The purpose of the present study was to examine the effects of cooperative training strategies to enhance students' socioscientific decision making as well as their metacognitive skills in the science classroom. Socioscientific decision making refers to both “describing socioscientific issues” as well as “developing and evaluating solutions” to socioscientific issues. We investigated two cooperative training strategies which differed with respect to embedded metacognitive instructions that were developed on the basis of the IMPROVE method. Participants were 360 senior high school students who studied either in a cooperative learning setting (COOP), a cooperative learning setting with embedded metacognitive questions (COOP+META), or a nontreatment control group. Results indicate that students in the two training conditions outperformed students in the control group on both processes of socioscientific decision making. However, students in the COOP+META condition did not outperform students in the COOP condition. With respect to students' learning outcomes on the regulation facet of metacognition, results indicate that all conditions improved over time. Students in the COOP+META condition exhibited highest mean scores at posttest measures, but again, results were not significant. Implications for integrating metacognitive instructions into science classrooms are discussed.
Over the past decades curriculum authorities as well as science educators and researchers worldwide have called for changes in the way science is taught at schools (e.g., [
A growing body of research within the area of science education highlights the notion that the implementation of socioscientific issues into science classrooms can enhance students’ learning outcomes with respect to conceptual scientific knowledge as well as reasoning and argumentation skills (e.g., [
Moreover, learning about complex issues needs to be carefully structured, as prior research also showed that students can easily be distracted when working on socioscientific issues where the outcome is uncertain [
Cooperative learning has been on the international agenda for more than half a century by now both in educational research and in educational practice (e.g., [
Numerous research studies could actually show that cooperative learning has beneficial effects not only on student achievement, but also on student interest as well as social skills [
Metacognitive guidance has been extensively used and analysed in the area of mathematics education (e.g., [
Within the area of science education, fewer studies explicitly implement cooperative-metacognitive trainings or self-regulated learning in science classrooms. Zion and colleagues transferred the use of IMPROVE to an intervention study on scientific inquiry in microbiology [
Metacognition and self-regulation are often treated as two separate concepts in the literature [
Socioscientific issues represent controversial issues of modern science that involve social, political, economical, and ethical considerations [
Working with socioscientific issues in the science classroom poses high processing demands on students because they are engaged in various information search and evaluation processes as well as argumentation and reasoning processes (e.g., [
There is empirical evidence that students can be promoted with respect to socioscientific decision making and reasoning. Several studies focused on the quality of argumentation and reasoning processes while dealing with socioscientific issues (e.g., [
Few studies exist that analyzed the effect of embedded metacognitive or self-regulated trainings on students’ socioscientific decision making and reasoning. Gresch and colleagues showed in a pre-post-follow up control-group design that a web-based training program with additional metacognitive prompts to support task analysis enhances students’ socioscientific decision making with respect to “evaluating solutions” [
On the basis of existing research, we aimed to investigate the effect of two cooperative training strategies on students’ socioscientific reasoning and decision making. As described above, working on socioscientific issues is a complex endeavor. We assume that cooperative learning settings will provide learners with multiple opportunities to engage in peer-to-peer interactions that are needed to reason and argue about complex socioscientific problems. This may than lead to deeper information processing as well as elaboration processes and eventually to better individual performance. Referring to Kirschner and colleagues [
In more detail, we hypothesize that students who study in cooperative learning settings will produce better learning outcomes with respect to socioscientific reasoning and decision making than students who study under more traditional, individual instruction.
