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    Factors Affecting Teacher Readiness for Online Learning (TROL) in Early Childhood Education: TISE and TPACK

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    This study aims to find empirical information about the effect of Technological Pedagogical Content Knowledge (TPACK), and Technology Integration Self Efficacy (TISE) on Teacher Readiness for Online Learning (TROL). This study uses a quantitative survey method with path analysis techniques. This study measures the readiness of kindergarten teachers in distance learning in Tanah Datar Regency, West Sumatra Province, Indonesia with a sampling technique using simple random sampling involving 105 teachers. Empirical findings reveal that; 1) there is a direct positive effect of Technology Integration Self Efficacy on Teacher Readiness for Online Learning; 2) there is a direct positive effect of PACK on Teacher Readiness for Online Learning; 3) there is a direct positive effect of Technology Integration Self Efficacy on TPACK. If want to improve teacher readiness for online learning, Technological Pedagogical Content Knowledge (TPACK) must be improved by paying attention to Technology Integration Self Efficacy (TISE). Keywords: TROL, TPACK, TISE, Early Childhood Education References: Abbitt, J. T. (2011). An Investigation of the Relationship between Self-Efficacy Beliefs about Technology Integration and Technological Pedagogical Content Knowledge (TPACK) among Preservice Teachers. Journal of Digital Learning in Teacher Education, 27(4), 134–143. Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments, 1–13. https://doi.org/10.1080/10494820.2020.1813180 Adnan, M. (2020). Online learning amid the COVID-19 pandemic: Students perspectives. Journal of Pedagogical Sociology and Psychology, 1(2), 45–51. https://doi.org/10.33902/JPSP.2020261309 Alqurashi, E. (2016). Self-Efficacy in Online Learning Environments: A Literature Review. Contemporary Issues in Education Research (CIER), 9(1), 45–52. https://doi.org/10.19030/cier.v9i1.9549 Amir, H. (2016). Korelasi Pengaruh Faktor Efikasi Diri Dan Manajemen Diri Terhadap Motivasi Berprestasi Pada Mahasiswa Pendidikan Kimia Unversitas Bengkulu. Manajer Pendidikan, 10(4). Anderson, T. (2008). The theory and practice of online learning. Athabasca University Press. Anggraeni, N., Ridlo, S., & Setiati, N. (2018). The Relationship Between TISE and TPACK among Prospective Biology Teachers of UNNES. Journal of Biology Education, 7(3), 305–311. https://doi.org/10.15294/jbe.v7i3.26021 Ariani, D. N. (2015). Hubungan antara Technological Pedagogical Content Knowledge dengan Technology Integration Self Efficacy Guru Matematika di Sekolah Dasar. Muallimuna: Jurnal Madrasah Ibtidaiyah, 1(1), 79–91. Birisci, S., & Kul, E. (2019). Predictors of Technology Integration Self-Efficacy Beliefs of Preservice Teachers. Contemporary Educational Technology, 10(1). https://doi.org/10.30935/cet.512537 Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., Lambert, S. R., Al-freih, M., Pete, J., Olcott, D., Rodes, V., Aranciaga, I., Bali, M., Alvarez, A. V, Roberts, J., Pazurek, A., Raffaghelli, J. E., Panagiotou, N., CoĂ«tlogon, P. De, 
 Paskevicius, M. (2020). UVicSPACE: Research & Learning Repository Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1–126. Brinkley-Etzkorn, K. E. (2018). Learning to teach online: Measuring the influence of faculty development training on teaching effectiveness through a TPACK lens. The Internet and Higher Education, 38, 28–35. https://doi.org/10.1016/j.iheduc.2018.04.004 Butnaru, G. I., Niță, V., Anichiti, A., & BrĂźnză, G. (2021). The effectiveness of online education during covid 19 pandemic—A comparative analysis between the perceptions of academic students and high school students from romania. Sustainability (Switzerland), 13(9). https://doi.org/10.3390/su13095311 Carliner, S. (2003). Modeling information for three-dimensional space: Lessons learned from museum exhibit design. Technical Communication, 50(4), 554–570. Cengiz, C. (2015). The development of TPACK, Technology Integrated Self-Efficacy and Instructional Technology Outcome Expectations of pre-service physical education teachers. Asia-Pacific Journal of Teacher Education, 43(5), 411–422. https://doi.org/10.1080/1359866X.2014.932332 Chou, P., & Ph, D. (2012). Effect of Students ’ Self -Directed Learning Abilities on Online Learning Outcomes: Two Exploratory Experiments in Electronic Engineering Department of Education. 2(6), 172–179. Crawford, J., Butler-Henderson, K., Rudolph, J., Malkawi, B., Burton, R., Glowatz, M., Magni, P. A., & Lam, S. (2020). COVID-19: 20 countries’ higher education intra-period digital pedagogy responses. Journal of Applied Learning & Teaching, 3(1). https://doi.org/10.37074/jalt.2020.3.1.7 Dolighan, T., & Owen, M. (2021). Teacher efficacy for online teaching during the COVID-19 pandemic. Brock Education Journal, 30(1), 95. https://doi.org/10.26522/brocked.v30i1.851 Dong, Y., Chai, C. S., Sang, G.-Y., Koh, J. H. L., & Tsai, C.-C. (2015). Exploring the Profiles and Interplays of Pre-service and In-service Teachers’ Technological Pedagogical Content Knowledge (TPACK) in China. International Forum of Educational Technology & Society, 18(1), 158–169. Donitsa-Schmidt, S., & Ramot, R. (2020). Opportunities and challenges: Teacher education in Israel in the Covid-19 pandemic. Journal of Education for Teaching, 46(4), 586–595. https://doi.org/10.1080/02607476.2020.1799708 Elas, N. I. B., Majid, F. B. A., & Narasuman, S. A. (2019). Development of Technological Pedagogical Content Knowledge (TPACK) For English Teachers: The Validity and Reliability. International Journal of Emerging Technologies in Learning (IJET), 14(20), 18. https://doi.org/10.3991/ijet.v14i20.11456 Ghozali, I. (2011). Aplikasi multivariate dengan program IBM SPSS 19. Badan Penerbit Universitas Diponegoro. Giles, R. M., & Kent, A. M. (2016). An Investigation of Preservice Teachers ’ Self-Efficacy for Teaching with Technology. 1(1), 32–40. https://doi.org/10.20849/aes.v1i1.19 Gil-flores, J., & RodrĂ­guez-santero, J. (2017). Computers in Human Behavior Factors that explain the use of ICT in secondary-education classrooms: The role of teacher characteristics and school infrastructure. Computers in Human Behavior, 68, 441–449. https://doi.org/10.1016/j.chb.2016.11.057 Habibi, A., Yusop, F. D., & Razak, R. A. (2019). The role of TPACK in affecting pre-service language teachers’ ICT integration during teaching practices: Indonesian context. Education and Information Technologies. https://doi.org/10.1007/s10639-019-10040-2 Harris, J. B., & Hofer, M. J. (2011). Technological Pedagogical Content Knowledge (TPACK) in Action. Journal of Research on Technology in Education, 43(3), 211–229. https://doi.org/10.1080/15391523.2011.10782570 Hatlevik, I. K. R., & Hatlevik, O. E. (2018). Examining the relationship between teachers’ ICT self-efficacy for educational purposes, collegial collaboration, lack of facilitation and the use of ICT in teaching practice. Frontiers in Psychology, 9(JUN), 1–8. https://doi.org/10.3389/fpsyg.2018.00935 Hung, M. L. (2016). Teacher readiness for online learning: Scale development and teacher perceptions. Computers and Education, 94, 120–133. https://doi.org/10.1016/j.compedu.2015.11.012 Hung, M. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers and Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004 Juanda, A., Shidiq, A. S., & Nasrudin, D. (2021). Teacher Learning Management: Investigating Biology Teachers’ TPACK to Conduct Learning During the Covid-19 Outbreak. Jurnal Pendidikan IPA Indonesia, 10(1), 48–59. https://doi.org/10.15294/jpii.v10i1.26499 Karatas, M. A.