Effect of Generative Learning Models Based on Cognitive Conflict on Students’ Creative Thinking Processes Based on Metacognitive

Metacognition is influenced the creative thinking process in Computational Physics courses. The Computational Physics is needed in the business and industrial. However, Computational Physics courses are less attractive for students. The challenge in learning Computational Physics is how to help students effectively develop creative and computational thinking skills. Based on the above, the purpose of this study is to determine the effectiveness of the PGOC3ARE learning model to create the students’ creative thinking skills in Computational Physics learning and to determine the effect of using the PGOC3ARE learning model on metacognitive-based creative thinking skills, especially in Computational Physics courses. The research method used was an explanatory sequential design research method. The research sample was taken through simple random sampling, where the sample was divided into an experimental class and a control class. The sampling technique for collecting qualitative data was purposive sampling. Data analysis using comparative test statistics. The result of the research is that the PGOC3ARE model is effective in shaping students’ creative thinking skills, especially in the Computational Physics course. Furthermore, the PGOC3ARE learning model has a significant positive effect on the development of students’ creative thinking skills in the Computational Physics course with base on metacognition.


Introduction
Computational Physics course discusses various approach methods used to formulate physical phenomena and solve physics phenomena by simulation.The discussion of Computational Physics includes error theory, the solving of nonlinear equations, systems of linear equations, the interpolation and the extrapolation, calculating derivatives numerically and numerical integration, and numerical solutions, ordinary differential equations, solving partial differential equations.The purpose of learning Computational Physics is for a student to master the process of formulating basic numerical analysis techniques to solve physics problems algorithmically.Students are required to have the skills to design computational coding (pseudocode) to solve the problems of physics, the behavior of physics, and natural phenomena by using computational application programs.Responsible for individual work and the achievement of group work, have curiosity, critical, logical thinking, creative, and innovative, disciplined, confident, love science, independent, responsible, and appreciate the work of others, communicative, appreciative and participatory in real life.But on the other hand, Computational Physics courses are less attractive for students [1].Mazvovsky found that to increase student enthusiasm in learning Computational Physics, one must consider useful and contextual material so that student attendance can increase.The challenge in learning Computational Physics is how to help students effectively develop creative and computational thinking skills in Computational Physics through contextual theory and practice.
The Computational Physics course is directed at explaining and understanding the physical phenomena derived from the findings in experiments.The objectives of Computational Physics learning will be achieved if students are encouraged to think computationally in order to form creative and productive individuals who can meet the needs of life and connect science with the needs of business and industry and education [1].This goal is in line with the national education goal, which is to develop students' potential to be a capable, creative, and self-dependent human being.Creative ideas of students learning Computational Physics cannot appear suddenly, but appear after going through an analysis of symbols, facts, and deep thinking about the problems found.The creativity is the result of the process of creative thinking.
Creative thinking is a skill that allows students to consider things from new perspectives and different points of view to face challenges and frame them into new ideas.Creative thinking also creates a safe space to experiment and take risks [2] by looking at the problem from a new perspective [3].Learning that contains elements of creative thinking means involving the students learning to generate and apply new ideas in a particular context, look at existing situations in new ways, identify alternative explanations, and see or make new relationships that produce positive results.Creative thinking skills include the ability (1) The ability to formulate hypotheses focused on the causes and effects of the phenomena encountered; (2) the ability to determine the relationship between variables that affect the phenomena encountered; (3) The ability to break the deadlock of the mind by proposing new algorithms to solve the phenomena at hand; (4) The ability to come up with extraordinary ideas and be able to evaluate the consequences they cause; (5) The ability to sense missing information from a given phenomenon by asking questions to get answers to the missing information; (6) The ability to decompose complex problems into more specific problems [4], [5], [6].The ability to think creatively produces creativity.
The creative thinking process in students at a high metacognitive rate consists of understanding the problem, formulating problem solving strategies, implementing problem solving strategies, evaluating problem solving solutions.Metacognition emphasizes the need to control cognitive thoughts while problem solving, so that metacognition can assist students in understanding concepts [7].Therefore, students with a high metacognitive level can evaluate through the use of different problem solving strategies.Students with a high metacognitive level evaluate the chosen problem solution carefully.The creative thinking process in students with low metacognitive level is understanding the problem, developing problem solving strategies, implementing problem solving strategies, but not evaluating.
The ability to think creatively includes the following aspects: 1) Sensitivity which is the ability to catch and find problems in response to a situation; 2) fluency is the ability to solve problems and provide many answers to problems related to the concept of solving Physics phenomena in a computational manner; 3) flexibility is the ability to use various problem solving algorithms related to the concept of solving Physics phenomena in a computational way; 4) Elaboration is the ability to explain the algorithm for solving Physics phenomena in detail and representatively; 5) Originality is the ability to use new algorithms to solve problems.
