work of Pintrich and Schunk,35 who stated that “peers are more often more effective models when children hold self-doubts about their competence... Observing a peer model increased efficacy and achievement better than did observing a teacher or not observing a model”. This literature, in sum, suggests that when students have more opportunities to engage in authentic scientific practices, they can improve their self-efficacy.
research reported that laboratory activities support self-efficacy in science teaching. We think that the argument-driven inquiry (ADI) model, which is a new laboratory instructional model, increases the self-efficacy beliefs of students because it not only emphasizes the empirical aspects of laboratories (such as asking questions and designing methods) but also places great importance on the representation of knowledge claims (such as argumentation and writing) in the development of students’ science proficiency. In order to realize this goal, the ADI instructional model involves seven interrelated steps that were explained by Sampson and Walker.27 The steps of the ADI instructional model and their purpose are presented in Table 1. Recently, studies have been conducted that speak to the effectiveness of ADI in developing high school students’ biology proficiency in the United States28 and that examine the effectiveness of this instructional practice in US college chemistry laboratories.29 Most of the research on ADI is related to the effectiveness of ADI on writing skills.30,31 No study has addressed the effect of ADI on self-efficacy. The present study investigates how students’ self-efficacy changes after participation in four lab investigations that were designed based on the ADI instructional model.
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RESEARCH QUESTIONS The main aim of this study was to investigate the effects of the ADI instructional model on students’ self-efficacy and perceptions concerning inquiry and laboratory skills and attitudes about various aspects of chemistry. On the basis of this objective, the research questions were as follows: (1) What is the effect of the ADI instructional model compared to traditional laboratory instruction on 10th grade students’ self-efficacy and perceptions concerning inquiry and laboratory skills and attitudes about various aspects of chemistry? (2) How does 10th grade students’ interest in pursuing science endeavors change after implementation of the ADI instructional model?
THEORETICAL PERSPECTIVE
The ADI laboratory instructional model is based on social constructivist theories of learning.32,33 This theory proposes that learning includes both personal and social processes. The social process of learning relies on supportive and educative interactions with people, while the personal process involves individual construction of knowledge and understanding. There are two significant results of this theoretical framework for instructional design. One is that students need authentic scientific practices in order to learn from their experiences. The other is that the scientific practices should also be educative for students so that they learn scientific knowledge and norms. Duschl, Schweingruber, and Shouse define argumentation as “logical discourse whose goal is to tease out the relationship between ideas and evidence”.34 Scientific argumentation includes claim, evidence, and justification of evidence. The evidence means the data that are collected and then used to support the claim by proofing and clarifying. There are two conditions required for this data to be considered evidence. It should explain (1) the tendency over time and (2) the difference between groups or a relationship. The justification of evidence of scientific argumentation refers to the explanation of the validity and the relevance of the evidence. With regard to this theoretical framework, the ADI instructional model is grounded on the hypothesis that it improves students’ skills in scientific argumentation and writing
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METHODOLOGY A nonequivalent control group design was used as a part of a quasi-experimental design36 to compare the effectiveness of the ADI instructional model to a traditional laboratory instructional model. For this purpose, two chemistry classes were selected: one class was randomly assigned as an experimental group and the other as a comparison group, and data were collected to allow for a comparison of students’ self-efficacy across treatment conditions. We think that this type of study offered many advantages for our research questions and aims. First and perhaps most importantly, the control group, an important variable in educational research, facilitated comparisons B
DOI: 10.1021/acs.jchemed.7b00934 J. Chem. Educ. XXXX, XXX, XXX−XXX
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knowledge about the topic. Students were assigned to groups of four or five; working together, they collected data and planned their investigation of the guiding question. After the data collection, the groups decided how to interpret and analyze the data. They tried to answer the guiding question by making a tentative argument that involved a claim. After they answered the question, the groups of students continued to develop evidence and provide justification for the evidence. Each group then presented arguments and ideas (using a large pasteboard) to the whole class (a detailed explanation about what counts as a claim, evidence, and rationale is given in Walker et al., 2012). The premise of the argument gave students the opportunity to discuss “what counts” as a good scientific argument and to evaluate alternative claims. When the groups presented the large pasteboard that included their claim, evidence, and justification of evidence, the whole class argumentation session started. In this argumentation session, groups presented their arguments by answering the guiding question and discussed the other groups’ arguments that were presented. This argumentation session gave students an opportunity to compare and contrast the strengths and weaknesses of their arguments. After the argumentation session, an investigation report, which involved a written scientific argument answering the guiding question, was desired from students individually. These investigation reports were distributed to other groups for checking and revising according to a peer-review form. The peer-review form was presented in the Sampson and Walker (2012)27 study on revising investigation reports in ADI activities. It included four criteria parts, namely, the goals, the investigation, the argument, and the writing and space to give feedback for writers. Students used these criteria to evaluate the quality of investigation reports. Group members completed these forms by discussing these items. This peer-review process gave students a chance to socially negotiate “what counts” as a good scientific argument. The last step of the ADI instructional model was the revision of students’ individual investigation reports based on peer feedback.
