Urgensi Komunikasi Non-Verbal dan Penerapan Pattern Recognition pada Otomatisasi Penilaian Keterampilan Mengajar

Pipit Utami, Universitas Negeri Yogyakarta, Indonesia

Abstract


Pada program pendidikan guru, keterampilan mengajar merupakan kompetensi yang sangat penting. Penilaian aspek non-verbal belum mendapat perhatian khusus. Aspek non-verbal berperan penting dalam keterampilan mengajar. Pada penilaian keterampilan mengajar secara manual  tidak mudah menghadirkan objektifitas penilaian. Artikel ini memaparkan urgensi pengembangan otomatisasi sistem penilaian keterampilan mengajar terkait aspek komunikasi menerapkan pattern recognition technology. Pengumpulan data dilakukan melalui kuesioner yang didistribusikan pada platform google form untuk keterjangkauan responden. Total responden adalah 172, terdiri atas 61 dosen dan 111 guru. Sebaran responden berasal dari pulau Sumatra, Jawa, Kalimantan, Sulawesi, Bali dan Nusa Tenggara Barat. Hasil menunjukkan bahwa: (i) tingkat kepentingan aspek komunikasi pada keterampilan mengajar adalah sangat penting (skor 4,38); (ii) tingkat kepentingan pengembangan teknologi otomatisasi penilaian adalah penting (skor 4,11); (iii) aspek-aspek komunikasi non-verbal yang diperlukan pada keterampilan mengajar merupakan kombinasi gerakan tubuh, gerakan tangan, ekspresi wajah dan intonasi suara; dan (iv) fitur-fitur yang perlu dikembangkan pada sistem penilaian keterampilan mengajar aspek komunikasi non-verbal adalah refleksi, umpan balik, dan penilaian berulang. Terdapat berbagai tantangan dan permasalahan terkait pengembangan system penilaian aspek non-verbal secara otomatis menggunakan pattern recognition technology. Diperlukan diskusi bersama terkait realisasi system tersebut antara pakar pendidikan dan praktisi engineering.

Full Text:

PDF

References


A. Okoli, “Relating Communication Competence to Teaching Effectiveness : Implication for Teacher Education,” J. Educ. Pract., vol. 8, no. 3, pp. 150–154, 2017.

Q. Yu, “Study On Establishing National Standard Of Vocational Teachers’ Training In China,” J. Tech. Educ. Train., vol. 1, no. 1, pp. 59–66, 2009.

C. Rees, Student employability profiles: a guide for higher education practitioners, 2nd revise. Newyork: The higher Education Academy, 2007.

H. Stolte, “Capacity Building in TVET Staff Development in the Context of International Cooperation,” in TVET Teacher Education on the Threshold of Internationalisation, Inwent: Bonn, 2006, pp. 25–33.

UPI, Assessing Teaching Skills in Higher Education. Office for Development of Teaching and Interactive Learning, (UPI), Uppsala University.

M. Grinder, Envoy: Your Personal Guide to Classroom Management 3rd Edition. Mga Pub Consortium, 1996.

H. Fawad and I. A. Manarvi, “Student feedback & systematic evaluation of teaching and its correlation to learning theories, Pedagogy & Teaching skills,” in Proceedings of 2014 IEEE International Conference of Teaching, Assessment and Learning (TALE), 2014,pp. 398–404.

M. Sulaiman, Z. H. Ismail, A. A. Aziz, and A. Zaharim, “Lesson study: Assessing pre-service teacher’s performance of teaching chemistry,” in 2011 3rd International Congress on Engineering Education (ICEED), 2011, pp. 208–213.

N. N. Padmadewi and L. P. Artini, “Assessment Instruments for Improving English Teaching Skills through Microteaching in Indonesia,” Asian EFL J. Res. Artic., vol. 21, no. 2.2, pp. 49–77, 2019.

S. Hashim, M. H. A. Rahman, D. Nincarean, N. F. Jumaat, and P. Utami, “Knowledge Construction Process in Open Learning System among Technical and Vocational Education and Training (TVET) Practitioners,” J. Tech. Educ. Train., vol. 11, no. 1, pp. 73–80, 2019.

Sugiyono, Metode Penelitian Kuantitatif Kualitataif dan Kombinasi (Mixed Methods). Bandung: Alfabeta, 2016.

N. Sudjana, Penilaian Hasil Proses Belajar Mengajar. Bandung: PT Remaja Rosdakarya, 2016.

P. Schober and L. A. Schwarte, “Correlation coefficients: Appropriate use and interpretation,” Anesth. Analg., vol. 126, no. 5, pp. 1763–1768, 2018.

A. Khan, S. Khan, S. Zia-Ul-Islam, and M. Khan, “Communication Skills of a Teacher and Its Role in the Development of the Students ’ Academic Success,” J. Educ. Pract., vol. 8, no. 1, pp. 18–21, 2017.

A. Osmanoglu, “Prospective teachers’ teaching experience: teacher learning through the use of video,” Educ. Res., vol. 58, no. 1, pp. 39–55, 2016.

C. Killingback, O. Ahmed, and J. Williams, “‘It was all in your voice’ -Tertiary student perceptions of alternative feedback modes (audio, video, podcast, and screencast): A qualitative literature review,” Nurse Educ. Today, vol. 72, pp. 32–39, 2019.