-K. (2020). COVID - 19 Pandemisinin Toplum Psikolojisine Etkileri ve Eğitime Yansımaları. Journal of Turkish Studies, Volume 15(Volume 15 Issue 4), 1–13. https://doi.org/10.7827/TurkishStudies.44336 Kaymak, Z. D., & Horzum, M. B. (2013). Relationship between online learning readiness and structure and interaction of online learning students. Kuram ve Uygulamada Egitim Bilimleri, 13(3), 1792–1797. https://doi.org/10.12738/estp.2013.3.1580 Keser, H., Karaoğlan Yılmaz, F. G., & Yılmaz, R. (2015). TPACK Competencies and Technology Integration Self-Efficacy Perceptions of Pre-Service Teachers. Elementary Education Online, 14(4), 1193–1207. https://doi.org/10.17051/io.2015.65067 Kim, J. (2020). Learning and Teaching Online During Covid-19: Experiences of Student Teachers in an Early Childhood Education Practicum. International Journal of Early Childhood, 52(2), 145–158. https://doi.org/10.1007/s13158-020-00272-6 Koehler, M. J., Mishra, P., & Cain, W. (2013). What is Technological Pedagogical Content Knowledge (TPACK)? Journal of Education, 193(3), 13–19. https://doi.org/10.1177/002205741319300303 Lee, Y., & Lee, J. (2014). Enhancing pre-service teachers’ self-efficacy beliefs for technology integration through lesson planning practice. Computers and Education, 73, 121–128. https://doi.org/10.1016/j.compedu.2014.01.001 Mallillin, L. L. D., Mendoza, L. C., Mallillin, J. B., Felix, R. C., & Lipayon, I. C. (2020). Implementation and Readiness of Online Learning Pedagogy: A Transition To Covid 19 Pandemic. European Journal of Open Education and E-Learning Studies, 5(2), 71–90. https://doi.org/10.46827/ejoe.v5i2.3321 Mishra, P. (2019). Considering Contextual Knowledge: The TPACK Diagram Gets an Upgrade. Journal of Digital Learning in Teacher Education, 35(2), 76–78. https://doi.org/10.1080/21532974.2019.1588611 Moorhouse, B. L. (2020). Adaptations to a face-to-face initial teacher education course ‘forced’ online due to the COVID-19 pandemic. Journal of Education for Teaching, 46(4), 609–611. https://doi.org/10.1080/02607476.2020.1755205 Mulyadi, D., Wijayatingsih, T. D., Budiastuti, R. E., Ifadah, M., & Aimah, S. (2020). Technological Pedagogical and Content Knowledge of ESP Teachers in Blended Learning Format. International Journal of Emerging Technologies in Learning (IJET), 15(06), 124. https://doi.org/10.3991/ijet.v15i06.11490 Murtaza, G., Mahmood, K., & Fatima, N. (2021). Readiness for Online Learning during COVID-19 pandemic: A survey of Pakistani LIS students The Journal of Academic Librarianship Readiness for Online Learning during COVID-19 pandemic: A survey of Pakistani LIS students. The Journal of Academic Librarianship, 47(3), 102346. https://doi.org/10.1016/j.acalib.2021.102346 Mustika, M., & Sapriya. (2019). Kesiapan Guru IPS dalam E-learning Berdasarkan: Survei melalui Pendekatan TPACK. 32–35. https://doi.org/10.1145/3306500.3306566 Niess, M. L. (2011). Investigating TPACK: Knowledge Growth in Teaching with Technology. Journal of Educational Computing Research, 44(3), 299–317. https://doi.org/10.2190/EC.44.3.c Oketch, & Otchieng, H. (2013). University of Nairobi, H. A. (2013). E-Learning Readiness Assessment Model in Kenyas’ Higher Education Institutions: A Case Study of University of Nairobi by: Oketch, Hada Achieng a Research Project Submitted in Partial Fulfillment of the Requirement of M. October. Pamuk, S., Ergun, M., Cakir, R., Yilmaz, H. B., & Ayas, C. (2015). Exploring relationships among TPACK components and development of the TPACK instrument. Education and Information Technologies, 20(2), 241–263. https://doi.org/10.1007/s10639-013-9278-4 Paraskeva, F., Bouta, H., & Papagianni, A. (2008). Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice. Computers and Education, 50(3), 1084–1091. https://doi.org/10.1016/j.compedu.2006.10.006 Putro, S. T., Widyastuti, M., & Hastuti, H. (2020). Problematika Pembelajaran di Era Pandemi COVID-19 Stud Kasus: Indonesia, Filipina, Nigeria, Ethiopia, Finlandia, dan Jerman. Geomedia Majalah Ilmiah Dan Informasi Kegeografian, 18(2), 50–64. Qudsiya, R., Widiyaningrum, P., & Setiati, N. (2018). The Relationship Between TISE and TPACK among Prospective Biology Teachers of UNNES. Journal of Biology Education, 7(3), 305–311. https://doi.org/10.15294/jbe.v7i3.26021 Reflianto, & Syamsuar. (2018). Pendidikan dan Tantangan Pembelajaran Berbasis Teknologi Informasi di Era Revolusi Industri 4.0. Jurnal Ilmiah Teknologi Pendidikan, 6(2), 1–13. Reski, A., & Sari, K. (2020). Analisis Kemampuan TPACK Guru Fisika Se-Distrik Merauke. Jurnla Kreatif Online, 8(1), 1–8. Ruggiero, D., & Mong, C. J. (2015). The teacher technology integration experience: Practice and reflection in the classroom. Journal of Information Technology Education, 14. Santika, V., Indriayu, M., & Sangka, K. B. (2021). Profil TPACK Guru Ekonomi di Indonesia sebagai Pendekatan Integrasi TIK selama Pembelajaran Jarak Jauh pada Masa Pandemi Covid-19. Duconomics Sci-Meet (Education & Economics Science Meet), 1, 356–369. https://doi.org/10.37010/duconomics.v1.5470 Semiz, K., & Ince, M. L. (2012). Pre-service physical education teachers’ technological pedagogical content knowledge, technology integration self-efficacy and instructional technology outcome expectations. Australasian Journal of Educational Technology, 28(7). https://doi.org/10.14742/ajet.800 Senthilkumar, Sivapragasam, & Senthamaraikannan. (2014). Role of ICT in Teaching Biology. International Journal of Research, 1(9), 780–788. Setiaji, B., & Dinata, P. A. C. (2020). Analisis kesiapan mahasiswa jurusan pendidikan fisika menggunakan e-learning dalam situasi pandemi Covid-19 Analysis of e-learning readiness on physics education students during Covid-19 pandemic. 6(1), 59–70. Siagian, H. S., Ritonga, T., & Lubis, R. (2021). Analisis Kesiapan Belajar Daring Siswa Kelas Vii Pada Masa Pandemi Covid-19 Di Desa Simpang. JURNAL MathEdu (Mathematic Education Journal), 4(2), 194–201. Sintawati, M., & Indriani, F. (2019). Pentingnya Technological Pedagogical Content Knowledge (TPACK) Guru di Era Revolusi Industri 4.0. Seminar Nasional Pagelaran Pendidikan Dasar Nasional (PPDN), 1(1), 417–422. Sojanah, J., Suwatno, Kodri, & Machmud, A. (2021). Factors affecting teachers’ technological pedagogical and content knowledge (A survey on economics teacher knowledge). Cakrawala Pendidikan, 40(1), 1–16. https://doi.org/10.21831/cp.v40i1.31035 Subhan, M. (2020). Analisis Penerapan Technological Pedagogical Content Knowledge Pada Proses Pembelajaran Kurikulum 2013 di Kelas V. International Journal of Technology Vocational Education and Training, 1(2), 174–179. Sum, T. A., & Taran, E. G. M. (2020). Kompetensi Pedagogik Guru PAUD dalam Perencanaan dan Pelaksanaan Pembelajaran. Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini, 4(2), 543. https://doi.org/10.31004/obsesi.v4i2.287 Suryawati, E., Firdaus, L. N., & Yosua, H. (2014). Analisis keterampilan technological pedagogical content knowledge (TPCK) guru biologi SMA negeri kota Pekanbaru. Jurnal Biogenesis, 11(1), 67-72. Suyamto, J., Masykuri, M., & Sarwanto, S. (2020). Analisis Kemampuan Tpack (Technolgical, Pedagogical, and Content, Knowledge) Guru Biologi Sma Dalam Menyusun Perangkat Pembelajaran Materi Sistem Peredaran Darah. INKUIRI: Jurnal Pendidikan IPA, 9(1), 46. https://doi.org/10.20961/inkuiri.v9i1.41381 Tiara, D. R., & Pratiwi, E. (2020). Pentingnya Mengukur Kesiapan Guru Sebagai Dasar Pembelajaran Daring. Jurnal Golden Age, 04(2), 362–368. Trionanda, S. (2021). Analisis kesiapan dan pelaksanaan pembelajaran matematika jarak jauh berdasarkan profil TPACK di SD Katolik Tanjungpinang tahun ajaran 2020 / 2021. In Prosiding Seminar Nasional Matematika Dan Pendidikan Matematika, 6, 69–76. Tsai, C.-C., & Chai, C. S. (2012). The ‘third’-order barrier for technology-integration instruction: Implications for teacher education. Australasian Journal of Educational Technology, 28(6). https://doi.org/10.14742/ajet.810 Wahyuni, F. T. (2019). Hubungan Antara Technological Pedagogical Content Knowledge (Tpack) Dengan Technology Integration Self Efficacy (Tise) Guru Matematika Di Madrasah Ibtidaiyah. Jurnal Pendidikan Matematika (Kudus), 2(2), 109–122. https://doi.org/10.21043/jpm.v2i2.6358 Wang, L., Ertmer, P. A., & Newby, T. J. (2014). Journal of Research on Technology in Education Increasing Preservice Teachers’ Self-Efficacy Beliefs for Technology Integration. Journal of Research on Technology in Education, 36(3), 37–41. https://doi.org/10.1080/15391523.2004.10782414 Warden, C. A., Yi-Shun, W., Stanworth, J. O., & Chen, J. F. (2020). Millennials’ technology readiness and self-efficacy in online classes. Innovations in Education and Teaching International, 00(00), 1–11. https://doi.org/10.1080/14703297.2020.1798269 Widarjono, A. (2015). Analisis Multivariat Terapan edisi kedua. UPP STIM YKPN. Wiresti, R. D. (2021). Analisis Dampak Work from Home pada Anak Usia Dini di Masa Pandemi Covid-19. Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini, 5(1), 641653. https://doi.org/10.31004/obsesi.v5i1.563 Yildiz Durak, H. (2019). Modeling of relations between K-12 teachers’ TPACK levels and their technology integration self-efficacy, technology literacy levels, attitudes toward technology and usage objectives of social networks. Interactive Learning Environments, 1–27. https://doi.org/10.1080/10494820.2019.1619591 Yudha, F., Aziz, A., & Tohir, M. (2021). Pendampingan Siswa Terdampak Covid-19 Melalui Media Animasi Sebagai Inovasi Pembelajaran Online. JMM (Jurnal Masyarakat Mandiri), 5(3), 964–978. YurdugĂŒl, H., & Demir, Ö. (2017). An investigation of Pre-service Teachers’ Readiness for E-learning at Undergraduate Level Teacher Training Programs: The Case of Hacettepe University. The Case of Hacettepe University. &nbsp