between ADI and the treatment being investigated. Second, it allowed us to conduct the intervention in an actual classroom environment.
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PARTICIPANTS All participants attended a public high school, which had accepted the students on the basis of their scores on a high school entrance exam. This exam had included multiple-choice questions about science, math, Turkish social sciences, and English. The available school accepted students with high scores on the exam, so these students were high achievers compared to the general population. There were 64 10th grade students from two classes enrolled in this study. The experimental group consisted of 32 students (16 girls and 16 boys), and the comparison group also consisted of 32 students (15 girls and 17 boys) with ages ranging from 15 to 16 years. The chemistry course was taught in a public high school in the northeast of Turkey. The socioeconomic status of the students’ families was not known, but the students all spoke the same native language.
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THE INTERVENTION Both the experimental and the control groups had the same chemistry courses and laboratories taught by the same instructor. However, the experimental group participated in laboratory activities that followed the ADI instructional model, while the control group was taught using more traditional laboratory instruction. The researcher conducted the intervention. Both groups had two 45 min laboratory sessions per week, and these sessions continued over a 7 week period. Experimental Group Condition
The students in the experimental group participated in 4 different laboratory activities that were designed according to the ADI instructional model. These investigations (translated from Sampson et al., 2014) were formed to explore important chemistry concepts such as reaction rates, characteristics of acids and bases, identification of an unknown based on physical properties, and the rate of dissolution. The names of the activities and the related guiding questions are presented in Table 2 (detailed explanation in Sampson et al., 2014).
Control Group Condition
The control group students engaged in the same four activities that the experimental group participated in, but these activities occurred in the context of traditional laboratory instruction. At the beginning of the laboratory instruction, the teacher distributed handouts that included background information about the task, the purpose of the experiment, the research question, the materials, and the procedure of the experiment. The students worked in groups. While the students were working on the experiment, the teacher asked questions to guide the students. They followed the steps of the procedure to answer the research questions. After the investigation, the students submitted their investigation report, which included the purpose of the experiment, the answer to the research question, and the results of the experiment. The teacher collected the investigation reports and summarized the results of the investigation questions.
Table 2. Descriptions of the Activities Name of the Activity Reaction rates Characteristics of acids and bases Identification of an unknown based on physical properties Rate of dissolution
The Guiding Question Why do changes in temperature and reactant concentration affect the rate of a reaction? How can the chemical properties of an aqueous solution be used to identify it as acid or a base? What are the products of the chemical reactions?
Why do the surface area of the solute, the temperature of the solvent, and amount of agitation that occurs when the solute and the solvent are mixed affect the rate of dissolution?
At the beginning of the ADI laboratory activities, the teacher distributed a handout that provided a guiding question for the experiment being conducted. Students were charged with designing and performing investigations in order to answer the guiding question. The handout also included related information and materials that could be used for the investigation. The handout helped students recall their
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DATA SOURCES
In order to investigate the research problems, two instruments were used as pretest and post-test. C
DOI: 10.1021/acs.jchemed.7b00934 J. Chem. Educ. XXXX, XXX, XXX−XXX
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Students Perceptions in Chemistry Evaluation (SPiCE) Instrument
reflects lower amounts of the attribute and a high number indicates greater amounts. It included five statements that were “I plan to become a scientist when I graduate school”, “When I graduate, I would like to work with people who make discoveries in science”, “A career in science interests me”, “I am interested in pursuing a science career in the future”, and “I am interested in pursuing a college degree in science”. The researchers calculated the α as 0.90 (n = 495). The highest point was 25, which indicated the highest interest in pursuing science endeavors. The author and the educator also translated this instrument into Turkish and shaped it into its final version through discussion. It was piloted with 116 high school students, and Cronbach’s α was calculated at 0.81. Students were allowed 15 min to complete the instrument.
