Nowadays, the rapid development of ICT has brought more flexible forms that push the boundaries of classic teaching methodology. This paper is an analysis of online teaching and learning forced by the COVID-19 pandemic, as compared with traditional education approaches. In this regard, we assessed the performance of students studying in the face-to-face, online and hybrid mode for an engineering degree in Computer Science at the Lublin University of Technology during the years 2019-2022. A total of 1827 final test scores were examined using machine learning models and the Shapley additive explanations method. The results show an average increase in performance on final tests scores for students using online and hybrid modes, but the difference did not exceed 10% of the point maximum. Moreover, the students' work had a much higher impact on the final test scores than did the study system and their profile features.
Preparing students for the workforce is a balancing act that involves theory, practice, and assessment. As students navigate an educational experience that is, however, often distant from real-world needs, it is imperative that academia finds a novel way to bridge the gap. As many organizations utilize open challenges to attract ideas and talent, academia can easily create such bridge, leading to greater engagement, greater student preparation, and a potential employment pipeline. This paper describes the experience of our students and faculty advisors who participated to the NASA SUITS (Spacesuit User Interface Technologies for Students) Design Challenge. In particular, we review the pedagogical value of the solution that they created and the changes that were implemented in the curriculum of an undergraduate degree program in Information Technology. This open-source, multi-year project is also a flexible platform that can be utilized for engagement in K-12 education as well as graduate research projects.
Integrating computational thinking into K-12 Education has been a widely explored topic in recent years. Particularly, effective assessment of computational thinking can support the understanding of how learners develop computational concepts and practices. Aiming to help advance research on this topic, we propose a data-driven approach to assess computational thinking concepts, based on the automatic analysis of data from learners’ computational artifacts. As a proof of concept, the approach was applied to a Massive Open Online Course (MOOC) to investigate the course’s effectiveness as well as to identify points for improvement. The data analyzed consists of over 3300 projects from the course participants, using the Scratch programming language. From that sample, we found patterns in how computational thinking manifests in projects, which can be used as evidence to guide opportunities for improving course design, as well as insights to support further research on the assessment of computational thinking.
Blended learning is becoming an attractive model in higher education as new innovative information technologies are becoming increasingly available. However, just blending face-to-face learning with information technologies cannot provide effective teaching and efficient solutions for learning. To be successful, blended learning must rely on solid learning theory and pedagogical strategies. In addition, there is a need for a design-based research approach to explore blending learning through successive cycles of experimentations, where the shortcomings of each cycle are identified, redesigned, and reevaluated. This paper reports on a study conducted on a blended learning model in Java programming at the introductory level. It presents the design, implementation, and evaluation of the model and its implications for the learning of introductory computer programming.