Sustainable Higher Education Development through Technology Enhanced Learning

[EN] Higher education is incorporating Information and Communication Technology (ICT) at a fast rate for different purposes. Scientific papers include within the concept of Technology Enhanced Learning (TEL) the myriad applications of information and communication technology, e-resources, and pedagogical approaches to the development of education. TEL¿s specific application to higher education is especially relevant for countries under rapid development for providing quick and sustainable access to quality education (UN sustainable development goal 4). This paper presents the research results of an online pedagogical experience in collaborative academic research for analyzing good practice in TEL-supported higher education development. The results are obtained through a pilot implementation providing curated data on TEL competency¿s development of faculty skills and analysis of developing sustainable higher education degrees through TEL cooperation, for capacity building. Given the increased volume and complexity of the knowledge to be delivered, and the exponential growth of the need for skilled workers in emerging economies, online training is the most effective way of delivering a sustainable higher education. The results of the PETRA Erasmus+ capacity-building project provides evidence of a successful implementation of a TEL-supported methodology for collaborative faculty development focused on future online degrees built collaboratively and applied locally.This research was co-funded by the European Commission through the Erasmus+ KA2 project "Promoting Excellence in Teaching and Learning in Azerbaijani Universities (PETRA)" project number 573630-EPP-1-2016-1-ES-EPPKA2-CBHE-JP.Orozco-Messana, J.; Martínez-Rubio, J.; Gonzálvez-Pons, AM. (2020). Sustainable Higher Education Development through Technology Enhanced Learning. Sustainability. 12(9):1-13. https://doi.org/10.3390/su12093600S113129Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238-256. doi:10.1016/j.chb.2015.11.036Becker, H. J., & Ravitz, J. (1999). The Influence of Computer and Internet Use on Teachers’ Pedagogical Practices and Perceptions. Journal of Research on Computing in Education, 31(4), 356-384. doi:10.1080/08886504.1999.10782260Mumford, S., & Dikilitaş, K. (2020). Pre-service language teachers reflection development through online interaction in a hybrid learning course. Computers & Education, 144, 103706. doi:10.1016/j.compedu.2019.103706Lee, D., Watson, S. L., & Watson, W. R. (2020). The Relationships Between Self-Efficacy, Task Value, and Self-Regulated Learning Strategies in Massive Open Online Courses. The International Review of Research in Open and Distributed Learning, 21(1), 23-39. doi:10.19173/irrodl.v20i5.4389Passey, D. (2019). Technology‐enhanced learning: Rethinking the term, the concept and its theoretical background. British Journal of Educational Technology, 50(3), 972-986. doi:10.1111/bjet.12783Lai, Y.-C., & Peng, L.-H. (2019). Effective Teaching and Activities of Excellent Teachers for the Sustainable Development of Higher Design Education. Sustainability, 12(1), 28. doi:10.3390/su12010028Lee, S., Lee, H., & Kim, T. (2018). A Study on the Instructor Role in Dealing with Mixed Contents: How It Affects Learner Satisfaction and Retention in e-Learning. Sustainability, 10(3), 850. doi:10.3390/su10030850“Continuous Improvement in Teaching Strategies through Lean Principles”. Teaching & Learning Symposium, University of Southern Indiana http://hdl.handle.net/20.500.12419/455The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. (2003). Journal of Management Information Systems, 19(4), 9-30. doi:10.1080/07421222.2003.11045748Goodman, J., Melkers, J., & Pallais, A. (2019). Can Online Delivery Increase Access to Education? Journal of Labor Economics, 37(1), 1-34. doi:10.1086/698895Alexander, J., Barcellona, M., McLachlan, S., & Sackley, C. (2019). Technology-enhanced learning in physiotherapy education: Student satisfaction and knowledge acquisition of entry-level students in the United Kingdom. Research in Learning Technology, 27(0). doi:10.25304/rlt.v27.2073How Can Adaptive Platforms Improve Student Learning Outcomes? A Case Study of Open Educational Resources and Adaptive Learning Platforms https://ssrn.com/abstract=3478134Sun, A., & Chen, X. (2016). Online Education and Its Effective Practice: A Research Review. Journal of Information Technology Education: Research, 15, 157-190. doi:10.28945/3502EU Commission https://ec.europa.eu/education/education-in-the-eu/digital-education-action-plan_enEssence Project https://husite.nl/essence/Orozco-Messana, J., de la Poza-Plaza, E., & Calabuig-Moreno, R. (2020). Experiences in Transdisciplinary Education for the Sustainable Development of the Built Environment, the ISAlab Workshop. Sustainability, 12(3), 1143. doi:10.3390/su12031143Kurilovas, E., & Kubilinskiene, S. (2020). Lithuanian case study on evaluating suitability, acceptance and use of IT tools by students – An example of applying Technology Enhanced Learning Research methods in Higher Education. Computers in Human Behavior, 107, 106274. doi:10.1016/j.chb.2020.10627

