Informatics in Education

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.

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.

Online learning has become a widespread method for providing learning at different levels of education. It has facilitated the learning in many ways and made it more flexible and available by providing learners with more opportunities to learn information, further access to different learning resources, and collaboration rather than face-to-face learning. In spite of these benefits and rapid growth of online education, success and persistence in such courses is one the important aspects of online learning research and it relies on different factors. Therefore investigating the reasons of students' dropout of an online education course or program and its contributing factors is essential in this area. One of the most barriers in online learning system is lack of interactions. In learning, interaction between students themselves, with the course content, and course instructors is important for conveying information, enhancing teaching quality, give directions, and many more functions. The aim of this research is to review the literature to propose a clearer picture of studies have been conducted regarding online interaction and factors that impact it in online education systems.

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.