Creativity takes place in five stages, namely preparation, incubation, insight, evaluation and elaboration [8].[9].Preparation is looking at previous research related to the problem at hand and seeing what previous researchers have done.The incubation stage is a period of storing information that has been collected in linking various ideas to produce something new and unique.The insight stage is the stage of deep understanding of the problems at hand.The evaluation stage is the stage of self-reflection and testing the understanding of the ideas that have been obtained and determining the most appropriate ideas to work on.The elaboration stage is the process of testing ideas, working out all the ideas that come to mind.Students in the creative thinking process are encouraged to be involved actively in learning to foster creative thinking skills in solving Physics phenomena computationally [10], [11], [12].Students are encouraged to actively participate in conducting open investigations and exploring various techniques and solutions, so that it has a positive impact on their critical and creative thinking skills.
A successful learning strategy in involving students in self-regulation and self-reflection of strengths, weaknesses and strategies for controlling thought processes is a metacognitive strategy [13].Metacognitive ability is a student's ability to control cognitive abilities.student abilities.Students through metacognition are expected to be able to control the six levels of cognitive aspects defined by Benjamin Bloom in Bloom's taxonomy which consist of stages of memory, understanding, applied, analysis and synthetic and evaluation.Metacognitive strategies facilitate students how to learn.Students through metacognition in formal or informal learning experiences can ask questions, develop selfreflection, encouragement to question themselves, direct learning.Get autonomous learning, solve problems with a team, get the opportunity to make mistakes [14].The concept of metacognition is classified into three interrelated components, namely metacognitive knowledge, metacognitive experience, and metacognitive monitoring and control [15].Metacognitive knowledge is based on a declarative knowledge of the cognitive processes and products [16], [17] can be divided into personal knowledge and task knowledge as well as strategic knowledge in the form of specific cognitive operations [18].
Creative thinking can be considered a metacognitive process in which a combination of an individual's cognitive knowledge and evaluation of actions results in creation.Specifically, creative thinking entails a series of cognitive processes, like knowledge and skill acquisition, transformation of knowledge into new forms, and internal and external verification of standardized products.The involvement of metacognition in creative thinking is important, for example, for any creative act to be successful, students must consciously select relevant prior knowledge, and a plan of work should be implemented.Strategies should be flexible and originality and usefulness of a product evaluated.Metacognitive knowledge guides students to select, evaluate, and refine cognitive strategies, which are essential for creative thinking.Students' metacognitive knowledge contributes to specific domain creativity [19] and correlates to metacognitive knowledge and visual-spatial creativity as well as creativity in performing calculations [20].Metacognitive knowledge training significantly improves students' creative problem solving abilities [12], [21].
One of the learning models that encourages students to be involved in building knowledge through the process of knowledge assimilation is the generative learning model.It is one of the learning models based on the view of constructivism.Learning in constructivism encourages students to think critically [22].The constructivism learning model is effective for learning Physics and forming scientific attitudes [23].Proper paradigms of teaching and learning and design models can now be supported by consumer technology to implement constructivism learning theory [24].The model builds on existing research in the areas of cognitive psychology, cognitive development, brain processes, ways of acquiring knowledge, attention, motivation, and knowledge transfer as well as an understanding of human learning and ability, information processing, and talent-treatment interaction.The basic assumption of a Generative learning model is simply that students construct knowledge with their own minds [25] and successfully understand complex everyday situations when actively generating and testing concepts.The generative model implemented with cognitive conflict strategy encourages them to focus on the problem solving process by exploring various information to define their own concepts by following the clues prepared a lecturer that leads to the attainment of learning objectives.Based on the above, a generative learning model with a cognitive conflict strategy oriented to creative thinking (PGOC3ARE) was formed.
The PGOC3ARE learning model and tools have been tested on a limited scale to determine their practicality [26].Practicality is seen from the aspects of the instructions for use, the achievement of learning outcome, student responses, and the difficulty of the lecturer following each learning syntax, as well as the availability of time.The PGOC3ARE model and its tools are practical with a 95% confidence level based on the Aiken scale [27].The practicality coefficient of the PGOC3RE model and supporting equipment by model users (lecturers) is between 0.78 to 0.98 or very practical category [28].This means that the Respondent's Level of Achievement (TCR) of the PGOC3ARE learning model and its supporting devices is categorized as very high.The coefficient of practicality of the PGOC3RE model and its supporting tools from the object point a view of students in the user trial of the model is between 0.68 and 0.82.(a rater of 30 people) or the Respondent Achievement Level (TCR) of the PGOC3ARE learning model and its supporting devices in the high category based on the Aiken scale [27].The PGOC3ARE model developed has six stages, namely orientation, cognitive conflict, disclosure, construct, application, and Reflection Evaluation.Based on the description above, the aim of this study is to determine the efficacy of the PGOC3ARE model in building students' creative thinking skills in Computational Physics learning and to determine the effect of using the PGOC3ARE learning model on metacognitive-based creative thinking skills, especially in Computational Physics courses.