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

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., Coëtlogon, 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., & Brînză, 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., & Rodríguez-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. Yurdugül, 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

Advancing the debate on architecture, planning, and built environment research

With an acceptance rate that does not exceed 25% of the total papers and articles submitted to the journal, IJAR – International Journal of Architectural Research is moving forward to position itself among the leading journals in architecture and urban studies worldwide. As this is the case since the beginning of volume 5, issue 1, March 2011, one must note that the journal has been covered by several data and index bases since its inception including Avery Index to Architectural Periodicals, EBSCO-Current Abstracts-Art and Architecture, INTUTE, Directory of Open Access Journals, Pro-Quest, Scopus-Elsevier and many university library databases across the globe. This is coupled with IJAR being an integral part of the archives and a featured collection of ArchNet and the Aga Khan Documentation Centre at MIT: Massachusetts Institute of Technology, Cambridge, MA. In 2014, IJAR was included in Quartile 2 / Q2 list of Journals both in ‘Architecture’ and ‘Urban Studies.’ As of May 2015, IJAR is ranked 23 out of 83 journals in ‘Architecture’ and 59 out of 119 in ‘Urban Studies.’ Rankings are based on the SJR (SCImago Journal Ranking); an Elsevier- SCOPUS indicator that measures the scientific influence of the average article in a journal. SJR is a measure of scientific influence of scholarly journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from. See here for more information (http://www.scimagojr.com/index.php) and (http://www.journalmetrics.com/sjr.php). While the journal is now on top of many of the distinguished journals in Elsevier- SCOPUS database, we will keep aspiring to sustain our position and move forward to Q1 group list and eventually in the top 10 journal list in the field. However, this requires sustained efforts and conscious endeavours that give attention to quality submissions through a rigorous review process. This edition of IJAR: volume 9, issue 2, July 2015 includes debates on a wide spectrum of issues, explorations and investigations in various settings. The issue encompasses sixteen papers addressing cities, settlements, and projects in Europe, South East Asia, and the Middle East. Papers involve international collaborations evidenced by joint contributions and come from scholars in universities, academic institutions, and practices in Belgium; Egypt; Greece; Italy; Jordan; Malaysia; Palestine; Qatar; Saudi Arabia; Serbia; Spain; Turkey; and the United Kingdom. In this editorial I briefly outline the key issues presented in these papers, which include topics relevant to social housing, multigenerational dwelling, practice-based research, sustainable design and biomimetic models, learning environments and learning styles, realism and the post modern condition, development and planning, urban identity, contemporary landscapes, and cultural values and traditions

Partial Correctness of a Power Algorithm

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 Białystok, PolandGrzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, 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 Korniłowicz, 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 Korniłowicz. 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 Korniłowicz, 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 Korniłowicz, 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 Korniłowicz, 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 Korniłowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165–173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur Korniłowicz, 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 Świątek, 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 Korniłowicz, 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 Korniłowicz, 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

Analisis Pengaruh Quality, Image, Brand Equity, dan Value terhadap Loyalitas Seller sebagai Salah Satu Partner E-marketplace di Lazada Indonesia

