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One of the fundamental human cognitive processes is problem solving. As a higher-layer cognitive process, problem solving interacts with many other cognitive processes such as abstraction, searching, learning, decision making, inference, analysis, and synthesis on the basis of internal knowledge representation by the object–attribute-relation (OAR)...
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... Recent research on cognition shows that the cognitive process has a physical basis concerning the brain process with over a hundred million nerves in sensory organs [Adam [1], Baars and Gage [3], Berthoz [5], Hugdahl [12], John and Schwartz [16], Mesulam [18], Mountcastle [20], O'Shea [21], Swanson [25], Tucker [26]]. Each of these cells can possess up to twenty thousand connections with different other nerve cells called the neurons [Shepard and Podgorny [23], Turk and Salovey [27], Van Gog et al. [28], Wang and Chiew [29]]. ...
The cognitive response is a range of mental processes relating to the acquisition, manipulation, storage, and retrieval of information. It helps to underpin a lot of daily life activities both health, age span, and diseases. The main ability to test and monitor cognitive performance across the lifespan opens up the chance for both patients and users to be identified and access certain treatments faster and stay healthy and also increase cognitive perception by helping to optimise a given process. The paper addresses concepts in cognitive response by data marginalisation using aggregate residuals of the user to understand their cognitive response based on five main classes of user cognition to solve a particular problem. Forty participants were recruited to test the level of cognition on a complex mathematical problem, they were asked to solve these problems using the shortest means to arrive at the solution. The result shows that the complex mood is usually related to these forms of problem while the user is relaxed and complexity in a problem doesn't necessarily mean a high optimal response at peak level but rather a decrease in amplitude of the person's response to task performance.
... Problem-solving is a cognitive process of the brain that searches for a solution to a problem or a path to a goal. Once a problem object has been identified, problem-solving can be viewed as a memory-based search for a relationship between a set of solution goals and alternative paths (Wang & Chiew, 2010). Therefore, the cognitive process is based on problem-solving in learning and decision-making. ...
... Numerous disciplines, such as cognitive informatics, computer science, management science, economics, sociology, psychology, political science, and statistics, employ decision theories extensively. Additionally, the results support Wang and Chiew (2010) that human problem-solving is one of the most fundamental cognitive functions. As a higher-order cognitive process, problem-solving interacts with various other cognitive processes, including abstraction, searching, learning, decision-making, inference, analysis, and synthesis. ...
Objective: With the sudden COVID-19 shift away from the classroom in many parts of the world, some question whether adopting online learning or distance education will persist post-pandemic and how such a shift would affect the global education sector. This study explains how distance education (online learning) effectiveness can be improved by focusing on engagement, motivation, and cognitive processes by enhancing student satisfaction among higher education students at a university in Thailand. Method: A qualitative approach was used, with six respondents being interviewed. Purposive sampling was used to select university students who had completed distance education and online learning at a Thai university. The data was analysed using content analysis. Result: Online learning effectiveness is influenced by student satisfaction with online learning methods related to student engagement, motivation, and cognitive process. Moreover, student satisfaction is very crucial in distance education (online learning) and learning effectiveness. Conclusion and Recommendation: The implications could be applied to increase online learning effectiveness by focusing on student engagement, motivation, and cognitive processes and enhancing student satisfaction. The recommendation is to consider focus group discussions, which could provide insightful findings for future research. Moreover, a quantitative study, such as online questionnaires, should be considered.
... In humans, problem-solving ability is measured using various psychometric tests that can target more specific cognitive traits than those designed for non-human animals. Human problem-solving ability has been shown to rely on inferential and causal reasoning, exploration, innovation, general intelligence, and several executive functions (i.e., perception, recognition, memory, learning) (Wang and Chiew 2010). However, identifying the mechanisms underlying behavioural responses in non-human animals is much more challenging because a language-based approach cannot be used. ...
Although problem-solving tasks are frequently used to assess innovative ability, the extent to which problem-solving performance reflects variation in cognitive skills has been rarely formally investigated. Using wild breeding great tits facing a new non-food motivated problem-solving task, we investigated the role of associative learning in finding the solution, compared to multiple other non-cognitive factors. We first examined the role of accuracy (the proportion of contacts made with the opening part of a string-pulling task), neophobia, exploration, activity, age, sex, body condition and participation time on the ability to solve the task. To highlight the effect of associative learning, we then compared accuracy between solvers and non-solvers, before and after the first cue to the solution (i.e., the first time they pulled the string opening the door). We finally compared accuracy over consecutive entrances for solvers. Using 884 observations from 788 great tits tested from 2010 to 2015, we showed that, prior to initial successful entrance, solvers were more accurate and more explorative than non-solvers, and that females were more likely to solve the task than males. The accuracy of solvers, but not of non-solvers, increased significantly after they had the opportunity to associate string pulling with the movement of the door, giving them a first cue to the task solution. The accuracy of solvers also increased over successive entrances. Our results demonstrate that variations in problem-solving performance primarily reflect inherent individual differences in associative learning, and are also to a lesser extent shaped by sex and exploratory behaviour.