The Students’ Perceptions in Chemistry Evaluation (SPiCE) Instrument was used to measure students’ self-efficacy and perceptions concerning inquiry and laboratory skills and attitudes about various aspects of chemistry. It was developed by Wilkermann37 and involved 32 Likert-type items. Also, it had four subscales with eight items that deal with perceptions of abilities regarding Inquiry Skills, Lab Skills, Lecture Material, and perceptions of the Real World affected by chemistry. Additionally, SPiCE addressed self-efficacy with 13 items that were in four subscales, mainly the Inquiry Skills subscale. The Likert scale values ranged from 1 (strongly disagree) to 5 (strongly agree). Wilkermann developed half of the instrument items and shaped the remaining items on the basis of available surveys: the Chemistry Expectations Survey (CHEMX),38 the Chemistry Attitude and Experiences Questionnaire (CAEQ),39 and the Colorado Learning About Science Survey (CLASS).40 A hybrid survey was used because no single available instrument was able to measure students’ attitude and perceptions in the desired subscale issues. All analyses of reliability and validity of SPiCE were conducted and presented by Wilkermann. Factor analysis was done by Wilkermann to determine its dimensionality and construct validity. Analyses involved a Kaiser−Meyer−Oikin (KMO) test for sampling adequacy and a χ-square test to identify the factor structure of the items in the SPiCE measure.37 Wilkermann calculated the KMO values above 0.8 for data sets from two different semesters. Moreover, a significant χ-square value (ρ < 0.000) for the data sets supported further factor analysis of scale items (e.g., how closely items in the four subscales reflect factors in the data set). Wilkermann conducted an analysis of the factor structure of the SPiCE scale in order to determine the degree of correspondence between SPiCE subscales and the empirical factors underlying the SPiCE data sets. These analyses defined patterns within each data set, and each pattern was referred to as a factor. A four-factor solution was checked using varimax rotation due to including four subscales of SPiCE. Also, Wilkermann assigned 13 items (#8 Inquiry Skills, #3 Real World, #1 Lab Skill, and #1 Lecture Material) to address selfefficacy because of the relationship between self-efficacy and attitude about chemistry, students’ confidence, and anxiety in the lab. In addition, the degree of the relationship of each item to these four factors was then identified (i.e., on a scale of 0 to ±1.0), referred to as factor loadings. In general, factor loadings above 0.3 are considered valid and presented. He reported a table of results of reliability and validity analyses of SPiCE data sets and factor analysis. The author and one chemistry educator translated SPiCE into Turkish independently. They then negotiated together to resolve the differences in the translation and formed the final version. The Turkish version of the instrument was piloted with 116 high school students, and Cronbach’s α was calculated at 0.72. Also, Cronbach’s α for each subscale was found to be 0.71 for Inquiry Skills, 0.70 for Lab Skills, 0.73 for Lecture Material, and 0.72 for Real World. Students were given 40 min to complete the instrument.