Method
The type is a quasi-experimental research with mixed methods.The research method used in this study is a combination of explanatory sequential design research methods [29].The approach used in this research is descriptive qualitative, which seeks to describe the creative thinking process of students in solving computational physics problems.The explanatory sequential design begins with the collection of quantitative data that provides an overview of the research problem followed by the collection of qualitative data to help explain or elaborate on the quantitative results.Quantitative data was obtained from the results of the creative thinking ability test in Computational Physics while qualitative data was obtained through observation.The study design was a quasi-experimental design with repeated measurements with counterbalance [30].The population is students who are enrolled in the Computational Physics semester July-December 2022.The research sample is divided into two classes, namely the experimental class and the control class totaling 82 people.
The treatment given to the experimental class was learning with the PGOC3ARE learning model, while the control class used a guided inquiry learning model.The procedures for selecting research subjects are: (1) assigning problem-solving tasks to all research subjects; (2) analyzing the results of the task and then grouping the subjects into three categories of high, medium, and high; (4) selecting a subject that represents the answers from each group of answers purposively, namely based on the adequacy of the information or data required; (5) the selected subject is then asked and answered to verify the data on the results of the problem solving task and explore data about the creative thinking process of each research subject.
The research instrument consisted of the main instruments, namely problem solving test questions and creative thinking assessment sheets.Indicator of creative thinking is fluency, flexibility, elaborasi, originality, flexibility dan analysis) serta evaluative.The test conducted in this research is a problem solving test.The questions and answers in this study were to verify the problem-solving project assignments, then analyzed so that students' creative thinking processes in solving computational physics problems were obtained.The indicators of creative thinking skills are fluency, flexibility, elaboration, originality, flexibility and analysis) and evaluative [31], [32], [33].Data were collected from presentations of project assignments and initial practicum assignments done by students.Data on students' creative thinking skills were adopted by Torrance Tests of Creative Thinking [34], [35], [36], [37].The data were analyzed with the statistical similarity test of two averages.The data are normally distributed and homogeneous, parametric statistics are used: one sample Kolmogorov-Smirnov and Shapiro-Wilk and the data are not normally distributed and homogeneous, non-parametric statistics are used, namely the Mann-Whitney U independent sample test.Point in the learning outcomes section in the 3 domains of creative thinking

Pretest
The pretest was used to determine whether the two sample groups had the same creative thinking skills.The pretest data analysis was carried out by independent-samples t-test.The result are as in Table 1.Variance Equality Test F = 0.063 and Sig = 0.803, this number is greater than 0.05, meaning that the variant of the pretest is homogeneous at a significance level of 0.05.Price equal variances assumed with Sig.(2-tailed) on the t-test for the similarity of the means was 0.899.This result shows that there is no difference in the pretest results of the two classes that are the object of research or in other words the two classes have the same initial ability.

