Computational Problem Solving Research Articles

Computer cooking vs. problem solving

Computer cooking vs. problem solving

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

Implementing high-performance computing (HPC) to solve problems in energy infrastructure resilience research in a heterogeneous environment based on an in-memory data grid (IMDG) presents a challenge to workflow management systems. Large-scale energy infrastructure research needs multi-variant planning and tools to allocate and dispatch distributed computing resources that pool together to let applications share data, taking into account the subject domain specificity, resource characteristics, and quotas for resource use. To that end, we propose an approach to implement HPC-based resilience analysis using our Orlando Tools (OT) framework. To dynamically scale computing resources, we provide their integration with the relevant software, identifying key application parameters that can have a significant impact on the amount of data processed and the amount of resources required. We automate the startup of the IMDG cluster to execute workflows. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our solution allows us to investigate large infrastructures by modeling multiple simultaneous failures of different types of elements down to the number of network elements. In terms of task and resource utilization efficiency, we achieve almost linear speedup as the number of nodes of each resource increases.

An Ontology to Formalize a Creative Problem Solving Activity

Our study is set in an educational context: to better teach and assess twenty-first century skills, such as computational thinking or creative problem solving, we propose to formalize a specific activity that involves these competencies. This activity, referred to as #CreaCube, is presented as an open-ended problem which consists of assembling a set of robotic cubes into an autonomous vehicle. We not only anchor our formalization in classical learning science frameworks but we also propose to draw on neuro-cognitive models to describe the observed behaviors of learners engaged in this activity. The chosen formalism is symbolic and is aligned on upper ontologies to ensure that the vocabulary is well specified. This allows for a better communication between the summoned research fields, namely learning science, cognitive neuroscience and computational modeling. Beyond this specification purpose, we suggest performing inferences using available reasoners to better guide the analysis of the observables collected during the experiments. This operationalization of a creative problem-solving activity is part of an exploratory research action. In addition, an effective proof of concept is described in this study.

Fostering Computational Thinking and Problem-Solving in Programming: Integrating Concept Maps Into Robot Block-Based Programming

Computational thinking (CT) has gained considerable attention and in-depth discussion over the last two decades. Although the significance of CT has been highlighted, it could be challenging for educators to teach CT. Fortunately, adopting robots in education has been evidenced to be of benefit to promoting students’ learning motivation, CT, and higher-order thinking skills. However, several significant factors affecting students’ programming performances in robot-assisted learning activities have been identified, such as cognitive needs and organization. In this study, a CMR-BBP (concept map robot block-based programming) approach was designed by integrating concept maps into robot block-based programming to enhance students’ programming learning. Moreover, a three-group experiment was carried out in an elementary school to evaluate their learning outcomes. The experimental results revealed that the CMR-BBP approach benefited the students’ perceptions of their computational thinking and problem solving in comparison with the R-BBP (robot block-based programming) and C-BBP (conventional block-based programming) approaches. Furthermore, regarding cognitive load, both the CMR-BBP and R-BBP approaches enhanced the students’ germane cognitive load, while the CMR-BBP approach effectively reduced their extrinsic cognitive load. This study could be a notable reference for designing other courses in conjunction with programming learning activities.

The Development of Computational Thinking and Mathematics Problem Solving Skills Through Mathematics Modelling Activities

The latest TIMSS report highlighted that secondary school students from Malaysia did not perform well in this global assessment on mathematics achievement. Some studies have pointed out that students’ mathematics achievement can be improved by equipping them with computational thinking. Therefore, this study examined the development of computational thinking skill and mathematics problem-solving skills via mathematics modelling activities among secondary students in Malaysia. The research instrument used for the assessment of computational thinking was adapted from UK Berbras Challenges and CAS Barefoot Team from United Kingdom. In addition, rubrics for development of mathematics problem solving skill was adapted from Polya problem solving model. This study adopted qualitative approach and the modelling activities were conducted for six weeks. The activities were introduction of modelling, individual modelling task and group modelling task. Data were also collected based on results of computational thinking test and mathematics test. Data from observation and interviews were analyzed, and the scores obtained from both tests were compared and analyzed as well. Based on the findings of the study, it could be concluded that the students progressed at different levels during the development of their computational thinking skill and mathematics problem-solving competency via mathematics modelling activities. These results indicated that mathematics modelling activities can be conducted at schools to improve students’ performance in Mathematics.