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RESULTS AND DISCUSSION This part was divided into two sections that each included research questions. Data analyses and their outcomes for each research question in subsections were presented. Also, the brief discussion was given on the basis of the research questions and the outcomes of analyses. What is the ef fect of the ADI instructional model compared to traditional laboratory instruction on 10th grade students’ selfef f icacy and perceptions concerning inquiry and laboratory skills and attitudes about various aspect of chemistry? In order to answer this question, the SPiCE instrument was conducted as pretest and post-test for the experimental and control groups. To decide the differences between the experimental and control group, using repeated measures analysis of variance for each of the SPiCE subscales (Self-Efficacy, Inquiry Skills, Lab Skills, Lecture Material, Real World). Pretest and post-test means are presented in Table 3 for each of the SPiCE subscales. Table 3. Pretest and Post-Test Means and Standard Deviations for the Control and Experimental Groups on the SPiCE Subscales
SPiCE Subscale Self-Efficacy Inquiry Skills Lab Skills Lecture Material Real World
Experimental Group Scores, N = 32
Control Group Scores, N = 32
Administration
Mean
SD
Mean
SD
Pretest Post-test Pretest Post-test Pretest Post-test Pretest Post-test Pretest Post-test
43.9 52.6 26.4 32.5 31.4 32.7 28.5 31.4 28.2 32.6
6.80 5.70 4.40 3.75 3.04 3.28 3.79 3.04 3.27 3.78
43.6 46.8 26.1 28.0 30.8 29.0 29.1 30.8 27.6 29.5
5.90 9.00 4.70 6.19 3.13 4.71 4.40 4.44 4.59 5.52
Self-Efficacy
Thirteen SPiCE items (1, 4, 7, 9, 11, 14, 16, 17, 22, 23, 24, 30, and 32) were related to self-efficacy. The analysis of variance (ANOVA) on the Self-Efficacy subscale pretest showed no significant differences (F = 0.053, p = 0.819) between the experimental group (M = 43.65, SD = 6.86) and control group (M = 43.96 SD = 5.96). Statistically significant differences were found on post-test between the experimental (M = 52.68, SD = 5.76) and control (M = 46.81, SD = 9.09) groups on the subscale Self-Efficacy (F = 9.517, p = 0.003).
Interest in Science Pursuits Instrument
The Interest in Science Pursuits Instrument was developed by Lawless and Brown.41 It was used to evaluate students’ interest in pursuing science endeavors after the intervention. It was a five-point, Likert-type rating scale, where a lower number D
DOI: 10.1021/acs.jchemed.7b00934 J. Chem. Educ. XXXX, XXX, XXX−XXX
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efficacy and perceptions about inquiry skills and lab skills by ADI instructional model are important in their science career. To evaluate students’ attitudes about chemistry that involved the lecture class and chemistry experienced in the real world, two subscales’ (Lecture Material and Real World) items were analyzed.
The repeated measures ANOVA showed a statistically significant difference (F = 23.74, p < 0.001) on the SelfEfficacy subscale between groups (i.e., experimental pretest and post-test scores versus control group pretest and post-test scores). Also, a statistically significant difference (F = 76.80, p < 0.001) was found on this subscale between pretest and post-test scores for the experimental group (within subjects, Table 4).
Lecture Material
This subscale included eight items (3, 4, 5, 6, 18, 19, 20, 21). The analysis of variance (ANOVA) on the Lecture Material subscale pretest showed no significant differences (F = 0.359, p = 0.551) between the experimental group (M = 28.5, SD = 3.79) and control group (M = 29.1, SD = 4.40). Although the mean score of students’ perceptions about Lecture Material in the experimental group (M = 31.4) was higher and increased more than that of the control group (M = 30.1), there was not a significant difference between the post-test scores for the control group and experimental group (F = 1.827, p = 0.181) The repeated measures ANOVA also showed no statistically significant difference (F = 2.32, p = 0.132) on the Lecture Material subscale between groups (i.e., experimental pretest and post-test scores versus control group pretest and post-test scores). However, a statistically significant difference (F = 21.52, p < 0.001) was found on this subscale between pretest and post-test scores for the experimental group (within subjects, Table 4).
Table 4. Repeated Measures ANOVA of Subscales for the Experimental Group, Within Subjects
a
Subscales
Mean (Pretest)
Mean (Post-Test)
Partial η Square
Significance: F (1, 31); p < 0.001
Self-Efficacy Inquiry Skills Lab Skills Lecture Material Real World
43.93 26.37 31.43 28.78 28.43
52.51 32.50 32.75 31.40 32.65
0.719 0.693 0.128 0.410 0.546
76.800 70.020 4.534a 21.520 37.290
p = 0.041.
Inquiry Skills
This subscale included eight items (9, 11, 14, 16, 17, 22, 23, 24). The analysis of variance (ANOVA) on the Inquiry Skills subscale pretest showed no significant differences (F = 0.053, p = 0.819) between the experimental group (M = 26.4, SD = 4.4) and control group (M = 26.1, SD = 4.7). Statistically significant differences were found on the post-test between the experimental (M = 32.5, SD = 3.75) and control (M = 28.0, SD = 6.19) groups on the subscale Inquiry Skills (F = 12.35, p = 0.001). The repeated measures ANOVA showed a statistically significant difference (F = 9.71, p = 0.003) on the Inquiry Skills subscale between groups (i.e., experimental pretest and post-test scores versus control group pretest and post-test scores). Also, a statistically significant difference (F = 70.02, p < 0.001) was found on this subscale between pretest and post-test scores for experimental group (within subjects, Table 4).
