Moodle-Based Tool to Improve Teaching and Learning of Relational Databases Design and SQL DML Queries

Computer-based concept mapping combined with learning management system use: An explorative study under the self- and collaborative-mode

Hierarchical part-of relationships/aggregation structures and related queries are essential parts of information systems. However, relational database query languages do not explicitly support hierarchical relationships and queries. A hierarchical query may require a great number of join operations, which increases the effort in query formulation. Therefore, we propose path expressions in formulating hierarchical views over relational data because path expressions are a conventional and compact way to represent hierarchical relationships. We embed path expressions within SQL queries and compile them to standard SQL. This ensures that the path expressions can straightforwardly be implemented on the top of standard relational database systems. The compilation of a path expression is given by an attribute grammar, a conventional formalism to define the semantics of a language.

Purpose: This study aims to examine the implementation of technology in educational assessments, specifically using the Learning Management System (LMS) Moodle at SMK Brantas Karangkates. Traditional paper-based tests limit multimedia integration and efficient scoring, whereas online exams offer a more effective and streamlined alternative for learning evaluations. Method: The research focuses on Moodle’s implementation process, detailing steps like preparing questions, setting up quiz features, conducting exams, and managing automated scoring. Observational data and school records were used to analyze Moodle's application. Practical Applications: Using LMS Moodle, with its multimedia and automated grading capabilities, enhances exam efficiency, accessibility, and result management. This practical approach supports schools in modernizing their assessment processes. Conclusion: SMK Brantas Karangkates has effectively used Moodle for online exams over the past five years, showing significant improvements in assessment efficiency. This study illustrates how e-learning platforms like Moodle can support schools in adapting to technological changes in education.

Digital technologies are an enabler for the enhancement of the quality of learning and teaching. By incorporating ICT (Information and Communication Technologies) in the learning process (and therefore achieving blended learning), HEIs (Higher Education Institutions) have the potential to complete the shift from the ,,old way" of teaching and learning (based on the mere transmission of information) to the development of a partnership between the student and teacher that can have a significant impact on the learning and teaching experience overall. Therefore, in order to augment academic performance and to withstand the challenges of an increasingly competitive environment, the Romanian HEIs have concentrated their efforts to develop or configure e-learning platforms that enable the implementation of the blended learning concept. In our previous research we identified that in the Romanian higher educational system, Moodle LMS (Learning Management System) or VLE (Virtual Learning environment) is frequently chosen as the solution for offering e-learning services (56,81% of the Romanian HEIs, both public and private, which have implemented an e-learning system have adopted Moodle LMS). In this paper we will present the case of the University Of Economic Studies Of Bucharest that offers new and improved services for its students by implementing an e-learning platform available as online.ase.ro. The e-learning platform implemented by the University Of Economic Studies Of Bucharest is the Moodle LMS. We will present which were the challenges of this project (for example, the modality in which Moodle LMS was integrated with the university information system - SIMUR) and we will highlight the solutions that have been adopted to overcome them.

The Learning Management System (LMS) continues to persuade instructors and students that the use of the Moodle platform is the correct choice to meet their educational needs. This study presents the personalization of the Moodle LMS based on students’ needs and interest in meeting the intended course objectives. The study employed a quantitative method administered by a questionnaire. The data were analyzed quantitatively and discussed to meet the study objective. The study findings indicated that 61.3% of the respondents have confidence in the use of personalised Moodle LMS to improve their understanding of their lessons. The study also revealed that almost all respondents (95%) agreed that the personalised Moodle LMS motivated students’ learning. Further, and unexpected, the study findings revealed that the Moodle learning environment and pedagogical underpinning were minor challenges to students; instead, the major challenges were infrastructure challenges such as internet access and tools. The study recommends that instructors and students should make the Moodle LMS an essential asset for improving teaching and learning in Higher Learning Institutions. The originality of the contribution of this study is the conclusion that personalized Moodle LMS should be maintained to attract and motivate students in learning activities.

This study examined the use of Advancity Learning Management Systems (ALMS) and the Moodle Learning Management Systems (LMS) in learning settings, as well as online exams, within the framework of Transactional Distance Theory. With 146 college students (nfemale = 102, nmale = 44) as voluntary participants, data was gathered through an online questionnaire. A time series design was used for two different LMS sessions, and participants who voluntarily participated in ALMS and Moodle LMS sessions were matched. The findings revealed that while Moodle and ALMS both receive relatively similar assessment ratings for online exams, Moodle scored better in terms of learning setting. When factors of the Learning Management Systems Evaluation Scale (LMSES) based on Transactional Distance Theory were compared, the dialogue and autonomy factors were significantly higher for Moodle LMS than for ALMS. When online exams in the LMS were compared, there was no significant difference between ALMS and Moodle LMS, and for both LMS, the reliability factor was a determinant indicator than the other factors. As a result, in assessing and using an LMS, choices should be based on how well the LMS characteristics address an institution’s demands.