    Partial Correctness of a Power Algorithm

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    This work continues a formal verification of algorithms written in terms of simple-named complex-valued nominative data [6],[8],[15],[11],[12],[13]. In this paper we present a formalization in the Mizar system [3],[1] of the partial correctness of the algorithm: i := val.1 j := val.2 b := val.3 n := val.4 s := val.5 while (i n) i := i + j s := s * b return s computing the natural n power of given complex number b, where variables i, b, n, s are located as values of a V-valued Function, loc, as: loc/.1 = i, loc/.3 = b, loc/.4 = n and loc/.5 = s, and the constant 1 is located in the location loc/.2 = j (set V represents simple names of considered nominative data [17]).The validity of the algorithm is presented in terms of semantic Floyd-Hoare triples over such data [9]. Proofs of the correctness are based on an inference system for an extended Floyd-Hoare logic [2],[4] with partial pre- and post-conditions [14],[16],[7],[5].Institute of Informatics, University of BiaƂystok, PolandGrzegorz Bancerek, CzesƂaw ByliƄski, Adam Grabowski, Artur KorniƂowicz, Roman Matuszewski, Adam Naumowicz, and Karol Pąk. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9–32, 2018. doi:10.1007/s10817-017-9440-6.R.W. Floyd. Assigning meanings to programs. Mathematical aspects of computer science, 19(19–32), 1967.Adam Grabowski, Artur KorniƂowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191–198, 2015. doi:10.1007/s10817-015-9345-1.C.A.R. Hoare. An axiomatic basis for computer programming. Commun. ACM, 12(10): 576–580, 1969.Ievgen Ivanov and Mykola Nikitchenko. On the sequence rule for the Floyd-Hoare logic with partial pre- and post-conditions. In Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, Kyiv, Ukraine, May 14–17, 2018, volume 2104 of CEUR Workshop Proceedings, pages 716–724, 2018.Ievgen Ivanov, Mykola Nikitchenko, Andrii Kryvolap, and Artur KorniƂowicz. Simple-named complex-valued nominative data – definition and basic operations. Formalized Mathematics, 25(3):205–216, 2017. doi:10.1515/forma-2017-0020.Ievgen Ivanov, Artur KorniƂowicz, and Mykola Nikitchenko. Implementation of the composition-nominative approach to program formalization in Mizar. The Computer Science Journal of Moldova, 26(1):59–76, 2018.Ievgen Ivanov, Artur KorniƂowicz, and Mykola Nikitchenko. On an algorithmic algebra over simple-named complex-valued nominative data. Formalized Mathematics, 26(2):149–158, 2018. doi:10.2478/forma-2018-0012.Ievgen Ivanov, Artur KorniƂowicz, and Mykola Nikitchenko. An inference system of an extension of Floyd-Hoare logic for partial predicates. Formalized Mathematics, 26(2): 159–164, 2018. doi:10.2478/forma-2018-0013.Ievgen Ivanov, Artur KorniƂowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165–173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur KorniƂowicz, and Mykola Nikitchenko. On algebras of algorithms and specifications over uninterpreted data. Formalized Mathematics, 26(2):141–147, 2018. doi:10.2478/forma-2018-0011.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the algebra of nominative data in Mizar. In Maria Ganzha, Leszek A. Maciaszek, and Marcin Paprzycki, editors, Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3–6, 2017., pages 237–244, 2017. ISBN 978-83-946253-7-5. doi:10.15439/2017F301.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the nominative algorithmic algebra in Mizar. In Leszek Borzemski, Jerzy ƚwiątek, and Zofia Wilimowska, editors, Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017 – Part II, Szklarska Poręba, Poland, September 17–19, 2017, volume 656 of Advances in Intelligent Systems and Computing, pages 176–186. Springer, 2017. ISBN 978-3-319-67228-1. doi:10.1007/978-3-319-67229-8_16.Artur KorniƂowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. An approach to formalization of an extension of Floyd-Hoare logic. In Vadim Ermolayev, Nick Bassiliades, Hans-Georg Fill, Vitaliy Yakovyna, Heinrich C. Mayr, Vyacheslav Kharchenko, Vladimir Peschanenko, Mariya Shyshkina, Mykola Nikitchenko, and Aleksander Spivakovsky, editors, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, Kyiv, Ukraine, May 15–18, 2017, volume 1844 of CEUR Workshop Proceedings, pages 504–523. CEUR-WS.org, 2017.Artur KorniƂowicz, Ievgen Ivanov, and Mykola Nikitchenko. Kleene algebra of partial predicates. Formalized Mathematics, 26(1):11–20, 2018. doi:10.2478/forma-2018-0002.Andrii Kryvolap, Mykola Nikitchenko, and Wolfgang Schreiner. Extending Floyd-Hoare logic for partial pre- and postconditions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications: 9th International Conference, ICTERI 2013, Kherson, Ukraine, June 19–22, 2013, Revised Selected Papers, pages 355–378. Springer International Publishing, 2013. ISBN 978-3-319-03998-5. doi:10.1007/978-3-319-03998-5_18.Volodymyr G. Skobelev, Mykola Nikitchenko, and Ievgen Ivanov. On algebraic properties of nominative data and functions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications – 10th International Conference, ICTERI 2014, Kherson, Ukraine, June 9–12, 2014, Revised Selected Papers, volume 469 of Communications in Computer and Information Science, pages 117–138. Springer, 2014. ISBN 978-3-319-13205-1. doi:10.1007/978-3-319-13206-8_6.27218919

    Effect of Gamification on students’ motivation and learning achievement in Second Language Acquisition within higher education: a literature review 2011-2019

