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Contribution: This article features a systematic literature review with the objective of presenting a study that reflects the current scenario of research on the cognitive load theory (CLT) in the domain of teaching and learning computer programming. Background: Computer programming is a highly cognitive skill, requiring mastering multiple competencies, and recognized as being difficult to learn, for this reason, the cognitive load (CL) in the learner’s working memory emerged as an influential concept, making CLT one of the most common theories in computing education research. Research Questions: What are the approaches that relate CLT to teaching and learning computer programming? What CLT-related concepts are covered? What evidence is reported with respect to this context? Methodology: Following a formal protocol, a survey was performed for papers linking CLT to teaching and learning programming published between 2010 and 2020. The selection of papers was based on a set of criteria established to drive the selection process, including alignment with the research questions and paper quality assessment. Findings: The approaches applied in the papers are based on measuring the CL; through instructional design based on the development or use of resources or tools, a range of different pedagogy strategies and the CLT concepts. With respect to the concepts, the subjective measurement technique and worked example effect are the most commonly deployed. As far as the evidence reported, the better part is related to the worked example effect and measuring CLs. [ABSTRACT FROM AUTHOR]

Contribution: This article lends empirical evidence to this research area of factors influencing students’ choice of and success in science, technology, engineering, and mathematics (STEM). Background: Understanding these factors is crucial as it informs recruitment and support interventions provided to students and constitutes a premise to improving graduation rates. The social cognitive career theory (SCCT) was used as a theoretical framework to provide insight regarding factors influencing students’ choice of qualifications. Research Questions: What is the state of research on the factors influencing students’ choice of and success in STEM programmes? Which of these factors have interested most researchers? What research themes are covered in articles investigating these factors? Methodology: This study followed the general bibliometric analysis workflow—study design, data collection, data analysis, data visualization, and interpretation. Data collection followed the preferred reporting items for systematic review and metaanalysis (PRISMA) guidelines. From an initial set of 408 articles, 179 related to the theme and were published in the Web of Science between 2004 and 2020. These articles were analyzed using the standard bibliometric metrics. Findings: Findings indicate that this research field is still growing. Thirty-two factors were identified and rated based using an objective assessment criterion. In addition, a classification of the factors is presented based on the SCCT. This study provides a theoretical reference for improving success rates for STEM qualifications and better understanding the theme. The study proposes a research agenda of what future research in the field should focus on, based on current gaps. [ABSTRACT FROM AUTHOR]

Contribution: In this study, we accumulated the knowledge and generated evidence on how and in what context CDIO framework has been used in software engineering (SE) education. The aggregated evidence will enable SE academics in making informed decisions while adopting CDIO for SE education and build upon it. Background: CDIO framework is relevant for SE as it focuses on enabling engineering graduates in conceiving, designing, implementing, and operating complex systems and products. We were not able to find any study that identifies and aggregates the evidence on the use of CDIO for SE education. Research Questions: This study attempts to answer the following research questions: 1) how CDIO has been used in SE education? and 2) what are the experiences of academics in applying the CDIO framework in SE education? Methodology: Using a mixed-method approach (systematic mapping study and interview study with experienced academics in SE), we established the state of the art and practice on the use of CDIO in SE education. Findings: Getting a commitment from the higher management, teachers, and students is a major challenge in the adoption of the CDIO initiative followed by a lack of competence, finance, and resources. Ownership, motivation, persistence, and training of teachers and students are required not only to adopt CDIO for SE but also to sustain it. [ABSTRACT FROM AUTHOR]

Contribution: Demonstrates how to use experiential learning (EL) to improve argumentative writing. Presents the design and development of a natural language processing (NLP) application for aiding instructors in providing feedback on student essays. Discusses how EL combined with automated support provides an analytical approach to improving written-communication skills. Background: High-quality, timely, feedback is an effective way to improve students’ writing. However, large class sizes and limited instructor backgrounds often make formative feedback impossible. Recent trends, including lowering entry requirements, have added to these challenges. Assistive technologies for implementing inclusive education provide viable solutions. Research Questions: 1) How and why can EL be used to develop argumentative writing skills in university STEM students? 2) How can technologies be developed to support using EL in teaching writing? and 3) How might the holistic impact of using such analytic techniques be evaluated? Methodology: Participants in an EL project were assigned two essays in sequence. They were given instructions on making good arguments and shown how to use an analytic rubric to maximize their scores. The essays were hand scored by tutors who provided scores for each dimension of the rubric. Subsequently, the content and argumentation of the essays were analyzed using NLP techniques to obtain independent scores. Qualitative data were also collected. Findings: The project produced transformative writing experiences for the participants. It showed how analytical techniques help improve writing skills and how relevant automated instructor assistance can be developed using NLP technologies. [ABSTRACT FROM AUTHOR]

Contribution: A systematic interdisciplinary engineering and technology instructional model using cutting-edge technologies is proposed in this research. This model consists of four key components: 1) interdisciplinary collaboration; 2) hands-on projects; 3) real-world simulations; and 4) cutting-edge technologies. The model was designed to engage students in the real-world engineering projects and experience through the following activities: 1) performing the design, fabrication, and lab testing; 2) modeling and analyzing testing samples; 3) conducting on-site experiments; and 4) performing data processing and analysis. Background: Engineering programs are challenged by the rapid development of innovative technologies. To address this challenge, it is required to provide engineering graduates with “soft skills” for the capability of project management, especially the communication and collaboration among disciplines through university education. Therefore, it is desired to develop a systematic interdisciplinary engineering and technology educational strategy. Research questions: 1) is the proposed systematic interdisciplinary instructional model appropriate and feasible to be integrated into the engineering curriculum? 2) what were the students’ perceptions and experiences about the interdisciplinary model? 3) does the interdisciplinary model facilitate engineering students’ soft skills, such as interdisciplinary communication and collaboration? and 4) does the interdisciplinary model help to enhance engineering students’ real-world professional experience, develop design thinking and problem-solving skills, which will help them to transfer their learning experience from the classroom setting to the real-world setting? Methodology: A systematic interdisciplinary engineering and technology model was developed, implemented, and evaluated. Findings: The feasibility and effectiveness of the proposed systematic instructional model were validated by various data sources. The tested model is recommended for broader adaptation in various STEM disciplines. [ABSTRACT FROM AUTHOR]

Contribution: This article adds to the results of previous systematic mapping study by addressing a more ample context of problem-based learning (PBL) in computing education. Background: PBL is defined as an instructional method of constructivist teaching that uses real problems as a motivating element for learning. Although PBL was born in medical education, it has been used in computing education to facilitate the students’ engagement and learning capacity, contributing to developing skills, such as teamwork, holistic vision, critical thinking, and solving problem. Considering that approach much more descriptive than prescriptive, it favors the implementation of diverse methodologies on its behalf. Research Question: “How the PBL approach has been applied in teaching computing?” Methodology: From the initial set of 3837 studies, 102 primary studies were selected and categorized through Kitchenham methodology for analysis from 1999 to 2019. Findings: Based on these studies, it was possible to verify a greater adoption of PBL in undergraduate education and a great diversity of strategies involving real-world problems, developing technical and no-technical skills and making the student much more motivated and engaged. Challenges were also mapped, which shows a very interesting field for new research. [ABSTRACT FROM AUTHOR]