Similar to existing research that highlights the importance of metacognitive guidance to support group processing, we also assume that individual student achievement will be enhanced through an additional metacognitive training that explicitly supports students in formulating and answering questions. Referring to Mevarech and Kramarski’s work on mathematical problem solving [
Participants included 360 senior high school students (151 males and 209 females, mean age: 17.35 years;
Both training conditions (COOP and COOP+META) were identical in terms of lesson structure and time as well as context and tasks. They only differed with respect to the presence or absence of metacognitive instruction. While students in the COOP+META condition spent time on the metacognitive guidance, students in the COOP condition had time to elaborate on the socioscientific issue of palm oil production in Indonesia (see below). Both, the COOP as well as the COOP+META condition used the same set of cooperative learning methods such as the jigsaw and the fishbowl method. In addition, think-pair-share processes were included in all of the lessons [
The COOP+META condition was developed using the IMPROVE method [
The socioscientific issue addressed in both training conditions was the issue of palm oil production in Indonesia. There is an increasing demand on palm oil worldwide as an ingredient for cosmetics and food, but especially with respect to its potential as a biofuel. Palm oil is typically produced on monocultures within the Indonesian rainforest. Due to the increasing demand, more and more plantations emerge. Many people on Sumatra, one of the main islands in Indonesia, work on these plantations to earn their living. As a consequence, the Indonesian rainforest decreases. In addition, indigenous people who traditionally live in and subsist on the rainforest are negatively affected. The described problem represents a typical socioscientific issue. It is factually and ethically complex and needs to be addressed by incorporating ecological, economical, and social aspects and perspectives [
Students in the nontreatment control group received traditional, individual instruction. They studied according to their regular school curriculum, which did not include the specific socioscientific issue of palm oil production in Indonesia. However, working on socioscientific issues is mandatory according to the national educational standards and all training conditions were obliged to teach to these standards [
Teachers in both training groups received an introductory training on the learning material. All teachers were familiar with cooperative learning and implemented it regularly in their classrooms. Teachers in the COOP+META condition received a one day introductory training on the IMPROVE method. The training was designed in the biology education research group and administered to the teachers by the researchers themselves. Teachers were first introduced to the theoretical construct behind the IMPROVE method and then worked on exemplary student tasks that included the four different metacognitive questions. Teachers in the control group received no specific training.
Students’ learning outcomes were measured using two 45 min paper-and-pencil tests on socioscientific decision making prior to and after the intervention. The pre- as well as the posttest consisted of three socioscientific issues (SSI) that were identical in structure but used different contexts in order to keep students motivated at the posttest. In addition, different contexts were used to counteract increases in students’ learning outcomes at the posttest that are only due to training effects on the questionnaire (Appendix
Contexts for the different SSIs used in the pre- and posttest questionnaire on socioscientific decision making.
Pretest | Posttest | |
---|---|---|
Describing socioscientific issues | Issue no. 1: |
Issue no. 1: |
Developing solutions to socioscientific issues | Issue no. 2: |
Issue no. 2: |
| ||
Evaluating solutions to socioscientific issues | Issue no. 3: |
Issue no. 3: |
All test items to these socioscientific issues were presented in an open-ended format. With respect to the first two socioscientific issues, students had to describe the problem as well as to develop sustainable solutions to the problem. With respect to the third socioscientific issue, students were asked to evaluate presented solutions in terms of their sustainability and to suggest improvements to these solutions. Students’ responses to the open-ended questions were coded independently by two of the researchers. The final scoring guide consisted of 10 items (Table
Scoring guide for the assessment of students’ socioscientific decision making (pre- and posttest).
