Learning Path For Students Research Articles

Research on the Construction Method of Curriculum Teaching Knowledge Graph Based on Bi-LSTM and CNN Algorithm

The aim of the paper is to explore a method of constructing a curriculum teaching knowledge graph by combining Bi-LSTM and convolutional neural network (CNN) algorithm. The field of education is constantly seeking innovation to improve teaching results and student learning experience. Knowledge graph, as an advanced technology of structured representation of knowledge, is expected to provide effective support for teaching management and personalized learning. First, this paper introduces the background and significance of the curriculum teaching knowledge graph. By establishing knowledge maps, we can more clearly present the knowledge system and correlation in the curriculum, which helps teachers to design more targeted teaching content and provide personalized learning paths for students. However, traditional knowledge graph construction methods are often faced with problems such as incomplete information capture and inaccurate semantic association, so it is necessary to introduce advanced deep learning algorithms to improve the quality of knowledge graph. Secondly, this paper elaborates on the construction method of fusion Bi-LSTM and CNN algorithm. Bi-LSTM, as a recurrent neural network capable of capturing sequence information, can better model the evolution process of knowledge in the course. As a CNN is good at extracting local features, CNN can effectively capture the spatial structure information in the knowledge graph. By integrating two, we can improve the expression ability and reasoning accuracy of knowledge graph. Further, the experimental results show that the fusion Bi-LSTM and the CNN algorithm have significantly improved the accuracy of information capture and inference compared with the traditional method. In summary, this paper proposes an innovative construction method of curriculum teaching knowledge graph by integrating Bi-LSTM and CNN algorithm, which provides new ideas and solutions for informatization and personalized teaching in the field of education. In the future, the applicability of this method in different disciplines and teaching scenarios can be further discussed, and more advanced technologies can be combined to continuously improve and expand the research.

TRANSFORMASI PENDIDIKAN DAN EKONOMI DI YAYASAN AL-JADID KELURAHAN BARU MELALUI KOLABORASI AKSI SOSIAL DAN PENGETAHUAN INOVATIF

Education is very important for human development completely to educate and improve the life of the nation. Social Work Lectures (KKS) are a concrete manifestation of the duties of lecturers and students in implementing the Tri Dharma of Higher Education, namely the service aspect. Through community service activities in Baru Village, one of which is the Al- Jadid Foundation, there is synergy between universities and the community as a form of democratic knowledge. The aim of this KKS activity is to move away from the traditional education model which is one size fits all and focuses on providing personalized learning paths for students so as to optimize educational and economic values ​​in empowering society. KKS is carried out through activities: hydroponic empowerment, KKS teaching RA and TPQ, socialization of student savings, Ar Riyadh Lil Sihhah (gymnastics), making wall panels, Arabic language socialization, sharia banking seminars, cleaning mosques, and Islamic arts performances. The results of the service provide an illustration of the increasing enthusiasm of children, teachers, the community and Foundation officials in socializing and implementing Islamic-based education.

Ukrainian education for peace and security 2023: Technological convergence, artificial intelligence

The article highlights the impact of the integration of artificial intelligence (AI) into the educational environment, focusing on the possibilities of technological convergence. Based on the recognition of the changing world and the need to adapt educational approaches to the challenges of today, the study offers a deeper understanding of the role of innovative technologies. The study reveals the potential of AI to create personalised, adaptive learning paths for students of different educational and qualification levels. The use of AI algorithms to customise the learning process to individual needs promotes critical thinking and collaboration, which are important for building a safe social environment. The study highlights the possibility of using AI to reduce social inequality in areas affected by military aggression. The introduction of AI in the educational process can ensure equal access to quality education for all regions. The authors of the article emphasise the need for a multidisciplinary approach to the use of AI in education, where the interaction of educators and civil society is crucial for the implementation of technologies with ethics and efficiency. An innovative approach to education supported by AI can foster cooperation, understanding, and cohesion, contributing to a stable and harmonious society.