Real World
This subscale included eight items (1, 2, 7, 28, 29, 30, 31, 32). The analysis of variance (ANOVA) on the Real World subscale pretest showed no significant differences (F = 0.275, p = 0.602) between the experimental group (M = 28.2, SD = 3.27) and control group (M = 27.6, SD = 4.59). Although the mean score of students’ perceptions about Real World in the experimental group (M = 32.6) was higher and increased more than that of the control group (M = 29.5), there was not a significant difference between the post-test scores for the control group and the experimental group (F = 6.69, p = 0.012). The repeated measures ANOVA also showed no statistically significant difference (F = 6.49, p = 0.013) on the Real World subscale between groups (i.e., experimental pretest and posttest scores versus control group pretest and post-test scores). However, a statistically significant difference (F = 37.29, p < 0.001) was found on this subscale between pretest and post-test scores for the experimental group (within subjects, Table 4). While it was disappointing that there was no significant difference between the experimental and the control group about students’ attitudes toward chemistry, there might have been some reasons in Turkey. Actually, the increase in the experimental group was higher than that for the control group, but there was no significant difference statistically. In Turkey, there is an university entrance examination, and it has a powerful effect in shaping the teaching and learning in Turkish high schools.42 This examination includes a broad range of the content knowledge, and teachers struggle to teach all the topics in a limited time, so the practices of science that need more time than lecture are too few in schools.43 Therefore, the control group students’ attitudes about chemistry also increase, because they were engaged by traditional laboratory instruction. In their regular chemistry course, there is a limited time for laboratory activities. This might lead to positive effects on their attitudes toward chemistry. How does 10th grade students’ interest in pursuing science endeavors change af ter the ADI instructional model? To evaluate
Lab Skills
This subscale involved eight items (3, 4, 5, 6, 18, 19, 20, 21). The analysis of variance (ANOVA) on the Lab Skills subscale pretest showed no significant differences (F = 0.70, p = 0.406) between the experimental group (M = 31.4, SD = 3.04) and control group (M = 30.8, SD = 3.13). Statistically significant differences were found on the post-test between the experimental (M = 32.7, SD = 3.28) and control (M = 29.0, SD = 4.71) groups on the subscale Lab Skills (F = 13.623, p < 0.001). The repeated measures ANOVA showed a statistically significant difference (F = 9.17, p = 0.004) on the Lab Skills subscale between groups (i.e., experimental pretest and posttest scores versus control group pretest and post-test scores). However, no statistically significant difference (F = 4.53, p = 0.041) was found on this subscale between pretest and post-test scores for the experimental group (within subjects, Table 4). Given these analyses and findings, the results indicated that the ADI instructional model improved students’ self-efficacy and perceptions about inquiry skills and lab skills compared to traditional laboratory instruction. As Multon and Bandura reported that students’ perceptions were crucial and foretold their achievement in science, the improvement of students’ selfE
DOI: 10.1021/acs.jchemed.7b00934 J. Chem. Educ. XXXX, XXX, XXX−XXX
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efficacy can undermine an individual’s actual levels of ability, talent, and potential.”45 The present study tried to improve students’ self-efficacy through the ADI instructional model. In addition, the importance of self-efficacy as a promoting factor for achievement was approved in the research in terms of motivation achievement and goal effects.46 In order to develop students’ self-efficacy in chemistry, we believe that students should engage in practices of science that are more authentic and novel in the ADI instructional model. With regard to student’ attitudes toward chemistry, we did not find significant differences between the ADI instructional model and traditional laboratory instruction. We wonder if this study needs more time to find differences between the experimental and the control groups. In other words, students might need more time to change their attitudes. Also, improving student attitudes by the ADI instructional model should be taken into consideration in other countries. We consider that a significant difference was not found between the ADI instructional model and traditional laboratory instruction because of the conditions of school that have to give a limited time for laboratory activities in regular courses. In addition, we found that students’ interests in pursuing science endeavors were unchanged. We think that the socio-cultural aspects of Turkey affect this outcome. So, we wonder about the effect of the ADI instructional model on students’ interest in pursuing science endeavors in other countries. Despite some limitations, the study suggests that the ADI instructional model is able to increase students’ self-efficacy, perceptions of inquiry, and lab skills. We hope that the ADI instructional model can be an alternative and be useful for teachers in chemistry laboratory instruction.
