Supervised Learning Applied to Graduation Forecast of Industrial Engineering Students

<p style="text-align: justify;">The article aims to develop a machine-learning algorithm that can predict student’s graduation in the Industrial Engineering course at the Federal University of Amazonas based on their performance data. The methodology makes use of an information package of 364 students with an admission period between 2007 and 2019, considering characteristics that can affect directly or indirectly in the graduation of each one, being: type of high school, number of semesters taken, grade-point average, lockouts, dropouts and course terminations. The data treatment considered the manual removal of several characteristics that did not add value to the output of the algorithm, resulting in a package composed of 2184 instances. Thus, the logistic regression, MLP and XGBoost models developed and compared could predict a binary output of graduation or non-graduation to each student using 30% of the dataset to test and 70% to train, so that was possible to identify a relationship between the six attributes explored and achieve, with the best model, 94.15% of accuracy on its predictions.</p>

Evaluating system usability of mobile augmented reality application for teaching Karnaugh-Maps

The education system evolves and transforms towards interactive and immersive learning tools in this digital age. Augmented reality has also evolved as a ubiquitous, robust, and effective technology for providing innovative educational tools. In engineering education, many abstract concepts require technological intervention for conceptual understanding and better instructional content. While learning through the immersive tools, system usability has great importance in terms of effectiveness, efficiency, and satisfaction. Effectiveness refers to users' accuracy and completeness in achieving defined goals; efficiency relates to expended resources about the precision and completeness with which users achieve their objectives; satisfaction deals with a positive attitude towards using the product. If the system fails to provide good usability, it may cause adverse effects such as increasing stress, lacking necessary features, increasing the users' cognitive load, and negatively impacting the student's motivation. In this study, two mobile augmented reality (MAR) applications were developed as an instructional tool to teach the students about Karnaugh maps in the digital electronics course. The first application is a Keypad-based MAR application that uses a keypad matrix for user interaction and the second application is a Marker-based MAR application that uses multiple markers to solve K-Map for producing an optimum solution of the given problem. An experimental study was conducted to determine the student's opinion of the developed MAR applications. The study was designed to determine the system usability of the two MAR applications using the System Usability Score (SUS) and Handheld Augmented Reality Usability Score (HARUS) models. 90 engineering students participated in the study, and they were randomly divided into two different groups: keypad-based group and Marker-based group. The keypad-based group included 47 students who had hands-on experience with a keypad-based MAR application, whereas the marker-based group included 43 students who had hands-on experience with multiple marker-based MAR applications. The experimental outcomes indicated that the keypad-based MAR application has better SUS and HARUS scores than the marker-based MAR application which suggests that the keypad-based MAR application has provided better user interaction.

“Clicking vs. Writing”—The Impact of a Chatbot’s Interaction Method on the Working Alliance in AI-based Coaching

Coaching has become an important didactic tool for reflecting learning processes in higher education. Digital media and AI-based technologies such as chatbots can support stimulating self-coaching processes. For the use case of student coaching on the topic of exam anxiety, the working alliance between a coaching chatbot and a human coachee is investigated. Two coachbot interaction methods are compared: A click-based chatbot (implemented in a rule-based system), where the coachee can only click on one answer, and a writing-based chatbot (implemented in a conversational AI), which allows the coachee to freely type in their answers. The focus is on which coachbot interaction method enables a stronger working alliance between coach and coachee: a click-based or a writing-based chatbot. The working alliance and the technical realization of the chatbot systems were investigated in an exploratory quantitative study with 21 engineering students. The results indicate that the working alliance in both study conditions can be classified as medium to high overall. The results further show higher values for bonding on a writing-based platform than when using a click-based system. However, click-based systems seem to be more helpful as a low-threshold entry point to coaching, as they guide coachees better through the process by providing predefined answers. An evaluation of the technical realization shows that self-reflection processes through digital self-coaching via chatbot are generally well accepted by students. For further development and research, it is therefore recommendable to develop a “mixed” coachbot that allows interaction via clicking as well as via free writing.

First-year engineering students' computational reasoning abilities

Computational thinking is an essential skill set for today's students, given the digital age in which we live and work (CT). Without a precise definition, it is generally understood to be a collection of abilities and attitudes required to deal with difficulties in any aspect of life, whether or not a computer is involved. Measurement and evaluation of students' progress in CT abilities are critical, and this can only be done using instruments that have been tested and shown to work before. New students at the Basque Country's University of the Basque Country's Engineering Degrees are tested for critical thinking, algorithmic thinking, problem solving, cooperation and creativity using a previously proven tool.