... The meta-unsupervised algorithm involves the next steps: feature extraction of the samples of a current base-task; normalization of the extracted features; application of either Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (T-SNE) [36], or Uniform Manifold Approximation and Projection [37], for dimensionality reduction of the extracted features; application of an unsupervised method for clustering; and selection of the best metaparameters, considering clustering accuracy metrics, to solve the current base-task. These steps are described next. ...
Humans can solve image classification tasks by learning from a few images and reusing prior-knowledge. In Artificial Intelligence, deep-learning models have been implemented to simulate human learning and face problems with little data available, few-shot learning. Nevertheless, one crucial problem of deep-learning is the selection of architectures and initial parameters that accomplish the requirements for a specific task. Therefore, we propose a novel methodology based on the meta-learning paradigm, which reuses prior- and meta-knowledge to select the best architecture and its initial parameters to solve different few-shot image classification tasks, as humans do. Our methodology was designed to understand the knowledge flow of the meta-learning paradigm by dividing the learning into prior-models, meta-models, meta-unsupervised algorithm, and base-models. We considered 9 architectures of deep convolutional neural networks as prior-models. Also, we propose a meta-unsupervised algorithm inspired by the human-cognitive problem-solving process, which acquires knowledge by solving tasks to recommend initial parameters to solve other new tasks. Furthermore, we propose a New Task Distribution Scheme to better evaluate few-shot learning models and analyze the difficulty of the new tasks. We evaluated our meta-learning methodology by applying the NTDS to the Mini-ImageNet and Caltech-UCSD-Birds-200-2011 (CUB) datasets. The achieved Adjusted Mutual Information average scores are 0.955 (zero-shot) and 0.957 (five-shot) for Mini-ImageNet, and 0.822 (zero-shot) and 0.848 (five-shot) for CUB. Moreover, we demonstrated the applicability of our meta-learning methodology in a real-world scenario using a new copro-parasite dataset. The performances of our meta-learning methodology are competitive regarding the state-of-the-art unsupervised few-shot learning models.
... The constructivism learning theory may influence these students to decide based on their experiences. Making a decision is a cognitive process within the brain in which the students search for solutions to any decision or problem (Wang & Chiew, 2010). Generally, students who graduate from secondary school are often confronted with deciding on a career path (Latifah, 2015;Lee, 2009;Winson & Yazdanifard, 2021). ...
Most students in Malaysia will continue their studies at a higher level after completing their SPM examination. Tertiary education is becoming increasingly crucial as Malaysia strives to become a developed country. Students frequently face difficulties when deciding whether to continue their studies or not. Their minds will be preoccupied with where to study and what field to learn. In reality, many students are hesitant to continue their education and begin working immediately upon completion of secondary school, even more so when they have developed diverse skills throughout their years in upper secondary school. This study explores the motivation factors that upper secondary vocational programs students to pursue further studies in hospitality programs. Understanding SPM leavers' intentions to continue their education in the hospitality sector is critical for higher education institutions and the hospitality industry. This study will contribute to a better understanding of what is going on in the minds of students considering pursuing their studies in hospitality programs. The industry's labour force requires more intellectual capital and competencies to satisfy growing demands. This study can generate ideas and insight into the acceptance and appeal of the upper secondary vocational program among secondary school students and recommend ways to improve the syllabus if necessary. This study may assist students in better comprehending the choices and benefits of continuing their education in hospitality programs.
... However, those constructs organically emerged from both the qualitative and quantitative data. Problem solving and leadership are soft skills that have been identified as basic soft skills relevant across cultures (Agarwal & Ahuja, 2014;Cukier et al., 2015;Holmes, 2014;WHO, 2012;Zhong et al., 2010). Despite data-driven nature of this scale development, we will still suggest that there should investigate the degree to which assessment of the problem-solving skill and leadership skills fits the context of Botswana in order to expand the scale for future use. ...
