Physical activity in the school setting: cognitive performance is not affected by three different types of acute exercise

Recent studies indicate that a single bout of physical exercise can have immediatepositive effects on cognitive performance of children and adolescents. However, thetype of exercise that affects cognitive performance the most in young adolescents isnot fully understood. Therefore, this controlled study examined the acute effects ofthree types of 12-min classroom-based exercise sessions on information processingspeed and selective attention. The three conditions consisted of aerobic, coordination,and strength exercises, respectively. In particular, this study focused on the feasibilityand efficiency of introducing short bouts of exercise in the classroom. One hundredand ninety five students (5th and 6th grade; 10–13 years old) participated in a doublebaseline within-subjects design, with students acting as their own control. Exercise typewas randomly assigned to each class and acted as between-subject factor. Before andimmediately after both the control and the exercise session, students performed twocognitive tests that measured information processing speed (Letter Digit SubstitutionTest) and selective attention (d2 Test of Attention). The results revealed that exercisingat low to moderate intensity does not have an effect on the cognitive parameters testedin young adolescents. Furthermore, there were no differential effects of exercise type.The results of this study are discussed in terms of the caution which should be takenwhen conducting exercise sessions in a classroom setting aimed at improving cognitive performance.

Predicting Academic Performance Based on Students' Blog and Microblog Posts

This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in the context of a project-based learning scenario run on our eMUSE platform. Data is collected from six student cohorts, from six consecutive installments of the Web Applications Design course, comprising of 343 students. A significant model was obtained by relying on the textual complexity and longitudinal analysis indices, applied on the English contributions of 148 students that were actively involved in the undertaken projects.

Predicting Student Performance and Differences in Learning Styles based on Textual Complexity Indices applied on Blog and Microblog Posts

Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.