Penelitian ini bertujuan untuk mengetahui pengaruh dari beberapa faktor yaitu quality, image, brand equity dan value terhadap loyalitas seller sebagai salah satu partner e-marketplace di Lazada Indonesia. Sampel diambil dengan menggunakan metode purposive sampling, dengan jumlah sampel sebanyak 82 responden. Teknik pengumpulan data menggunakan kuesioner dan literatur. Metode analisis yang digunakan adalah metode analisis regresi berganda untuk mengetahui pengaruh antara variabel-variabel bebas terhadap variabel terikat. Hasil penelitian ini menunjukkan bahwa; 1). Kualitas e-marketplace tidak berpengaruh positif dan siginifikan terhadap loyalitas seller 2). Citra Perusahaan penyedia e-marketplace berpengaruh positif dan signifikan terhadap loyalitas seller 3). Ekuitas brand Perusahaan e-marketplace berpengaruh positif dan signifikan terhadap loyalitas seller 4). Nilai yang dimiliki oleh Perusahaan e-marketplace berpengaruh positif dan signifikan terhadap loyalitas seller 5). Kualitas Pelayanan, citra Perusahaan, ekuitas brand dan nilai Perusahaan secara bersama-sama berpengaruh positif dan signifikan terhadap loyalitas seller sebagai salah satu partner e-marketplace di Lazada Indonesia. Loyalitas seller sebagai salah satu partner e-marketplace di Lazada Indonesia terbukti dipengaruhi oleh keempat variabel yang diteliti yaitu sebesar 74% dan sisanya 26% dipengaruhi oleh faktor atau variabel-variabel lainnya.Kata Kunci: Quality, Image, Brand Equity, Value, Loyalitas Seller2 This study aims to determine the effect of e-service quality, image, brand equity, and value to seller's loyalty as a partner in Lazada Indonesia e-marketplace. Samples were taken by using purposive sampling method, with the total number of sample is 82 respondents. The technique of collecting data is using questionnaires and literatures. The analytical method that used in this research is multiple regression analysis to determine the effect of independent variables on the dependent variable. The results of this study indicate that; 1). E-service quality does not affect significantly on seller's loyalty. 2). Image has a possitive and significant effect on seller's loyalty. 3). Brand Equity has a possitive and significant effect on seller's loyalty. 4). Value has a possitive and significant effect on seller's loyalty. 5). E-Service quality, value, brand equity, and value jointly has a positive and significant effect on seller's loyalty as a partner in Lazada Indonesia e-marketplace. The seller's loyalty shown to be affected by the independent variables in this study at 74% and 26% is influenced by other factors or variables.Keywords: Quality, Image, Brand Equity, Value, Seller's Loyalty DAFTAR PUSTAKA Arikunto, Suharsimi. 2006. Prosedur Penelitian Suatu Pendekatan Praktik. Jakarta: Rineka Cipta. Aydın Erdal, and Savrul Burcu Kilinç, 2014. The Relationship between Globalization and E-Commerce: Turkish Case, Procedia - Social and Behavioral Sciences 150 1267 – 1276 Bresolles Grégory, Durrieu François, Senecal Sylvain. 2014. A consumer typology based on e-service quality and e-satisfaction. Journal of Retailing and Consumer Services 21, 889–896 Brunn Peter, Jensen Martin, Skovgaard Jakob. 2002. e-Marketplaces: Crafting A Winning Strategy. European Management Journal Vol. 20, No. 3, pp. 286–298 Cunha. 2012. An E-marketplace of Healthcare and Social Care Services: the perceived interest. Procedia Technology 5, 959 – 966 Chi Hsin Kuang, Yeh Huery Ren, Yang Ya Ting. 2009. The Impact of Brand Awareness on Consumer Purchase Intention: The Mediating Effect of Perceived Quality and Brand Loyalty. The Journal of International Management Studies, Volume 4, Number 1 Chien Shu-Hua, Chen Ying-Hueih, Hsu Chin-Yen. 2012. Exploring the impact of trust and relational embeddedness in e-marketplaces: An empirical study in Taiwan. Industrial Marketing Management 41, 460–468 Chircu Alina.M., Mahajan Vijay. 2006. Managing electronic commerce retail transaction costs for customer value. Decision Support Systems 42, 898– 914 D'ambra John, Ramburuth, Prem., & Vatanasakdakul, Savanid. 2010. IT Doesn't Fit! The Influence of Culture on B2B in Thailand. Journal of Global Information Technology Management (Ivy League Publishing). 10-38 Ghozali, Imam. 2006. Aplikasi Analisis Multivariate dengan Sess. Cetakan Keempat. Semarang: Badan Penerbit Universitas Diponogoro ------------------. 2011. Aplikasi Analisis Multivariate dengan Program IBM SPSS19, Badan Penerbit Universitas Diponegoro, Semarang. ------------------. 