检索结果-内蒙古大学图书馆

7th International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM)

作者： Schez-Sobrino, Santiago Garcia, Maria A. Gomez, Cristian Vallejo, David Lacave, Carmen Glez-Morcillo, Carlos Molina, Ana I. Albusac, Javier A. Redondo, Miguel A. Univ Castilla La Mancha Escuela Super Informat Ciudad Real Spain

ISBN: (纸本)9781450371919

programming is a field that influences other disciplines in a transversal way, so its learning is necessary considering the emergence of new jobs that will require programming knowledge in the future. However, programming raises certain difficulties during its learning, especially in understanding programming concepts due to the high level of abstraction required. This level of abstraction can be reduced by using graphic representations that motivate the student and facilitate the understanding of certain programming concepts that arise at the beginning of the learning process. Therefore, this paper introduces ANGELA, a graphic notation based on the metaphor of roads and traffic signs that is meant to complement the learning process of beginner students who are starting to program by visualizing programs. These visualizations can be automatically generated from the source code of the programs, thanks to the modular and scalable design of the notation, and used by teachers to explain programming concepts during classes. The proposal has been evaluated with students in order to validate if the notation is appropriate to represent the concepts it tries to abstract from and if it results easy for the students to understand. Additionally, some use cases are presented in real-world scenarios in order to demonstrate the flexibility of the proposal.

关键词： Program visualization algorithm visualization programming learning augmented reality metaphors

来源：评论

学校读者我要写书评

暂无评论

Student learning effect using flipped classroom with WPSA learning mode - An Example of programming Design Course

引用

Innovations in Education and Teaching International 2023年第6期60卷 824-835页

作者： Kuo, Yu-Chen Lin, Yu-Hsuan Wang, Tao-Hua Lin, Hao-Chiang Koong Chen, Ju-I Huang, Yueh-Min Department of Computer Science & Information Management Soochow University Taipei City Taiwan General Research Service Centre National Pingtung University Science and Technology Pingtung City Taiwan Department of Engineering Science National Cheng Kung University Tainan Taiwan Department of Information and Learning Technology National University of Tainan Tainan Taiwan

Flipped classroom is one of the important teaching modes among many novel teaching methods in recent years, students watch the video in the pre-class. However, if students cannot focus on the pre-class video learning or have problems with the learning content, the learning effect will be less than expected. Therefore, this research proposes a flipped classroom combined with the WPAQ learning model extended by the WSQ learning model to carry out programming courses, allowing students to perform flipped classroom learning with peers online before class and jointly complete the tasks of flipped classroom learning lists, and share with them a summary of learning content to enhance learning effectiveness. The research results show that the use of flipped classrooms combined with the WPAQ learning model of the learning system can help students improve learning effectiveness, learning motivation, self-efficacy, reflective ability, programming learning attitudes, and reduce students’ cognitive load. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： flipped learning programming learning WSQ learning mode

来源：评论

学校读者我要写书评

暂无评论

UNIVERSITY STUDENTS' METACOGNITIVE AND PROBLEM SOLVING SKILLS TOWARDS learning A programming LANGUAGE

UNIVERSITY STUDENTS' METACOGNITIVE AND PROBLEM SOLVING SKILL...