An important issue to extend database management systems functionality is to allow the expression of imprecise queries to make these systems able to satisfy user needs more closely. In the last few years, some authors have dealt with the problem of relaxing the relational model in order to admit some imprecision. Two significant data mining problems have been addressed recently, namely, mining fuzzy association. rules, and set-oriented mining for association rules in relational database (SETM algorithms). At present, the problem of how to express the mining fuzzy association rules algorithm as SQL queries has not been proposed. In this paper, we attempt to develop a fuzzy version of SETM algorithms that can be expressed as SQL queries in relational databases and discuss optimization of the algorithm.

The main problem has been managing databases because they are continuously expanding quickly and getting more complicated in terms of volume, variety, and velocity. Currently, Relational Database Management Systems (RDMS), also known as SQL, or traditional search engines are primarily used to manage and utilize data collection. Due to their highly semantic properties and applications, relational databases have emerged as powerful and superior during the previous two decades. The handling of a high volume of data and the variability in data type and structure has become a laborious task since Big Data entered the IT industry. Relational databases are inadequate to handle such big data due to their rigid data limitations, structure, relations, and other factors. As a result, data aggregation is rendered impossible. NoSQL databases offer a practical and understandable foundation for combining massive amounts of data, structures, and interactions. Data modeling and migration are now needed in order to define the issue. There isn't yet a tool for switching from relational to no-SQL databases. For this migration, relational (SQL) database queries must be converted to NoSQL database queries. Since relational databases (RDBMS) have found it difficult to keep up with modernization, NoSQL has emerged as the most practical database. This essay aims to highlight and assess the applications of NoSQL, the notion of NoSQL data modeling, and the NoSQL database migration procedure. NoSQL, NoSQL Roadmap, Data Modeling, ETL Approach for Data Migration, Data Loading, and Data Extraction.

<abstract><p>The objective of this paper was to examine the present state of geometric constructions in both international and national mathematics assessments. Additionally, it aimed to shed light on the noticeable lack of geometric construction items in these assessments and propose a solution to incorporate such items by utilizing a web-based mathematics assessment tool. After providing a brief summary of the unique benefits associated with geometric construction problems, the subsequent paper explored the development of a web-based mathematics assessment tool, the procedure for generating automatic evaluation GeoGebra applets for geometric construction problems, and their integration into Moodle learning management system (LMS). The purpose of this assessment tool was to enhance the evaluation of a substantially larger group of students within the realm of geometric constructions. The final section of the paper examined the difficulties encountered in the creation of the automatic evaluation applets and their incorporation into Moodle LMS. Through the development of such a web-based mathematics assessment tool, we enabled the evaluation of a significantly larger number of students, thus aiding not only national and international mathematics examinations but also assisting mathematics teachers in tracking students' scores and progress.</p></abstract>

Asynchronous e-learning allows for targeted teaching, particularly advantageous when bedside and didactic education is insufficient. An asynchronous e-learning curriculum has not been studied across multiple centers in the context of a clinical rotation. We hypothesize that an asynchronous e-learning curriculum during the pediatric emergency medicine (EM) rotation improves medical knowledge among residents and students across multiple participating centers. Trainees on pediatric EM rotations at four large pediatric centers from 2012 to 2013 were randomized in a Solomon four-group design. The experimental arms received an asynchronous e-learning curriculum consisting of nine Web-based, interactive, peer-reviewed Flash/HTML5 modules. Postrotation testing and in-training examination (ITE) scores quantified improvements in knowledge. A 2 × 2 analysis of covariance (ANCOVA) tested interaction and main effects, and Pearson's correlation tested associations between module usage, scores, and ITE scores. A total of 256 of 458 participants completed all study elements; 104 had access to asynchronous e-learning modules, and 152 were controls who used the current education standards. No pretest sensitization was found (p = 0.75). Use of asynchronous e-learning modules was associated with an improvement in posttest scores (p < 0.001), from a mean score of 18.45 (95% confidence interval [CI] = 17.92 to 18.98) to 21.30 (95% CI = 20.69 to 21.91), a large effect (partial η(2) = 0.19). Posttest scores correlated with ITE scores (r(2) = 0.14, p < 0.001) among pediatric residents. Asynchronous e-learning is an effective educational tool to improve knowledge in a clinical rotation. Web-based asynchronous e-learning is a promising modality to standardize education among multiple institutions with common curricula, particularly in clinical rotations where scheduling difficulties, seasonality, and variable experiences limit in-hospital learning.

