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  • Sep 26, 2021 - 4:25pm
    Flavia Santos

    Numeracy deficits in childhood have a negative impact on socioeconomic status and academic performance achieved in adulthood. We designed the NMT (Numeracy Musical Training) and carried out a study with preschool children to investigate its potential to stimulate early numerical cognition. Then, we applied the NMT in 3rd and 4th graders with low achievement in mathematics to test its effects on remediation. Contrasting pre- and post-test assessments, results from both studies indicated improvements in specific components of numerical cognition in comparison to the control group.

  • Sep 26, 2018 - 2:20pm
    Jonte Taylor, The Pennsylvania State University

    Using music, especially song lyrics, to motivate students has long been a practice for in education to get and keep students engaged and to teach academic content. Most song based instruction involves writing/creating original works that focus on specific content or skills. Unfortunately, these songs may not resonate with all students, thus it may not be as effective as a mechanism for learning. This reality is particularly possible for students with disabilities and students in alternative settings who are usually considered as having behavioral struggles.

  • Sep 26, 2018 - 2:00pm
    LaMar Queen, Music Notes Online

    We can effectively promote student discourse, deeper level understanding, and student content creation when we use music and hip hop to teach. Since hip hop is our youths culture we can effectively use it as a tool to build relationships and teach our next generation of learners. The key is a solid understanding of implementation within the context of social emotional, developmental, and physiological needs.

  • Sep 25, 2022 - 6:30pm
    Filipe J. Zabala (UFRGS, Brazil)

    We introduce 'voice' package, developed to be a free and easy-to-use set of tools to perform audio analysis in R. Three main approaches are presented: (i) extract_features, (ii) tag and (iii) poetry. Such approaches aim to (i) easily build data frames containing the main features from multiple audio files, (ii) attach summarized columns from audio files to canonical data and (iii) map the best spoken words in the best order. The open datasets (Mozilla) Common Voice and VoxForge are presented to illustrate the main functionalities of (i) and (ii).