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Investigating the effectiveness of speech-to-text recognition applications on learning performance, attention, and meditation

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Abstract

In this study, the effectiveness of the application of speech-to-text recognition (STR) technology on enhancing learning and concentration in a calm state of mind, hereafter referred to as meditation (An intentional and self-regulated focusing of attention in order to relax and calm the mind), was investigated. This effectiveness was further explored with regard to foreign language ability and gender. Finally, students’ perceptions towards STR-texts were surveyed. 60 non-native English speaking undergraduates participated in this study. All students were randomly assigned into either a control or an experimental group, with 30 students in each group. Two lectures, both in English but at different levels of difficulty, were given in a classroom environment. Students in the control group received a lecture containing only a video of the instructor and slides; students in the experimental group received the video of the instructor and slides as well as STR-texts of the lecture. The following main findings were obtained: First, STR-texts had a positive effect on the learning performance, attention and meditation of students. In addition, most students had positive perceptions regarding the usefulness of STR-texts for learning. This is because students in the experimental group received instructional content in both verbal (i.e., speech) and visual (i.e., STR-texts) forms, which made the content more comprehensible and easier to process. Second, during lectures with STR, high ability and female students had higher levels of attention and meditation in most cases compared to their counterparts. This finding can be explained by the difference in learning motivation and in the use of learning strategies. That is, high ability and female students are more interested in learning and display greater use of various learning strategies. Based on these results, it is suggested that educators and researchers integrate STR-texts during lectures in English in order to enhance learning and to increase the level of attention and meditation of non-native English speaking students.

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Notes

  1. Apart from STR-texts, the video of the instructor and slides for the lecture were presented to the experimental students, so they could focus on any of these learning media. We asked this question to make sure that students used the STR-texts before we asked further questions.

References

  • Anand, K., Ruchika, K., Ram, S. K., Iqbal, A., & Puneet, W. (2014). Alternative healing therapies in todays era. International Journal of Research in Ayurveda and Pharmacy, 5(3), 394–396.

    Article  Google Scholar 

  • Barnes, B. D., & Lock, G. (2010). The attributes of effective lecturers of english as a foreign language as perceived by students in a Korean University. Australian Journal of Teacher Education, 35(1), 139–152.

    Article  Google Scholar 

  • Campion, J., & Rocco, S. (2009). Minding the mind: the effects and potential of a school-based meditation programme for mental health promotion. Advances in school mental health promotion, 2(1), 47–55.

    Article  Google Scholar 

  • Chen, C. M., & Wu, C. H. (2015). Effects of different video lecture types on sustained attention, emotion, cognitive load, and learning performance. Computers & Education, 80, 108–121.

    Article  Google Scholar 

  • Chou, M. H. (2015). Strategy use for listening in english as a foreign language: A comparison of academic and vocational high school students. TESOL Journal. doi:10.1002/tesj.214.

    Google Scholar 

  • Chow, M., & Conway, A. R. (2015). The scope and control of attention: Sources of variance in working memory capacity. Memory & cognition, 43(3), 325–339.

    Article  Google Scholar 

  • Clark, R. C., & Mayer, R. E. (2011). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. San Francisco, CA: Wiley.

    Book  Google Scholar 

  • de Oliveira Neto, J. D., Huang, W. D., & de Azevedo Melli, N. C. (2015). Online learning: audio or text? Educational Technology Research and Development, 63(4), 555–573.

    Article  Google Scholar 

  • Duckworth, A. L., Shulman, E. P., Mastronarde, A. J., Patrick, S. D., Zhang, J., & Druckman, J. (2015). Will not want: Self-control rather than motivation explains the female advantage in report card grades. Learning and individual differences, 39, 13–23.

    Article  Google Scholar 

  • Ghaith, G., & Harkouss-Rihan, S. (2012). An investigation of the relationship of learning and communication strategies, gender, and reading proficiency in english as a foreign language. International Journal of Global Education, 1(4), 40–47.

    Google Scholar 

  • Główka, D. (2014). The impact of gender on attainment in learning english as a foreign language. Studies in Second Language Learning and Teaching, 4(4), 617–635.

    Article  Google Scholar 

  • Hsu, C. K., Hwang, G. J., Chang, Y. T., & Chang, C. K. (2013). Effects of video caption modes on English listening comprehension and vocabulary acquisition using handheld devices. Journal of Educational Technology & Society, 16(1), 403–414.

    Google Scholar 

  • Huang, Y. M., Liu, C. L., Shadiev, R., Shen, M. H., & Hwang, W. Y. (2015). Investigating an application of speech-to-text recognition: a study on visual attention and learning behaviour. Journal of Computer Assisted learning, 31(6), 529–545.

    Article  Google Scholar 

  • Huang, Y. M., Shadiev, R., & Hwang, W. Y. (2016). Investigating the effectiveness of speech-to-text recognition applications on learning performance and cognitive load. Computers & Education, 101, 15–28.