2005. Aplikasi Analisis Multivariate Dengan Program SPSS. Semarang: UNDIP Goes Paulo, Tu Yanbin, Tung Y.Alex. 2013. Seller heterogeneity in electronic marketplaces: A study of new and experienced sellers in eBay. Decision Support Systems 56, 247–258 Gunasekaran, A., Marri, H. B., McGaughey, R. E., & Nebhwani, M. D. 2002. E-Commerce and its impact on operations management. International Journal of Production Economics, 75,185–197. Hashemi Malayeri, B dan Bastani, F.2000. An introduction to the Internet and the World Wide Web, Part I, Journal of Medical Sciences, TarbiatModarres University, Summer 77, Issue 1, pp. 111. Ho Shu-Chun, and Kauffman Robert.J. 2010. Internet-based selling technology and e-commerce growth: a hybrid growth theory approach with cross-model inference. Inf Technol Manag, 12:409–429 Hong Ilyoo B. 2015. Understanding the consumer's online merchant selection process: The roles of product involvement, perceived risk, and trust expectation. International Journal of Information Management 35, 322–336 Janita M.Soledad, and Miranda F.Javier. 2013. The antecedents of client loyalty in business-to-business (B2B) electronic marketplaces. Industrial Marketing Management 42 814–823 Juntunen Mari, Juntunen Jouni, Juga Jari. 2010. Corporate brand equity and loyalty in B2B markets: A study amonglogistics service purchasers. Macmillan Publishers Ltd. Brand Management Vol. 18, 4/5, 300–311 Malhotra, Naresh, dan Birks, David, 2007. Marketing Research: An Applied Orientation 3rd Edition. London: Practice Hall Nam Janghyeon, Ekinci Yuksel, Whyatt Georgina. 2011. Brand Equity, Brand Loyalty and Consumer Satisfaction. Annals of Tourism Research, Vol. 38, No. 3, pp. 1009–1030 Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL a multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213–233. Pradiani, Theresia. 2014. Pengaruh Trait Competitiveness Terhadap Sales Performance (Studi Kasus di PT Allianz Life Indonesia). Jurnal JIBEKA, volume 8, 55 – 62. Rauyruen Papassapa, Miller Kenneth.E, Groth Markus. 2009. B2B services: linking service loyalty and brand equity, Journal of Service Marketing 23/3 175–186 Rayport, Jeffrey F and Jaworski, Bernard J. 2002. Introduction to E-commerce. Mcgraw Hill Rong Huang and Emine Sarigollu. 2011. How Brand Awareness Relates to Market Outcome, Brand Equity and the Marketing Mix. Journal of Business Research, vol.65, pp.92-99. S. Muylle, A. Basu, 2008. Online support for business processes by electronic intermediaries, Decision Support Systems 45 (4) 845–857. Savrul Mesut, Incekara Ahmet, Sener Sefer. 2014. The Potential of E-Commerce for SMEs in a Globalizing Business Environment, Procedia - Social and Behavioral Sciences 150 35 – 45 Sekaran, Uma, Bougie, Roger, 2010. Research methods for business: a skill building approach. Bandung: Alfabeta Severi Erfan, and Ling Kwek Choon. 2013. The Mediating Effects of Brand Association, Brand Loyalty, Brand Image and Perceived Quality on Brand Equity, Asian Social Science; Vol. 9, No. 3; 2013 Sugiyono. 2002. Metode Penelitian Administrasi. Bandung: CV Alfabeta ------------. 2008. Metode Penelitian Bisnis. Cetakan Keduabelas. Bandung: Alfabeta -----------. 2010. Metode Penelitian Kuantitatif Kualitatif & RND. Bandung: Alfabeta Syuhada Ahmad Anshorimuslim, dan Gambetta Windy. 2013. Online Marketplace for Indonesian Micro Small and Medium Enterprises Based on Social Media. Procedia Technology 11, 446 – 454 Tabachnick BG dan Fidel L.S, 2007. “Using Multivariate Statistic” (Fifth Edition) USA: Pearson Eduction Inc. Umar, Husein. 200. Metodologi Penelitian Untuk Skripsi dan Tesis Bisnis, Jakarta: PT. Gramedia Pustaka. White, A., Daniel, E., Ward, J., & Wilson, H., 2007. The adoption of consortium B2B emarketplaces: An exploratory study. Journal of Strategic Information Systems, 16, 71–103. Wu, Jen-Her., & Hisa, Tzyh-lih. 2004. Analysis of E-commerce innovation and impact: a hypercube model, Electronic Commerce Research and Applications Volume 3, Issue 4, Pages 389–404 Wang Shan, and Archer Norm. 2007. Business-to-business collaboration through electronic marketplaces: An exploratory study. Journal of Purchasing & Supply Management 13 113–126 Zhao Jing, Wang Shan, Huang Wilfred.V. 2008. A study of B2B e-market in China: E-commerce process perspective. Information & Management 45, 242–248 Zhao Kexin, Xia Mu, Shaw Michael.J., Subramaniam Chandrasekar. 2009. The sustainability of B2B e-marketplaces: Ownership structure, market competition, and prior buyer–seller connections. Decision Support Systems 47, 105–114 Zikmund, William G. 2003. Customer Relationship Management: Integrating Marketing Strategy and Information Technology. New Jersey: John Wiley and Sons Zuo Wenming, Huang Qiuping, Fan Chang, Zhang Zhenpeng. 2013. Quality management of B2C e-commerce service based on human factors engineering, Electronic Commerce Research and Applications 12, 309–32