Level of Perceived Employability of Engineering Students in Kathmandu Valley

The discourse of employability revolves around the mitigation of mismatch between educational outcomes and the job market demand. This discourse is pertinent in engineering education as it is dedicated to producing human resources with the required employability skills. In this context, the students - to whom employability is transformed - are in the central focus. Their perceptions about their abilities in demonstrating and performing in the world of work require attention to connect education and their work. Considering this, the level of perceived employability of the engineering students studying in their final year was measured by using a self-constructed scale in a representative sample of 314 students of Kathmandu valley. The finding shows that the graduating students’ perceived employability was not consolidated and optimised to reflect on their behaviour and practices. It is at the level of ‘emergence’ and ‘presence’, which is thus not enough to see in their abilities to perform better. Therefore, the students were not able to perform as per the expectation of the market. The key implication of this study is that the gap of work-study transition stipulated to be minimised for the employability of the graduates with their exposure in the world of work.

Who will man the rigs when we go?” transnational demographic fever dreams between Qatar and Texas

The educational project of producing engineers in Qatar is uniquely embedded in global capitalism, particularly as a field closely tied to the development of the oil and gas industry, the military and logistics spaces across the Gulf. Over the past two decades, U.S. universities based in the region have become significant spaces where new generations of managerial engineering labor are educated. Drawing on 18 months of institutional ethnographic research, I examine Texas A&M University at Qatar’s (TAMUQ) role in managing the gender demographics of Qatari engineering labor and the experiences of students navigating these institutional mechanisms. The increasing number of women studying at Texas A&M’s engineering branch campus are publicly celebrated by the university as the embodiment of progress in Qatar. At the same time, TAMUQ has worked to mitigate the feminization of engineering through outreach activities that present engineering as a masculine patriotic endeavor. To unpack these contradictory tendencies, I build on the feminist concept of “demographic fever dreams.” Through an examination of contradictory population-based anxieties about Qatari engineering students, I argue that a U.S. land-grant university is a participant and driver of fantasies and fears regarding the future of racialized and gendered labor hierarchies and fossil-fueled capitalism in the Gulf. In doing so, this article offers a grounded feminist intervention to examine the connections between transnational education, U.S. hegemony, and the fossil fuel industry.

A Case Study of English Language Learning Strategies used by Engineering Students in Malaysia

The aim of this paper is to investigate the language learning strategies employed by 22 technical university undergraduates in Malaysia, particularly in oral presentation skills. The study employed focus group interviews and the data gathered were recorded, transcribed and analysed thematically based on O'Malley and Chamot's (1990) taxonomy. The findings showed that the participants used more metacognitive and cognitive strategies compared to the social and affective strategies. The study highlights that students' preferred language learning strategies may not always be effective. Hence, educators have to identify effective language learning strategies for their students and scaffold students' learning into using appropriate strategies.

Knowledge and Awareness of Masks and N95 Respirators Used for COVID-19 Prevention Among Chemical Engineering Students at Al-Balqa Applied University, Jordan

Background and Objectives: On March 11, the World Health Organization stated coronavirus disease 2019 (COVID-19) was a global pandemic; the rapid and extended spread of the COVID-19 pandemic has become a significant cause of concern for face-to-face university study. This study investigated the knowledge and awareness of chemical engineering students in Al-Balqa Applied University (BAU) in Jordan about respiratory protective measures against COVID-19.Materials and Methods: A cross-sectional study was developed using a multi-stage random sampling technique conducted from April 21–28, 2020. The data were collected through an online questionnaire distributed to BAU's chemical engineering students, with 179 responders completed the survey correctly. The data were analyzed statistically using the SPSS program. The questionnaire consisted of two parts: the first measured the student's general knowledge about the COVID-19 pandemic, while the second focused on the respiratory protection methods against COVID-19; it was structured to assess the student's knowledge about the suitable types of masks and respirators used in COVID-19 prevention, their detailed mechanism of action and filtration process type, their production materials, and finally how the student's knowledge affects choosing a proper preventive method.Results: The study found moderate awareness among engineering students about COVID-19 causative agent, effective preventive masks/respirators used, and the mask's viral blockage mechanisms. A total of 89 respondents (49.7%) pointed to the correct best protective mask, i.e., N95 mask. On the other hand, 119 respondents (66.5%) believed that a surgical mask is the best protective mask. The study also showed differences in knowledge between different academic years; the knowledge about respirators, masks, and their action mechanism among senior students in the last three academic years was better than the younger students with a P-value of 0.047 for knowledge about respirator used for protection against coronavirus disease and the P-value of 0.028 for knowledge of the comparisons between the N95 and surgical mask. On the other hand, the study showed a lack of awareness of the most suitable mask types used in pandemics and the appropriate use method.Conclusions: The study found that chemical engineering students in Al-Balqa university were moderately knowledgeable regarding COVID-19 respiratory preventive methods; these results provided an overview of each student's community's knowledge level. Therefore, efforts are needed to improve public awareness through comprehensive educational campaigns to increase students' knowledge, attitude, and practice.