Construction and validation of a questionnaire to assess student satisfaction with mathematics learning materials

Sixth Edition Technological Ecosystems for Enhancing MulticulturalityMathematics is an essential branch for the scientific development and its study is mandatory in most university degrees. However, currently the level of academic performance and motivation of students to learn this science is not the desired one. The students can use different learning tools inside and outside the math classroom, enhancing the quality of the learning materials that are designed essentially to facilitate the learning of mathematics. The present research project aims to determine the validity and reliability of a measurement instrument that allows theassessment of the satisfaction of the students with the availablelearning materials. To fulfill the objectives of this research, the method of survey was used. A study with a quantitative approach was developed, which led to the design and validation of a questionnaire by a group of 7 experts. The validation closed after applying a pilot study with 728 students. It concluded positively, obtaining nine factors that coincide with the revision of the literature: technological quality, quality of content, visual quality, didactic significance, adequacy of content, relationship between theory and practice, involvement, contribution to learning, relevance and interaction between educational actors. The results of this questionnaire provide to the international scientific community with relevant information for the design, selection, and use of study materials in the classrooms, which will contribute to raising the levels of student engagement, and their academic performance in mathematics, secondaril

Design and validation of a questionnaire to assess student satisfaction with mathematics study materials

This paper shows the design and validation of a questionnaire aimed at college students to assess their satisfaction level with mathematics study materials. Starting from the theoretical framework presented, we proposed three dimensions: overall quality of mathematics study materials, didactic adequacy and motivation capacity. To that effect, we hereby explain the analysis and validation procedure of the psychometric properties of the assessment instrument. The study sample comprised 1,666 university students. Sample was chosen using a random sampling technique. The exploratory factor analysis (EFA) and the confirmatory factor analysis (CFA) performed on two consecutive samples of freshmen studying Computer Science Engineering confirmed that the Questionnaire to assess student satisfaction with mathematics study materials measures satisfaction conditions in five scales: Didactic Adequacy, Relevance, Engagement, Interaction and Technological Quality. The results revealed the existence of significant psychometric features of the constructed questionnaire

A data transformation model for relational and non-relational data

The information systems that support small, medium, and large organisations need data transformation solutions from multiple data sources to fulfill the requirements of new applications and decision-making to stay competitive. Relational data is the foundation for the majority of applications programme, whereas non-relational data is the foundation for the majority of newly produced applications. The relational model is the most elegant one; nonetheless, this kind of database has a drawback when it comes to managing very large volumes of data. Because they can handle massive volumes of data, non-relational databases have evolved into relational database substitutes. The key issue is that rules for data transformation processes across various data types are becoming less well-defined, leading to a steady decline in data quality. Therefore, to handle relational and non-relational data and satisfy the requirements for data quality, an empirical model in this domain knowledge is required. This study seeks to develop a data transformation model used for different data sources while satisfying data quality requirements, especially the transformation processes in relational and non-relational model, named Data Transformation with Two ETL Phases and Central-Library (DTTEPC). The different stages and methods in the developed model are used to transform the metadata information and stored data from relational to non-relational systems, and vice versa. The model is developed and validated through expert review, and the prototype based on the final version is employed in two case studies: education and healthcare. The results of the usability test demonstrate that the developed model is capable of transforming metadata data and stored data across systems. So enhancing the information systems in various organizations through data transformation solutions. The DTTEPC model improved the integrity and completeness of the data transformation processes. Moreover, supports decision-makers by utilizing information from various sources and systems in real-time demands