Research on Strategies for Cultivating Piano Players’ Psychological Quality in the Information Age

[1] Springer, D. G., & Silvey, B. A. (2018). The role of accompaniment quality in the evaluation of solo instrumental performance. Journal of Research in Music Education, 002242941876104. Search in Google Scholar

[2] Brooker, E. (2018). Music performance anxiety: a clinical outcome study into the effects of cognitive hypnotherapy and eye movement desensitisation and reprocessing in advanced pianists:. Psychology of Music(1). Search in Google Scholar

[3] Ma, W. (2022). Comprehensive evaluation system for realizing the ability of university piano teaching. Mobile Information Systems. Search in Google Scholar

[4] Rucsanda, M., Cazan, A. M., & Trua, C. (2020). Musical performance and emotions in children.pdf. Psychology of Music(4). Search in Google Scholar

[5] Mita, S., Sato, N., Fujimoto, M., Sugimoto, S., Fujimoto, T., & Ozawa, M., et al. (2023). 5 lanes 5 fingers portable touch-typing interface ‘parotone’ for efficient sensorimotor learning: musical performance acquisition much faster than piano. International journal of human-computer interaction(16/20), 39. Search in Google Scholar

[6] Cornett, V., & Gülbahar Urhan. (2021). Performance anxiety experiences and coping techniques of turkish music students and their teachers:. International Journal of Music Education, 39(4), 504-519. Search in Google Scholar

[7] Huang, L. (2019). Research on the cultivation of the indoor piano performance skills from the perspective of psychology. Basic & clinical pharmacology & toxicology.(S2), 125. Search in Google Scholar

[8] Finch, K. K., Oakman, J. M., Milovanov, A., Keleher, B., & Capobianco, K. (2021). Mental imagery and musical performance: development of the musician’s arousal regulation imagery scale:. Psychology of Music, 49(2), 227-245. Search in Google Scholar

[9] Langton, E. K., Miguel, C. F., Diaz, J. E., Cordeiro, M. C., & Heinicke, M. R. (2020). An evaluation of matrix training to teach college students piano notes and rhythms. Journal of Applied Behavior Analysis, 53(3). Search in Google Scholar

[10] Griffith, K. R., Ramos, A. L., Hill, K. E., & Miguel, C. F. (2018). Using equivalence‐based instruction to teach piano skills to college students. Journal of Applied Behavior Analysis. Search in Google Scholar

[11] Churchill, S., Jessop, D. C., Goodwin, S., Ritchie, L., & Harris, P. R. (2018). Self-affirmation improves music performance among performers high on the impulsivity dimension of sensation seeking. Psychology of Music(2). Search in Google Scholar

[12] Guo, R., Ding, J., & Zang, W. (2021). Music online education reform and wireless network optimization using artificial intelligence piano teaching. Wireless Communications and Mobile Computing. Search in Google Scholar

[13] Kurara, B., Taira, I., & Kazuo, O. (2018). Characteristics of psychophysiological responses during amateur and professional piano performances: focus on the presence and absence of an audience. International Journal of Modern Physics A, 6. Search in Google Scholar

[14] Tief, V. J., & Grpel, P. (2020). Pre-performance routines for music students: an experimental pilot study. Psychology of Music, 49(2), 030573562095362. Search in Google Scholar

[15] Butkovi, A., Vukojevi, N., & Carevi, S. (2022). Music performance anxiety and perfectionism in croatian musicians:. Psychology of Music, 50(1), 100-110. Search in Google Scholar

[16] Wiedemann, A., Vogel, D., Voss, C., & Hoyer, J. (2021). How does music performance anxiety relate to other anxiety disorders?. Psychology of Music. Search in Google Scholar

[17] Dharma Wibawa Adhi, Pramunanto Eko & Rahayuningsih Ifut. (2019).Sign Language Classification Based on EMG using Time Domain Features Extraction.Journal of Engineering and Applied Sciences(17), 6274-6281. Search in Google Scholar

[18] Li Yin,Fumin Chen,Qi Zhang & Xu Ma.(2019).Arrhythmia classification based on multi-domain feature extraction.Journal of Physics: Conference Series(2),022062 (7pp). Search in Google Scholar

[19] Abdelhalim Ghediri & Noureddine Goléa.(2024).Induction motor failures detection using Motor Current SignalAnalysis (MCSA) and two-step Support Vector Machine (SVM)classifier.PRZEGLĄD ELEKTROTECHNICZNY(2). Search in Google Scholar