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    [EN] This paper focuses on a fairly new motivational technique, the so-called Gamification, which consists of introducing game mechanics in non-game environments to promote motivation and engagement. By the turn of the 21rst century, Gamification took off in the business field and soon after became an attractive concept for researchers and professionals in education as it appears to be an increasingly popular method to motivate learners. Nevertheless, it is still a nascent field in terms of empirical evidence available to firmly support its educational benefits. This paper intends to shed some more light on this topic through a comprehensive review of literature published in the most prominent journals. The present study is framed within the field of Second Language Acquisition (SLA) in higher education and Computer-Assisted Language Learning, and focuses on the effects of gamified learning environments on student’s motivation and learning. A Meta-analysis method was used to explore relevant empirical research published between 2011 and 2019. After reviewing a corpus of 68  papers drawn from the leading databases Scopus and Web Of Science, and from which only 15 could be included in the study, we can point out two main findings: (i) there is still very limited literature in the field of SLA and, (ii) results seem to be predominantly positive in terms of motivation and engagement but only a few studies confirm clear interconnections with learning outcomes. The results suggest a lack of solid correlations between Gamification, motivation and cognitive processes. Azzouz Boudadi, N.; GutiĂ©rrez-ColĂłn, M. (2020). Effect of Gamification on students’ motivation and learning achievement in Second Language Acquisition within higher education: a literature review 2011-2019. The EuroCALL Review. 28(1):40-56. https://doi.org/10.4995/eurocall.2020.12974OJS4056281Bandura, A. (2012). Social cognitive theory. In P. A. Van Lange A. W. Kruglanski & E. T. Higgins Handbook of theories of social psychology: volume 1 (pp. 349-374). London: SAGE Publications Ltd. https://doi.org/10.4135/9781446249215.n18Barcena, E., & Sanfilippo, M. (2015). The audiovisual knowledge pill as a gamification strategy in second language online courses. Circulo de Linguistica Aplicada a La Comunicacion, 63, 22- 151. https://doi.org/10.5209/rev_CLAC.2015.v63.50172Bartle, R. (1996). Hearts, clubs, diamonds, spades: Players who suit MUDs. Journal of MUD Research, 1(1), 19-42. Retrieved from https://urlzs.com/HTjvG%0ABeatty, K. (2013). Teaching and researching computer-assisted language learning, second edition. London, UK: Routledge. https://doi.org/10.4324/9781315833774Berns, A., Isla-Montes, J.-L., Palomo-Duarte, M., & Dodero, J.-. (2016). Motivation, students' needs and learning outcomes: A hybrid game-based app for enhanced language learning. SpringerPlus, 5(1). https://doi.org/10.1186/s40064-016-2971-1Bustillo, J., Rivera, C., GuzmĂĄn, J., & Ramos, L. (2017). Benefits of using a mobile application in learning a foreign language. Sistemas & TelemĂĄtica, 15(40), 55- 68. https://doi.org/10.18046/syt.v15i40.2391Cardoso, W., Rueb, A., & Grimshaw, J. (2017). Can an interactive digital game help French learners improve their pronunciation? In K. Borthwick, L. Bradley & S. ThouĂ«sny (Eds), CALL in a climate of change: adapting to turbulent global conditions - short papers from EUROCALL 2017 (pp. 67-72). Researchpublishing.net. https://doi.org/10.14705/rpnet.2017.eurocall2017.691Castañeda, D. A., & Cho, M.-H. (2016). Use of a game-like application on a mobile device to improve accuracy in conjugating spanish verbs. Computer Assisted Language Learning, 29(7), 1195-1204. https://doi.org/10.1080/09588221.2016.1197950Chapelle, C. A. (2003). English Language Learning and Technology: Lectures on applied linguistics in the age of information and communication technology. Amsterdam/Philadelphia: John Benjamins Publishing Company. https://doi.org/10.1075/lllt.7Chapelle, C. A. (2009). The relationship between second language acquisition theory and computer-assisted language learning. Modern Language Journal, 93(1), 741- 753. https://doi.org/10.1111/j.1540-4781.2009.00970.xChapelle, C. A. (2016). Call in the year 2000: A look back from 2016. Language Learning and Technology, 20(2), 159-161. https://doi.org/http://hdl.handle.net/10125/44468Csikszentmihalyi, M. (1991). Flow: The psychology of optimal experience. New York, USA: Academy of Management Review.Deci, E. L., & Ryan, R. M. (2010). Self-Determination. In The Corsini Encyclopedia of Psychology. https://doi.org/10.1002/9780470479216.corpsy0834Deterding, S., Khaled, R., Nacke L.E. and Dixon, D. (2011). Gamification: Toward a Definition. In CHI 2011 Gamification Workshop Proceedings, Vancouver, 2011 (pp. 1215.). https://doi.org/978-1-4503-0268-5/11/0Dichev, C., & Dicheva, D. (2017). Gamifying education: what is known, what is believed and what remains uncertain: a critical review. International Journal of Educational Technology in Higher Education, 14(1), 9. https://doi.org/10.1186/s41239-017-0042-5Dicheva, D., Dichev, C., Agre, G., & Angelova, G. (2015). Gamification in education: A systematic mapping study. Educational Technology and Society, 18(3), 75- 88. https://doi.org/10.1109/EDUCON.2014.6826129DomĂ­nguez, A., Saenz-De-Navarrete, J., De-Marcos, L., FernĂĄndez-Sanz, L., PagĂ©s, C., & MartĂ­nez-HerrĂĄiz, J. J. (2013). Gamifying learning experiences: Practical implications and outcomes. Computers and Education. https://doi.org/10.1016/j.compedu.2012.12.020Dörnyei, Z., & Ryan, S. (2015). The psychology of the language learner revisited. Routledge. New York. https://doi.org/10.4324/9781315779553Figueroa Flores, J. F. (2015). Using gamification to enhance second language learning. Digital Education Review, 27, 32-54. Retrieved from http://revistes.ub.edu/index.php/der/article/view/11912/pdfGafni, R., Biran Achituv, D., & Rahmani, G. (2017). Learning Foreign Languages Using Mobile Applications. Journal of Information Technology Education: Research, 16, 301- 317. https://doi.org/10.28945/3855Gardner, R. C., & Lambert, W. E. (1972). Attitudes and Motivation in Second Language Learning. Rowley, MA: Newbury House Publishers.Godwin-Jones, R. (2015). Emerging technologies the evolving roles of language teachers: trained coders, local researchers, global citizens. Language, Learning and Technology, 19(1), 10-22.Hamari, J., Koivisto, J., & Sarsa, H. (2014). Does gamification work? - A literature review of empirical studies on gamification. In Proceedings of the Annual Hawaii International Conference on System Sciences (pp. 3025-3034). https://doi.org/10.1109/HICSS.2014.377Hew, K., Huang, B., Wah Samuel Chu, K., & Chiu, D. (2016). Engaging Asian students through game mechanics: Findings from two experiment studies. Computers & Education, 92-93, 221- 236. https://doi.org/10.1016/j.compedu.2015.10.010Hubbard, P. (2008). CALL and the Future of Language Teacher Education. CALICO Journal, 25(2), 175. https://doi.org/10.11139/cj.25.2.175-188Hung, H.-T. (2017). Clickers in the flipped classroom: bring your own device (BYOD) to promote student learning. Interactive Learning Environments, 25(8), 983-995. https://doi.org/10.1080/10494820.2016.1240090Iaremenko, N. (2017). Enhancing English language learners' motivation through online games. Information Technologies and Learning Tools, 59, 126-133. https://doi.org/10.33407/itlt.v59i3.1606Kapp, K. M. (2012). The Gamification of Learning and Instruction: Game-based Methods and Strategies for Training and Education. San Francisco, USA: Pfeiffer & Company. https://doi.org/10.1145/2207270.2211316KĂ©tyi, A. (2016, September 1). From Mobile Language Learning to Gamification: an Overlook of Research Results with Business Management Students over a Five-Year Period. Innovating in the Didactic Second Language Scenario Innovating in the Didactic Second Language Scenario: New Mobile, Open and Social Model, Edition: MonogrĂĄfico I., 45-59. Retrieved from https://urlzs.com/iZXtMLi, L. (2016). Benefits of CALL in lexico-grammatical acquisition. The Routledge Handbook of English Language Teaching (p. 463). London and New York: Routledge.Liu, Y., Holden, D., & Zheng, D. (2016). Analyzing students' Language Learning Experience in an Augmented Reality Mobile Game: An Exploration of an Emergent Learning Environment. Procedia - Social and Behavioral Sciences, 228, 369-374. https://doi.org/10.1016/j.sbspro.2016.07.055MacIntyre, P. D. (2002). Motivation, anxiety and emotion in second language acquisition. Individual Differences and Instructed Language Learning, 2, 45-68. https://doi.org/10.1075/lllt.2.05macMarczewski, A. (2019). Introduction to Gamification Part 4: Motivation (R.A.M.P, Maslow, SDT and more). Retrieved from https://www.gamified.uk/2019/01/30/introduction-to-gamification-part4-motivation-r-a-m-p-maslow-sdt-and-more/Mateo-Gallego, C., & Ruiz Yepes, G. (2018). Terapias de errores con aprendizaje mĂłvil y gamificaciĂłn: estudio comparativo en español de los negocios. Folios, 48, 121-135. https://doi.org/10.17227/folios.48-8139Munday, P. (2016). The case for using Duolingo as part of the language classroom experience. RIED. Revista Iberoamericana de EducaciĂłn a Distancia, 19 (1), 83-101. https://doi.org/10.5944/ried.19.1.14581Palomo-Duarte, M., Berns, A., Cejas, A., Dodero, J. M., Caballero, J. A., & Ruiz-Rube, I. (2016). Assessing Foreign Language Learning Through Mobile Game-Based Learning Environments. International Journal of Human Capital and Information Technology Professionals (IJHCITP), 7(2), 53-67. https://doi.org/10.4018/IJHCITP.2016040104Perry, B. (2015). Gamifying French Language Learning: A Case Study Examining a Quest-based, Augmented Reality Mobile Learning-tool. Procedia - Social and Behavioral Sciences, 174, 2308- 2315. https://doi.org/10.1016/j.sbspro.2015.01.892Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of Game-Based Learning. Educational Psychologist, 50, 258-283. https://doi.org/10.1080/00461520.2015.1122533Purgina, M., Mozgovoy, M., & Blake, J. (2019). WordBricks: Mobile Technology and Visual Grammar Formalism for Gamification of Natural Language Grammar Acquisition. Journal of Educational Computing Research. https://doi.org/10.1177/0735633119833010Rickinson, M., & May, H. (2009). A Comparative Study of Methodological Approaches to Reviewing Literature. UK : Higher Education AcademySeverengiz, M., Roeder, I., Schindler, K., & Seliger, G. (2018). Influence of Gaming Elements on Summative Assessment in Engineering Education for Sustainable Manufacturing. In Procedia Manufacturing (pp. 429-437). https://doi.org/10.1016/j.promfg.2018.02.141Sheldon, L. (2012). The Multiplayer Classroom: Designing Coursework as a Game. Boston, MA: Cengage Learning.Skinner, B. F. (1958). Teaching machines. Science. https://doi.org/10.1126/science.128.3330.969Werbach, K., & Hunter, D. (2012a). For the win: How game thinking can revolutionize your business. Wharton Digital Press.Werbach, K., & Hunter, D. (2012b). The Gamification Toolkit Game Elements. In For the Win: How Game Thinking Can Revolutionize Your Business. https://doi.org/10.1017/CBO9781107415324.004Zichermann, G. (2011). Intrinsic and extrinsic motivation in Gamification. Retrieved from https://www.gamification.co/2011/10/27/intrinsic-and-extrinsic-motivation-in-gamification