Purpose: This study had as purpose to examine the factors influencing instructors and students use of the Moodle Platform in teaching online courses in the ICT University, then the theories used in the use and adoption of Moodle platform.Methodology: The article focuses on the systematic review of empirical studies in the use and adoption of Moodle Learning Management System (MLMS) in higher institutions. The authors examined 58 publications on the subject from 2010 to 2019, making critical analysis of theories adopted in the study, the research approach, adoption factors, barriers, constructs used and research context.Findings: Findings from the literature review shown that technological factors, social factors, human factors and reinforcement factors affect the adoption and use of moodle platform. Most publications on this subject are reported using the quantitative research approach. Only a few studies have gained the attention of qualitative approach. Among the technology acceptance models used in the studies, TAM has gained more attention than any other has. The systematic review of literature has brought to the understand that institutes of higher learning in developed as well as developing countries are making remarkable progress in the Moodle Learning Management System (MLMS) as distance-learning tool for knowledge disseminate and acquisition. This practice however, has received more attention in the developed than in the developing countries. The outbreak of CCOVID-19 led to the promotion of social distancing. Institutions of higher learning can only become sustainable in the present dispensation if they promote the use of distance learning tools such as MLSM.

The purpose of the study is to highlight the theoretical and methodological aspects of preparing the test questions of the most common types in the form of text files for further import into learning management system (LMS) Moodle. The subject of the research is the automated filling of the Moodle LMS test database.The objectives of the study: to analyze the import files of test questions, their advantages and disadvantages; to develop guidelines for the preparation of test questions of common types in the form of text files for further import into Moodle LMS.The action algorithms for importing questions and instructions for submitting question files in such formats as Aiken, GIFT, Moodle XML, “True/False” questions, “Multiple Choice” (one of many and many of many), “Matching”, with an open answer – “Numerical” or “Short answer” and “Essay” are offered in this article. The formats for submitting questions, examples of its designing and developed questions were demonstrated in view mode in Moodle LMS.

This study aims to develop a MOODLE-based training model for innovative learning integrated with deep learning to enhance teachers’ teaching abilities. This research employed the Borg and Gall research and development (R&amp;D) model up to the expert validation stage. The participants consisted of five school principals and twenty teachers. Data were collected through interviews, open-ended and closed-ended questionnaires, and focus group discussions. Qualitative data were analyzed using the Miles and Huberman model, while quantitative data were analyzed using descriptive statistical techniques, including percentages, categories, and mean scores. During the Research and Information Collecting phase, the findings indicated that teachers’ ability to implement innovative learning methods integrated with deep learning was categorized as sufficient, highlighting the need for further improvement. The developed training model is an online training program based on the MOODLE learning management system. The model consists of a visual representation and a detailed description outlining the concept of online training for innovative learning integrated with deep learning. Based on the validation conducted by four experts in content, technology, and instructional design, the conceptual model was rated very good, with an average score of 4.2. This result indicates that the model is valid and feasible to be further developed into a procedural training model to improve teachers' pedagogical competence. This study implies that technology-supported professional development models, such as INDEEP-MOODLE, provide a structured, sustainable, and scalable alternative to conventional workshop-based training for integrating innovative and deep learning principles into teachers’ pedagogical practices.

At present, storing XML document in a relational database is a hot topic because relational databases are mature and scale well. In this paper, a novel relational database storage structure that can store XML document is proposed. An algorithm that translates XML document to relational database is given according to the proposed storing structure and algorithms that translate XPath Query to SQL Query which runs on SQL Server 2000 is also given. The steps and algorithms are given in detail to describe how to use the storing structure to storage and query XML document in relational database. Then, an example is presented to show how to use this method and approve the correct of the proposed storing structure and given algorithms. Compared with other methods, the method in this paper has advantage in compact translated SQL, lesser relational database space and quicker query speed.

SQL is the programming language for communicating with relational databases, but writing SQL queries is challenging for many end users due to lack of programming knowledge. In this paper, we present an efficient and accurate algorithm that helps users to synthesize SQL queries from IO examples, which is the first algorithm to encode SQL synthesis problem into constraint-solving problem. We propose an axiom that encodes the semantics of a SQL query into logic constraints, and decompose the SQL synthesis problem into two parts: problem-encoding and constraint-solving. For the problem-encoding part, we use a SQL template that is same as prior work and parameterize it, then based on this axiom, we encode the parameters into logic constraints. For the constraint-solving part, we use the off-the-shelf modern SMT solvers. Our algorithm supports multiple IO examples, therefore users can add more examples to refine the solution until a correct one is found. We implemented a tool, SqlSol, and evaluated it on 171 benchmarks. The results showed that it efficiently solved 68% of the benchmarks in 3 s in average. For those SqlSol cannot solve, SqlSol terminated in 4 s in average.