评估由自适应音乐学习软件引起的流动状态的差异
Assessing differences in flow state induced by an adaptive music learning software
摘要：
技术可以促进自学学术和休闲活动，如音乐学习。一般来说，学习在电子钢琴或任何其他乐器上演奏一首未知的音乐歌曲可能是一件相当繁琐的事情。在传统的自学环境中，音乐家只能通过将他们演奏的内容与乐谱进行比较来获得反馈，即他们自己可以听到哪些错误。研究表明，达到流动状态会在活动中创造更愉快的体验。这项工作探讨是否可以应用流理论和游戏设计的原则，使初学者的音乐体验适应他们的需要，创造更高的流。我们在一项有21名参与者的研究中创建并评估了一个围绕这些考虑因素的工具。我们发现，提供反馈和难度缩放可以帮助实现流，并且参与者对音乐的经验越多，效果就越明显。在进一步的研究中，我们想检查我们学习乐谱的方法的影响。
英文摘要：
Technology can facilitate self-learning for academic and leisure activities such as music learning. In general, learning to play an unknown musical song at sight on the electric piano or any other instrument can be quite a chore. In a traditional self-learning setting, the musician only gets feedback in terms of what errors they can hear themselves by comparing what they have played with the score. Research has shown that reaching a flow state creates a more enjoyable experience during activities. This work explores whether principles from flow theory and game design can be applied to make the beginner's musical experience adapted to their need and create higher flow. We created and evaluated a tool oriented around these considerations in a study with 21 participants. We found that provided feedback and difficulty scaling can help to achieve flow and that the effects get more pronounced the more experience with music participants have. In further research, we want to examine the influence of our approach to learning sheet music.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