An empirical study of the efficacy of AI chatbots for English as a foreign language learning in primary education

ABSTRACT This experimental research examined the effectiveness of using chatbots in English as a Foreign Language (EFL) classrooms at a Chinese elementary school. Seventy-four students were divided into two groups: one employing traditional methods, and the other using chatbots. Before and after the 3-month teaching period, pre- and post-tests were used to measure students’ oral English proficiency, and a questionnaire was employed to assess their willingness to communicate (WTC). Data from interviews with teachers and students provided insights into chatbot usage and modification. Data analysis involved using SPSS to identify significant differences in pre- and post-test scores and NVivo 11 to code qualitative feedback from student and teacher interviews. The results show that chatbot integration significantly improved oral English proficiency and WTC in the experimental group compared with the control group. Teachers can enhance instruction by adopting tailored chatbot features to refine teaching methods, thus creating a more adaptive learning path for students. Further, chatbot improvements such as personalised error correction and user-centric features pave the way for immersive and fruitful language learning. This study provides valuable insights for integrating chatbots into language classrooms and suggests opportunities for further chatbot enhancements..

Research on the Optimization Pathways of University Education and Teaching Reform based on OBE Concepts

Abstract This paper proposes to introduce OBE theory in the curriculum map so as to build a curriculum master map based on the concept of engineering education accreditation-oriented and professional training objectives. In order to provide personalized services to students in the curriculum map, this paper applies the user-based collaborative filtering recommendation algorithm to the curriculum map and uses a similarity calculation based on Barclay’s coefficient improved similarity (BCCF) to finally implement the curriculum recommendation algorithm. The results show that the AUC of the recommendation algorithm constructed in this paper reaches 0.867. After the teaching reform, the mean values of students in the course reform class are 0.68, 0.61, and 1.31 higher than those in the non-course reform class at the level, of course, affect perception, teacher teaching, and student learning. Therefore, the OBE-based teaching method in this paper can develop personalized learning paths for students, which helps students learn better and plan the overall learning paths and make the most of educational resources.

A Novel Method for Constructing Online Learning Paths Based on Cognitive Level Assessment of College Students

The cognitive level of students is a very important factor that should be considered when constructing learning paths, however, it’s not that all students could have sufficient technical skills to participate in learning programs offered by the learning paths, so in real cases, the learning paths can hardly meet the actual learning requirements of each student. To solve this matter, this paper aims to explore a new method for constructing online learning paths based on the cognitive level assessment of college students. At first, this paper introduced a deep learning model into the assessment of college students’ cognitive level, that is, the collected data of the feedback assessment information of student learning was adopted to assess the cognitive level of students, then the paper introduced in detail the structure and principle of the proposed model. After that, this paper proposed a weighted learning method that integrates the learning paths of students with different cognitive levels to ensure the interpretability of the generated learning paths. For a specific student cognitive level on learning paths, the proposed method assigns different weights for learning paths based on history student cognitive level on each node of the learning paths, thereby planning better and easier learning paths for students to achieve their learning goals. At last, experimental results verified the validity of the constructed model and the proposed method.

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.

Factors influencing civil engineering university students’ decision making

ABSTRACT A qualitative study is presented to answer the research questions of (1) What are the main factors influencing the decision-making behaviours of civil engineering students and (2) What role could education play in enhancing the decision making of both students and practitioners. A pilot co-curricular intervention programme is described that blurs the lines between an academic’s ‘teaching’ and ‘research’ time and a student’s ‘curricular’ and ‘extracurricular’ time engagement to diversify and elevate student-learning paths and career outcomes. The results indicate that the intervention improved critical thinking. Moreover, motivation features heavily in decision making, particularly over the conflict between interest and enjoyment and the reward structures of traditional education and industry. This involves higher levels of intrinsic motivation, especially relatedness with peers and instructors. The findings have both ontological and practical implications and lead to the application of interventions in academic project environments.

ADA for IBL: Lessons Learned in Aligning Learning Design and Analytics for Inquiry-Based Learning Orchestration

Orchestrating technology-enhanced learning is a difficult task, especially in demanding pedagogical approaches like inquiry-based learning (IBL). To foster effective teacher adoption, both the complexity of designing IBL activities and the uncertainty about the student learning path during enactment need to be addressed. Previous research suggests that aligning learning design and learning analytics can be an effective way to provide such orchestration support. This paper reports on a design-based research (DBR) project to explore teachers’ orchestration needs in Go-Lab (a technological ecosystem for IBL used by thousands of primary and secondary school teachers around the world), and on how solutions that align learning design and analytics can fulfill such needs. The analysis of data from multiple events (including surveys, case studies, workshops with teachers, and platform usage analyses) led to a catalogue of IBL orchestration needs that can be tackled by aligning learning design and analytics, as well as a list of guidelines for technology development aiming to support IBL orchestration. These two contributions can support the creation of future learning analytics–enhanced IBL environments that are both pedagogically grounded and usable by teachers in authentic settings.