Second Comparative Test
The second test was used to determine the effectivity of the PGOC3ARE learning model in building students' creative thinking skills in learning Computational Physics.Data were then analyzed using independent sample t-test statistics.The treatment results data are as in Table 2. Table 3 shows that F_count on Creative Thinking ability after the second stage of treatment is 2,967 with probability 0.091, probability > 0.05 (0.091 > 0.05), then Ho is accepted and can be stated for both variances the same.Because the two variances are the same, in the t-test (t-test) it will be even more appropriate to use the Equal variance assumed basis (it is assumed that both variants are the same).The number shown in t_count Creative Thinking ability after the second stage of treatment with Equal variance assumed is -0.412 with a probability of 0.682.Because 0.682 > 0.05, Ho is accepted so there will be not significant differences in students' creative thinking skills after the treatment is reversed.To see the impact of PGOC3ARE learning model on students' creative thinking ability, the change in students' creative thinking ability between the second test and the third test was calculated.Data were analyzed using independent sample t-test statistics.The data on the students' creative thinking ability differences after the second treatment are shown in Table 4. .with an asymptotic significance 2-tailed or P Value of 0.002 < 0.05).This p value < 0.05 critical limit, meaning that there is a significant difference between the two groups or which means H0 is rejected.These results indicate that there is a significant difference in the creative thinking scores of the two groups that are the object of research or in other words the two classes have different creative thinking abilities at the 0.05 significance level.Group A students were treated with the PGOC3ARE learning model.The creative thinking ability of students in class A (who received PGOC3ARE learning model) was higher than class B (who received Guided Inquiry learning model).This means that the PGOC3ARE learning model will have a significant impact on the creative thinking skills of computational physics students.The results of the second test data analysis and the change in his second test score with the third test show that the PGOC3ARE learning model has a significantly positive effect on the creative thinking skills of students in computational physics courses.showed.Therefore, it can be said that the PGOC3ARE learning model is effective for the creative thinking skills of students in computational physics courses.Then, to find out whether or not there is a strong relationship between the use of the PGOC3ARE learning model on metacognitive-based creative thinking skills, especially in the Computational Physics course, regression analysis was carried out.The results of the practicality regression analysis of the PGOC3ARE model on creative thinking skills are in Table 5.The data in Table 5 shows a regress coefficient x of 0.637 which state for every 1% aditional of the practicality score of the PGOC3ARE model, the level of metacognitive-based creative thinking skills increases by 63.7%.The consistency of the practicality variable of the PGOC3ARE model is 20.714.
where x = Practicality of PGOC3ARE Model and y = Creative Thinking Process Based on Metacognitive.Table 5 shows the value of the determination or R coeficient square is 0.229.The termination coefficient (R) is 0.229, meaning that the effect of practicality of the PGOC3ARE learning model is 22.9%.While the rest (100% -22.9% = 77.1%) was influenced by variables other than the practicality of the PGOC3ARE learning model which were not studied.

