The Effectiveness of Neurofeedback Training in Algorithmic Thinking Skills Enhancement

Abstract

Although research on learning difficulties are overall in an advanced stage, studies related to algorithmic thinking difficulties are limited, since interest in this field has been recently raised. In this paper, an interactive evaluation screener enhanced with neurofeedback elements, referring to algorithmic tasks solving evaluation, is proposed. The effect of HCI, color, narration and neurofeedback elements effect was evaluated in the case of algorithmic tasks assessment. Results suggest the enhanced performance in the case of neurofeedback trained group in terms of total correct and optimal algorithmic tasks solution. Furthermore, findings suggest that skills, concerning the way that an algorithm is conceived, designed, applied and evaluated are essentially improved.

Algorithmic Thinking Skills without Computers for Prospective Computer Science Teachers

“…Even if the execution process of this approach involves algorithms, the main purpose is to teach a programming language (Galezer et al, 1995). Consequently, students do not acquire AT skills due to their intense effort to learn the programming language and inappropriate teaching practices (Grover et al, 2015;Hubálovský et al, 2010;Plerou et al, 2017). This approach is not effective particularly for younger students (Brusilovsky et al, 1997;Dagiene et al, 2017).…”

“…Unfortunately, it can be claimed that the prospective computer science teachers graduate without having sufficient AT skills. Additionally, it is also stated that there are few studies on AT (Katai, 2015;Plerou et al, 2017) and no compromise on how AT skills can be gained (Grover et al, 2015;Milková, 2005;Milkova & Sevcikova, 2017;Silapachote & Srisuphab, 2017).…”