No. | Item description | Score | |||||
---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | |||
Scale 1: describing socioscientific issues | 1, 3 | Sociosocial relation (sustainable and nonsustainable users) | No response or describes either the role of nonsustainable or sustainable users | Describes both social groups but not the relation between the two | Describes both social groups and their relation | ||
2, 4 | Socioecological relation (nonsustainable users and resource) | No response or describes either the role of nonsustainable users or the resource | Describes the nonsustainable users and the resource but not the relation between the two | Describes the nonsustainable users and the resource and their relation | |||
| |||||||
5, 6 | Developing solutions | No response | Develops a solution on the basis of one solitary aspect (ecological, economical, or one of the social aspects) | Develops a solution on the basis of 2–4 solitary aspects | Develops a solution on the basis of two aspects and their relation | Develops a solution on the basis of two or more relations | |
Scale 2: developing and evaluating solutions to socioscientific issues | 7, 8 | Evaluating solutions | No response | Evaluates a presented solution by referring to one solitary aspect |
Evaluates a presented solution by referring to 2–4 solitary aspects | Evaluates a presented solution by referring to one or more relations between aspects | |
9, 10 | Suggesting improvement to solutions | No response | Makes a sensible suggestion but not on the basis of relevant aspects | Makes a suggestion on the basis of one aspect |
Makes a suggestions on the basis of 2-3 solitary aspects | Makes a suggestion on the basis of one or more relations between aspects |
The socioscientific decision making questionnaire (pre-and posttest version) includes two scales. Scale 1 consists of four items that represent the description of SSIs (items 1-2 for issue no. 1, items 3-4 for issue no. 2; Table
To assess general metacognition a questionnaire developed by A. Kaiser and R. Kaiser [
With respect to the socioscientific decision making scales, data were analysed as follows. Concerning “Describing Socioscientific Issues”, we conducted a one-way ANOVA to examine group differences between the control group and the two experimental groups at the pretest. Results indicated no significant differences prior to the beginning of the intervention with respect to scale 1 (
Mean scores and standard deviations on “describing socioscientific issues” (scale 1) by time and treatment.
COOP | COOP+META | Control | |
---|---|---|---|
Pretest | |||
|
2.59 | 2.80 | 2.60 |
SD | 1.87 | 1.82 | 1.70 |
| |||
Posttest | |||
|
5.04 | 4.88 | 3.53 |
SD | 1.61 | 1.64 | 1.66 |
The repeated measures ANOVA indicated a significant main effect for time (
With respect to “Developing and Evaluating Solutions” we also conducted a one-way ANOVA to check group differences on the pretest scores. Results indicated that there was a significant difference between groups (
Mean scores and standards deviations on “developing and evaluating solutions” (scale 2) by time and treatment.
COOP | COOP+META | Control | |
---|---|---|---|
Pretest | |||
|
9.54 | 8.72 | 8.59 |
SD | 3.08 | 2.91 | 2.82 |
| |||
Posttest | |||
|
11.98 | 10.69 | 9.05 |
SD | 3.33 | 3.46 | 3.34 |
Results from regression analyses showed that prior knowledge as well as both contrasts predict students’ learning outcomes at posttest measures. Table
Multiple regression predicting posttest performance on “developing and evaluating solutions” (scale 2) by prior knowledge and treatment condition.
|
SE |
| |
---|---|---|---|
Step 1 | |||
Prior knowledge (pretest scores) | 0.53 | 0.06 | .44*** |
| |||
Step 2 | |||
Prior knowledge (pretest scores) | 0.51 | 0.06 | .42*** |
Contrast 1 (control versus COOP and COOP+META) | 0.66 | 0.12 | .26*** |
| |||
Step 3 | |||
Prior knowledge (pretest scores) | 0.49 | 0.06 | .41*** |
Contrast 1 (control versus COOP and COOP+META) | 0.67 | 0.12 | .27*** |
Contrast 2 (COOP versus COOP+META) | −0.44 | 0.20 | −.10* |
Note:
With respect to the regulation facet of general metacognition, a one-way ANOVA was conducted to examine possible differences between groups at the pretest. Results indicated no significant differences prior to the beginning of the intervention (
Mean scores and standards deviations on metacognition (regulation facet) by time and treatment.
