Is it possible that playing a video game might help you improve your computational thinking abilities?

In this research, we looked at the cognitive and behavioral effects of playing Penguin Go, a video game that was created to help middle school kids improve their computational thinking (CT) abilities. Apart from the general efficacy of the game, we looked at the effects of a single game feature—constraints on the amount of blocks that may be used in a solution. Students' CT abilities increased dramatically after playing Penguin Go for fewer than two hours, according to the findings, but the extra limits had no meaningful effect on learning. Furthermore, although the game as a whole had no effect on students' views toward computer science, the limitations condition of the game had a detrimental effect on students' attitudes toward computer science. The outcomes of this study, as well as suggested possibilities for future research in the area of employing these sorts of games to build computational thinking abilities, are reviewed.

Higher education blended learning: a network study of student learning paths

For the aim of this research, a model of students' learning pathways as a network that records time and sequence of learning events is introduced. These learning pathways networks also establish the online learning rate. Results demonstrate that pupils who passed learned more online than those who failed. The findings of the person-centered study demonstrate that only test anxiety affects the number of nodes and arcs of the individual learning pathway network, which was represented as an individual network. Also, the qualities of social networks are influenced by how active or inactive users are. There is evidence to back up the theory that pupils who are driven to learn do not necessarily study more information. As a result of exam anxiety, engagement, and disengagement, the learning pathways of individuals are shaped and reshaped throughout time.

First-year engineering students' computational reasoning abilities

Computational thinking is an essential skill set for today's students, given the digital age in which we live and work (CT). Without a precise definition, it is generally understood to be a collection of abilities and attitudes required to deal with difficulties in any aspect of life, whether or not a computer is involved. Measurement and evaluation of students' progress in CT abilities are critical, and this can only be done using instruments that have been tested and shown to work before. New students at the Basque Country's University of the Basque Country's Engineering Degrees are tested for critical thinking, algorithmic thinking, problem solving, cooperation and creativity using a previously proven tool.

Creating an environment that encourages both extensive and intense threaded dialogue The growth of discussion threads and the size of the class

The purpose of this research is to investigate the beginning and development of asynchronous discussion threads in various class sizes over the course of 25 graduate-level courses and 22 interviews. The paper also aims to create some recommendations for promoting threaded discourse during the initiation, advancement, summary, and evaluation phases of a discussion thread from pedagogical, technological, and theoretical viewpoints. The statistical analysis revealed that class size did influence the number of threads and the length of threads created by students and instructors, which showed the importance of certain themes in the conversation. The majority of participants said that it was difficult to follow threaded conversations in order to establish meaningful cooperation in huge classrooms. Instructors and graduate students each expressed a preference as to whether they should begin or follow a conversation. Some pedagogical tactics were used by the instructors to facilitate the commencement and growth of discussion threads. This research may have consequences for both practitioners and academics in terms of developing new software features and designing efficient educational tactics in order to produce more successful comprehensive and intense knowledge-building discourse in the classroom.

Implementation of the Analytical Hierarchy Process Method and Multi Objective Optimization on the Basis of Ratio Analysis in the Selection of Insurance Products

Insurance product offerings are not always understood by prospective customers (CN) due to limited information related to products. This can cause confusion so that CN does not want to buy it. The purpose of this study is to analyze the selection of insurance products PT. AIA Financial Samarinda, East Kalimantan, Indonesia uses the Analytical Hierarchy Process (AHP) and Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) approach so that CNs can choose based on insurance product facilities that match their abilities. In this study, as many as 10 types of insurance products and 10 CN criteria were then analyzed based on the two methods used. Then, the calculation accuracy of the two methods has been using the confusion matrix (CM) method. Based on the results of CM calculations from 27 CN datasets with a conformity level of 81.5%, it has been obtained which indicates that the two methods can be implemented as an alternative in choosing insurance products according to ability or based on CN criteria. The results show that this method is quite effective, efficient and relatively easy to use in determining insurance products that meet the criteria or according to CN's economic capabilities

Analyzing metaheuristic methods to build an optimal composite foot prosthesis insole

This paper uses metaheuristic algorithms to develop and optimize composite materials. To calculate the characteristics that allow the planned item to withstand particular loads, ABC and Differential Evolution algorithms are utilized. One of the key challenges in these designs is determining the piece's thickness. Designing a carbon fibre insole for Latin American users will improve the design process by generating functional solutions that are feasible to manufacture and in less time than traditional design methods. The results reported in this work demonstrate that a functional design may be developed, validated by finite element method, with minimal material waste and in a reasonable period.