changes of students’ interest in pursuing science endeavors, the Interest in Science Pursuits Instrument was used. Conducting an independent t-test for pretest and post-test results for the experimental and the control groups was used to analyze the differences. There was no significant difference between the experimental (M = 16.9, SD = 5.27) and control (M = 13.5, SD = 6.515) groups; t (62) = 2.31 and p > 0.05 for post-test scores, and items were unchanged for both groups (Table 5). Table 5. Comparative Results from Independent Samples’ tTests Analysis of Student Response Scores on the Instruments, N = 32 Interest in Science Pursuits Instrument Administration Pretest Post-test
Group
Mean
SD
t-Value
p-Value
Experimental Control Experimental Control
16.9 14.0 16.9 13.5
6.66 7.44 5.27 6.55
1.65
0.103
2.31
0.240
As shown from analyses, there was no significant difference between the experimental and the control group. Actually, this finding was unacceptable and surprising. Because research has demonstrated that when students’ self-efficacy in science increases, their interest and, in return, their future career choices in science can also be increased.4,10 In this case, there might have some reasons based on the socio-cultural characteristics of Turkey. In a developing country like Turkey, future career choices generally are shaped on the basis of salaries.44 A career in science in Turkey meant a low salary and much effort. So, the ADI instructional model could not change their ideas about a science career. This might be fthe irst and most important reason for this finding. Another reason might be perceptions about science culturally. Actually, students have not had enough knowledge and meaningful knowledge about science. This might lead to low future career choices in science for students.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
Guluzar Eymur: 0000-0002-3316-5464
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Notes
LIMITATIONS As in the evalution of all research studies, the study’s limitations should be in mind. The main limitation of the study was a sample size that refines the generalizability of the results. However, the study had to be done in actual school and classes with a limited population. The second limitation was a limited time implementation of the study. The study was conducted in 7 weeks, which may be an insufficient time to assess the effectiveness of one instructional model especially to change attitudes of the students. Lastly, this study was implemented by a researcher who is experienced in the ADI instructional model, so the usability of the ADI instructional model with inexperienced teachers should be in mind when the model is carried out.
The author declares no competing financial interest.
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ACKNOWLEDGMENTS This work was supported by the Giresun University under Grant EĞ T-BAP-A-140316-106.
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REFERENCES
(1) Fenichel, M.; Schweingruber, H. A. Surrounded by Science: Learning Science in Informal Environments; National Academies Press: Washington, DC, 2010. (2) Arnot, M.; David, M.; Weiner, G. Closing the Gender Gap; Polity Press: Cambridge, 2001. (3) Harackiewicz, J. M.; Barron, K. E.; Pintrich, P. R.; Elliot, A. J.; Thrash, T. M. Revision of achievement goal theory: Necessary and illuminating. J. Edu. Psyc. 2002, 94, 638−645. (4) Multon, D. K.; Brown, S. D.; Lent, R. W. Lent Relation of selfefficacy beliefs to academic outcomes: a meta-analytic investigation. J. Coun. Psy. 1991, 38, 30−38. (5) Bandura, A. Guide for constructing self-efficacy scales. In SelfEfficacy Beliefs of Adolescents; Pajares, F., Urdan, T., Eds.; Information Age Publishing: Greenwich, CT, 2006; Vol. 5, pp 307−337. (6) Tai, R. H.; Liu, C. Q.; Maltese, A. V.; Fan, X. Planning Early for Careers in Science. Science 2006, 312 (5777), 1143−1144.