Computational Triangulation in Mathematics Teacher Education

The paper is written to demonstrate the applicability of the notion of triangulation typically used in social sciences research to computationally enhance the mathematics education of future K-12 teachers. The paper starts with the so-called Brain Teaser used as background for (what is called in the paper) computational triangulation in the context of four digital tools. Computational problem solving and problem formulating are presented as two sides of the same coin. By revealing the hidden mathematics of Fibonacci numbers included in the Brain Teaser, the paper discusses the role of computational thinking in the use of the well-ordering principle, the generating function method, digital fabrication, difference equations, and continued fractions in the development of computational algorithms. These algorithms eventually lead to a generalized Golden Ratio in the form of a string of numbers independently generated by digital tools used in the paper.

컴퓨팅사고력, 창의적 문제해결력 신장을 위한 대학 교양 SW 기초 교육의 효과 분석

대학 교양 SW 기초 교육은 SW를 기반으로 일상 생활의 문제를 창의적으로 해결할 수 있는 능력을 기르는 데 중점을 두어야 한다. 따라서, 본 연구에서는 컴퓨팅사고력, 창의적 문제해결력을 신장시키기 위한 수업을 설계하고, 수업의 효과를 검증하고자 하였다. 이를 위해 A 대학교 학생 38명을 대상으로 융합프로젝트, CT-CPS 모형을 고려하여 SW 기초 교육을 실 시하고 그 효과를 분석하였으며, 연구 결과는 다음과 같다. 첫째, SW 기초 교육을 진행한 후 전체 학생들의 컴퓨팅사고력, 창 의적 문제해결력이 유의하게 향상되었다. 둘째, 상위, 하위 집단의 컴퓨팅사고력과 하위 집단의 창의적 문제해결력이 유의하 게 향상되었으나, 상위 집단의 창의적 문제해결력은 향상되지 않았다. 셋째, 인문사회계열과 자연과학계열의 컴퓨팅사고력과 자연과학계열의 창의적 문제해결력이 유의하게 향상되었으나, 인문사회계열의 창의적 문제해결력은 향상되지 않았다. 본 연 구는, 컴퓨팅사고력, 창의적 문제해결력 신장에 초점을 두어 수업을 설계하고, 수업의 효과를 사전 검사 결과 및 계열에 따라 심층적으로 분석하였다는 점에서 연구의 의의를 찾을 수 있다.

Students’ response to the introduction of active learning and computational practices in a bachelor-level earth science course

Earth science education should provide space for students to engage with real-world problems involving complex earth systems and their societal implications. However, the ill-structured nature of such problems creates uncertainty among both teachers and learners. To explore the effect of this uncertainty, we designed and taught a bachelor-level earth science course that introduced geology students to computational practices allowing them to work with authentic data, methods, and ill-structured problems. In addition, the course was designed entirely for active learning and formative assessment. Students provided reflection notes as part of every learning activity, and a series of focus group interviews were conducted at the end of the course to triangulate student experiences with computational practices and problem solving in groups. Our findings suggest that the introduction of computational practices to novices, combined with the transition from passive to active forms of learning, were major sources of uncertainty. This uncertainty needs to be understood and confronted in order for students to engage with real-world problems in an effective manner. On the other hand, our results indicate that collaborative work in groups can alleviate some of the effects of this uncertainty. Our study also supports the systematic use of student reflections as a means of fostering feedback literacy among students as well as teachers.

Centering teacher and parent voice to realize culturally relevant computational thinking in early childhood

The specific mechanisms by which teachers and parents can provide culturally relevant opportunities for computational thinking for racially/ethnically and linguistically diverse groups of preschoolers remain unknown. Accordingly, the purpose of this research is to examine how PreK parent and teacher voice directed efforts to realize a culturally relevant computing program. We drew data sources from a subsample of design-based research meetings in which partners collaborated to co-develop the first iteration of the program. Using qualitative analysis, we examined how parent voice and teacher voice, conceptualized as perspectives and participation, influenced theories of culturally responsive computing and computational thinking in early childhood education and the translation of theory into practice in classroom and home settings. Findings showed that connecting powerful ideas from computational thinking, namely algorithms and problem solving (e.g., debugging), to familiar activities and experiences served as a powerful entry point. Yet, differences arose in how teachers and parents conceptualized culturally relevant computing and made connections to familiar routines. We discuss what can be learned from parent voice in regards to bolstering children's self-expression, access to increasingly complex computational thinking tasks, and opportunities for learning cultural and community values through computing.

