Data Structures Course Research Articles

Metrics With Performance Indicators Used For Calculating the Mapping Strength of Course Outcome With Program Outcome

Abstract : Outcome-Based Education (OBE) worldwide plays a pivotal role in enhancing academic standards by equipping students with problemsolving skills. To effectively assess the quality of education, it is essential to intricately map courses with specific program objectives (POs). The AICTE introduced a comprehensive exam reform policy in 2018, aiming to enhance assessment methodologies. This innovative approach involves categorizing each Program Outcome (PO) into distinct competencies and subsequently breaking down each competency into a specific number of performance indicators. This innovation enables a more nuanced evaluation of educational outcomes. In this context, a developed metric proves instrumental in aligning the data structure course with relevant performance indicators (PIs). This systematic mapping ensures that educational programs align with desired outcomes, fostering a dynamic and responsive learning environment conducive to addressing complex challenges. Keywords : Performance indicators, Competencies, Course outcome, Program outcome

Fathom: a technology-enhanced learning environment for teaching-learning of expand-reduce skills in software design

Software design problems are often characterized as ill-structured because the requirements are not clearly defined. These problems offer various solution paths and the criteria used to select the solution may not be known initially. The expertise and experience of designers play a crucial role in determining the quality of software design. Less experienced designers often tend to prematurely narrow down their options to a single solution without fully exploring the problem-solution space. This tendency has a negative impact on the overall quality of software design. Studies have shown that systematically expanding the problem space before reducing to problem formulation and exploring the solution space before reducing it to a single solution (expand-reduce skills) improves the quality of the design. We have designed and developed a technology-enhanced learning environment (TELE) named Fathom for scaffolding expand-reduce (ER) skills in software design problems in a data structures course. In this paper, we present three cycles of design, development, and evaluation of Fathom based on the design-based research (DBR) approach. In the first DBR cycle, we identified and evaluated Fathom’s pedagogical features in learning ER skills. In the second cycle of DBR, the aim was to improve the design of Fathom for the learning and transfer of ER skills. Fathom was revised in the third cycle of the DBR to scaffold metacognitive skills. The main contribution of this research is pedagogical design for facilitating the learning of expand-reduce skills in solving software design problems.

Research on Teaching Methods to Improve the Teaching Effect of Data Structure Course for Electronic Information Specialty

Research on Teaching Methods to Improve the Teaching Effect of Data Structure Course for Electronic Information Specialty

Application of Algorithm Visualization Techniques in Teaching Computer Data Structure Course

Abstract With the current development of computer science education, traditional teaching methods can no longer meet students’ needs for in-depth understanding of complex data structures and algorithmic concepts. Using algorithm visualization technology, an emerging teaching aid, dramatically enhances the intuitiveness and interactivity of teaching by presenting abstract data structures and algorithmic processes graphically. Effectively integrating algorithm visualization technology into teaching computer data structure courses to improve teaching effectiveness and students’ learning efficiency remains a significant challenge in today’s education field. The experimental control method in the article compares and analyzes the differences between the teaching practice integrating algorithmic visualization techniques and the traditional teaching methods in improving students’ computer thinking ability, academic performance, satisfaction, and learning effectiveness. After one semester of teaching experiment, the average improvement of computer thinking dimensions such as abstraction ability and decomposition ability of the experimental group is significantly higher than that of the control group, in which the abstraction ability is improved by 21.53% and the decomposition ability is improved by 0.61 compared with that of the control group. In terms of learning achievement, the average achievement of the experimental group is 18.67% higher than that of the control group, and the algorithmic visualization technology significantly enhances learning efficiency and achievement. The algorithmic visualization technology has a significant effect on improving learning efficiency and achievement. Students in the experimental group rated higher than the control group in all dimensions of teaching satisfaction and learning effectiveness, especially in teaching intuition. It can be seen that algorithm visualization technology can effectively improve the teaching effectiveness of computer data structure courses, and enhance students’ learning interest and efficiency.

Reform and Exploration of BOPPPS Teaching Model based on Problem-Based Learning in the course of Data Structure and Algorithm

With the continuous development of computer science and technology, data structure and algorithm have become one of the core courses of computer major. However, traditional teaching methods are often difficult to stimulate students’ learning interest and initiative, resulting in students’ difficulty in flexibly applying the knowledge in practical application. Therefore, this paper proposes a BOPPPS teaching model based on problem-based learning (PBL). Through the introduction of practical problems, attract students’ attention, use BOPPPS mode to guide students to actively participate in classroom activities, improve students’ subjective initiative, and combine intelligent teaching platform and curriculum ideological and political elements to help students learn professional knowledge while cultivating correct outlook on life, values and world outlook.