Discussion
The results of the different test pretest variable showed no difference because students had the same initial ability that was good in understanding the completion of the Computational Physics phenomenon.This statement can be interpreted that the initial conditions of students can control the level of success of students in creative thinking.The data in Table 2 and Table 4 show that the PGOC3ARE learning model is effective for learning Computational Physics.This happens because the PGOC3ARE model with stages of orientation, cognitive conflict, expressing ideas, building and applying which are the main variables directing Computational Thinking facilitates students in solving problems creatively with high expectations [38].Productive ideation allows learners to make important discoveries about information processing further in learning.
Reflection and evaluation activities also determine the success of learning implementation [39], including Computational Physics lectures and improving academic performance [40].Reflection and evaluation also play a role in increasing students' self-efficacy and self-regulation [41].This means that the PGOC3ARE learning model will have a significant impact on the creative thinking skills of computational physics students.The results of the second test data analysis and the change in his second test score with the third test show that the PGOC3ARE learning model has a significantly positive effect on the creative thinking skills of students in computational physics courses.showed.Therefore, it can be said that the PGOC3ARE learning model is effective for the creative thinking skills of students in computational physics courses.
Students are passionately and actively involved in the learning process, developing concepts and participating in the management of the learning process [43].The application of concepts can increase the stimulation of students in processing relevant information to get new concepts [44].Students through application can test the application of concepts in other practical conditions [45], so that students actively build concepts.Students connect with their own learning experiences and topics studied [46].Students enrich discriminatory ideas with a clear conceptual structure [47].The feedback given has encouraged students to think ahead [48].The process of confession stimulates critical creative cognition to build and explore ideas to solve problems [49].The effect of disclosed variables on real-world efficiency is very useful for making effective real-world decisions [50].Embodiment like this is thought to cause the PGOC3ARE model to be effective in learning Computational Physics.
Students develop critical and creative thinking skills for problems with cognitive conflicts to assess existing knowledge, define concepts and ideas, seek opportunities, consider alternatives, and solve problems.develop.Creative thinking students are involved in thinking broadly and deeply using cognitive or metacognitive skills, using logic, reason, awareness and innovation in their learning at school and in life outside of school.The processing mechanisms underlying creative thinking assume metacognition as the sole cognitive component in self-regulation during representational change and metacognitive self-reflection or self-confidence when generating ideas [51], [52].Creative thinking patterns are metacognitive knowledge that refers to the view of individual creativity (eg, creative thinking patterns) [53] that can affect students' creative performance [42].That is, each student with different types of creative thinking has disparate cognitive processing traits, such as: B. Alternative methods of learning, goal orientation, strategic decision-making, and cognitive persistence, considered important aspects of creativity [54].It has been concluded that creative thought patterns can influence creativity indirectly through other cognitive variables [26].Therefore, further empirical studies are needed to clarify the mechanisms of different entrails of metacognitive awareness in creative thinking.
In this case, students must control and manage their own learning processes and strategies [55 In the era of information and technology, the acceleration and amount about information are changing day by day, and today's information alone cannot conduct up with the times.Therefore, the current education system aims to develop individuals who are able to pass their own cognitive filters and build knowledge rather than simply memorizing existing knowledge.In this case, individuals are expected to possess higher order thinking skills such as self-regulation strategies, critical thinking, problem solving and metacognitive thinking.
Learning that encourages students to think critically can foster meaningful learning and is seen as learning that uses existing knowledge to solve problems and make decisions.In other words, critical thinking is a process of using prior knowledge to clearly understand a problem and make good decisions about it [56].It can be definite that people use critical thinking during the problem-solving process and that problem-solving activities increase the use of critical thinking [57], [58].Some studies have concluded that is related to critical thinking.The construct stage in PGOC3ARE model through the process of student assimilation is sought to develop and change thinking as a consequence of observing the given cognitive conflict, this is done by the lecturer [55].Conflict resolution is a process that includes using a lot of mental operations to move from the existing situation to the target goal [59] by using the background knowledge, skills, and abilities to solve familiar problems.Every individual must have problem solving skills to achieve learning objectives problem solving is a basic required skill for today learners.Problem solving is very important for student success in education and society [60], [61], This leaves students with the problem-solving skills they acquired in the course of teaching and learning.A student's ability to think innovatively in problem solving is the driving force behind intense international competition [62].analysis (breaking down a problem into smaller and more understandable parts), evaluation (determining whether an object or activity meets certain criteria), imagination (forming appearance and ideas in one's mind), synthesis contain (combining actual concepts, object new) [3] which was implemented in the implementation of the PGOC3ARE learning model causing this model to be effective for learning Computational Physics.
Learning that explores creative thinking behavior in the implementation of the PGOC3ARE model encourages students to think creatively.The implementation of the PGOC3ARE model is not only concentrated on the creative dimension, it also considers metacognition.Research still limits the scope of the empirical investigation of individual creativity.However, this study has not highlighted some points of difference regarding the conceptualization of creativity, such as how the elements of novelty and usefulness interact; who should judge a person's creativity; whether creativity refers to a person, process, or product; and how to distinguish creativity from individual innovation.…… The implementation of the PGOC3ARE model at the disclosure stage and the construct stage is given the opportunity to brainstorm ideas, draw or paint algorithms, ask questions, give answers will give birth to different ideas to solve the problems given.Students can do things in different ways and let their minds be influenced by new stimuli and an attitude of being open to new ideas will make students work on developing ideas continuously.Students practice creative thinking skills through various exercises and activities to develop abilities in defining and solving problems.The above process is actually a creative thinking activity.
Based on field notes, it is recorded that in many metacognitive processes, such as analyzing, evaluating, and creating, students appear to apply the build your own problem-solving concept.This implies that students advance and advance their higher order thinking skills when engaged in creative endeavors.Furthermore, indicators of thinking ability (fluency, flexibility, elaboration, and originality) should be strongly manifested in lessons planned to engage students' curiosity through the stages of cognitive conflict.Creative efforts must involve the traits and the affective dimension of creativity is a fundamental dimension in building creative students in Computational Physics lectures.Creative elements of making algorithms and flowcharts as preliminary tasks that appear in Computational Physics learning are highly recommended considering the opportunities for fluency in coding.This study reveals cognitive and affective creative characteristics that blend in originality, innovation and creativity providing a useful basis for creative thinking behavior to solve subsequent problems.The limitations of the research were time and limitations of numerical literacy.It is hoped that the research can be tested on other subjects of the same character.