There are concerns that soft skills assessment has been conceptualized within the Western context and may not reflect the indigenous African worldview. Without relevant soft skills assessment contextualized in the African cultural cosmology, there is a limitation in assessing African conceptions of abilities. The purpose of this study was to identify relevant soft skills for secondary/high school students and develop a scale relevant for assessing soft skills in Botswana. An exploratory sequential mixed methods design was used to explore the perceptions of 23 education stakeholders on relevant soft skills for secondary students through in-depth interviews. The qualitative findings were used to develop a 63-item Soft Skills Assessment Scale which was administered to a sample of 306 senior secondary school students selected from three educational regions in Botswana. Exploratory factor analysis was conducted to assess the latent factor structure of the scale. Through principal component analysis, four factors were extracted with underlying 38 items. However, a confirmatory factor analysis confirmed a four-factor model (Perseverance, Civic virtue, Teamwork, and Communication) based on a final 14-item scale with Cronbach’s alphas above .60 and Cronbach’s alpha of .82 for the entire scale. Convergent and discriminant validities of the scale were within an acceptable range. The key contribution of this study was the development of a psychometrically valid and reliable Soft Skills Assessment Scale (SSAS) in the context of Botswana.
... By engaging in problem-solving activities, students can enhance their thinking abilities and become more proficient in resolving mathematical issues. The acquisition of problem-solving skills is not solely a desired outcome in the study of mathematics, but, rather, it is the primary focus that lies in the development of effective problem-solving strategies (Wang & Chiew, 2010). ...
The purpose of this study was to obtain a description of the results of the analysis of mathematical problem solving for students with musical intelligence and kinesthetic intelligence. This type of research is qualitative research. The research subjects were one student with musical intelligence and one student with kinesthetic intelligence. The results of this study indicate: Students with musical intelligence have low problem-solving abilities. It can be seen from the students' ability to solve the given mathematical problems, that is, students are less thorough in obtaining information about what is known and asked, students are not able to express a plan to explain the problem solving plan they want to do. students do not write down the complete solution, students do the calculation again only in the final step. Meanwhile, students who have kinesthetic intelligence have good problem-solving skills. It can be seen from the students' ability to solve the given mathematical problems, namely students are able to express what is known and asked in the questions using their own language. students cannot express the steps to be taken in solving the problem, students write down in full what is known and asked in full, students re-examine the results of their work by looking at and recalculating the answers that have been obtained.
... Problem-solving skills are part of individual skills to overcome various existing problems through cognitive structures owned (Wang & Chiew, 2010) and with scientific methods and procedures. These skills are closely related to the talents and cognitive structures possessed by individuals, and this can be found from an early age because they will find problems when they play (Stacey, 2005). ...
This study aims to see an overview of students' mathematical problem-solving skills in elementary school. This study uses a quantitative approach with a descriptive method. The subjects in this study amounted to 25 grade 5 students in one of the elementary schools in Bandung with details of 10 male and 15 female students. The data collection technique used is a mathematical problem-solving test instrument based on Polya theory on fractional concept material. The data analysis carried out was to calculate descriptive statistics using Microsoft excel and SPSS version 24 to see an overview of mathematical problem-solving skills, categorization of problem-solving scores based on high, medium, and low, and the achievement of students' mathematical problem-solving indicators. From these data, it is then analyzed in depth and linked with relevant theories. The results of this study showed that based on the categorization of student scores, 4 students were in the high category, 15 students were in the medium category, and 6 students were in the low category. The indicator that has a high percentage of students mastered is understanding the problem at 73%, and the lowest indicator at re-checking is 44%. This research can contribute to efforts to create meaningful learning in mathematics by involving complex thinking skills including mathematical problem-solving skills. Keywords: Complex Thinking, Mathematical Problem-Solving Skills, Elementary School
... La resolución de problemas es un proceso mental y se considera como una expresión natural de inteligencia en organismos superiores (Wang y Chiew, 2010). Esta habilidad ha garantizado la supervivencia y adaptación del ser humano, a nivel individual el resolver problemas permite estimular y fortalecer capacidades como la creatividad y el razonamiento lógico. ...