COOP | COOP+META | Control | |
---|---|---|---|
Pretest | |||
|
16.66 | 17.23 | 16.86 |
SD | 4.08 | 3.87 | 3.73 |
| |||
Posttest | |||
|
18.63 | 19.17 | 17.59 |
SD | 4.75 | 4.32 | 4.54 |
The repeated-measures ANOVA indicated a significant main effect for time (
The major purpose of the present study was to examine the effects of two cooperative training settings (COOP and COOP+META) on students’ socioscientific decision making and metacognition. Socioscientific decision making refers to the description of socioscientific issues as well as to the development and evaluation of solutions to socioscientific issues. Findings show that both training groups outperformed the nontreatment control group on both scales. This is in line with a large body of research that identified beneficial effects of structured cooperative learning settings on students’ learning outcomes (for an overview, e.g., [
However, with respect to the COOP+META treatment condition, findings did not meet our expectations. Students who studied in the COOP+META condition did not benefit from the embedded metacognitive training, as there were no differences on “Describing Socioscientific Issues” (scale 1) between the COOP and the COOP+META condition. With respect to “Developing and Evaluating Solutions” (scale 2), findings even exhibited a negative relationship between the corresponding contrast variable and students’ performance on the scale at the posttest. This, at first side astonishing, negative impact raises several questions. Why did students not benefit from the additional embedded metacognitive training and in more detail, which factors can be identified that lead to the decline in posttest measures when compared to the COOP condition? What can we deduce with respect to future research?
Empirical research on the effects of cooperative learning settings on student achievement suggests that students benefit most from collaboration if task complexity is high because individuals are more willing to distribute information processing among group members to reduce cognitive load [
When confronted with socioscientific issues students have to perform a variety of information search and evaluation processes as well as reasoning and argumentation processes. Students may likely have experienced cognitive overload during group work as they had to solve a complex socioscientific issue, collaborate with their peers, and understand and work with the metacognitive instructions (cf. [
Another important aspect addresses the issue of successful implementation of metacognitive trainings into the science classroom. Referring to existing research three fundamental principles have to be acknowledged: ensuring connectivity, being explicit about the function of metacognitive guidance, and extensive and prolonged metacognitive training [
Moreover, written comments on lesson plans from teachers who taught in the COOP+META condition revealed that the use of reflection questions especially at the end of lessons often fell short. This has two possible reasons. On the one hand, lesson plans were quite packed with respect to learning goals on socioscientific decision making, the socioscientific issues taught as well as the extra metacognitive guidance. Although teachers aimed faithfully to implement the lessons according to our instructions, it is only reasonable that they considered the curricular requirements with respect to socioscientific decision making first.
On the other hand, teachers in the COOP+META condition had no prior experience with metacognitive instruction, which might have led to difficulties during the intervention. Although they were trained in using the metacognitive questions, a shortcoming of the present study is that teachers were not additionally supported during the intervention in their classrooms.
With respect to posttest measures for metacognition, results indicate that all groups, including the control group, improved on the metacognition scale at posttest measures. Although the COOP+META condition had the highest mean score, differences between groups were not statistically significant. Thus, one has to be cautious about interpreting these results. However, they might still contribute to the discussion described above that students either concentrated more on solving the socioscientific issues or on working with the metacognitive questions. Given the highest mean scores on the posttest measures, one might argue that students who studied under the COOP+META condition focused more on working with the metacognitive guidance.