Building Learning Paths of Students’ Creative Thinking Circle Topics by Applying The Scaffolding Metacognition Approach

Mathematics is knowledge which generally has prerequisite material that students must have to understand new material. This means that to understand a material in mathematics learning trajectory is needed. Prior knowledge is the most crucial thing that makes students able to connect all existing information so that they can construct new knowledge through the process of assimilation or accommodation. This study aims to: (1) build student learning trajectories in solving problems about circles, (2) find out how students’ creative thinking abilities with learning paths are designed that apply the Scaffolding metacognition approach. This type of research is Design Research to improve the quality of learning. In this study the researchers gave 3 items about the ability to think creatively. Two trials were conducted, the first trial was conducted in class A and the second trial was conducted in class B. The results of the study indicate (1) There are 3 phases in the learning trajectory of students’ creative thinking abilities, namely: 1. Analysing, including determining information from questions, selecting important information, and choosing the right strategy in solving it; 2. Identifying, including determining the adequacy of the elements in the problem, making mathematical models, and can describe the problem; 3. Evaluating, including finding and detecting important matters in the problem and drawing appropriate conclusions. (2) The results of students’ creative thinking ability tests in trial 1 shows that students have not been able to solve problems optimally. Students’ lack of understanding of the concept of a circle and determining the circumference of a circle make it difficult for students to solve problems regarding the length of the tangent circle. By developing the previous learning trajectory, in trial 2 there was an increase in students’ creative thinking abilities. The design of a correct learning trajectory is also very influential in increasing the ability of students. And make the learning process fun and meaningful so that students will remember knowledge in long-term memory.

Engagement of Students in Data Visualization for the Purpose of E-Learning Improvement

The study describes an approach to e-learning based on the Moodle platform that is used to visualize participation in the learning community and is proposed to be used to inform students and teachers about their involvement in the social learn-ing environment. The experiment involved 5 teachers and 3 experts who deter-mined the most significant visualization indicators for the virtual learning envi-ronment dashboards. There were 42 students aged 21 to 23. The virtual learning environment is based on the Moodle and Blackboard platforms that are common-ly used in universities. SocialWall allowed participants to perform actions in the social environment that are visualized in graphs under the specified criteria. A Wiki repository plugin was also added in order to accumulate student knowledge in shared structured documents stored in a shared repository. The relational data-base management system MySQL allows creation of additional relations, data-base design and administration. The visualization activities described in the study are based on modified state transition networks to analyze and visualize the stu-dent learning path. Student trajectory networks show the interaction of individual learners or groups with the course structure and material.

Intelligent Support System for Personalized Online Learning

The current conditions of the COVID-19 pandemic have required universities to transfer educational processes in the online environment. eLearning systems provide educational institutions and students with the opportunity to effectively organize the educational process and share knowledge. They provide each student with freedom of access to information and flexibility of the learning process. The student can individually determine the duration and sequence of courses by changing the trajectory of the educational process following their needs. In the context of the pandemic, students and teachers have to optimize their work over the Internet. This requires more extended personalization of the learning process. Intelligent technologies allow you to construct personalized learning paths for each student, varying methods, forms, and speed of learning. This study presents the architecture of the e-learning support system for the selection of online resources and for including them in the student's learning path. The system developed as a set of personal agents and services that interact based on a set of interconnected ontological models. Ontologies provide a more adequate representation of online resources and compatibility of the user request format with descriptions of training resources from different developers. The system recommends training modules based on current requests and user characteristics that match their profile. The system dynamically updates the knowledge base user characteristics, thereby increasing the effectiveness of recommendations.

