Informatics in Education

This research investigates university students’ success in their first programming course (CS1) in relation to their motivation, mathematical ability, programming self-efficacy, and initial goal setting. To our knowledge, these constructs have not been measured in a single study before in the Finnish context. The selection of the constructs is in line with the statistical model that predicts student performance (“PreSS”) (Quille and Bergin, 2018). The constructs are compared with various demographic and background variables, such as study major, prior programming experience, and average weekly working hours. Some of the main results of this study are as follows: (1) students generally entered with a high interest in programming and high motivation, but these factors did not increase during the course, i.e., interest in programming did not increase. (2) Having prior experience yielded higher initial programming self-efficacy, grade expectations, and spending less time on tasks, but not better grades (although worse neither). While these results can be seen as preliminary (and alarming in some parts), they give rise to future research for investigating possible expectation–performance gaps in CS1 and later CS studies. As our dataset accumulates, we also hope to be able to construct a valid success prediction model.

Nowadays, few professionals understand the techniques and testing criteria to systematize the software testing activity in the software industry. Towards shedding some light on such problems and promoting software testing, professors in the area have established Massive Open Online Courses as educational initiatives. However, the main limitation is the professor’s lack of supervision of students. A conversation agent called TOB-STT has been defined in trying to avoid the problem. A previous study introduced TOB-STT; however, it did not analyze its efficacy. This article addresses a controlled experiment that analyzed its efficacy and revealed it was not expressive in its current version. Therefore, we conducted an in-depth analysis to find what caused this result and provided a detailed discussion. The findings contribute to the TOB-STT since the experimental results show that improvements need to be made in the conversational agent before we use it in Massive Open Online Courses.

This paper proposes and validates a short and simple Expectancy-Value-Cost scale, called EVC Light. The scale measures the motivation of students in computing courses, allowing the easy and weekly application across a course. One of the factors related directly to the high rate of failure and dropout in computing courses is student motivation. However, measuring motivation is complex, there are several scales already carried out to do that job, but only a few of them consider the longitudinal follow-up of motivation throughout the courses. The EVC Light was applied to 245 undergraduate students from four universities. The Omega coefficient, scale items intercorrelation, item-total correlation, and factor analysis are used to validate and measure the reliability of the instrument. Confirmatory and exploratory factor analyses supported the structure, consistency, and validity of the EVC Light scale. Moreover, a significant relationship between motivation and student results was identified, based mainly on the Expectancy and Cost factors.

In this study, effectiveness of a computer science course at the secondary school level is investigated through a holistic approach addressing the dimensions of instructional content design, development, implementation and evaluation framed according to ADDIE instructional design model where evaluation part constituted the research process for the current study. The process has initiated when the computer science curriculum had major revisions in order to provide in-service teachers with necessary support and guidance. The study is carried through as a project, which lasted more than one year and both quantitative and qualitative measures were used through a sequential explanatory method approach. The intention was to investigate the whole process in detail in order to reveal the effectiveness of the process and the products. In this regard, not only teachers' perceptions but also students' developments in their perceptions of academic achievement and computational thinking, as well as correlations between the computational thinking sub-factors were investigated. The findings showed that the instructional materials and activities developed within the scope of the study, positively affected the computational thinking and academic achievement of students aged 10 and 12 years old. The teachers' weekly feedbacks regarding application structures and implementation processes were also supported the findings and revealed some more details that will be useful both for instructional designers and teachers.

Mathematical logic is a discipline used in sciences and humanities with different point of view. Although in tertiary level computer science education it has a solid place, it does not hold also for secondary level education. We present a heterogeneous study both theoretical based and empirically based which points out the key role of logic in computer science, computer science education and knowledge representation. We focus on the key contrast of semantics and syntax, the resolution principle as a leading inference technique (giving also interesting non-clausal generalization of the rule). Further we discuss the possibilities of inclusion the non-classical (many-valued) logics in education together with the original generalization of the non-clausal resolution rule into fuzzy logic. The last part describes partial results of the research concerning the secondary education in the Czech Republic especially in the mathematical logic field. The generalization of the presented ideas entails the article.