    Parents’ Role in Children's Learning During and After the Covid-19 Pandemic

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    When children only see their friends in little squares via Google Meet or Zoom, can teachers really address concepts like the importance of teamwork or how to manage conflict?  This is a learning phenomenon during the COVID-19 pandemic and the era after it. This study aims to see the role of parents as children's learning companions in terms of mentors and motivators when online education takes place. This research using photovoice within phenomenological methodology and have been doing with thematic analysis and collecting data through interviews and observations. The participants were eight parents and one female teacher as a homeroom teacher. The research findings show that although there are many obstacles in online learning for children, learning during the COVID-19 pandemic can still run by involving the role of parents and teachers as pillars of education for preschool-age children. For further research, it is hoped that the findings will be a way in solving learning problems for children. Keywords: early childhood education, parents’ role, online learning References: Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: The challenges and opportunities. In Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1813180 Aras, S. (2016). Free play in early childhood education: A phenomenological study. Early Child Development and Care, 186(7). https://doi.org/10.1080/03004430.2015.1083558 Arkorful, V. (2021). The role of e-learning, advantages and disadvantages of its adoption in higher The role of e-learning, the advantages and disadvantages of its adoption in Higher Education . International Journal of Education and Research, 2(December 2014). Atiles, J. T., AlmodĂłvar, M., ChavarrĂ­a Vargas, A., Dias, M. J. A., & ZĂșñiga LeĂłn, I. M. (2021). International responses to COVID-19: Challenges faced by early childhood professionals. European Early Childhood Education Research Journal, 29(1). https://doi.org/10.1080/1350293X.2021.1872674 Barnett, W. S., Grafwallner, R., & Weisenfeld, G. G. (2021). Corona pandemic in the United States shapes new normal for young children and their families. In European Early Childhood Education Research Journal (Vol. 29, Issue 1). https://doi.org/10.1080/1350293X.2021.1872670 Basham, J. D., Blackorby, J., & Marino, M. T. (2020). Opportunity in Crisis: The Role of Universal Design for Learning in Educational Redesign. In Learning Disabilities: A Contemporary Journal (Vol. 18, Issue 1). Beatriks Novianti Bunga, R. Pasifikus Christa Wijaya & Indra Yohanes Kiling (2021) Studying at Home: Experience of Parents and Their Young Children in an Underdeveloped Area of Indonesia, Journal of Research in Childhood Education, DOI: 10.1080/02568543.2021.1977436 Buheji, M., Hassani, A., Ebrahim, A., da Costa Cunha, K., Jahrami, H., Baloshi, M., & Hubail, S. (2020). Children and Coping During COVID-19: A Scoping Review of Bio-Psycho-Social Factors. International Journal of Applied Psychology, 10(1). https://doi.org/10.5923/j.ijap.20201001.02 Celik, M. Y. (2021). The dual role of nurses as mothers during the pandemic period: Qualitative study. Early Child Development and Care. https://doi.org/10.1080/03004430.2021.1917561 Coulter, M., Britton, Ú., MacNamara, Á., Manninen, M., McGrane, B., & Belton, S. (2021). PE at Home: Keeping the ‘E’ in PE while home-schooling during a pandemic. Physical Education and Sport Pedagogy. https://doi.org/10.1080/17408989.2021.1963425 Creswell, J. W. (2015). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (Fifth edition). Pearson. Dodd, H. F., Fitzgibbon, L., Watson, B. E., & Nesbit, R. J. (2021). Children’s play and independent mobility in 2020: Results from the british children’s play survey. International Journal of Environmental Research and Public Health, 18(8). https://doi.org/10.3390/ijerph18084334 Duran, A. (2019). A Photovoice Phenomenological Study Exploring Campus Belonging for Queer Students of Color. Journal of Student Affairs Research and Practice, 56(2). https://doi.org/10.1080/19496591.2018.1490308 Ebbeck, M., Yim, H. Y. B., Chan, Y., & Goh, M. (2016). Singaporean Parents’ Views of Their Young Children’s Access and Use of Technological Devices. Early Childhood Education Journal. https://doi.org/10.1007/s10643-015-0695-4 Ekyana, Luluk, Fauziddin Muhammad & Arifiyanti Nurul. (2021). Parents’ Perception: Early Childhood Social Behaviour During Physical Distancing in the Covid-19 Pandemic. JPUD: Jurnal Pendidikan Usia Dini, Volume 15 (2),DOI: https://doi.org/10.21009/JPUD.152.04 Eslava, M., Deaño, M., Alfonso, S., Conde, Á., & GarcĂ­a-SeñorĂĄn, M. (2016). Family context and preschool learning. Journal of Family Studies, 22(2). https://doi.org/10.1080/13229400.2015.1063445 Finn, L., & Vandermaas-Peeler, M. (2013). Young children’s engagement and learning opportunities in a cooking activity with parents and older siblings. Early Childhood Research and Practice, 15(1). Gee, E., Siyahhan, S., & Cirell, A. M. (2017). Video gaming as digital media, play, and family routine: Implications for understanding video gaming and learning in family contexts. Learning, Media, and Technology, 42(4). https://doi.org/10.1080/17439884.2016.1205600 Gelir, I., & Duzen, N. (2021). Children’s changing behaviours and routines, challenges and opportunities for parents during the COVID-19 pandemic. Education 3-13. https://doi.org/10.1080/03004279.2021.1921822 Giannini, S., Jenkins, R., & Saavedra, J. (2021). Mission: Recovering Education 2021. In UNICEF, UNESCO, and World Bank. Goodhart, F. W., Hsu, J., Baek, J. H., Coleman, A. L., Maresca, F. M., & Miller, M. B. (2006). A view through a different lens: Photovoice as a tool for student advocacy. Journal of American College Health, 55(1). https://doi.org/10.3200/JACH.55.1.53-56 Gong, S., Wang, X., Wang, Y., Qu, Y., Tang, C., Yu, Q., & Jiang, L. (2019). A descriptive qualitative study of home care experiences in parents of children with tracheostomies. Journal of Pediatric Nursing, 45. https://doi.org/10.1016/j.pedn.2018.12.005 Hamaidi, D. A., Arouri, Y. M., Noufa, R. K., & Aldrou, I. T. (2021). Parents’ Perceptions of Their Children’s Experiences with Distance Learning During the COVID-19 Pandemic. International Review of Research in Open and Distance Learning, 22(2). https://doi.org/10.19173/irrodl.v22i2.5154 Hammersley, M., & Traianou, A. (2015). Ethics in Qualitative Research: Controversies and Contexts. In Ethics in Qualitative Research: Controversies and Contexts. https://doi.org/10.4135/9781473957619 Harris, K. I. (2021). Parent Cooperative Early Childhood Settings: Empowering Family Strengths and Family Engagement for All Young Children. International Journal of Contemporary Education, 4(1). https://doi.org/10.11114/ijce.v4i1.5143 Hassinger-Das, B., Zosh, J. M., Hansen, N., Talarowski, M., Zmich, K., Golinkoff, R. M., & Hirsh-Pasek, K. (2020). Play-and-learn spaces: Leveraging library spaces to promote caregiver and child interaction. Library and Information Science Research, 42(1). https://doi.org/10.1016/j.lisr.2020.101002 Henter, R., & Nastasa, L. E. (2021). Parents’ Emotion Management for Personal Well-Being When Challenged by Their Online Work and Their Children’s Online School. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.751153 Houston, S. (2017). Towards a critical ecology of child development in social work: Aligning the theories of Bronfenbrenner and Bourdieu. Families, Relationships and Societies, 6(1). https://doi.org/10.1332/204674315X14281321359847 Ihmeideh, F., AlFlasi, M., Al-Maadadi, F., Coughlin, C., & Al-Thani, T. (2020). Perspectives of family–school relationships in Qatar based on Epstein’s model of six types of parent involvement. Early Years, 40(2). https://doi.org/10.1080/09575146.2018.1438374 Iruka, I. U., DeKraai, M., Walther, J., Sheridan, S. M., & Abdel-Monem, T. (2020). Examining how rural ecological contexts influence children’s early learning opportunities. Early Childhood Research Quarterly, 52. https://doi.org/10.1016/j.ecresq.2019.09.005 Jiles, T. (2015). Knock, knock, may I come in? An integrative perspective on professional development concerns for home visits conducted by teachers. Contemporary Issues in Early Childhood, 16(1). https://doi.org/10.1177/1463949114567274 Kartini, K. (2021). Analisis Pembelajaran Online Anak Usia Dini Masa Pandemi COVID -19 Kota dan Perdalaman. Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini, 6(2). https://doi.org/10.31004/obsesi.v6i2.880 Kurniati, E., Nur Alfaeni, D. K., & Andriani, F. (2020). Analisis Peran Orang Tua dalam Mendampingi Anak di Masa Pandemi Covid-19. Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini, 5(1). https://doi.org/10.31004/obsesi.v5i1.541 La Paro, K. M., & Gloeckler, L. (2016). The Context of Child Care for Toddlers: The “Experience Expectable Environment”. Early Childhood Education Journal, 44(2). https://doi.org/10.1007/s10643-015-0699-0 Lau, E. Y. H., & Lee, K. (2021). Parents’ Views on Young Children’s Distance Learning and Screen Time During COVID-19 Class Suspension in Hong Kong. Early Education and Development, 32(6). https://doi.org/10.1080/10409289.2020.1843925 Lau, E. Y. H., Li, J. Bin, & Lee, K. (2021). Online Learning and Parent Satisfaction during COVID-19: Child Competence in Independent Learning as a Moderator. Early Education and Development, 32(6). https://doi.org/10.1080/10409289.2021.1950451 Lilawati, A. (2020). Peran Orang Tua dalam Mendukung Kegiatan Pembelajaran di Rumah pada Masa Pandemi. Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini. https://doi.org/10.31004/obsesi.v5i1.630 Lim, K. F. (2020). Emergency remote teaching and learning in the time of COVID-19. Chemistry in Australia, August. Lin, X., & Li, H. (2018). Parents’ play beliefs and engagement in young children’s play at home. European Early Childhood Education Research Journal, 26(2). https://doi.org/10.1080/1350293X.2018.1441979 Michele L. Stites, Susan Sonneschein & Samantha H. Galczyk (2021) Preschool Parents’ Views of Distance Learning during COVID-19, Early Education and Development, 32:7, 923-939, DOI: 10.1080/10409289.2021.1930936 Muhdi, Nurkolis, & Yuliejantiningsih, Y. (2020). The Implementation of Online Learning in Early Childhood Education During the Covid-19 Pandemic. JPUD - Jurnal Pendidikan Usia Dini, 14(2). https://doi.org/10.21009/jpud.142.04 Ortlipp, M. (2015). Keeping and Using Reflective Journals in the Qualitative Research Process. The Qualitative Report. https://doi.org/10.46743/2160-3715/2008.1579 Paat, Y. F. (2013). Working with Immigrant Children and Their Families: An Application of Bronfenbrenner’s Ecological Systems Theory. Journal of Human Behavior in the Social Environment, 23(8). https://doi.org/10.1080/10911359.2013.800007 Plowman, L., Stephen, C., & McPake, J. (2010). Supporting young children’s learning with technology at home and in preschool. Research Papers in Education, 25(1). https://doi.org/10.1080/02671520802584061 Rona Novick, Suzanne Brooks & Jenny Isaacs (2021) Parental Report of Preschoolers’ Jewish Day School Engagement and Adjustment During the Covid-19 Shutdown, Journal of Jewish Education, 87:4, 301-315, DOI: 10.1080/15244113.2021.1977098 Sandi Ferdiansyah, S. S., & Angin, R. (2020). Pengalaman Mahasiswa Thailand dalam Pembelajaran Daring di Universitas di Indonesia pada Masa Pandemi COVID-19. Journal of International Students, 10(S3). Sonnenschein, S., Stites, M., & Dowling, R. (2021). Learning at home: What preschool children’s parents do and what they want to learn from their children’s teachers. Journal of Early Childhood Research, 19(3). https://doi.org/10.1177/1476718X20971321 Sri Indah Pujiastuti, Sofia Hartati & Jun Wang (2022) Socioemotional Competencies of Indonesian Preschoolers: Comparisons between the Pre-Pandemic and Pandemic Periods and among DKI Jakarta, DI Yogyakarta and West Java Provinces, Early Education and Development, DOI: 10.1080/10409289.2021.2024061 Stone, K., Burgess, C., Daniel, B., Smith, J., & Stephen, C. (2017). Nurture corners in preschool settings: Involving and nurturing children and parents. Emotional and Behavioural Difficulties, 22(4). https://doi.org/10.1080/13632752.2017.1309791 Suzanne M. Egan & ChloĂ© Beatty (2021) To school through the screens: the use of screen devices to support young children's education and learning during the COVID-19 pandemic, Irish Educational Studies, 40:2, 275-283, DOI: 10.1080/03323315.2021.1932551 Thomson, S. (2007). Do’s and don’ts: Children’s experiences of the primary school playground. Environmental Education Research, 13(4). https://doi.org/10.1080/13504620701581588 Vallejo-Ruiz, M., & Torres-Soto, A. (2020). Teachers’ conceptions on the quality of the teaching and learning process in early childhood education. Revista Electronica Educare, 24(3). https://doi.org/10.15359/REE.24-3.13 Widodo, H. P. (2014). Methodological considerations in interview data transcription. International Journal of Innovation in English Language, 3(1). Wijaya, Candra., Dalimunthe, Rasyid Anwar., & Muslim. Parents’ Perspective on The Online Learning Using Zoom Application in Early Childhood Education. JPUD: Jurnal Pendidikan Usia Dini, Volume 15 Number 2. DOI: https://doi.org/10.21009/JPUD.152.06 Winship, M., Standish, H., Trawick-Smith, J., & Perry, C. (2021). Reflections on practice: Providing authentic experiences with families in early childhood teacher education. In Journal of Early Childhood Teacher Education (Vol. 42, Issue 3). https://doi.org/10.1080/10901027.2020.1736695 &nbsp