A novel approach to source code assembling in the field of algorithmic complexity

Computational complexity analysis plays an essential part in the education of computer and software engineers. For that reason, it is carefully studied in programming courses, as well as in the algorithms and data structures courses. The number of students who learn programming is rapidly growing, but the number of teachers cannot keep up with that trend. Therefore, it is necessary to develop tools that can ease and accelerate the daily tasks of teachers, especially for learning purposes and in the context of automating the processes of exam preparation. We propose a novel template- and rule-based approach and a corresponding software system for assembling synthetic source code segments of defined time complexity. Based on the developed grammar, the system can produce source code segments with a broad scope of different time complexities while guaranteeing the complexity of the generated segment. The system can be used for generating questions for exams as it can assemble a large number of different code segments that can be given as questions that have similar difficulty levels. The system was evaluated both by human experts and ChatGPT tool.

Cognitive Aspects in Problem Solving: The Case of a Data Structures Course for IS Students

Cognitive Aspects in Problem Solving: The Case of a Data Structures Course for IS Students

Research on Project-driven Data Structure Teaching Reform

This paper proposes relevant solutions to the current problems in data structure teaching design. Introducing project-driven teaching methods into data structure courses, relying on actual projects, enables students to master data structure knowledge during the process of completing projects, and achieve the teaching purpose of data structure. Teaching practice has shown that project-driven teaching methods not only effectively overcome the drawbacks of traditional teaching methods, but also enhance students' comprehensive abilities and cultivate their comprehensive qualities.

Exploration of Online and Offline Mixed Teaching Model for Data Structure Courses Based on the Ideological and Political Education

The traditional offline teaching in the data structure courses had problems such as programming training, concept and application separation. The paper analyzed the current situation of mixed online and offline teaching research in the data structure courses, explored the implementation path of ideological and political education, used diversified teaching methods and multi-dimensional evaluation systems, and strengthened the organic combination of ideological and political education with course content. A online and offline mixed teaching model based on the ideological and political perspective of the curriculum has been proposed. This provided valuable reference for the ideological and political education courses.

Dungeon Code: Educational Game For Algorithm and Data Structure Courses by Applying The Game Development Life Cycle Method

Algorithm and Data Structure is a basic course in Informatics Study Program, at Khairun University. This subject needs to be mastered because it becomes the foundation that can support the learning process in the future. However, from the results of a survey conducted, as many as 40% of students felt bored with the teaching methods used by Algorithm and Data Structure lecturers in class. In addition, there were also 73.33% of students that even though they paid attention to the material presented in class, they still found it difficult to understand the material. To overcome this problem, new learning media is needed in the classroom, such as games. This study aims to design educational games that teach algorithms and data structures using the Game Development Life Cycle (GDLC) method. The GDLC is a game development method that is widely used to create educational games. The GDLC method has several development stages, namely initiation, pre-production, production, testing, beta, and release. Alpha test results show that all functionality is appropriate. While the results of beta testing show the number 3.43 of the total respondents' answers to the questionnaire related to game evaluation so they are included in the very good criteria.

The Effectiveness of Using a Congruent Visualization Framework on Learning a Data Structures Course