    Article  Google Scholar 

  • Hwang, W. Y., Shadiev, R., Kuo, T. C. T., & Chen, N. S. (2012). Effects of speech-to-text recognition application on learning performance in synchronous cyber classrooms. Journal of Educational Technology & Society, 15(1), 367–380.

    Google Scholar 

  • Jones, L. C. (2009). Supporting student differences in listening comprehension and vocabulary learning with multimedia annotations. Calico Journal, 26(2), 267–289.

    Google Scholar 

  • Kalyuga, S. (2014). The expertise reversal principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 576–597). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Kim, D. H., Wang, C., Ahn, H. S., & Bong, M. (2015). English language learners’ self-efficacy profiles and relationship with self-regulated learning strategies. Learning and Individual Differences, 38, 136–142.

    Article  Google Scholar 

  • Krashen, S. D. (1985). The input hypothesis: Issues and implications. New York: Laredo.

    Google Scholar 

  • Kuo, T. C. T., Shadiev, R., Hwang, W. Y., & Chen, N. S. (2012). Effects of applying STR for group learning activities on learning performance in a synchronous cyber classroom. Computers & Education, 58(1), 600–608.

    Article  Google Scholar 

  • Kushalnagar, R. S., Lasecki, W. S., & Bigham, J. P. (2014). Accessibility evaluation of classroom captions. ACM Transactions on Accessible Computing, 5(3), 1–24.

    Article  Google Scholar 

  • LaBerge, D. (2014). Perceptual learning and attention. In W. K. Estes (Ed.), Handbook of learning and cognitive processes: Attention and memory (pp. 237–273). Hove: Psychology Press.

    Google Scholar 

  • Lee, T. H., Shen, P. D., & Tsai, C. W. (2010). Enhance low-achieving students’ learning involvement in Taiwan’s higher education: an approach via e-learning with problem-based learning and self-regulated learning. Teaching in Higher Education, 15(5), 553–565.

    Article  Google Scholar 

  • Leitch, D. (2008). GIFT atlantic liberated learning high school pilot project: A study of the transfer of speech recognition technology from university classrooms to high school classrooms. Phase III report. Nova Scotia: Saint Mary’s University Press.

    Google Scholar 

  • Li, Y., Wald, M., Wills, G., Khoja, S., Millard, D., Kajaba, J., et al. (2011). Synote: Development of a web-based tool for synchronized annotations. New Review of Hypermedia and Multimedia, 17(3), 295–312.

    Article  Google Scholar 

  • Liu, J., & He, Q. (2014). The match of teaching and learning styles in SLA. Creative Education, 5(10), 728–733.

    Article  Google Scholar 

  • Marshall, J. E., Maynard, D. M., & Marshall, R. (2015). Learning processes and academic achievement among secondary school students in barbados. International Journal of Education, 7(3), 66–76.

    Article  Google Scholar 

  • Matteucci, M., & Mignani, S. (2011). Gender differences in performance in mathematics at the end of lower secondary school in Italy. Learning and Individual Differences, 21, 543–548.

    Article  Google Scholar 

  • Mayer, R. E. (2009). Multimedia learning. New York: Cambridge University Press.

    Book  Google Scholar 

  • McGraw, I., Yoshimoto, B., & Seneff, S. (2009). Speech-enabled card games for incidental vocabulary acquisition in a foreign language. Speech Communication, 51(10), 1006–1023.

    Article  Google Scholar 

  • Miller, L. (2007). Issues in lecturing in a second language: lecturer’s behaviour and students’ perceptions. Studies in Higher Education, 32(6), 747–760.

    Article  Google Scholar 

  • Napoli, M. (2004). Mindfulness training for teachers: A pilot program. Complementary Health Practice Review, 9(1), 31–42.

    Article  Google Scholar 

  • NeuroSky (2015). NeuroSky MindWave. Retrieved from http://press.neurosky.com/MindWave.html

  • Nisbet, P., Wilson, A., & Aitken, S. (2005). Speech recognition for students with disabilities. Proceedings of the Inclusive and Supportive Education Congress, ISEC 2005 Conference. Delph, UK: Inclusive Technology.

  • Parmar, J. R., Tejada, F. R., Lang, L. A., Purnell, M., Acedera, L., & Ngonga, F. (2015). Assessment of communications-related admissions criteria in a three-year pharmacy program. American journal of pharmaceutical education. doi:10.5688/ajpe79686.

    Google Scholar 

  • Poltavski, D. V. (2015). The Use of Single-Electrode Wireless EEG in Biobehavioral Investigations. Mobile Health Technologies: Methods and Protocols, 375–390

  • Ranchal, R., Taber-Doughty, T., Guo, Y., Bain, K., Martin, H., Robinson, J., et al. (2013). Using speech recognition for real-time captioning and lecture transcription in the classroom. IEEE Transactions on Learning Technologies, 6(4), 299–311.