Stevia Rebaudiana, Oligofructose and Isomaltulose as sugar replacers in marshmallows stability and antioxidant properties

[EN] Consumers are increasingly demanding products with natural ingredients and functional properties. The replacement of conventional sugars with recently available sugars or sweeteners could result in the perception of candies as healthier products. Therefore, the objective of this work was to evaluate the influence of isomaltulose, oligofructose and stevia extracts on the physicochemical, mechanical, optical and antioxidant properties as well as the shelf life of marshmallows. A sensory test was carried out in order to evaluate the influence of these ingredients on the acceptance of this product. The instrumental and sensorial textural results indicate that the sucrose and glucose syrup in commercial marshmallows could be replaced by a mixture of isomaltulose, oligofructose and stevia. Adults found the new and the traditional marshmallows to be very similar. However, children only found similarities in terms of the texture. These new marshmallows, besides being more microbiologically stable, have added value due to their antioxidant properties. Practical ApplicationsSociety is becoming increasingly aware of the importance of nutrition in health, and this has a decisive impact on the proposals of the candy sector in terms of innovation and new product development. The main trends of the market are focused on eliminating the unhealthy ingredients in the formulations, such as sugars, and even incorporate active ingredients with functional properties, but without forgetting customer satisfaction. At present, the industry is using both intense and volume artificial sweeteners as conventional sugar substitutes. However, the food industry now has the possibility of using alternative natural sweeteners such as stevia, oligofructose and isomaltulose, with the added value of providing certain healthy benefits. The results of the present study could provide pertinent information to the confectionary industry that wishes to take on the challenge of developing candies with functional ingredients.The authors thank the Universitat Politecnica de Valencia (Spain) (for funding the project PAID 2011-ref: 2012 and the PhD scholarship), and the Generalitat Valenciana (Spain) (for the project GV/2013/029).Periche Santamaría, A.; Castelló Gómez, ML.; Heredia Gutiérrez, AB.; Escriche Roberto, MI. (2016). Stevia Rebaudiana, Oligofructose and Isomaltulose as sugar replacers in marshmallows stability and antioxidant properties. Journal of Food Processing and Preservation. 40:724-732. https://doi.org/10.1111/jfpp.12653S72473240Barba, F. J., Grimi, N., & Vorobiev, E. (2015). Evaluating the potential of cell disruption technologies for green selective extraction of antioxidant compounds from Stevia rebaudiana Bertoni leaves. Journal of Food Engineering, 149, 222-228. doi:10.1016/j.jfoodeng.2014.10.028Barba, F. J., Criado, M. N., Belda-Galbis, C. M., Esteve, M. J., & Rodrigo, D. (2014). Stevia rebaudiana Bertoni as a natural antioxidant/antimicrobial for high pressure processed fruit extract: Processing parameter optimization. Food Chemistry, 148, 261-267. doi:10.1016/j.foodchem.2013.10.048Belda-Galbis, C. M., Pina-Pérez, M. C., Espinosa, J., Marco-Celdrán, A., Martínez, A., & Rodrigo, D. (2014). Use of the modified Gompertz equation to assess the Stevia rebaudiana Bertoni antilisterial kinetics. Food Microbiology, 38, 56-61. doi:10.1016/j.fm.2013.08.009Campbell, G. (1999). Creation and characterisation of aerated food products. Trends in Food Science & Technology, 10(9), 283-296. doi:10.1016/s0924-2244(00)00008-xCarbonell-Capella, J. M., Barba, F. J., Esteve, M. J., & Frígola, A. (2013). High pressure processing of fruit juice mixture sweetened with Stevia rebaudiana Bertoni: Optimal retention of physical and nutritional quality. Innovative Food Science & Emerging Technologies, 18, 48-56. doi:10.1016/j.ifset.2013.01.011Chatsudthipong, V., & Muanprasat, C. (2009). Stevioside and related compounds: Therapeutic benefits beyond