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Research Article

Leveraging Artificial Intelligence to Predict Young Learner Online Learning Engagement

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References

  • Astin, A. (1997). What matters in college? Four critical years revisited. San Francisco: Joseey-Bass.
  • Bell, A. (2007). Designing and testing questionnaires for children. Journal of Research in Nursing, 12(5), 461–469. doi:10.1177/1744987107079616
  • Bhatia, M., Davidson, J., Kalidindi, S., Mukherjee, S., & Peters, J. (2006). VoIP: An In-Depth Analysis (Indianapolis, Indiana: Cisco Press).
  • Blazar, D., & Kraft, M. A. (2017). Teacher and teaching effects on students’ attitudes and behaviors. Educational Evaluation and Policy Analysis, 39(1), 146–170. doi:10.3102/0162373716670260
  • Davidson, A. (1999). Negotiating social differences: Youth’s assessments of educators’ strategies. Urban Education, 34(3), 169–338. doi:10.1177/0042085999343004
  • Deng, J., Guo, J., Zhou, Y., Yu, J., Kotsia, I., & Zafeiriou, S. (2019). RetinaFace: Single-stage dense face localisation in the wild. Retrieved from http://arxiv.org/abs/1905.00641
  • Dewan, M. A. A., Lin, F., Wen, D., Murshed, M., & Uddin, Z. (2018). A deep learning approach to detecting engagement of online learners. 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), Guangzhou, China. (pp. 1895–1902).
  • Dewan, M. A. A., Murshed, M., & Lin, F. (2019). Engagement detection in online learning: A review. Smart Learning Environments, 6(1). doi:10.1186/s40561-018-0080-z
  • Dorneyi, Z., & Ryan, S. (2015). The psychology of the language learner revisited. New York, NY: Routledge.
  • Elyas, T., & Al-Bogami, B. (2019). The tole of the iPad as instructional tool in optimizing young learners’ achievement in EFL classes in the Saudi context. Arab World English Journal, 1(1), 144–162. doi:10.24093/awej/elt1.11
  • Fredricks, J. A., & McColskey, W. (2012). The measurement of student engagement: A comparative analysis of various methods and student self-report instruments. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 763–782). Boston, MA: Springer US.
  • Friesen, E., & Ekman, P. (1978). Facial action coding system: A technique for the measurement of facial movement. California, CA: Consulting Psychologists Press, Palo Alto.
  • Hall, L., Hume, C., & Tazzyman, S. (2016). Five degrees of happiness: Effective smiley face Likert scales for evaluating with children. Proceedings of IDC 2016 - The 15th International Conference on Interaction Design and Children (pp. 311–321). doi:10.1145/2930674.2930719.
  • He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. Proceedings of the IEEE conference on computer vision and pattern recognition. Las Vegas, NV, USA (pp. 770–778).
  • Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technology-mediated learning: A review. Computers and Education, 90, 36–53. doi:10.1016/j.compedu.2015.09.005
  • Hirschel, R. (2018). Teacher talk in the elementary school EFL classroom. Bulletin of Sojo University, 43, 31–41.
  • Hwang, K., & Yang, C. (2008). Fuzzy fusion for affective state assessment in distance learning based on image detection. 2008 International Conference on Audio, Language and Image Processing. Shanghai, China (pp. 380–384).
  • IBM. (n.d.a). What is computer vision? Retrieved from https://www.ibm.com/topics/computer-vision
  • IBM. (n.d.b). What is speech recognition? Retrieved from https://www.ibm.com/cloud/learn/speech-recognition
  • IBM Corp. (2020). SPSS Statistics for Windows (No. 27). Author.
  • Ivry, A., Berdugo, B., & Cohen, I. (2019). Voice activity detection for transient noisy environment based on diffusion nets. IEEE Journal of Selected Topics in Signal Processing, 13(2), 254–264. doi:10.1109/JSTSP.2019.2909472
  • Jakonen, T., & Evnitskaya, N. (2020). Teacher smiles as an interactional and pedagogical resource in the classroom. Journal of Pragmatics, 163, 18–31. doi:10.1016/j.pragma.2020.04.005
  • Khan, B. H. (2006). flexible learning in an information society. Hershey, Pennsylvania: Information Science Publishing.
  • Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory Into Practice, 41(4), 212–218. doi:10.1207/s15430421tip4104_2
  • Krithika, L. B., & Lakshmi Priya, G. G. (2016). Student Emotion Recognition System (SERS) for e-learning improvement based on learner concentration metric. Procedia Computer Science, 85, 767–776. doi:10.1016/j.procs.2016.05.264
  • Kuh, G. D., Cruce, T. M., Shoup, R., Kinzie, J., & Gonyea, R. M. (2008). Unmasking the effects of student engagement on first-year college grades and persistence. The Journal of Higher Education, 79(5), 540–563. doi:10.1080/00221546.2008.11772116