Another explanation to this finding is that the intervention itself aims to enhance students’ critical thinking and reflection on socioscientific issues and possible solutions strategies. While developing and evaluating solution strategies, students need to engage in critical thinking to be able to identify nonsustainable solutions, to incorporate multiple perspectives and to monitor and regulate their own problem-solving processes, especially during group work. Developing solutions to a socioscientific issue can be described as a special problem solving process, which can be divided into three main aspects. First, students need to understand and describe the problem situation, second they need to develop possible solutions on the basis of relevant information, and third, they need to evaluate possible solutions in order to reach an informed decision [
Implications for future research are diverse, but one major aspect refers to the improvement of teacher support during the intervention. Apparently, the introductory training to the metacognitive guidance was not sufficient to enable teachers to implement both socioscientific decision making and metacognitive instruction into their science classrooms as we had wished. In future research, we need to be even more aware of the “teachers’ dilemma” [
With respect to the methodological limitations of the present study, a mixed-method approach should be applied in future research that converges both product and process data (e.g., [
In addition, research needs to be done to shed more light on the relationship between the two concepts of socioscientific decision making and metacognition. As described above, dealing with socioscientific issues can be described as a problem solving process. Consequently, students are already engaged in reflection and monitoring processes. Thus, it would be extremely important to analyse in depth which processes with respect to the regulation of cognition are being promoted by socioscientific decision making in the science classroom. Therefore, process data are absolutely vital (cf. [
What are the goals of our task? Can we describe the current situation of the person we are dealing with? Take some notes. Which aspects are essential to develop a good solution from the perspective of …? Take some notes. How should we proceed to develop a solution and in which way can we apply the strategies from previous lessons? Quote some.
Are we still on task or are we running off the track? Are we incorporating all essential aspects?
From the perspective of …, did we consider all important aspects for our solution? If our solution to the problem was implemented, how would the situation improve from our perspective? Take some notes. Anticipate the consequences that our solution would have for the other social groups! Take some notes.
Rattan is a very popular material for the production of chairs, armchairs, or outdoor furniture. In the 1980s furniture that was made out of Rattan became popular in Europe and North America and has been popular ever since. 90% of the Rattan that is used in the furniture industry stems from Indonesian Rattan. […].
In Sulawesi, one of the Indonesian islands, indigenous people, who live in and subsist on the rainforest, collect Rattan. They use Rattan to make ropes for fishing or for farming. They also use Rattan for building their houses. […]. When collecting Rattan, they take care that some of the shoots will not be harvested, so that the Rattan plants are able to resprout.
Other Sulawesian people also collect Rattan. They do not only need it for their own supply but they collect and sell it to agents who in turn sell it to the furniture industry. These people also depend on collecting Rattan to assure their livelihood. The money that they get depends on the amount as well as the weight and diameter of the harvested Rattan stems. They harvest Rattan in large groups so that they can collect a large amount of Rattan per day. Often, they collect all of the Rattan shoots in one area. The harvest is being collected and then transported out of the rainforest.
Rattan is a palm that climbs through and over other vegetation. Depending on the Rattan species, it takes about 5–25 years to harvest Rattan for the first time. It grows 0.2–1.5 meters per year. For resprouting, it is important that enough Rattan shoots remain in the forest. Otherwise, Rattan species will likely decline within the area.
Although it is forbidden to collect Rattan within the national park on Sulawesi, illegal harvesting still takes place as park rangers often cannot control the whole area. As a consequence, Rattan species are also under threat in the national park.
Describe the problem situation and explain the interrelations of central aspects. Develop a possible solution to this problem that acknowledges these interrelations.
Due to the high demand for shrimps in Germany and worldwide, shrimp farming in mangrove areas of Southeast Asia is steadily increasing. Shrimp farms provide jobs for many people but also have negative side effects on mangrove areas as well as on the people who live in these areas and subsist on the mangroves.
In Europe, indoor shrimp aquacultures will be built that simulate conditions of mangrove areas, in particular marine water conditions. In such aquacultures, shrimps can be raised up to their requested size and then be sold to the food industry.
Evaluate both solutions with respect to their sustainable development. Consider positive and negative outcomes in case these solutions would be considered for implementation. Develop suggestions for improvement for both solutions. Explain!
The intervention study was conducted with support from the German Research Foundation (DFG) and its graduate research program 1195 “Understanding and Enhancing Educational Congruence in Schools.” The development of the test instruments for socioscientific decision making were supported by Grant BO 1730/3-2 from the German Research Foundation (DFG) in the Priority Program “Competence Models for Assessing Individual Learning Outcomes and Evaluating Educational Processes” (SPP 1293).