Conclusion
The PGOC3ARE learning model has a significant positive effect on the development of students' creative thinking skills in Computational Physics courses with metacognition as one of its components.So, the PGOC3ARE model is effective in building students' creative thinking skills, especially in Computational Physics courses.The regression coefficient of 0.637 means that the PGOC3ARE model contributes 63.7% to the improvement of metacognitive-based creative thinking skills.The consistency of the PGOC3ARE model practicality variable is 20.714.The ditermination coefficient (R) of 0.229 means that the use of the PGOC3ARE learning model contributes 22.9% to metacognitive-based creative thinking skills.

Recommendation
Research data are analyzed quantitatively and qualitative research paradigms can be employed to explore additional information and insights on comparable learning designs and topics.Testing of the PGOC3ARE model is therefore intended for computational physics courses only.Testing the reliability of the PGOC3ARE model requires the involvement of other courses that have similar course characteristics to the Numerical Analysis and Algorithms course and the Computer Programming course.

Table 1 .
Data and Results of Prestest Data Analysis

Table 2 .
Data on Creative Thinking Ability Results after the first stage of treatment The creative thinking ability of class B students (getting the PGOC3ARE learning model) is higher than class A (getting the Guided Inquiry learning model).This means that the PGOC3ARE learning model has a significant effect on students' creative thinking skills in the Computational Physics course.3.1.3.Third Comparative TestThe third test is used to find out the effectiveness of the PGOC3ARE learning model in building students' creative thinking skills. in Computational Physics learning as a counter balancing, where group A gets the PGOC3ARE learning model and group B gets the Guided Inquiry learning model.The third test data analysis was carried out by using the independent-samples t-test.The result are as in Table3.
critically limits, meaning that a significance difference exists between the two groups or which means H0 is rejected.These results indicate a meaningful difference in the creative thinking scores of the two groups that became the object of the study or in other words, the two classes have creative thinking skills that are different at the 0.05 significance level.Group B students were treated with the PGOC3ARE learning model.

Table 3 .
Data on Creative Thinking Ability Results after the second stage of treatment

Table 4 .
Data on the difference in students' Creative Thinking Ability scores on the second test and the Test

Table 4
reveals a U value of 199.00 and a corresponding W value of 605.00.If it is converted to Z value, the result is -3.047

Table 5 .
The results of the practicality regression analysis of the PGOC3ARE model on creative thinking skills