Need Analysis of Basic Chemistry Practicum Based on Computation

Computational chemistry is a branch of chemistry which is the theoretical translated into computer programs to calculate the properties of molecules and their changes. This study analyzes the need of computational-based chemistry practicum in the Basic Chemistry course at the Chemistry Education Study Program at Samudra University. This study was done by survey technique. Aspects analyzed in this study include: module analysis through a review of the Basic Chemistry practicum module used by the Chemistry Education study program, needs analysis through students' perceptions that has been carried out, and literatures analysis through computational studies for Basic Chemistry that have been developed. Basic Chemistry practicum implemented in Chemistry Education is a verification practicum (conventional), and it is necessary to implement a practicum that gives more freedom to students in exploring. Basic chemistry practicum in Chemistry Education is also not based on computational, so it is necessary to develop basic chemistry practicum activities that provide computational problem solving

Mathematical and computational awareness before and after the pandemic

Mathematical thinking and computational thinking go hand in hand. Both of them are based on awareness of problem-solving. However, consciousness does not exist without a proper mental and psychological state. Formerly we examined some mathematical psychological aspects that could have an impact on both mathematical and computational problem-solving. We taught novice computational programming by solving mathematical word problems. Our first experiments were performed years before the pandemic. In this study, we present the results of a new experiment on the same topic, but this was performed during the pandemic homeschool interval. The programming environment and the teaching material were the same as before. We present our results based on our homeschool experience. We expect that the results of homeschool study groups are not worse than the results of before-pandemic study groups in reaching the aforementioned aim. The experiment proved our previous hypothesis that we can successfully teach solving mathematical word problems in a computational environment, and at the same time with the help of word problems, we can successfully teach the basic elements of computer programming.

A Design and Application of Software Liberal Arts Course based on CT-CPS Model for Developing Creative Problem-Solving Ability and Learning Motivation of Non-software Majors

As the importance of computing education for nurturing computational thinking skills is emphasized in preparation for the era of the 4th industrial revolution, computing education for non-majors is also expanding in liberal arts education at universities. In this study, a software liberal arts course based on the CT-CPS model was designed and applied to non-software majored university students, and the effect on creative problem-solving ability and learning motivation were analyzed. The CT-CPS (computational thinking-based creative problem solving) model is an instructional model devised by fusing each element of computational thinking ability to the creative problem-solving stages. Creative problem-solving ability test paper and learning motivation test paper were used as test tools. Moreover, quantitative analysis through independent sample t-test and paired sample t-test and qualitative analysis through subjective responses were conducted. As a result of the study, it was verified that the software class applied with the CT-CPS model had a statistically significant effect on the creative problem-solving ability and learning motivation of non-software majors. In particular, compared to the control group, the experimental group showed significant changes in the motivational elements among the sub-factors of creative problem-solving ability and the self-efficacy factor among the sub-factors of learning motivation. In addition, it was confirmed through qualitative analysis that the software class to which the CT-CPS model was applied helped develop the problem-solving ability and learning motivation based on computational thinking through the process of discovering and solving problems on their own in real life.

The Effects of Cognitive Apprenticeship and Co-Regulated Learning on Improving Student Computer Problem-Solving Skills and Learning Motivation

This study makes use of online teaching in this environment and adopts it for use in a required computer skills course with Cognitive apprenticeship (CA) and Co-regulated learning (CRL) teaching methods to improve students’ computer skills, learning motivation, and experience of online learning. The subjects of this study are first-year students of a non-information-related department at a private university in northern Taiwan. A total of four classes comprising 111 students participated in the research. The CRL and CA group (C1, n=24) concurrently received CRL and CA treatments; the non-CRL and CA group (C2, n=25) received only the CA teaching method, and the CRL and non-CA group (C3, n=40) only the teaching method of CRL. The non-CRL and non-CA group (C4, n=22) served as the control group. The results show that the use of CA can significantly improve students’ computer skills; however, the expected effects of CRL were not found in this study.

The determinants of impact of personal traits on computational thinking with programming instruction

ABSTRACT Computational thinking is an important skill in computer science since the 1960s, and it is closely related to problem solving. Almost all research related to computational thinking mentions problem solving. Although some research has been conducted on computational thinking, few studies examined the impact of personal traits on students’ computation thinking skills and problem solving. This study modeled cooperative attitudes of programming, learning style, self-regulation, and enjoyment as its key elements, investigated personal traits as predictors of problem-solving skills, and examined the correlation between variables and computational thinking. The 252 research participants were all sixth-grade students in an elementary school in Taipei, Taiwan. After a 10-week experimental curriculum, a posttest was conducted, and a total of 244 observations were collected. Correlation and regression analyses show that computational thinking is positively correlated with problem-solving skills, and learning style has the predictive ability for computational thinking. Furthermore, cooperative attitude and self-regulation of programming are important variables for predicting problem-solving skills; the degree of students’ enjoyment in the curriculum will affect the cooperative attitude and self-regulation of their programming. In summary, the personal traits above could improve the participants’ problem-solving skills hierarchically and help them achieve better computational thinking.