Z. Ullah, A. Lajis, M. Jamjoom, A. Altalhi, A. Al-Ghamdi, and F. Saleem, “The effect of automatic assessment on novice programming: Strengths and limitations of existing systems,” Comput. Appl. Eng. Educ., vol. 26, no. 6, pp. 2328–2341, 2018.

J. L. Poza-Lujan, C. T. Calafate, J. L. Posadas-Yague, and J. C. Cano, “Assessing the Impact of Continuous Evaluation Strategies: Tradeoff between Student Performance and Instructor Effort,” IEEE Trans. Educ., vol. 59, no. 1, pp. 17–23, 2016.

R. I. Arends, Learning to Teach, 9th ed. NewYork: McGraw-Hill.

R. J. Chancey, E. M. Sampayo, D. S. Lemke, and C. B.Doughty, “Learners ’ Experiences During Rapid Cycle Deliberate Practice Simulations A Qualitative Analysis,” Simul. Healthc. J. Soc. Simul. Healthc., vol. 14, no. 1, pp. 18–28, 2019.

D. L. Anderson, D. Barr, and C. Labaij, “Repetitive Microteaching: Learning to Teach Elementary Social Studies,” J. Soc. Stud. Educ. Res., vol. 3, no. 2, pp. 21–44, 2012.

S. M. Darwish and S. K. Mohamed, “Automated Essay Evaluation Based on Fusion of Fuzzy Ontology and Latent Semantic Analysis,” Adv. Intell. Syst. Comput., vol. 921, pp. 566–575, 2020.

D. Tavrov and L. Kovalchuk-khymiuk, “Perceptual Computer for Grading Mathematics Tests within Bilingual Education Program,” in International Conference on Computer Science, Engineering and Education Applications -Advances in Computer Science for Engineering and Education, 2019, vol. AISC 754, pp. 724–734.

K. F. Ratumbuisang, Y. T. Wu, and H. D. Surjono, “The effectiveness of iCRT Video-based Reflection System on Pre-service Teachers’ Micro Teaching Practice Focusing on Meaningful Learning with ICT,” in Journal of Physics: Conference Series, 2018.

L. P. Artini and N. N. Padmadewi, “Learning to Reflect in English Teacher Education: An Analysis from Students’ Learning Experiences and Perceptions,” Asian EFL J., vol. 20, no. 12.4, pp. 171–192, 2018.

D. Shaw, “Accomplished Teaching : Using Video Recorded Micro-teaching Discourse to Build Candidate Teaching Competencies,” J. Interact. Learn. Res., vol. 28, no. 2, pp. 161–180, 2017.

Y.-L. Tian, T. Kanade, and J. F. Cohn, “Facial Expression Analysis,” in Handbook of Face Recognition, no. June 2014, 2005, pp. 247–275.

Mehdi Ghayoumi, “A Quick Review of Deep Learning in Facial Expression,” J. Commun. Comput., vol. 14, no. 1, pp. 34–38, Jan. 2017.

W. Leaders and A. R. E. Made, “Gestures: Your Body Speaks,” Toastmasters Int., 2011.

P. Utami, R. Hartanto, and I. Soesanti, “A study on facial expression recognition in assessing teaching skills: Datasets and methods,” in Procedia Computer Science, 2019, vol. 161.

P. Utami, R. Hartanto, and I. Soesanti, “A Study on Facial Expression Recognition in Assessing Teaching Skills : Datasets and Methods,” in Procedia Computer Science, 2019, vol. 161, pp. 544–552.

R. Barmaki and C. Hughes, “Gesturing and Embodiment in Teaching: Investigating the Nonverbal Behavior of Teachers in a Virtual Rehearsal Environment,” in The Eighth AAAI Symposium on Educational Advances in Artificial Intelligence 2018 (EAAI-18) Gesturing, 2018, pp. 7893–7899.

R. Barmaki and C. E. Hughes, “Embodiment analytics of practicing teachers in a virtual immersive environment,” J. Comput. Assist. Learn., vol. 34, no. 4, pp. 387–396, Aug. 2018.

Y. Kim, T. Soyata, and R. F. Behnagh, “Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education,” IEEE Access, vol. 6, no. Box I, pp. 5308–5331, 2018.

S. Park and J. Ryu, “Exploring Preservice Teachers’ Emotional Experiences in an Immersive Virtual Teaching Simulation through Facial Expression Recognition,” Int. J. Human–Computer Interact., vol. 35, no. 6, pp. 521–533, Apr. 2019.

J. Kunz, “Objectivity and subjectivity in performance evaluation and autonomous motivation : An exploratory study,” Manag. Account. Res., vol. 27, pp. 27–46, 2015.

D. M. de Souza, B. H. Oliveira, J. C. Maldonado, S. R. S. Souza, and E. F. Barbosa, “Towards the Use of An Automatic Assessment System in The Teaching of Software Testing,” in 2014 IEEE Frontiers in Education Conference (FIE)Proceedings, 2014.




DOI: https://doi.org/10.21831/elinvo.v5i2.40730

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Elinvo (Electronics, Informatics, and Vocational Education)

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Our Journal indexed by:

ISSN 2477-2399 (online) || ISSN 2580-6424 (print)

View My Stats

Flag Counter