The majority of computer science (CS) educationists agree that learning the Data Structures course (CS2) is very difficult among novices due to its complexity. Consequently, learning the Data Structures course has been associated with a high failure rate. To enable learners understand data structures, algorithms visualizations (AVs) were proposed. Despite the long-term use of AVs in teaching and learning data structures, research shows that such tools have not been as pedagogically effective as expected. This study aimed to evaluate the effectiveness of using a congruent visualization (CV) framework on learning data structures. The framework employs a combination of two congruent program visualization tools, which involve machine-driven and learner-driven approaches. The effectiveness of using the CV framework was evaluated using a combination of experiment, grade analysis, and questionnaire methods. The subjects of the study were 887 first-year undergraduate students from the College of Informatics and Virtual Education (CIVE) of the University of Dodoma in Tanzania, studying the CS 122 Data Structures course. Results show that the use of the CV framework improved both students’ test performance and examination pass rates compared to the traditional approach. Students’ responses from a follow-up survey showed that the use of the CV framework increased students’ motivation and confidence in learning the Data Structures course. Большинство преподавателей информатики (И) согласны с тем, что изучение курса структур данных и алгоритмов (CS2) является сложным процессом из-за его высокой когнитивной нагрузки. Следовательно, изучение CS2 было связано с высоким уровнем неуспеваемости. Чтобы помочь снизить высокую когнитивную нагрузку, возлагаемую на учащихся изучающих CS2, были предложены алгоритмы визуализации (АВ). Несмотря на длительное использование АВ в преподавании и изучении CS2, исследования показывают, что такие инструменты не были столь педагогически эффективными, как это ожидалось. Это исследование было направлено на изучение влияния использования подхода конгруэнтной визуализации (КВ) в преподавании и изучении CS2. В этом подходе используется комбинация двух совместимых инструментов визуализации программ, которые включают подходы, управляемые машиной, и подходы, управляемые учащимся. Воздействие использования КВ-подхода оценивалось с использованием комбинации экспериментов, анализа документов и методов анкетирования. Объектами исследования стали 887 студентов первого курса бакалавриата Колледжа информатики и виртуального образования (CIVE) Университета Додомы в Танзании, изучающих CS2. Результаты показывают, что использование подхода КВ улучшило как показатели непрерывной оценки учащихся, так и показатели результатов сдачи выпускных экзаменов по сравнению с традиционным подходом. Ответы учащихся на последующий опрос показали, что использование подхода CV повысило мотивацию и уверенность учащихся в обучении CS2.

AHP Evaluation Software for Intelligent Reform of Computer Majors in Colleges Based on Interactive Intelligent Testing Algorithm

Mathematics and other cross-composition, its content is very abstract, theoretically strong, students have great difficulty in the learning process. In the new era, in order to further improve the teaching quality of data structure courses for computer majors in colleges and universities, when generating test cases, the one·test-at-a-time strategy is used to generate test cases that cover more total gains through sequential optimization ant colony algorithm. The pheromone update adopts a phased approach. The AHP method is used to evaluate the importance of each influencing factor, and then according to the weight of each influencing factor, the curriculum setting of computer majors in higher vocational colleges is modularized and refined, and a computer curriculum setting plan suitable for the characteristics of higher vocational colleges is formulated accordingly.

Relationship Recognition between Knowledge and Ability Based on the Modularity of Complex Networks

The purpose of formal education is to increase students’ abilities, and its content is to impart knowledge through various courses. Thus, it is essential to accurately identify the relationship between knowledge and students’ ability increment to ensure the quality of education and the sustainable development of education. Currently, this relationship is mainly established based on previous educational data and teachers’ experience, which is often imprecise. This paper proposes a framework for knowledge and ability recognition based on the structural characteristics of complex network modules. The proposed framework utilizes a knowledge cognitive-interdependent network model (KCIN) as its object. First, the key knowledge nodes are identified via cognitive convergence flow of knowledge nodes in KCIN. Subsequently, the module structure of the knowledge network is identified by taking the key knowledge nodes as the core. Finally, the relationship between knowledge and ability is established by identifying the similar attributes of nodes in complex network modules. To validate the framework, we use teaching process data on the Data Structure course, which is a fundamental course for Information majors. The results show that the framework can effectively optimize the knowledge–ability relationship acquired from previous data and teacher experience.

Exploration on the Teaching Reform of Data Structure Course under the Background of "Si Xin" and Engineering Education Certification

Under the background of "Si Xin" and engineering education certification, taking the major of computing science and technology of the College of Information Science and Technology of Hebei Agricultural University as an example, in view of the problems existing in the teaching of data structure courses in the past, a result-oriented data structure course teaching system was built from four aspects: revising the syllabus, reforming teaching methods, improving the assessment and evaluation system, and establishing a continuous improvement mechanism, and scientifically quantified the teaching effect of data structure courses, so as to improve the teaching quality.

THE IMPACT OF COMBINING FOLLOW-UP QUESTIONS AND WORKED EXAMPLES IN PROGRAM VISUALIZATION TOOL ON IMPROVING STUDENTS’ HELD MENTAL MODELS OF POINTERS’ VALUE AND ADDRESS ASSIGNMENT

Previous studies have shown that the lack of a useful mental model of pointers is one of the reasons why many novice programmers fail the data structures course. This study had two main objectives: to analyze the status of mental models of pointers (focusing on value and address assignment); and to evaluate the impact of combining worked-examples and follow-up questions in CeliotM program visualization (PV) tool in the learning of pointers. The subjects of the study were sixty-two second-year undergraduate students taking a course on data structures (PMT 221) at the College of Natural and Mathematical Sciences (CNMS) of the University of Dodoma. Data were collected using pretest and posttest questionnaires. The collected data were analyzed using descriptive statistics. The results showed that 56.5% of the students had incorrect mental models of pointers. The results also showed that using the proposed strategy improved the students’ mental models of pointers from 56.5% to 87.1%. These results contribute to our understanding of the most common misconceptions that novice students may have when learning pointers. The findings of this study confirm previous studies that when the new innovative teaching strategies are used in combination with PV tools in teaching and learning programming can help improve students’ programming comprehension.