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IMPLICATIONS AND CONCLUSIONS The results of the study, due to the small sample size employed, suggest that the ADI instructional model improved students’ self-efficacy, perceptions of inquiry, and lab skills compared to traditional laboratory instruction. We think that this finding is so important because as Bandura stated, “...persons’ perceived self-efficacy has been linked to performance, motivation, and achievement in several domains. A low perception of selfF
DOI: 10.1021/acs.jchemed.7b00934 J. Chem. Educ. XXXX, XXX, XXX−XXX
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(7) National Research Council. Mineral Tolerance of Animals, National Research Council of the National Academies; The National Academies Press: Washington, DC, 2005. (8) O’Brien, V.; Martinez-Pons, M.; Kopala, M. Mathematics selfefficacy, ethnic identitiy, gender and career interests related to mathematics and science. J.Edu. Res. 1999, 92 (4), 231−235. (9) Bandura, A. Self-Efficacy: The Exercise of Control; W. H. Freeman: New York, NY, 1997. (10) Pajares, F. Self-efficacy beliefs in achievement settings. Rev. Edu. Res. 1996, 66, 543−578. (11) Wigfield, A.; Eccles, J. S. The Development of Competence Beliefs and Values from Childhood through Adolescence. In Development of Achievement Motivation; Wigfield, A., Eccles, J. S., Eds.; Academic Press: San Diego, 2002. (12) Zimmerman, B. J. Attaining self-regulation: A social cognitive perspective. In Handbook of Selfregulation;Boekaerts, M., Pintrich, P. R., Zeidner, M., Eds.; Academic Press: San Diego, CA, 2000; pp 13− 39. (13) Bandura, A. Social Foundations of Thought and Action: A Social Cognitive Theory; Prentice-Hall: Englewood Cliffs, NJ, 1986. (14) Tippins, D. J. The relationship of science self-efficacy and gender to ninth grade students’ intentions to enroll in elective science courses. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL, April 1991; ERIC Number: ED350144. (15) Miller, R. B.; Greene, B. A.; Montalvo, G. P.; Ravindran, B.; Nichols, J. D. Engagement in academic work: The role of learning goals, future consequences, pleasing others, and perceived ability. Con. Educ. Psych 1996, 21, 388−422. (16) Chemers, M. M.; Hu, L.; Garcia, B. F. Academic self-efficacy and first-year college student performance and adjustment. J. Educ. Psych 2001, 93 (1), 55−64. (17) Garcia, T.; Yu, S. L.; Coppola, B. P. Women and minorities in science: Motivational and cognitive correlates of achievement. Paper presented at the Annual Meeting of the American Educational Research Association, Atlanta, GA, April 12−16, 1993; ERIC Number: ED359235. https://files.eric.ed.gov/fulltext/ED359235.pdf (accessed Mar, 2018). (18) Zimmerman, B. J.; Bandura, A. Impact of self-regulatory influences on writing course attainment. Am. Edu. Res. J. 1994, 31, 845−862. (19) Uzuntiryaki, E.; Ç apa Aydın, Y. Development and validation of chemistry self-efficacy scale for college students. Res. Sci. Edu. 2009, 39, 539−551. (20) Uzuntiryaki-Kondakçı, E.; Senay, A. Predicting chemistry achievement through task value, goal orientations, and self-efficacy: a structural model. Croa. J. Edu 2015, 17 (3), 725−753. (21) Cook, A. F. Exploring freshmen college students’ self-efficacy, attitudes, and intentions toward chemistry. Honors College Capstone Experience/Thesis Projects, West Kentucky University, 2013. (22) Ferrell, B.; Barbera, J. Analysis of Students’ Self-Efficacy, Interest, and Effort Beliefs in General Chemistry,. Chem. Educ. Res. Pract. 2015, 16, 318−337. (23) Dalgety, J.; Coll, R. K. The influence of first-year chemistry students’ learning experiences on their educational choices. Ass. & Eva. High. Edu 2006, 31, 303−328. (24) Villafañe, S. M.; Garcia, C. A.; Lewis, J. E. Exploring diverse students’ trends in chemistry self-efficacy throughout a semester of college-level preparatory chemistry. Chem. Educ. Res. Pract. 2014, 15 (2), 114−127. (25) Aka, E. I. An Investigation into Prospective Science Teacher’ Attitudes towards Laboratory Course and Self-Efficacy Beliefs in Laboratory Use. International J. Env. Sci. Edu. 2016, 11 (10), 3319− 3331. (26) Azar, A. In-Service and Pre-Service Secondary Science Teachers’ Self-Efficacy Beliefs About Science Teaching. ZKU J. Soc. Sci. 2010, 6 (12), 235−252.