The problem of solid waste: origins, composition, disposal, recycling, and reusing

Solid waste disposal is a major challenge in many industrialized and developing nations, both in metropolitan regions as well as rural ones. The collection and disposal of municipal solid waste (MSW) is a serious issue facing metropolitan areas in many nations today. An effective MSW management strategy must satisfy all of these criteria: financial viability; technical feasibility; social and legal acceptability; and ecological friendliness. Small and large cities alike have a major difficulty in dealing with solid waste management. One of the current study topics is the valuation of food organic waste. Existing waste disposal methods include the typical landfill, incineration, composting, and other methods of handling solid waste. Composting and anaerobic digestion have traditionally been the most widely employed methods for the treatment and exploitation of the organic part of MSW (AD). The amount of organic solid waste (OSW) being generated globally is rising at an astronomical rate. Agricultural waste, domestic food waste, human and animal wastes, etc. comprise the majority of OSW. They're often used as animal feed, disposed of in landfills, or burnt. OAWs are made up of protein-, mineral-, and sugar-rich components that may be employed as substrates or raw materials in other processes.

K-Means and Fuzzy C-Means Optimization using Genetic Algorithm for Clustering Questions

The grouping of data can be used in the development strategy of an educational game application. The process of grouping data that initially behaved differently into several groups that now behaved more uniformly. As well as grouping the data on the difficulty level of the questions on the educational game question board. This grouping of questions is needed to get the dominant values ​​that will be the characteristics of each group of questions that exist. The clustering method is quite widely used to overcome problems related to data grouping. This clustering is a method of grouping based on the size of the proximity, the more accurate the cluster formed, the clearer the similarity of the difficulty level of the questions. Thus, educational game developers can determine the strategy for placing the existing questions more precisely. Many clustering methods can be used to group the data on this question, including K-Means and Fuzzy C-Means (FCM) which are then optimized using the Algorithm Genetics. From the results of the research conducted, optimization gives better results for clustering questions.

Application of Nave Bayes Algorithm for SMS Spam Classification Using Orange

Mobile phones have become a necessity for everyone. SMS is a communication service that is used to send and receive short messages in the form of text on mobile phones. Among all the advantages of SMS, there is a very annoying activity called spam (unsolicited commercial advertisements). Spam is the continuous use of electronic devices to send messages. called spammers. Spam messages are sent by advertisers with the lowest operating costs. Therefore, there are a lot of spammers and the number of messages requested is huge. Therefore, many aspects are harmed and disturbed. When SMS enters the user's mobile device, this study aims to classify spam and ham SMS. SMS classification adopts naive Bayes method. By looking at the contents of the SMS, the application of the naive Bayes method in data mining can distinguish unwanted SMS from non-spam. Results The classification accuracy rate is 0.999%. Based on the research that I have done, the Naive Bayes method can classify 1000 SMS spam data contained in the SMS spam data set file correctly.

Solar Preheating in Power Plants: An Overview Of The Current State Of The Technology

Utilizing preheating units is one of the most critical ways to improve the performance of thermal power plants. Increasing the overall efficiency of Brayton or Rankine cycles by preheating the air or stream may result in considerable increases in output power and efficiency. When it comes to renewable energy, solar energy is an appealing alternative for use as a source of preheating since it is readily accessible. The current article discusses the use of solar energy for preheating air and steam in thermal power plants, as well as other uses. The performance of the systems is being improved, according to evaluations, as a result of a variety of elements, including the configuration of the reference system, the operating environment, the applied technology, and so on. Aside from improving the overall efficiency of the power plant, the incorporation of a solar preheating system may significantly decrease fuel usage and, as a result, carbon dioxide emissions. Furthermore, owing to the unavailability of solar energy during the night and overcast hours, thermal storage units may improve the system's dependability while also increasing the contribution of solar energy to the system's output.