sweetness. Pharmacology & Therapeutics, 121(1), 41-54. doi:10.1016/j.pharmthera.2008.09.007(2011). Revised exposure assessment for steviol glycosides for the proposed uses as a food additive. EFSA Journal, 9(1), 1972. doi:10.2903/j.efsa.2011.1972Franck, A. (2002). Technological functionality of inulin and oligofructose. British Journal of Nutrition, 87(S2), S287-S291. doi:10.1079/bjn/2002550Gong, Q., & Bell, L. N. (2013). Degradation kinetics of rebaudioside A in various buffer solutions. International Journal of Food Science & Technology, 48(12), 2500-2505. doi:10.1111/ijfs.12241Kawai, K., Yoshikawa, H., Murayama, Y., Okuda, Y., & Yamashita, K. (1989). Usefulness of Palatinose as a Caloric Sweetener for Diabetic Patients. Hormone and Metabolic Research, 21(06), 338-340. doi:10.1055/s-2007-1009230ISO 5492 2008 Sensory analysis. Vocabulary. International Organization for StandardizationISO 8589 2007 Sensory analysis. General guidance for the design of test roomsKALETUNC, G., NORMAND, M. D., JOHNSON, E. A., & PELEG, M. (1992). INSTRUMENTAL DETERMINATION OF ELASTICITY OF MARSHMALLOW. Journal of Texture Studies, 23(1), 47-56. doi:10.1111/j.1745-4603.1992.tb00510.xLemus-Mondaca, R., Vega-Gálvez, A., Zura-Bravo, L., & Ah-Hen, K. (2012). Stevia rebaudiana Bertoni, source of a high-potency natural sweetener: A comprehensive review on the biochemical, nutritional and functional aspects. Food Chemistry, 132(3), 1121-1132. doi:10.1016/j.foodchem.2011.11.140Lina, B. A. R., Jonker, D., & Kozianowski, G. (2002). Isomaltulose (Palatinose®): a review of biological and toxicological studies. Food and Chemical Toxicology, 40(10), 1375-1381. doi:10.1016/s0278-6915(02)00105-9Muanda, F. N., Soulimani, R., Diop, B., & Dicko, A. (2011). Study on chemical composition and biological activities of essential oil and extracts from Stevia rebaudiana Bertoni leaves. LWT - Food Science and Technology, 44(9), 1865-1872. doi:10.1016/j.lwt.2010.12.002Periche, A., Koutsidis, G., & Escriche, I. (2013). Composition of Antioxidants and Amino Acids in Stevia Leaf Infusions. Plant Foods for Human Nutrition, 69(1), 1-7. doi:10.1007/s11130-013-0398-1Periche, A., Heredia, A., Escriche, I., Andrés, A., & Castelló, M. L. (2015). Potential use of isomaltulose to produce healthier marshmallows. LWT - Food Science and Technology, 62(1), 605-612. doi:10.1016/j.lwt.2014.12.024Sanz, T., Salvador, A., Baixauli, R., & Fiszman, S. M. (2009). Evaluation of four types of resistant starch in muffins. II. Effects in texture, colour and consumer response. European Food Research and Technology, 229(2), 197-204. doi:10.1007/s00217-009-1040-1Shahidi, F., Liyana-Pathirana, C. M., & Wall, D. S. (2006). Antioxidant activity of white and black sesame seeds and their hull fractions. Food Chemistry, 99(3), 478-483. doi:10.1016/j.foodchem.2005.08.009Shukla, S., Mehta, A., Mehta, P., & Bajpai, V. K. (2012). Antioxidant ability and total phenolic content of aqueous leaf extract of Stevia rebaudiana Bert. Experimental and Toxicologic Pathology, 64(7-8), 807-811. doi:10.1016/j.etp.2011.02.002Sivaram, L., & Mukundan, U. (2003). In vitro culture studies on Stevia rebaudiana. In Vitro Cellular & Developmental Biology - Plant, 39(5), 520-523. doi:10.1079/ivp2003438Struck, S., Jaros, D., Brennan, C. S., & Rohm, H. (2014). Sugar replacement in sweetened bakery goods. International Journal of Food Science & Technology, 49(9), 1963-1976. doi:10.1111/ijfs.12617Tadhani, M. B., Patel, V. H., & Subhash, R. (2007). In vitro antioxidant activities of Stevia rebaudiana leaves and callus. Journal of Food Composition and Analysis, 20(3-4), 323-329. doi:10.1016/j.jfca.2006.08.004Tan, J. M., & Lim, M. H. (2008). Effects of gelatine type and concentration on the shelf-life stability and quality of marshmallows. International Journal of Food Science & Technology, 43(9), 1699-1704. doi:10.1111/j.1365-2621.2008.01756.xVarzakas, T., & Labropoulos, A. (2012). Other Sweeteners. Sweeteners, 175-208. doi:10.1201/b12065-8Vasiljevic, T., & Varzakas, T. (2012). Bulking and Fat-Replacing Agents. Sweeteners, 395-418. doi:10.1201/b12065-1

