Developing programming competencies is essential for systems, information science, computer science, and electrical engineering students. Engineering students usually face the complexity of working with programming languages that demand compliance with syntactic and semantic rules, which typically represent a daunting task for novice students. Watching textual messages on the screen only, like the classic "hello world" is no longer attractive in the current information society, a missing motivation and possible obstacle to developing programming competencies. Students would like to interact with hardware and appreciate environmental reactions. Arduino board permits developing solutions like that. This article presents the academic experience of first-year students of Ingeniería de Sistemas e Informática at the Universidad Continental (ISI-UC) of Huancayo, Perú, using the Arduino microcontroller board for the teaching-learning process to develop programming competencies. The results obtained show a positive impact regarding the previous year's experience using traditional text-based programming languages. Using Arduino, students create digital circuits and computational electronics competencies, another significant benefit. This experience used an online simulator, and the results obtained permit us to plan future online education strategies for this major. Next step will be the application of Arduino and the online simulator to deepen the programming competencies including recursivity, real time constraints , multitasking features, data structure and object-oriented programming. The main limitations encountered in this experiment were the student limitations regarding electronics concepts in order to build up circuits and in in some cases low internet speeds to attend online education. Performing simulated experiences in classes were not a big challenge for teachers and most students. Nevertheless, problems could appear when performing practical experiences using real Arduino boards, which would may not be available in traditional classes.
People are increasingly open to using online education mainly to break the distance and time barriers of presential education. This type of education is sustainable at all levels, and its relevance has increased even more during the pandemic. Consequently, educational institutions are saving large volumes of data containing relevant information about their operations, but they do not know why students succeed or fail. The Knowledge Discovery in Databases (KDD) process could support this challenge by extracting innovative models to identify the main patterns and factors that could affect the success of their students in online education programs. This work uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to analyze data from the Distance Education Center of the Universidad Católica del Norte (DEC-UCN) from 2000 to 2018. CRISP-DM was chosen because it represents a proven process that integrates multiple methodologies to provide an effective meta-process for data knowledge projects. DEC-UCN is one of the first centers to implement online learning in Chile, and this study analyses 18,610 records in this period. The study applies data mining, the most critical KDD phase, to find hidden data patterns to identify the variables associated with students’ success in online learning (e-learning) programs. This study found that the main variables explaining student success in e-learning programs are age, gender, degree study, educational level, and locality.
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