(27) Sampson, V.; Walker, J. Argument-Driven Inquiry as a way to help undergraduate students write to learn by learning to write in chemistry. Int. J. Sci. Edu. 2012, 34 (10), 1443−1485. (28) Strimaitis, A. M.; Southerland, S. A.; Sampson, V.; Enderle, P.; Grooms, J. Promoting Equitable Biology Lab Instruction by Engaging All Students in a Broad Range of Science Practices: An Exploratory Study. Sch. Sci. Math. 2017, 117 (3−4), 92−103. (29) Walker, J.; Sampson, V.; Grooms, J.; Anderson, B.; Zimmerman, C. Argument-Driven Inquiry in undergraduate chemistry labs: The impact on students’ conceptual understanding, argument skills, and attitudes towards science,. J. Coll. Sci. Teach. 2012, 41 (4), 74−81. (30) Sampson, V.; Enderle, P.; Grooms, J.; Witte, S. Writing to learn and learning to write during the school science laboratory: Helping middle and high school students develop argumentative writing skills as they learn core ideas. Sci. Educ. 2013, 97 (5), 643−670. (31) Walker, J.; Sampson, V. Learning to argue and arguing to learn in science: Argument-Driven Inquiry as a way to help undergraduate chemistry students learn how to construct arguments and engage in argumentation during a laboratory course. J. Res. Sci. Teach. 2013, 50 (50), 561−596. (32) Driver, R.; Asoko, H.; Leach, J.; Mortimer, E.; Scott, P. Constructing scientific knowledge in the classroom. Edu. Res. 1994, 23 (7), 5−12. (33) Anderson, C. A. Belief perseverance. In Encyclopedia of Social Psychology; Baumeister, R. F., Vohs, K. D., Eds.; Sage: Thousand Oaks, CA, 2007. (34) Taking Science to School: Learning and Teaching Science in Grades K-8; Duschl, R. A., Schweingruber, H. A., Shouse, A. W., Eds.; National Academies Press: Washington, DC, 2007. (35) Pintrich, P. R.; Schunk, D. H. Motivation in Education: Theory, Research, and Applications, 2nd ed.; Prentice Hall: Upper Saddle River, NJ, 2002. (36) Gay, L. R.; Airasian, P. Educational Research: Competencies for Analysis and Application; Merrill: NJ, 2000. (37) Winkelmann, K.; Baloga, M.; Marcinkowski, T.; Giannoulis, C.; Anquandah, G.; Cohen, P. Improving Students’Inquiry Skills and SelfEfficacy throuh Research-Inspired Modules in the General Chemistry Laboratory. J. Chem. Educ. 2015, 92 (2), 247−255. (38) Grove, N.; Bretz, S. L.CHEMX: An Instrument to Assess Students’ Cognitive Expectations for Learning Chemistry. J. Chem. Educ. 2007, 84, 1524−1529. (39) Coll, R. K.; Dalgety, J.; Salter, D. The Development of a Chemistry Attitudes and Experiences Questionnaire (CAEQ). Chem. Educ. Res. Pract. 2002, 3, 19−32. (40) Barbera, J.; Adams, W. K.; Wieman, C. E.; Perkins, K. K. Modifying and Validating the Colorado Learning Attitudes about Science Survey for Use in Chemistry. J. Chem. Educ. 2008, 85, 1435− 1439. (41) Lawless, K. A.; Brown, S. W. Developing Scientific Literacy Skills Through Interdisciplinary, Technology-Based Global Simulations: Global Ed 2. T. Curr. J. 2015, 26 (2), 268−289. (42) Irez, S. Are we prepared?: An assessment of pre-service science teacher educators’ beliefs about nature of science. Sci. Educ. 2006, 90 (6), 1113−1143. (43) Elmas, R.; Ö ztürk, N.; Irmak, M.; Cobern, W. An investigation of teacher response to national science curridlum reforms in Turkey. Eur. J. Phys. Chem. Edu. 2014, 6 (1), 2−33. (44) Pekkaya, M.; Ç olak, N. Determining the factors in choosing professions. J. Acad. Soc. Sci. Stu. 2013, 6 (2), 797−818. (45) Bandura, A. Social Learning Theory; Prentice-Hall: Englewood Cliffs, NJ, 1977. (46) Bandura, A.; Locke, E. A. Negative self-efficacy and goal effects revisited. J. Appl. Psych 2003, 88 (1), 87−99.
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