Prompt Tuning for Multi-Label Text Classification: How to Link Exercises to Knowledge Concepts?

Exercises refer to the evaluation metric of whether students have mastered specific knowledge concepts. Linking exercises to knowledge concepts is an important foundation in multiple disciplines such as intelligent education, which represents the multi-label text classification problem in essence. However, most existing methods do not take the automatic linking of exercises to knowledge concepts into consideration. In addition, most of the widely used approaches in multi-label text classification require large amounts of training data for model optimization, which is usually time-consuming and labour-intensive in real-world scenarios. To address these problems, we propose a prompt tuning method for multi-label text classification, which can address the problem of the number of labelled exercises being small due to the lack of specialized expertise. Specifically, the relevance scores of exercise content and knowledge concepts are learned by a prompt tuning model with a unified template, and then the multiple associated knowledge concepts are selected with a threshold. An Exercises–Concepts dataset of the Data Structure course is constructed to verify the effectiveness of our proposed method. Extensive experimental results confirm our proposed method outperforms other state-of-the-art baselines by up to 35.53% and 41.78% in Micro and Macro F1, respectively.

Thinking and Practice of Online Teaching in the Context of the Normalization of the COVID-19 Epidemic

Today, when the new crown epidemic has become normal, college teaching must be ready for online teaching at any time, so how to ensure the quality of online teaching is a problem we must think about.In early 2020, in response to the COVID-19 outbreak, classes in the new semester were largely replaced by online teaching to ensure continued learning.Teachers are actively exploring effective online teaching methods to provide a good learning atmosphere for students at home to ensure that students have a good learning effect at home.This paper proposes an online teaching model based on active interaction, and discusses the design of teaching process and problems by taking the data structure course as an example.

Some methods for improving data structure teaching efficiency

Computer simulation and modeling are now widely used in computer science teaching. There are various approaches to make the educational process more efficient. Visualization is one of them, and the flipped classroom approach is another. The goal of this research is to show how to improve the efficiency of teaching data structures (hashing, trees) in the Algorithms and Data Structures course. We conducted two tests with four study groups of second-year bachelor students in two Algorithms and Data Structures subjects – (1) Hashing, (2) Trees (BST, RBT, AVL). In the first experiment, study groups on subjects (1) and (2) were formed using the same type of teaching technique, either with or without visualization tools. In contrast to the first experiment, we employed flipped classroom approaches for one study group and a traditional teaching method for the other.

A demographic analysis on prerequisite preparation in an advanced data structures course

research-article Open Access Share on A demographic analysis on prerequisite preparation in an advanced data structures course Authors: Sophia Krause-Levy University of California San Diego University of California San DiegoView Profile , Sander Valstar University of California San Diego University of California San DiegoView Profile , Leo Porter University of California San Diego University of California San DiegoView Profile , William G. Griswold University of California San Diego University of California San DiegoView Profile Authors Info & Claims ACM InroadsVolume 13Issue 2June 2022 pp 34–41https://doi.org/10.1145/3534563Online:17 May 2022Publication History 0citation114DownloadsMetricsTotal Citations0Total Downloads114Last 12 Months114Last 6 weeks24 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF

Linked List Implementation “Online learning”

Student enrollment in recent years and institutions of higher education have a keen interest in offering quality online MBA programs to meet the demands. This study aimed to develop an online learning platform. The project is a description of one of the methods of the Data Structure Course, which describes how to store data inside the Ram Memory. It is a website that contains a video to explain one of the methods of storing data within the memory of the computer, and the site contains a special page of training, which distinguishes it from the rest of the educational sites. The site helps to test the health of solving the issues of the student training on the lesson. The site shows how to use the pop front method, pop back method, push front method, push back method and delete the list from the memory. All of these functions could be difficult to imagine in reality, so the researchers designed a webpage to do this task.
 
 Keywords: Linked List; online learning; webpage design.