The Effects of SW Education Using EPL and Coding robot on the Computational thinking and Problem solving

본 연구는 소프트웨어 교육의 다양한 교수·학습 방법 중 EPL과 코딩 로봇을 활용한 SW교육이 컴퓨팅 사고력과 문제해결력에 미치는 효과를 살펴보고자 하였다. 이를 위해 광주광역시·전라남도 소재 A중학교와 B중학교 350명의 학생들을 대상으로 설문조사를 실시하였고, 변인간의 관계를 규명하기 위하여 대응 표본 t-검증, 일원변량분석 방법 등을 통해 평균의 차이를 분석하였다. 이를 통해 얻어진 연구결과를 토대로 EPL과 코딩 로봇을 활용 SW교육의 효과 및 장단점을 파악하고 효율적인 SW교육의 교수·학습 방법을 위한 기초자료 및 정보를 제공하여, 더 나아가 학문적·실용적 측면에서 보다 좋은 방향을 제시하고자 한다.

Integration of Python into Science Teacher Education, Developing Computational Problem Solving and Using Information and Communication Technologies Competencies of Pre-service Science Teachers

This study reports the findings of a program that aims to develop pre-service science teachers’ computational problem-solving skills and views on using information and communications technology in science education. To this end, pre-service science teachers were trained on computational thinking, computational problem solving, designing an algorithm, and Python coding, and then they were asked to solve problem situations determined within the science education program using the computational problem-solving process. The study was conducted in a faculty of education in Turkey and carried out conducted in an elective course in the spring semester of the 2019 - 2020 academic year (in an online platform due to the Covid-19 Pandemic). 38 pre-service science teachers were included in the study. In this process, pre-service science teachers’ conceptual development levels regarding computational thinking and their views regarding the use of ICT in schools were collected quantitatively. The development of computational problem-solving skills of pre-service science teachers was scored by a rubric developed in this study. According to the analyzes, pre-service science teachers increased knowledge of computational thinking (t = -5,969, p = .000), enhanced views regarding the use of ICT in schools (t = -2,436, p = .020), and developed computational problem-solving skills (χ2(2) = 9.000, p = 0,011). These findings have the potential to provide evidence on how computational problem-solving skills can be integrated into science teacher education programs.

Collaborative versus individual problem solving in computational thinking through programming: A meta‐analysis

AbstractComputational thinking (CT), which is a cognitive skill used to solve problems with computational solutions, has drawn increasing attention among researchers and practitioners due to the growing recognition of CT competence as a 21st century skill. Collaboration is commonly integrated into CT education to facilitate novice learning, but there is inadequate knowledge regarding the influences of collaboration in CT education. This meta‐analysis examined the overall effects on the cognitive, social and affective competencies of collaborative versus individual problem solving in CT through programming. We identified 33 publications involving 4717 learners, which allowed for 220 effect size comparisons. We found a medium effect size (Hedges' g = 0.562; p < 0.001) in favour of collaborative problem solving on cognitive learning outcomes and a small effect size (Hedges' g = 0.316; p < 0.01) on affective learning outcomes using a random‐effects model. Categorical moderator analysis revealed the moderating effects of educational level, programming environment, study duration, grouping method and group size. The competency model that was generated from the synthesized literature on collaborative computational problem solving yielded insights into the learning design and assessment of relevant activities. Practitioner notesWhat is already known about the topic? Although professional programming usually requires collaboration to accomplish common goals in the work environment, programming is predominantly taught on an individual basis in educational settings. Some intervention studies have reported inconsistent learning outcomes (positive and negative) from integrating collaborative problem solving (CPS) into programming education. There is a need for further scrutiny and exploration of the role of collaboration in the process of learning to program. What does this paper add? Our meta‐analysis showed that CPS is an effective pedagogical tool for developing students' cognitive, affective and social competencies. The moderator analysis revealed that CPS in programming has cognitive benefits irrespective of grouping method, group size and educational levels; however, there is a need for caution in regard to designing collaborative problem‐solving activities for different programming environments and durations. The model generated from the literature synthesis can yield insights into better assessing and designing collaborative problem‐solving activities. Implications for practice and/or policy? Integrating CPS into programming education can prepare students with 21st century skills. Social and affective competencies are crucial to students' learning capacity, which is an issue that needs to be better assessed. Future studies could look more rigorously into the effects of CPS in visual programming and robotics programming among younger age groups, such as primary or middle school students.