引用

作者： RAJAA. JAWADI. H. FOURTI NEAR EAST UNIVERSITY

学位级别：硕士

The complexity of the educational processes made it necessary to look for new appropriate strategies. It is important that students acquire metacognitive skills so that they can keep abreast of the great progress in Science and Technology. Educational methods should be questioned about their role in preparing a student to possess not only thinking but being able to have metacognitive skills. Computer programming skills require a good quality of education through a comprehensive development of the educational processes and the knowledge of the latest approaches which require the preparation of students' abilities to choose the most appropriate strategies. Metacognitive skills increase students' abilities to understand how to think positively, and how to solve the problems they face in Computer Science. The Thesis attempts to provide an understanding of the metacognitive skills towards problem solving in programming language learning amongst university students in North Cyprus. Research based model and questionnaire were used in the study where data were collected randomly from 300 volunteered students. The students were chosen from departments of Computer Information Systems, Computer Engineering, Information Technology and Management Information Systems during 2016-2017 Fall semester. The dependent variable in the study is metacognitive skills for computer programming, and the independent variable is problem solving skills. SPSS was used to analyze the data, the descriptive statistics were used to analyze the characteristics of the study sample and the estimates of their responses. Pearson's correlation was used to study the effect of use metacognitive skills towards problem solving skills that students face when learning programming languages. After statistical analysis of the collected data, there was a negative correlation between metacognitive skills and problem solving skills. This study also showed a strong point among students in the skills of planning and mo

关键词： programming learning programming metacognitive skills problem solving problem solving skills

来源：评论

学校读者我要写书评

暂无评论

WebPGA: An Educational Technology That Supports learning by Reviewing Paper-Based programming Assessments

引用

INFORMATION 2021年第11期12卷 450页

作者： Paredes, Yancy Vance Hsiao, I-Han Arizona State Univ Sch Comp & Augmented Intelligence Tempe AZ 85281 USA Santa Clara Univ Dept Comp Sci & Engn Santa Clara CA 95053 USA

Providing feedback to students is one of the most effective ways to enhance their learning. With the advancement of technology, many tools have been developed to provide personalized feedback. However, these systems are only beneficial when interactions are done on digital platforms. As paper-based assessment is still a dominantly preferred evaluation method, particularly in large blended-instruction classes, the sole use of electronic educational systems presents a gap between how students learn the subject from the physical and digital world. This has motivated the design and the development of a new educational technology that facilitates the digitization, grading, and distribution of paper-based assessments to support blended-instruction classes. With the aid of this technology, different learning analytics can be readily captured. A retrospective analysis was conducted to understand the students' behaviors in an Object-Oriented programming and Data Structures class from a public university. Their behavioral differences and the associated learning impacts were analyzed by leveraging their digital footprints. Results showed that students made significant efforts in reviewing their examinations. Notably, the high-achieving and the improving students spent more time reviewing their mistakes and started doing so as soon as the assessment became available. Finally, when students were guided in the reviewing process, they were able to identify items where they had misconceptions.

关键词： programming learning reviewing behavior educational technology behavioral analytics

来源：评论

学校读者我要写书评

暂无评论

learning Dynamic System Oriented Model Based programming

Learning Dynamic System Oriented Model Based Programming

引用

2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)

作者： Jinling Wang Huichuan Duan School of Information Science and Engineering Shandong Normal University Jinan 250014China School of Information Science and Engineering Shandong Normal University Jinan 250014 China

As Dynamic System Oriented Model Based programming (DSO-MBP) platforms, such as Simulink, becomes more and more popular, more and more students desire to learn such kind of programming. However, college students in computer science or related disciplines cultivated with traditional textbased programming, such as structured, procedural and OOP, find it frustrating to learn DSO-MBP. Our experience exhibited that it is the distinct programming paradigm of DSO-MBP that causes the trouble. This paper reports our understanding on elements of DSO-MBP paradigm, including model based, block supported, GUI interfaced, Subsystem organized, time-variant signal driven, new parameter passing, call-back functioning, and more accessible look and feel. We point out their differences and similarities with respect to traditional programming paradigm elements. We hope our contribution can help newcomers easily switch from traditional programming paradigms to the DSO-MBP paradigm and learn DSO-MBP effectively.