    Development of Pisa 2015 Based Chemical Literacy Assessment Instrument For High School Students

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    This study aims to develop valid and reliable chemical literacy assessment instruments based on PISA 2015. The development procedures carried out were 1) research and information collecting, 2) planning, 3) development preliminary form of product, 4) preliminary field testing, and 5) main product revision. Instrument of development result was validated(content validity and empirical validity). Content validity assessment data was obtained from the validity test results from two chemistry lecturers. Empirical validity test data were acquired from68 grade XI students as test subjects who came from five high schools in Malang. An empirical validity test was used to obtain the level of validity, reliability, discrimination index, difficulty level, and effectiveness of distractors of the items developed in the instrument. The instrument of development results consisted of 20 multiple choice items and 4 attitude questionnaires. The results of the content validity test indicated a valid instrument (the average score for the aspects of substance, construction, and language was 83.9). The results of the empirical validity test showed that multiple-choice items had a correlation value of 0.37-0.77, categorized as valid, and the reliability value was 0.86, classified as highly reliable. The discrimination index obtained was five items ranked as sufficiently good and 15 items categorized as good, while five items classified as easy item, 14 moderate items, and one difficult item, all distractors were functioning. The empirical validity test results in the form of an attitude questionnaire showed a correlation value of 0.65-0.69, so they were valid, and the reliability value was 0.59, classified as quite high criteria. Instrument development results proved to be valid and reliable, so it is feasible to be used to measure students' chemical literacy skills.ReferencesAmerican Association for the Advancement of Science (AAAS). (1993). Benchmarks for science literacy: a project 2061 report. New York: Oxford University Press.Arikunto, S. (1993). Dasar-Dasar Evaluasi Pendidikan. Jakarta: Bumi Aksara.Bond, D. (1989). In Pursuit of Chemical Literacy: A Place for Chemical Reactions. Journal of Chemical Education, 66(2), 157.Celik, S. (2014).Chemical Literacy Levels of Science And Mathematics Teacher Candidates. Australian Journal of Teacher Education, 39(1), 1 – 15Cigdemoglu, C., & Geban, O. (2015). Improving Students' Chemical Literacy Level on Thermochemical And Thermodynamics Concepts through Context-Based Approach. Chemistry Education Research And Practice, 16, 302 – 317.Cigdemoglu, C., Arslan, H. O., & Cam, A. (2017).Argumentation to Foster Pre-Service Science Teachers' Knowledge, Competency, And Attitude on The Domains of Chemical Literacy of Acids And Bases. Chemistry Education Research And Practice, 18(2), 288 – 303.Direktorat Pembinaan SMA. (2017). Panduan Penilaian oleh Pendidik dan Satuan Pendidikan Sekolah Menengah Atas. Jakarta: Kementerian Pendidikan dan Kebudayaan RI.Kohen, Z., Herscovitz, O., & Dori, Y. J. (2020). How to Promote Chemical Literacy? Online Question Posing And Communicating With Scientists. Chemistry Education Research And Practice, 21(1), 250 – 266Mudiono, A. (2016). Keprofesionalan Guru dalam Menghadapi Pendidikan di Era Global. Makalah disajikan dalam Seminar Nasional, Jurusan KSDP FIP UM, Malang 25 September.Mumba, F., & Hunter, W. J. F. (2009). Representative Nature of Scientific Literacy Themes in A High School Chemistry Course: The Case of Zambia. Chemistry Education Research And Practice, 10(3), 219 – 226.Naganuma, S. (2017). An Assessment of Civic Scientific Literacy in Japan: Development of A More Authentic Assessment Task And Scoring Rubric. International Journal of Science Education, Part B, 7(4), 301 – 322Norris, S. P., & Philip, L. M. (2003). How literacy in its fundamental sense in central to scientific literacy. Science Education, 87(2), 224 – 240.Organisation for Economic Co-operation and Development (OECD). (2016). PISA 2015 Assessment And Analytical Framework: Science, Reading, Mathematic And Financial Literacy. Paris: OECD PublishingOrganisation for Economic Co-operation and Development (OECD). (2018). PISA 2018 Result Combined Executive Summaries Volume I, II, & III. Paris: Organisation for Economic Co-operation and Development.Osborne, J. F. (2010). Arguing to Learn in Science: The Role of Collaborative, Critical Discourse. Science, 328(5977), 463 – 466Rahayu, S. (2014). Menuju Masyarakat Berliterasi Sains: Harapan dan Tantangan Kurikulum 2013. Makalah disajikan dalam Seminar Nasional Kimia dan Pembelajarannya, Jurusan Kimia FMIPA UM, Malang 6 September.Rahayu, S. (2017). Mengoptimalkan Aspek Literasi dalam Pembelajaran Kimia Abad 21. Makalah disajikan dalam Seminar Nasional Kimia, Jurusan Pendidikan Kimia FMIPA UNY, Yogyakarta, 14 Oktober.Riduwan. (2011). Belajar Mudah Penelitian: untuk Guru-Karyawan, dan Peneliti Pemula. Bandung: AlfabetaRiduwan. (2013). Dasar-Dasar Statistika. Bandung: AlfabetaShe, H. C., Stacey, K., & Schmidt, W. H. (2018).Science And Mathematics Literacy: PISA for Better School Education. International Journal of Science And Mathematics Education, 16(1), 1 – 5Shwartz, Y., Ben-Zvi, R., & Hofstein, A. (2005). The Importance of Involving High-School Chemistry Teachers in The Process of Defining the Operational Meaning of Chemical Literacy. International Journal of ScienceEducation, 27(3), 323 – 344.Thummathong, R., & Thathong, K. (2016). Construction of A Chemical Literacy Test for Engineering Students. Journal of Turkish Science Education, 13(3), 185 – 198.United Nations Environment Programme (UNEP). (2012). 21 Issues for the 21st Century: Result of the UNEP Foresight Process on Emerging Environmental Issues. Nairobi, Kenya: United Nations Environment Programme.Vogelzang, J., Admiraal, W. F., & van Driel, J. H. (2020). Effects of Scrum Methodology on Students' Critical Scientific Literacy: The Case of Green Chemistry. Chemistry Education Research And Practice, 21(3), 940 – 952.World Economic Forum (WEF). (2016). New Vision for Education: Fostering Social And Emotional Learning through Technology