Processing Analysis of Swift Playgrounds in a Children’s Computational Thinking Course to Learn Programming

Computational thinking courses can cultivate students’ ability to apply logic in the fields of mathematics and information science. The new 12-year Basic Education Curriculum Guidelines were implemented in Fall 2019 in Taiwan. Courses on computational thinking, problem solving, and programming are contained in the technology education field in junior and senior high schools. Swift Playgrounds is an innovative app for the iPad and Mac that makes learning Swift interactive and fun. No programming knowledge is required to use Swift Playgrounds, making it very suitable for beginners. This study was carried out by letting elementary school teachers and students participate in Swift Playgrounds computational thinking courses. By trying this app, teachers of different disciplines attempted to realize more learning situations. Students learned how to cope with functions and loop skills by playing with “Byte”, which is a character in Swift Playgrounds. There were three purposes for this study: first, designing a computational thinking course for the most basic part, “Hello! Byte”, in Swift Playgrounds; second, assigning elementary school teachers to assess the qualitative analysis of tasks in Swift Playgrounds; and third, assigning elementary school students to do the tasks and assign a difficulty index in Swift Playgrounds after learning with this app. The results show that most teachers considered this approach to be able to improve logical thinking and inferential capability after assessing, and most students considered functions and loops quite difficult after using the app. According to the students’ indices, about 86 percent of students considered that adding commands is easy, and about 37 percent of students considered that functions are easy. On the other hand, about 24 percent of students considered that applying the Slotted Stairways is difficult, and about 34 percent of students considered that using loops is hard. It is suggested that more instructions for the course or extendibility for classes is required.

Modeling human activity dynamics: an object-class oriented space\u2013time composite model based on social media and urban infrastructure data

Modeling human activity dynamics is important for many application domains. However, there are problems inherent in modeling population information, since the number of people inside a given area can change dynamically over time. Here, a cyberGIS-enabled spatiotemporal population model is developed by combining Twitter data with urban infrastructure registry data to estimate human activity dynamics. This model is an object-class oriented space–time composite model, in which real-world phenomena are modeled as spatiotemporal objects, and people can move from one object to another over time. In this research, all spatiotemporal objects are aggregated into 14 spatiotemporal object classes, and all objects in a given space at different times can be projected down to a spatial plane to generate a common spatiotemporal map. A temporal weight matrix is derived from Twitter activity curves for each spatiotemporal object class and represents population dynamics for each object class at different hours of a day. Finally, model performance is evaluated by using a comparison to registered census data. This spatiotemporal human activity dynamics model was developed in a cyberGIS computing environment, which enables computational and data intensive problem solving. The results of this research can be used to support spatial decision-making in various application areas such as disaster management where population dynamics plays an important role.

La planificación de estrategias de enseñanza en un entorno virtual de aprendizaje

En el presente artículo se define como objetivo general analizar la importancia que tiene la planificación de estrategias de enseñanza en un Entorno Virtual de Aprendizaje (EVA) que en la actualidad se incrementa debido a la influencia de la era digital, donde la educación convencional presencial quedará invisibilizada por los avances de las Tecnologías de la Información y Comunicación (TIC), lo que supone nuevas formas de abordar el acto educativo para desarrollar en el alumnado el pensamiento computacional y de resolución de problemas, asumir una postura autocritica, y critica frente a la realidad social. Por otra parte, el proceso metodológico se abordó a partir del paradigma cuantitativo mediante la investigación descriptiva con un diseño documental. Además, se aplicó una encuesta a los profesores de la Universidad Tecnológica Israel del Distrito Metropolitano de Quito, Ecuador, en el Lapso Académico 2020/A, que permitió el análisis estadístico y de contenido. De esta manera, se concluye que la planificación de estrategias en un ambiente virtual exige en el profesorado la organización minuciosa para administrar a tiempo el aula virtual, seleccionar los recursos y medios tecnológicos que más se adapten a las necesidades o requerimientos del aprendiz, con la finalidad de propiciar la autogestión del aprendizaje independiente y el trabajo colaborativo entre estudiante/estudiantes desde un enfoque constructivista en una experiencia contextualizada, interactiva y de responsabilidades compartidas.