    Article  Google Scholar 

  • Reilly, N. (2015). Anxiety and depression in the classroom: A teacher’s guide to fostering self-regulation in young students. New York: WW Norton & Company.

    Google Scholar 

  • Revlin, R. (2013). Cognition: Theory and practice. New York: Worth Publishers.

    Google Scholar 

  • Reynolds, B. L. (2013). A web-based ELF writing environment as a bridge between academic advisers and junior researchers: A pilot study. British Journal of Educational Technology, 44(3), E77–E80.

    Article  Google Scholar 

  • Reynolds, B. L. (2015). Helping Taiwanese graduate students help themselves: Applying corpora to industrial management English as a foreign language academic reading and writing. Computers in the Schools, 32(3–4), 300–317.

    Article  Google Scholar 

  • Roivainen, E. (2011). Gender differences in processing speed: A review of recent research. Learning and Individual Differences, 21(2), 145–149.

    Article  Google Scholar 

  • Ryba, K., McIvor, T., Shakir, M., & Paez, D. (2006). Liberated learning: Analysis of university students’ perceptions and experiences with continuous automated speech recognition. Journal of Instructional Science and Technology, 9(1), 1–19.

    Google Scholar 

  • Sears, S. R., Kraus, S., Carlough, K., & Treat, E. (2011). Perceived benefits and doubts of participants in a weekly meditation study. Mindfulness, 2(3), 167–174.

    Article  Google Scholar 

  • Shadiev, R., & Huang, Y. M. (2016). Facilitating cross-cultural understanding with learning activities supported by speech-to-text recognition and computer-aided translation. Computers & Education, 98, 130–141.

    Article  Google Scholar 

  • Shadiev, R., Hwang, W. Y., Chen, N. S., & Huang, Y. M. (2014). Review of speech-to-text recognition technology for enhancing learning. Educational Technology & Society, 17(4), 65–84.

    Google Scholar 

  • Shadiev, R., Hwang, W. Y., Huang, Y. M., & Liu, C. J. (2016). Investigating applications of speech to text recognition for face to face seminar to assist learning of non-native English participants. Technology, Pedagogy and Education, 25(1), 119–134.

    Article  Google Scholar 

  • Smith, E. E., & Kosslyn, S. M. (2013). Cognitive psychology: Mind and brain. London: Pearson Higher Ed.

    Google Scholar 

  • Sontag, C., & Stoeger, H. (2015). Can highly intelligent and high-achieving students benefit from training in self-regulated learning in a regular classroom context? Learning and Individual Differences, 41, 43–53.

    Article  Google Scholar 

  • Sparks, R. L., Humbach, N., & Javorsky, J. (2008). Individual and longitudinal differences among high and low-achieving, LD, and ADHD L2 learners. Learning and individual differences, 18(1), 29–43.

    Article  Google Scholar 

  • Sparks, R. L., Patton, J., & Ganschow, L. (2012). Profiles of more and less successful L2 learners: A cluster analysis study. Learning and Individual Differences, 22(4), 463–472.

    Article  Google Scholar 

  • Stinson, B., & Arthur, D. (2013). A novel EEG for alpha brain state training, neurobiofeedback and behavior change. Complementary therapies in clinical practice, 19(3), 114–118.

    Article  Google Scholar 

  • Su, M. H. M., & Wang, J. J. (2012). A study of english self-efficacy and english reading proficiency of Taiwanese junior high school students. International Journal of Asian Social Science, 2(7), 984–998.

    Google Scholar 

  • Sun, J. C. Y. (2014). Influence of polling technologies on student engagement: An analysis of student motivation, academic performance, and brainwave data. Computers & Education, 72, 80–89.

    Article  Google Scholar 

  • Wald, M., & Bain, K. (2008). Universal access to communication and learning: the role of automatic speech recognition. International Journal Universal Access in the Information Society, 6(4), 435–447.

    Article  Google Scholar 

  • Weggerle, A., Schmidt, P., & Schulthess, P. (2009). Speech to multi-media document transcription for university lectures. In 2nd International Conference of Education, Research and Innovation, Madrid, Spain. 435–447

  • Wu, T. T. (2014). The use of a mobile assistant learning system for health education based on project-based learning. Computers, Informatics, Nursing, 32(10), 497–503.

    Article  Google Scholar 

  • Wu, T. T. (2015). A learning log analysis of an English-reading e-book system combined with a guidance mechanism. Interactive Learning Environments. doi:10.1080/10494820.2015.1070272.

    Google Scholar 

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Shadiev, R., Huang, YM. & Hwang, JP. Investigating the effectiveness of speech-to-text recognition applications on learning performance, attention, and meditation. Education Tech Research Dev 65, 1239–1261 (2017). https://doi.org/10.1007/s11423-017-9516-3

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