    On potential cognitive abilities in the machine kingdom

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11023-012-9299-6Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be different for the ‘machine kingdom’. While machines can be characterised by a set of cognitive abilities, and measuring them is already a big challenge, known as ‘universal psychometrics’, a more informative, and yet more challenging, goal would be to also determine the potential cognitive abilities of a machine. In this paper we investigate the notion of potential cognitive ability for machines, focussing especially on universality and intelligence. We consider several machine characterisations (non-interactive and interactive) and give definitions for each case, considering permanent and temporal potentials. From these definitions, we analyse the relation between some potential abilities, we bring out the dependency on the environment distribution and we suggest some ideas about how potential abilities can be measured. Finally, we also analyse the potential of environments at different levels and briefly discuss whether machines should be designed to be intelligent or potentially intelligent.We thank the anonymous reviewers for their comments, which have helped to significantly improve this paper. This work was supported by the MEC-MINECO projects CONSOLIDER-INGENIO CSD2007-00022 and TIN 2010-21062-C02-02, GVA project PROMETEO/2008/051, the COST - European Cooperation in the field of Scientific and Technical Research IC0801 AT. Finally, we thank three pioneers ahead of their time(s). We thank Ray Solomonoff (1926-2009) and Chris Wallace (1933-2004) for all that they taught us, directly and indirectly. And, in his centenary year, we thank Alan Turing (1912-1954), with whom it perhaps all began.HernĂĄndez-Orallo, J.; Dowe, DL. (2013). On potential cognitive abilities in the machine kingdom. Minds and Machines. 23(2):179-210. https://doi.org/10.1007/s11023-012-9299-6S179210232Amari, S., Fujita, N., Shinomoto, S. (1992). Four types of learning curves. Neural Computation 4(4), 605–618.Aristotle (Translation, Introduction, and Commentary by Ross, W.D.) (1924). Aristotle’s Metaphysics. Oxford: Clarendon Press.Barmpalias, G. & Dowe, D. L. (2012). Universality probability of a prefix-free machine. Philosophical transactions of the Royal Society A [Mathematical, Physical and Engineering Sciences] (Phil Trans A), Theme Issue ‘The foundations of computation, physics and mentality: The Turing legacy’ compiled and edited by Barry Cooper and Samson Abramsky, 370, pp 3488–3511.Chaitin, G. J. (1966). On the length of programs for computing finite sequences. Journal of the Association for Computing Machinery, 13, 547–569.Chaitin, G. J. (1975). A theory of program size formally identical to information theory. Journal of the ACM (JACM), 22(3), 329–340.Dowe, D. L. (2008, September). Foreword re C. S. Wallace. Computer Journal, 51(5):523–560, Christopher Stewart WALLACE (1933–2004) memorial special issue.Dowe, D. L. (2011). MML, hybrid Bayesian network graphical models, statistical consistency, invariance and uniqueness. In: P. S. Bandyopadhyay, M. R. Forster (Eds), Handbook of the philosophy of science—Volume 7: Philosophy of statistics (pp. 901–982). Amsterdam: Elsevier.Dowe, D. L. & Hajek, A. R. (1997a). A computational extension to the turing test. Technical report #97/322, Dept Computer Science, Monash University, Melbourne, Australia, 9 pp, http://www.csse.monash.edu.au/publications/1997/tr-cs97-322-abs.html .Dowe, D. L. & Hajek, A. R. (1997b, September). A computational extension to the Turing Test. in Proceedings of the 4th conference of the Australasian Cognitive Science Society, University of Newcastle, NSW, Australia, 9 pp.Dowe, D. L. & Hajek, A. R. (1998, February). A non-behavioural, computational extension to the Turing Test. In: International conference on computational intelligence and multimedia applications (ICCIMA’98), Gippsland, Australia, pp 101–106.Dowe, D. L., HernĂĄndez-Orallo, J. (2012). IQ tests are not for machines, yet. Intelligence, 40(2), 77–81.Gallistel, C. R., Fairhurst, S., & Balsam, P. (2004). The learning curve: Implications of a quantitative analysis. In Proceedings of the National Academy of Sciences of the United States of America, 101(36), 13124–13131.Gardner, M. (1970). Mathematical games: The fantastic combinations of John Conway’s new solitaire game “life”. Scientific American, 223(4), 120–123.Goertzel, B. & Bugaj, S. V. (2009). AGI preschool: A framework for evaluating early-stage human-like AGIs. In Proceedings of the second international conference on artificial general intelligence (AGI-09), pp 31–36.HernĂĄndez-Orallo, J. (2000a). Beyond the Turing Test. Journal of Logic, Language & Information, 9(4), 447–466.HernĂĄndez-Orallo, J. (2000b). On the computational measurement of intelligence factors. In A. Meystel (Ed), Performance metrics for intelligent systems workshop (pp 1–8). Gaithersburg, MD: National Institute of Standards and Technology.HernĂĄndez-Orallo, J. (2010). On evaluating agent performance in a fixed period of time. In M. Hutter et al. (Eds.), Proceedings of 3rd international conference on artificial general intelligence (pp. 25–30). New York: Atlantis Press.HernĂĄndez-Orallo, J., & Dowe, D. L. (2010). Measuring universal intelligence: Towards an anytime intelligence test. Artificial Intelligence, 174(18), 1508–1539.HernĂĄndez-Orallo, J. & Dowe, D. L. (2011, April). Mammals, machines and mind games. Who’s the smartest?. The conversation, http://theconversation.edu.au/mammals-machines-and-mind-games-whos-the-smartest-566 .HernĂĄndez-Orallo J., Dowe D. L., España-Cubillo S., HernĂĄndez-Lloreda M. V., & Insa-Cabrera J. (2011). On more realistic environment distributions for defining, evaluating and developing intelligence. In: J. Schmidhuber, K. R. ThĂłrisson, & M. Looks (Eds.), Artificial general intelligence 2011, volume 6830, LNAI series, pp. 82–91. New York: Springer.HernĂĄndez-Orallo, J., Dowe, D. L., & HernĂĄndez-Lloreda, M. V. (2012a, March). Measuring cognitive abilities of machines, humans and non-human animals in a unified way: towards universal psychometrics. Technical report 2012/267, Faculty of Information Technology, Clayton School of I.T., Monash University, Australia.HernĂĄndez-Orallo, J., Insa, J., Dowe, D. L., & Hibbard, B. (2012b). Turing tests with Turing machines. In A. Voronkov (Ed.), The Alan Turing centenary conference, Turing-100, Manchester, volume 10 of EPiC Series, pp 140–156.HernĂĄndez-Orallo, J., & Minaya-Collado, N. (1998). A formal definition of intelligence based on an intensional variant of Kolmogorov complexity. In Proceedings of the international symposium of engineering of intelligent systems (EIS’98) (pp 146–163). Switzerland: ICSC Press.Herrmann, E., Call, J., HernĂĄndez-Lloreda, M. V., Hare, B., & Tomasello, M. (2007). Humans have evolved specialized skills of social cognition: The cultural intelligence hypothesis. Science, 317(5843), 1360–1366.Herrmann, E., HernĂĄndez-Lloreda, M. V., Call, J., Hare, B., & Tomasello, M. (2010). The structure of individual differences in the cognitive abilities of children and chimpanzees. Psychological Science, 21(1), 102–110.Horn, J. L., & Cattell, R. B. (1966). Refinement and test of the theory of fluid and crystallized general intelligences. Journal of educational psychology, 57(5), 253.Hutter, M. (2005). Universal artificial intelligence: Sequential decisions based on algorithmic probability. New