关键词： model based programming programming paradigm programming learning dynamic system Simulink

来源：评论

学校读者我要写书评

暂无评论

learning problem generator for introductory programming courses

引用

SOFTWARE IMPACTS 2023年 17卷

作者： Prokudin, Artem Sychev, Oleg Denisov, Mikhail Volgograd State Tech Univ Software Engn Dept Volgograd Russia

Automatic learning-problem generation saves effort on creating problem banks. It allows creating banks containing thousands problems, which prevents cheating, allows training until mastery, and lets intelligent tutoring systems find problems for every learning situation. We present a learning problem generator ToP, designed to generate problems for introductory programming courses from open-source code. It supports teaching determining the order of expression evaluation and program tracing. It was integrated into the CompPrehension tutor to generate initial problem banks problems and update them on the fly. It was used in studies of learning-problem generation that demonstrated that generated problems are indistinguishable from human-authored ones.

关键词： Question generation learning problem generation Intelligent tutoring systems programming learning

来源：评论

学校读者我要写书评

暂无评论

A modern approach to supporting program visualization: from a 2D notation to 3D representations using augmented reality

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2021年第1期80卷 543-574页

作者： Schez-Sobrino, Santiago Garcia, Maria A. Lacave, Carmen Molina, Ana I. Glez-Morcillo, Carlos Vallejo, David Redondo, Miguel A. Univ Castilla La Mancha Spain Dept Informat Technol & Syst Paseo Univ 4 Ciudad Real 13071 Spain

The visualization of programs and algorithms has been demonstrated to be essential when learning to program. Nevertheless, existing graphic representations require a high level of abstraction that most beginner programmers cannot understand. Current state-of-the-art approaches provide promising alternatives, but a significant part leaves the advantages of graphic representation in the background. These advantages include abstracting the source code by means of symbols that make them easier to understand without previous training. This work introduces the evolution of a 2-D graphic notation to a 3-D environment, which represents an improvement to a complete platform for collaborative programming learning through problem solving, named COLLECE-2.0. This improvement provides the platform with capabilities to visualize programs through augmented reality by using a new set of graphic representations, which are based on roads and traffic signs in the context of programming learning. These visual models have been evaluated by Computer Science students to know whether the proposed notation is intuitive and useful. The obtained results show that the proposed notation is suitable for representing programming concepts and easy to understand. We also present a series of improvements, integrated as a new subsystem in the aforementioned platform, which allows the automatic construction of 3-D visualizations on an augmented reality environment. These visualizations use the proposed notation and leverage the scalability and architecture of COLLECE-2.0.

关键词： Computer-Supported Collaborative learning (CSCL) Program visualization programming learning Three-dimensional displays Augmented reality Eclipse

来源：评论

学校读者我要写书评

暂无评论

Multi-Label Code Error Classification Using CodeT5 and ML-KNN

引用

IEEE ACCESS 2024年 12卷 100805-100820页

作者： Amin, Md Faizul Ibne Shirafuji, Atsushi Rahman, Md Mostafizer Watanobe, Yutaka Univ Aizu Grad Dept Comp & Informat Syst Aizu Wakamatsu Fukushima 9658580 Japan Dhaka Univ Engn & Technol Informat & Commun Technol Cell Gazipur 1707 Bangladesh

programming is an essential skill in computer science and in a wide range of engineering-related disciplines. However, occurring errors, often referred to as "bugs" in code, can indeed be challenging to identify and rectify, both for students who are learning to program and for experienced professionals. These errors can lead to unexpected behaviors in programming. Understanding, finding, and effectively dealing with errors is an integral part of programming learning as well as software development. To classify the errors, we propose a multi-label error classification of source code for dealing with programming data by using the ML-KNN classifier with CodeT5 embeddings. In addition, several deep neural network (DNN) models, including GRU, LSTM, BiLSTM, and BiLSTM-A (attention mechanism) are also employed as baseline models to classify the errors. We trained all the models by using a large-scale dataset (original error labels) as well as modified datasets (summarized error labels) of the source code. The average classification accuracy of the proposed model is 95.91% and 84.77% for the original and summarized error-labeled datasets, respectively. The exact match accuracy is 22.57% and 27.22% respectively for the original and summarized error-labeled datasets. The comprehensive experimental results of the proposed approach are promising for multi-label error classification over the baseline models. Moreover, the findings derived from the proposed approach and data-driven analytical results hold significant promise for error classification, programming education, and related research endeavors.

