cognitive complexity

The purpose of this study was to investigate the effect of educational approaches on cognitive complexity and social problem solving skills of high school students in district 2 of Shiraz. This research was practical in terms of purpose and descriptive in terms of nature and method, semi-experimental with two groups and cross-sectional in terms of time. The statistical population of this research includes all male and female high school students of district 2 of Shiraz, and according to the purposeful sampling, 40 people (pre-test and post-test groups) were tested. In this research, in order to measure the independent variables, training sessions were held with a combined and traditional approach in 10 two-hour sessions for students. To measure cognitive complexity from the standard questionnaire of Mobaraki et al. (2015) and to measure the social problem solving skill from the short form of the Revised Social Problem Solving Questionnaire (SPSI-R), (Dzorila et al., 2014), the use and Cronbach's alpha level were used, respectively. 0.892 and 0.961 were obtained. The collected data were statistically analyzed using SPSS software and at two levels of descriptive statistics and inferential statistics (independent t-test and one-way analysis of covariance). The results of the covariance analysis test showed that the combined educational approach had a significant impact on cognitive complexity and problem solving skills.

A crucial objective of education is to enhance the cognitive functions and deepen the knowledge of learners. This is accomplished by strengthening higher mental functions and fostering cognitive development through engagement in complex thinking. Activities such as exploration and problem-solving play a significant role in facilitating cognitive development among learners. The Norman Webb Depth of Knowledge (DOK) framework enables teachers to elevate the cognitive complexity of learners.

This study aimed to introduce a curriculum model grounded in the Depth of Knowledge (DOK) framework to enhance the cognitive complexity level of learners. The research employed document mining and categorical content analysis methods. Various databases including Science Direct, Google Scholar, Springer, Taylor & Francis, Eric, and Emerald were scrutinized for relevant literature published between 1997 and 2014. Initially, specific keywords and terms such as  of knowledge of Webb, complexity of learners, of depth of knowledge, of cognitive complexity articles and texts. A total of 65 documents were identified, with 30 of them aligning with the research objectives. Through content analysis, primary and secondary themes were extracted from the resources, leading to the development of a knowledge-based curriculum model. To ensure validity, the model was reviewed by experts, and their feedback was used to calculate the Content Validity Coefficient (CVR), indicating the model's acceptance among experts.

The research findings in this model introduce four levels of recall and reproduction, skills and concepts, strategic thinking, and extended thinking. These levels predict elements of objectives, method of action, activities, and evaluation appropriate to each level. The curriculum model, based on the depth of knowledge, aims to strengthen skills such as analysis, reasoning, judgment, decision-making, leadership, problem-solving, critical thinking, flexible thinking, and creative thinking. The content based on in-depth knowledge aims to prepare learners to confront complex and ambiguous situations in life. The assessment aligned with in-depth knowledge adjusts the level of questions and activities from low to high complexity.

In the knowledge depth model, learners participate in exploratory and problem-solving tasks, often acquiring knowledge through mental exertion and engagement. Involving students in activities such as interpretation, prediction, inference, classification, analysis, reasoning, critique, invention, design, execution, participation, research, synthesis, self-monitoring, production, and presentation contributes significantly to their cognitive development.

The purpose of this study was to investigate how an experiential science curriculum, based on depth of knowledge, affects the cognitive complexity level of students in the experimental science course. The researcherws employed a quasi-experimental pre-test, post-test design with a control group. The sample of the study involved 46 fifth-grade male students in Famenin city, chosen through cluster sampling and randomly assigned to either the control or experimental group. A cognitive complexity test, developed by the researchers, was used to assess the fifth-grade experiential science curriculum. Initially, both groups underwent a pre-test to measure cognitive complexity in the science lesson. The experimental group followed the experiential science curriculum utilizing a depth of knowledge model, while the control group received traditional instruction. After the intervention, a post-test evaluating cognitive complexity in science was given to both groups. Covariance analysis of the data (F(1,43)=526/36; p<0/05, p=0/001) indicated a significant difference in post-test cognitive complexity scores between the two groups, demonstrating a positive impact of the experiential science curriculum, based on depth of knowledge, on the cognitive development of students in the science curriculum

Competitiveness is a complex and multidimensional concept, making it possible to get high-quality feedback from the environment. This research was designed in order to improve the competitiveness capability; because competitiveness plays a basic role in an organization’s productivity. To this end, we employed the cognitive complexity as a strategic concept using its key components including market sensation and customer psychology. Moreover, we examined three dimensions of market intelligence to develop the model. Data was collected through in library studies and interview with master students of Tehran University, school for performing arts and music. Collected data was analyzed by the system dynamics method with the aim of variables’ future behavior estimation. In doing so, 2 scenarios were simulated using Vensim PLE software. In the first scenario, market sensation led to strategic innovation through requisite infrastructure to create and disseminate intelligence. In the second scenario, customer psychology was identified as an effective factor in market accountability and competency creation. Findings showed that little improvement in customer psychology causes more customer perceptual competency. To understand and interpret the complex environment, designing an integrated and intelligence information systems is recommended. This is required to achieve both strategic innovation and organization competency simultaneously in order to increase the capacity of competitiveness.