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.
Games for learning are currently used in several disciplines for motivating students and enhancing their learning experience. This new approach of technology-enhanced learning has attracted researchers' and instructors' attention in the area of programming that is one of the most cognitively demanding fields in Computer Science. Several educational, or else serious, games for learning programming have been developed and the first results of their evaluation as a means of learning are quite positive. In this paper, we propose using arcade games as a means for learning programming. Based on this approach students first play a simple game, such as Snake or Tetris, study its code and then extend it. In a pilot study carried out in the context of an undergraduate programming course, students studied the source code of the well-known game Snake and extended it with new functionalities. The analysis of students' replies in a questionnaire showed that using arcade games as a means of learning programming concepts enhances students' motivation for learning programming, supports them in comprehending complex concepts and engages them in carrying out programming activities.
The aim of this work is to adapt and test, in a Brazilian public school, the ACE model proposed by Borkulo for evaluating student performance as a teaching-learning process based on computational modeling systems. The ACE model is based on different types of reasoning involving three dimensions. In addition to adapting the model and introducing innovative methodological procedures and instruments for collecting and analyzing data, our main results showed that the ACE model is superior than written tests for discriminating students on the top and bottom of the scale of scientific reasoning abilities, while both instruments are equivalent for evaluating students in the middle of the scale.
Computer programming is perceived as an important competence for the development of problem solving skills in addition to logical reasoning. Hence, its integration throughout all educational levels, as well as the early ages, is considered valuable and research studies are carried out to explore the phenomenon in more detail. In light of these facts, this study is an exploratory effort to investigate the effect of Scratch programming on 5th grade primary school students' problem solving skills. Moreover, the researchers wondered what 5th grade primary school students think about programming. This study was carried out in an explanatory sequential mixed methods design with the participation of 49 primary school students. According to the quantitative results, programming in Scratch platform did not cause any significant differences in the problem solving skills of the primary school students. There is only a non-significant increase in the mean of the factor of "self- confidence in their problem solving ability". When the thoughts of the primary students were considered, it can be clearly stated that all the students liked programming and wanted to improve their programming. Finally, most of the students found the Scratch platform easy to use.
Text mining has been used for various purposes, such as document classification and extraction of domain-specific information from text. In this paper we present a study in which text mining methodology and algorithms were properly employed for academic dishonesty (cheating) detection and evaluation on open-ended college exams, based on document classification techniques. Firstly, we propose two classification models for cheating detection by using a decision tree supervised algorithm. Then, both classifiers are compared against the result produced by a domain expert. The results point out that one of the classifiers achieved an excellent quality in detecting and evaluating cheating in exams, making possible its use in real school and college environments.