关键词： programming profession Codes Accuracy Source coding Education Task analysis Machine learning Big Data Error analysis learning systems Software engineering CodeT5 data analysis educational big data error classification learning analytics ML-KNN multi-label classification programming learning software engineering

来源：评论

学校读者我要写书评

暂无评论

Knowledge Tracing Within Single programming Practice Using Problem-Solving Process Data

引用

IEEE TRANSACTIONS ON learning TECHNOLOGIES 2020年第4期13卷 822-832页

作者： Jiang, Bo Wu, Simin Yin, Chengjiu Zhang, Haifeng East China Normal Univ Dept Educ Informat Technol Shanghai 200062 Peoples R China Zhejiang Univ Technol Coll Educ Sci & Technol Hangzhou 310014 Peoples R China Kobe Univ Informat Sci & Technol Ctr Kobe Hyogo 6578501 Japan Carnegie Mellon Univ Human Comp Interact Inst Pittsburgh PA 15213 USA

Accurately tracing the state of learner knowledge contributes to providing high-quality intelligent support for computer-supported programming learning. However, knowledge tracing is difficult when learners have only had a few practice opportunities, which is often common in block-based programming. This article proposed two knowledge tracing models that can exploit the problem-solving process data generated by learners from a single programming task. A novel metric, the approaching index, was developed using the tree edit distance in abstract syntax trees to measure the similarities between the learners' intermediate solutions and the optimal solution. The proposed method allows for each learner's programming path to be represented as a raw approaching index sequence (AISeq) or as a single variable (AIScore) by averaging the AISeq. A logistic regression model was first designed to predict the learners' performances using their AIScore, the number of attempts, and their current performance. A second model, a recurrent neural network model, was also developed to directly use the AISeq and to make predictions. To verify the effectiveness of these models, a series of statistical analyses and experiments were conducted on two existing large-scale block-based programming datasets, the results from which revealed that the proposed models were competitive with four state-of-the-art models on multiple metrics, such as the precision-recall curve, accuracy, specificity, and Cohen's Kappa. Especially, the proposed models were found to be more robust than the compared models in predicting who would fail to complete the tasks.

关键词： programming Hidden Markov models Predictive models Problem-solving Task analysis Indexes Data models Knowledge tracing performance prediction programming learning recurrent neural network (RNN)

来源：评论

学校读者我要写书评

暂无评论

Multilingual Program Code Classification Using n-Layered Bi-LSTM Model With Optimized Hyperparameters

引用

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2024年第2期8卷 1452-1468页

作者： Rahman, Md. Mostafizer Watanobe, Yutaka Univ Aizu Dept Comp & Informat Syst Fukushima 9650006 Japan Dhaka Univ Engn & Technol Informat & Commun Technol Cell Gazipur 1707 Bangladesh

Programmers are allowed to solve problems using multiple programming languages, resulting in the accumulation of a huge number of multilingual solution codes. Consequently, identifying codes from this vast archive of multilingual codes is a challenging and non-trivial task. Considering the codes' complexity compared to natural languages, conventional language models have had limited success. Deep neural network models have achieved state-of-the-art performance in programming-related tasks. However, the multilingual code classification based on the problem name or algorithm remains an open problem. This paper presents a novel multilingual program code classification model for the code classification task based on algorithms and problem names. First, a layered bidirectional long short-term memory model is designed to better understand the complex code context. Second, preprocessing, tokenization, and encoding processes are performed on real-life datasets. Next, clean and trainable formatted data are prepared. Finally, experiments are conducted on real-life datasets (e.g., sorting, searching, graphs and trees, numerical computations, basic data structures, and their combinations) with optimized hyperparameter settings. The results show that the proposed model can effectively improve the code classification accuracy compared to other baseline models.

关键词： Multilingual program code code classification bidirectional lstm (bi-lstm) layered bi-lstm programming learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：