The contribution of Social Network Analysis in conceptualizing school failure: A methodological reflection on an exploratory inquiry

This paper presents the rationale for adopting Social Network Analysis (SNA), as a methodology for inquiring into the complex system of causal factors that impacts on the scholastic achievements of at-risk students. SNA provides an analytical perspective that can be contextualized within a socio-cultural theoretical model, by considering development as a factor that is closely interconnected with the cultural, social and relational environment in which the student is immersed. The unit of concern in Social Network Analysis is the pattern of social relationships, constituted by connections, boundaries and gaps among educational communities. Through the use of SNA, it is possible to investigate the structure of social relationships that influence the learning paths of students at-risk of school failure, and the processes and underlying dynamics.In this contribution, the role of SNA is examined by reference to an ongoing research with students at risk of school failure in a professional school. We report an exploratory inquiry in which the SNA is applied to highlight the development of the social relationships in a class of students, during the course of a group activity in a vulnerable school context (developed inside the FAMI-IMPACT FVG 2018-2020 project). The SNA highlights the role that innovative activities can have in sustaining interdependence and reciprocity among students and support their motivation to learn.

Implementing the Adaptive Learning Techniques

The concept of adaptive learning emerged a few decades ago, but most theoretical findings have never been put into practice, and software solutions had no significant reach for a long time due to insufficient e-learning technology development and coverage. The recent advancements of information technology allow the elaboration of complex big data analytics and artificial intelligence solutions, in adaptive learning in particular. This article investigates exploitation of adaptive learning technology and techniques.The solutions proposed allow mapping optimal individualized learning paths for students in online courses, using the ratio of the level of knowledge at course completion to time spent on the course as an optimality criterion. A genetic algorithm is used to solve this optimization problem. A model based on the speed of forgetting was applied to extrapolate the level of retained knowledge. Practical implementation of the technology proposed involves a set of tools to expand the adaptive learning opportunities of distance learning systems and a module to operate the genetic algorithm. We developed a few options of software architecture using different technologies and programming languages and either one or two servers. The solution was tested during the design of adaptive learning courses for National University of Science and Technology MISIS (NUST MISIS) and Tomsk State University of Control Systems and Radioelectronics (TUSUR).

ЦИФРОВЫЕ ИНСТРУМЕНТЫ В ОБУЧЕНИИ СТУДЕНТОВ-ЮРИСТОВ В УСЛОВИЯХ ДИСТАНЦИОННОГО И СМЕШАННОГО ОБУЧЕНИЯ

The article discusses the problems of organizational, legal and software and technical implementation of distance and blended learning based on the creation of an educational platform of the university, implemented using cloud computing. The combination of new approaches to the organization of training and educational solutions allows you to create effective digital resources for a more visual presentation of educational material, work in small groups, using the technology of the inverted classroom, gamification, and building individual student learning paths. The analysis of the possibilities of educational platforms for the creation and placement of multimedia digital content, journals of student activities, testing, scientific research is presented. As a result, it was concluded that existing digital technologies, including cloud computing, make it possible to form a system of electronic, distance and blended learning, based on the requirements of educational standards for the content of courses and disciplines, planning students' activities, monitoring and correcting their activities, assessing and the formation of assignments for self-study.

Influence of Motivation Learning, Lecturer Competence, Family Environment and Community Environmental on Learning Achievement of Student in State University of Jakarta

This research is made to know and analyze the factors that Affect Learning Achievement in the form of Motivation, Competence Lecturer, Environmental Family and Community Environment. The technique used in the sampling in this study was the Smart PLS, with a sample of 244 respondents. Data collection using questionnaires using Smart Partial Least Square with Smart PLS 3.0 software. The results and implications of this study are terrorism that this study supports previous research the which states that previous research has been Carried out by Bebi Ratnasari (2016) with the title Influence Of Learning Motivation, Teacher Competency, And The Family Environment Of Learning Achievements Accounting Trade Company Class XI Accounting Vocational School YPKK 2 Sleman where the results of this study indicate that customer satisfaction has a positive effect on improving Learning Achievement. Based on the results of data analysis known that there posisif influence and significant correlation between learning motivation towards Achievement of Student Learning Path coefficient value 0,066. Lecturer competence significantly influence the achievement of Student Learning Path coefficient value of 0.047. Family environment significantly affect the value of Student Learning Achievement Path coefficient 0,981. While no effect on the Community Environmental Achievement of Student Learning. It is seen from the results obtained path is negative coefficient that is equal to -0.049.