La formación universitaria debe propender por el desarrollo de competencias para la integralidad de los futuros profesionales, en donde la Resolución de Problemas es relevante para solucionar asertivamente los retos que la sociedad impone. El objetivo de éste trabajo es analizar la estrategia que los estudiantes, en diferentes estadios universitarios deben apropiar para resolver problemas, marcando una tendencia generacional. El estudio fue no experimental de tipo longitudinal y de carácter mixto. Se configuraron tres grupos de estudiantes de las generaciones Millennials y Centennials de tres Instituciones de Educación Superior en diferentes períodos: inducción (PreAD), semestre uno (AD) y semestre seis (PostAD), quienes resolvieron un estudio de caso sobre una problemática ambiental. Se compararon las estrategias para resolver y se estableció estadísticamente las diferencias entre grupos. Los participantes demostraron tener conciencia ambiental, los resultados del grupo PostAD, son categóricos al ser un grupo de edad que tiene como ideal salvar el mundo. Como el grupo AD cursaba química general en el momento de la prueba, mostró buen desempeño, mientras que el grupo PostAD tuvo resultados que no evidenciaron el aprendizaje significativo, sin embargo, todos los grupos priorizaron el uso de análisis dimensional para resolver los problemas relacionado con análisis matemático. 1. INTRODUCCIÓN La universidad debe propender por el desarrollo de competencias que logren la formación integral de los futuros profesionales, la Resolución de Problemas en una competencia relevante, entendiendo que el reto de los profesionales es resolver asertivamente los problemas que la sociedad impone. Una de las principales limitaciones que muestran los estudiantes universitarios es desconocer los pasos que deben abordar para resolver, y en carreras que requieren un alto componente de análisis matemático, todo lo relacionado con el análisis dimensional; generando confusiones, resultados errados y frustración, lo que a lo largo del tiempo redunda en aversión hacia los programas que se fundamentan en ciencias básicas y deserción. Se propone para el estudio una estrategia de investigación mixta, que analiza la forma en la que tres grupos de estudiantes resuelven problemas. La resolución de problemas es un proceso mental y se considera como una expresión natural de inteligencia en organismos superiores (Wang y Chiew, 2010). Esta habilidad ha garantizado la supervivencia y adaptación del ser humano, a nivel individual el resolver problemas permite estimular y fortalecer capacidades como la creatividad y el razonamiento lógico. En ese sentido desde la educación, las propuestas diseñadas para fortalecer los procesos cognitivos son perfectas para unificar distintos conocimientos específicos, generando redes conceptuales significativas (Pérez y Ramírez, 2011). Se entiende por solucionar problemas a los eventos que ocurren cuando se acepta una tarea para la cual no se tiene una solución, pueden existir diferentes categorías, que van desde la cotidianidad de la vida hasta ejercicios mentales estructuralmente construidos para fines específicos. Lo anterior, implica una serie de pasos que actúan sinérgicamente, la respuesta puede variar en función de las rutas que se tomen para llegar a la solución, esta última puede tomar valores absolutos o relativos dependiendo de la naturaleza misma del problema (Rojas, 2010). Los procesos mentales asociados a la resolución de problemas se pueden agrupar en tres categorías: el procesamiento de la información, referida a la búsqueda en la memoria de corto o largo plazo; estructuración, en términos de las actividades secuenciales o algoritmos que permiten formular posibles soluciones y por último la representación mental, asociada al constructo generado en el espacio inmaterial del pensamiento, el cual formula y delimita espacialmente una representación de la situación (Rojas, 2010). Para la resolución de problemas asociados al análisis dimensional en contextos educativos institucionalizados, se deben reconocer ciertas particularidades: Fomentar el componente motivacional propiciando en los estudiantes la actitud correcta, el acceso a material académico no genera la motivación suficiente para garantizar un ambiente de formación académica Garantizar la progresividad de la dificultad con la finalidad de generar una curva de conocimiento, que no afecte la motivación y que prepare al estudiante frente a desafíos más equilibrados. Promover la comprensión lectora, asegurando que el estudiante maneja el glosario de terminologías. Manejar adecuadamente herramientas como calculadora y/o software e interpretar datos y representaciones gráficas correctamente (Willis, 1995).
... It is a consequence of this definition that problem solving does not only apply to Mathematics or professional life, but it is useful also for everyday life as citizens of the present world: the well-known 20 th century philosopher and epistemologist Karl Popper once said all life is problem solving (Camiller and Popper, 1999). Some basic strategies of problem solving are (Wang and Chiew, 2010): ...
The spread of Artificial Intelligence (AI) has been recently generating worries among teachers and educators about the validity of assessment when students make use of AI tools to solve tasks. To tackle this issue, we propose mathematical problem solving activities to be carried out with the aid of ChatGPT, showing how problem solving and critical thinking continue to be pivotal in solving mathematical problems, even if this is performed with the aid of AI. After discussing theoretical frameworks on strategies of problem solving and phases of the critical thinking process, we present six problems of combinatorics that we submitted to ChatGPT. We also asked 40 university students to solve the six problems in group with the aid of ChatGPT during an international module on Problem Solving and Critical Thinking and collected the tutors' observations about the activities. Analyzing ChatGPT solutions and tutors' reflections, we show that the proposed activity requires problem solving and critical thinking to be accomplished. The results corroborate the idea that, instead of limiting the use of AI in education, it is possible to integrate it within learning and assessment to achieve the learning goals.