  • Leona, N. L., van Koert, M. J., van der Molen, M. W., Rispens, J. E., Tijms, J., & Snellings, P. (2021). Explaining individual differences in young English language learners’ vocabulary knowledge: The role of Extramural English Exposure and motivation. System, 96, 102402. doi:10.1016/j.system.2020.102402
  • Marsh, A. A., Rhoads, S. A., & Ryan, R. M. (2019). A multi-semester classroom demonstration yields evidence in support of the facial feedback effect. Emotion, 19(8), 1500–1504. doi:10.1037/emo0000532
  • Meticulous Research. (2020). Online language learning market by product (SaaS, Apps, Tutoring), Mode (Consumer, Government, K-12, Corporate), Language (English, German, Japanese, Korean, Mandarin Chinese) and Geography - Global Forecast to 2027. Retrieved from https://www.meticulousresearch.com/product/online-language-learning-market-5025
  • Nikolov, M. (2002). Issues in English language education. Bern, Switzerland: P. Lang.
  • Oga-Baldwin, W. L. Q., & Nakata, Y. (2017). Engagement, gender, and motivation: A predictive model for Japanese young language learners. System, 65, 151–163. doi:10.1016/j.system.2017.01.011
  • Oga-Baldwin, W. Q., & Nakata, Y. (2020). How teachers promote young language learners’ engagement: Lesson form and lesson quality. Language Teaching for Young Learners, 2(1), 101–130. doi:10.1075/ltyl.19009.oga
  • Paul, D. (2003). Teaching English to children in Asia. Hong Kong, China: Longman Asia ELT.
  • Raji, I. D., Gebru, T., Mitchell, M., Buolamwini, J., Lee, J., & Denton, E. (2020, February). Saving face: Investigating the ethical concerns of facial recognition auditing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. New York, USA (pp. 145–151).
  • Ramakrishnan, A., Ottmar, E., LoCasale-Crouch, J., & Whitehill, J. (2019). Toward automated classroom observation: Predicting positive and negative climate. 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019) (pp. 1–8). doi:10.1109/FG.2019.8756529.
  • Reeve, J., & Tseng, C. M. (2011). Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36(4), 257–267. doi:10.1016/j.cedpsych.2011.05.002
  • Sharma, K., Giannakos, M., & Dillenbourg, P. (2020). Eye-tracking and artificial intelligence to enhance motivation and learning. Smart Learning Environments, 7(1). doi:10.1186/s40561-020-00122-x
  • Shirama, A. (2012). Stare in the crowd: Frontal face guides overt attention independently of its gaze direction. Perception, 41(4), 447–459. doi:10.1068/p7114
  • Short, M. E., Goetzel, R. Z., Pei, X., Tabrizi, M. J., Ozminkowski, R. J., Gibson, T. B., … Wilson, M. G. (2009). How accurate are self-reports? Analysis of self-reported health care utilization and absence when compared with administrative data. Journal of Occupational & Environmental Medicine, 51(7), 786–796. doi:10.1097/JOM.0b013e3181a86671
  • Sinatra, G. M., Heddy, B. C., & Lombardi, D. (2015). The challenges of defining and measuring student engagement in science. Educational Psychologist, 50(1), 1–13. doi:10.1080/00461520.2014.1002924
  • Song, Y., Wang, W., & Feng-Juan Guo, F. (2009). Feature extraction and classification for audio information in news video. 2009 International Conference on Wavelet Analysis and Pattern Recognition (pp. 43–46). doi:10.1109/ICWAPR.2009.5207452.
  • Stiefelhagen, R., & Zhu, J. (2002, April). Head orientation and gaze direction in meetings. CHI’02 extended abstracts on human factors in computing systems. Minneapolis, Minnesota, USA (pp. 858–859).
  • Taylor, L., & Parsons, J. (2011). Improving student engagement. Current Issues in Education, 14(1), 1–32.
  • Walsh, S., & Li, L. (2013). Conversations as space for learning. International Journal of Applied Linguistics, 23(2), 247–266. doi:10.1111/ijal.12005
  • Whitehill, J., Serpell, Z., Lin, Y., Foster, A., & Movellan, J. R. (2014). The faces of engagement: Automatic recognition of student engagementfrom facial expressions. IEEE Transactions on Affective Computing, 5(1), 86–98. doi:10.1109/TAFFC.2014.2316163
  • Xie, S., Girshick, R., Dollár, P., Tu, Z., & He, K. (2017). Aggregated residual transformations for deep neural networks. Proceedings of the IEEE conference on computer vision and pattern recognition. Honolulu, HI, USA (pp. 1492–1500).
  • Yang, T.-Y., Chen, Y.-T., Lin, -Y.-Y., & Chuang, -Y.-Y. (2019). FSA-Net: Learning fine-grained structure aggregation for head post estimation from a single image. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Long Beach, CA, USA (pp. 1087–1096).
  • Yataganbaba, E., & Yıldırım, R. (2016). Teacher interruptions and limited wait time in EFL young learner classrooms. Procedia - Social and Behavioral Sciences, 232, 689–695. doi:10.1016/j.sbspro.2016.10.094

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