Design and implementation of data collection mechanism for 3D design course based on xAPI standard

ABSTRACT 3D design software is a commonly used interactive learning tool in STEM education. It is generally believed that 3D design can effectively train students’ spatial thinking and engineering design abilities. There have been many theoretical and practical achievements in the application of 3D printing education, but the evaluation of 3D design is mainly based on diagnostic and summative evaluations, which ignores the growth of students’ spatial thinking and engineering design ability. Students’ creativity and problem-solving abilities are limited, while teachers have not been able to teach students in accordance with their aptitude. In this study, we propose a 3D printing course data collection model based on xAPI specifications, and use GeekCAD design software to implement the xAPI profile and apply it to the 3D printing course. The successful implementation of this model at Li Jun primary school proved that xAPI can completely record the learning paths of students. Through the analysis of interactive data, we found that students have different operating habits and learning paths which provide the basis for the evaluation of students’ spatial thinking ability and engineering design skill in interactive learning environment.

The Profile of Student Analytical Skills through Hypothetical Learning Trajectory on Colligative Properties Lesson

Students often have difficulty in understanding chemistry lessons, especially Colligative Properties. Teachers should have systematic learning plans so that students understand the content of learning well. Hypothetical Learning Trajectory (HLT) is effective to be used in the learning process because it becomes an idea in designing detailed learning paths. Besides that, learning outcomes can be achieved well and optimally. This study uses qualitative and quantitative approaches. Data processing is carried out based on four assessment criteria. First, student responses that appear based on response predictions, second, student ability test scores, third, analysis of learning activities, and finally science process skills (SPS). The results showed that the didactic presented by the teacher as a student learning path was good enough. Only 12% of student responses are beyond predictions. Furthermore, student SPS through the use of HLT shows that classification and communication skills have a high value, respectively 82% and 81%. Meanwhile, based on Piaget's approach, students' conceptual abilities are better (56%), compared to other abilities. Therefore, the application of HLT to the material of colligative properties towards students is very good.

Interactive Learning Environment Supporting Visualization in the Teaching of Probability

AbstractThe probability is exceptional in the teaching of mathematics because students often have difficulties to understand the basic terms and the problem solving strategies. Understanding lacks of the probability concept and various types of misconceptions arise from the misleading intuition and misinterpretations of experience with the stochastic phenomena. The probability concept seems too abstract to some students therefore it is advisable to use mathematical problems based on real-life ideas, such as drug efficacy testing, tests for diagnosing of diseases in medicine, sports competitions, and games. By eliminating misconceptions and improving understanding of the problem solving strategies, it is possible to use various types of visualization to solve problems from this field of mathematics. Tables and different types of graphic diagrams can help students to understand the basic rules and problem solving techniques. This paper describes the main objectives and the structure of an interactive worksheet, prepared in spreadsheet environment, in which students are guided to use the visualization to solve probability problems. The implementation of an automatic feedback enables to evaluate the students’ answers. In the case of incorrect answer, solutions of the additional tasks using tree diagram or a tangram are recommended to the students. Students can decide which type of the visualization is more understandable for them to solve the probability of random events. Solving different task sequences using the selected types of visualization allows more learning paths for students. The final part of the paper contains an evaluation of the results and experiences of problem solving in the teaching of probability at grammar schools.

Propuesta de modelo tecnológico para Flipped Classroom (T-FliC) en educación superior

The Technology Model, called T-FliC is proposed for Flipped Classroom. The aim is to provide IT facilities to the aforementioned pedagogical model. This proposal may be implemented at different levels of higher education. T-FliC is primarily based on the use of free technology resources, especially Google applications such as Classroom, Drive, and YouTube, because they are widely used by students and teachers. This extensive use permits to replicate this model in different educational contexts. The T-FliC model incorporates five ICT phases, ranging from the planning of teaching-learning activities to continuous learning assessments. The implementation of the T-FliC Model includes the following phases: a digital class (learning outside the classroom) with asynchronous guidance of a virtual tutor; a workshop involving dynamic activities for collaborative work (classroom learning) guided by a tutor in person; and an ongoing technological tools evaluation process (clickers, portfolio, and forum) which will generate the digital records of the student learning path. This article includes a bibliographic review of the role of ICT in the education processes and the fundamentals of the Flipped Classroom (FC) methodology. In the paper are included FC implementation experiences in higher education, followed by the presentation of the T-FliC Model as a technological proposal for this methodology. Finally, the conclusions present reflections on the proposal.