Learning computer programming is a slow process that may make learners depressed. Studies suggested that the students should take a problem in real world and then translated it to program code to solve it. Unfortunate...
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computer programming (CP) is difficult to teach and learn. Many students who enroll in CP courses have difficulty learning to program, as they have deficits in problem-solving skills and are unable to understand abstr...
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ISBN:
(纸本)9798400717819
computer programming (CP) is difficult to teach and learn. Many students who enroll in CP courses have difficulty learning to program, as they have deficits in problem-solving skills and are unable to understand abstract programming concepts. Some studies also state that teaching methods are often not the most appropriate as they are not personalized to each student's needs and do not complement their learning styles. We believe that Computational Thinking (CT) can help alleviate the difficulties in learning to program, especially if it is developed from an early age. However, it is also crucial that teachers use effective methods to help their students develop CT skills. There are several Learning Resources (LR) (digital or paper format) to develop CT skills, however, we argue that Neuroeducation can contribute to improving the effectiveness of these LR in the teaching and learning process. The evidence about the brain's learning process can be transformed into principles applicable in Education (Neuroeducation). To understand how we could train CT at various levels of education we built an ontology, OntoCnE, that describes the CT and CP domains. OntoCnE is composed of 3 layers that define: how to develop CT;which concepts should be taught at each level of education;and appropriate training materials. This paper aims to present a CT development approach based on this ontology together with Neuroeducation guidelines. The result of our research is the fourth layer for OntoCnE, which defines the Neuroeducation guidelines to characterize the materials. To illustrate our proposal, we will use LR PathIt as a case study. This approach can contribute to innovative and more efficient training of CT.
The scientific process is inherently creative, requiring the generation and exploration of ideas for scientific inspiration, projects, study design, and communication. As large language models (LLMs) advance rapidly, ...
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ISBN:
(纸本)9798400704857
The scientific process is inherently creative, requiring the generation and exploration of ideas for scientific inspiration, projects, study design, and communication. As large language models (LLMs) advance rapidly, scientists increasingly take advantage of their abilities. While LLMs show great promise in supporting many steps of the scientific process, researchers still face significant challenges in validating and steering their output. Interactions tailored to scientists and their specific tasks may empower them to harness the full creative potential of LLMs. I present a course of research that will lead to the development and evaluation of mixed-initiative methods for co-creation in scientific research. These methods aim to facilitate verification and control of AI output. I briefly describe my prior and proposed work on mixed-initiative methods for co-creating research inspiration, studies, and communication, and I detail my current project on an LLM-powered tool for co-creating research project ideas.
Learning programming is becoming more and more common across all curricula, as seen by the growing number of tools and platforms built to assist it. This paper describes the results of an empirical study that aimed to...
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ISBN:
(纸本)9789897585623
Learning programming is becoming more and more common across all curricula, as seen by the growing number of tools and platforms built to assist it. This paper describes the results of an empirical study that aimed to better understand students' programming habits. The analysis is based on unsupervised classification algorithms, including features from previous educational data mining research. The k-means method was used to identify the behaviors of six students profiles. The main and interaction impacts of those behaviors on their final course scores are tested using analysis of covariance.
We lack a shared and detailed understanding in gamification of what game elements are. To address this, we provide a scoping review of the last five years of gamification research, focusing primarily on how game eleme...
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Urban crowdsourcing platforms are becoming increasingly important, especially considering the relevance of citizen-centricity in smart cities. This systematic review aims at analyzing existing academic literature on u...
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This paper exhibits a systematic literature mapping of the considerations required to develop algorithmic thinking in a first course in computer programming (CS1) in university academic programs in computing. In the m...
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This paper exhibits a systematic literature mapping of the considerations required to develop algorithmic thinking in a first course in computer programming (CS1) in university academic programs in computing. In the methodological process of this study, 5 stages were proposed: research questions, search, selection, quality assessment and synthesis extraction. In this way, 5 guiding questions were drawn, 136 articles generated by the search stage were analyzed and the synthesis of 55 documents that met the criteria of this research was concluded, thus compiling the different practices used for the development of algorithmic thinking. In addition, as a result of the systematic literature mapping, a definition of Algorithmic Thinking oriented Software Engineering and didactics is proposed.
computers have revolutionized engineering calculations in recent years. Some fields in engineering owe their development to the emergence of powerful computers and efficient software. Optimization and reliability anal...
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computers have revolutionized engineering calculations in recent years. Some fields in engineering owe their development to the emergence of powerful computers and efficient software. Optimization and reliability analysis are remarkable instances of this kind. This paper introduces a free computer program called BI that has been developed to enhance the calculations of various reliability methods. BI estimates the probability of failure using various methods including the first- and second-order reliability methods;methods based on higher-order statistical moments of random variables;simulation methods such as Monte Carlo sampling, importance sampling, and sequential importance sampling;point estimation methods;and other novel reliability methods such as conjugate finite step length, directional stability transformation, and non-negative constraint. Furthermore, BI provides a combination of unified reliability analysis and the fast integration method to simulate risk analysis based on the Poisson point process for the first time. Furthermore, BI is equipped with reliability-based design optimization for fulfilling structural optimization purposes. This program is not restricted to internal models and functions, but permits the users to define input-oriented scripting model such as finite element models and Python codes. Because the proudest feature of this software is that it is equipped with a numerical fast integration method, the most important and complicated problem as an example of time-dependent reliability analysis is investigated in order to comprehensively review the software features. A full procedure of many numerical examples has been provided on the GitHub page of this software with complete instructions that are given, enabling users to model their own examples step by step. The GitHub page address is: https://***/Mehrshad-Ghorbanzadeh/BI
This paper examines the rapid introduction of AI and automation technologies within essential industries amid the COVID-19 pandemic. Drawing on participant observation and interviews within two sites of waste labor in...
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