York: Springer.Insa-Cabrera, J., Dowe, D. L., España, S., HernĂĄndez-Lloreda, M. V., & HernĂĄndez-Orallo, J. (2011a). Comparing humans and AI agents. In AGI: 4th conference on artificial general intelligence—Lecture Notes in Artificial Intelligence (LNAI), volume 6830, pp 122–132. Springer, New York.Insa-Cabrera, J., Dowe, D. L., & HernĂĄndez-Orallo, J. (2011b). Evaluating a reinforcement learning algorithm with a general intelligence test. In CAEPIA—Lecture Notes in Artificial Intelligence (LNAI), volume 7023, pages 1–11. Springer, New York.Kearns, M. & Singh, S. (2002). Near-optimal reinforcement learning in polynomial time. Machine Learning, 49(2), 209–232.Kolmogorov, A. N. (1965). Three approaches to the quantitative definition of information. Problems of Information Transmission, 1, 4–7.Legg, S. (2008, June). Machine super intelligence. Department of Informatics, University of Lugano.Legg, S. & Hutter, M. (2007). Universal intelligence: A definition of machine intelligence. Minds and Machines, 17(4), 391–444.Legg, S., & Veness, J. (2012). An approximation of the universal intelligence measure. In Proceedings of Solomonoff 85th memorial conference. New York: Springer.Levin, L. A. (1973). Universal sequential search problems. Problems of Information Transmission, 9(3), 265–266.Li, M., VitĂĄnyi, P. (2008). An introduction to Kolmogorov complexity and its applications (3rd ed). New York: Springer.Little, V. L., & Bailey, K. G. (1972). Potential intelligence or intelligence test potential? A question of empirical validity. Journal of Consulting and Clinical Psychology, 39(1), 168.Mahoney, M. V. (1999). Text compression as a test for artificial intelligence. In Proceedings of the national conference on artificial intelligence, AAAI (pp. 486–502). New Jersey: Wiley.Mahrer, A. R. (1958). Potential intelligence: A learning theory approach to description and clinical implication. The Journal of General Psychology, 59(1), 59–71.Oppy, G., & Dowe, D. L. (2011). The Turing Test. In E. N. Zalta (Ed.), Stanford encyclopedia of philosophy. Stanford University. http://plato.stanford.edu/entries/turing-test/ .Orseau, L. & Ring, M. (2011). Self-modification and mortality in artificial agents. In AGI: 4th conference on artificial general intelligence—Lecture Notes in Artificial Intelligence (LNAI), volume 6830, pages 1–10. Springer, New York.Ring, M. & Orseau, L. (2011). Delusion, survival, and intelligent agents. In AGI: 4th conference on artificial general intelligence—Lecture Notes in Artificial Intelligence (LNAI), volume 6830, pp. 11–20. Springer, New York.Schaeffer, J., Burch, N., Bjornsson, Y., Kishimoto, A., Muller, M., Lake, R., et al. (2007). Checkers is solved. Science, 317(5844), 1518.Solomonoff, R. J. (1962). Training sequences for mechanized induction. In M. Yovits, G. Jacobi, & G. Goldsteins (Eds.), Self-Organizing Systems, 7, 425–434.Solomonoff, R. J. (1964). A formal theory of inductive inference. Information and Control, 7(1–22), 224–254.Solomonoff, R. J. (1967). Inductive inference research: Status, Spring 1967. RTB 154, Rockford Research, Inc., 140 1/2 Mt. Auburn St., Cambridge, Mass. 02138, July 1967.Solomonoff, R. J. (1978). Complexity-based induction systems: comparisons and convergence theorems. IEEE Transactions on Information Theory, 24(4), 422–432.Solomonoff, R. J. (1984). Perfect training sequences and the costs of corruption—A progress report on induction inference research. Oxbridge research.Solomonoff, R. J. (1985). The time scale of artificial intelligence: Reflections on social effects. Human Systems Management, 5, 149–153.Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction. Cambridge: The MIT press.Thorp, T. R., & Mahrer, A. R. (1959). Predicting potential intelligence. Journal of Clinical Psychology, 15(3), 286–288.Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59, 433–460.Veness, J., Ng, K. S., Hutter, M., & Silver, D. (2011). A Monte Carlo AIXI approximation. Journal of Artificial Intelligence Research, JAIR, 40, 95–142.Wallace, C. S. (2005). Statistical and inductive inference by minimum message length. New York: Springer.Wallace, C. S., & Boulton, D. M. (1968). An information measure for classification. Computer Journal, 11, 185–194.Wallace, C. S., & Dowe, D. L. (1999a). Minimum message length and Kolmogorov complexity. Computer Journal 42(4), 270–283.Wallace, C. S., & Dowe, D. L. (1999b). Refinements of MDL and MML coding. Computer Journal, 42(4), 330–337.Woergoetter, F., & Porr, B. (2008). Reinforcement learning. Scholarpedia, 3(3), 1448.Zvonkin, A. K., & Levin, L. A. (1970). The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms. Russian Mathematical Surveys, 25, 83–124

    Organizational Excellence in Palestinian Universities of Gaza Strip

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    The research aims to identify the organizational excellence in Palestinian universities of Gaza Strip, from the perspective of senior management. The questionnaires were distributed the top senior management in the Palestinian universities, and the study population was (344) employees in senior management in Palestinian universities. A stratified random sample were selected from of employees in the Palestinian universities consist of (182) employees at return rate of (69.2%). SPSS program for analyzing and processing the data was used. The study reached the following results: the senior management agrees largely on the importance of the axis of "Leadership Excellence" and "Excellence service sectors". The senior management agrees moderately about the importance of the axis of the “Knowledge excellence". The study showed that there is a weakness in the employment of scientific research to serve the community, there is weakness in the follow-up of the universities management for the performance of their graduates in the institutions in which they work. Senior management agrees on the importance of the "Organizational Excellence" moderately. The recommendations of study includes: the need to develop principles and fair criteria for the selection of the best candidates for the university and university leaders based on specialization, competence, experience, skills, integrity and not on the basis of favoritism

    The Role of Technology in Music Education: a Survey of Computer Usage in Teaching Music in Colleges of Education in The Volta Region, Ghana

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    The study sought to find out the role of computer technology in music education in Colleges of Education in the Volta Region of Ghana. It aimed at surveying the use of computer technology for teaching music and exploring the instructional prospects for computer technology usage in music in Colleges of Education. The study employed Rogers’ Diffusion Innovation theory and descriptive survey research method. Data was collected from the respondents using questionnaire, interview, and observation. The study revealed that even though about 90% of the music tutors have good academic qualification and over five years teaching experience, lack of competence in handling computer technology in teaching music among some music tutors and incoherent ICT initiatives hindered proper application of computer technology in the field of music education. It is however envisaged that increasing access and coherent computer technology initiatives will be paramount for the teaching of music in the Colleges of Education
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