Mother's Perspective About Using the Gadget Safeness for Children

The rapid development of technology makes it easier for mothers to provide stimulation related to growth and development using gadgets. However, parental knowledge is needed about the safe limits of using a gadget in early childhood. This study aims to determine the perspective and behavior of mothers about the use of gadgets in toddlers. The method used is quantitative research with a cross-sectional approach. The participants of this study were thirty-one mothers who have early childhood and who are empowering family welfare. The inclusion criteria were mothers who agreed to be respondents, the exclusion criteria for mothers who did not have gadgets. This study uses a questionnaire measurement instrument for data collection. Data analysis was performed univariate and bivariate using the chi-square test. The results of the study concluded that the mother's knowledge regarding the safety of using a gadget was still lacking, with a value of around 54.8%, while the mother's behavior related to the same thing was better, which was around 58.1%. The relationship test shows that there is a strong enough relationship between maternal knowledge and maternal behavior in introducing or using gadgets in toddlers.  Keywords: Early Childhood, Mother Perspective, Gadget Safeness  References Appel, M. (2012). Are heavy users of computer games and social media more computer literate? Computers and Education, 59(4), 1339–1349. https://doi.org/10.1016/j.compedu.2012.06.004 Bandura, A. (1977). Social learning theory. Prentice-Hall. Cingel, D. P., & Krcmar, M. (2013). Predicting Media Use in Very Young Children: The Role of Demographics and Parent Attitudes. Communication Studies, 64(4), 374–394. https://doi.org/10.1080/10510974.2013.770408 Connell, S. L., Lauricella, A. R., & Wartella, E. (2015). Parental Co-Use of Media Technology with their Young Children in the USA. Journal OfChildren and Media, 9(1), 5–21. https://doi.org/10.1080/17482798.2015.997440 Haines, J., O’Brien, A., McDonald, J., Goldman, R. E., Evans-Schmidt, M., Price, S., King, S., Sherry, B., & Taveras, E. M. (2013). Television Viewing and Televisions in Bedrooms: Perceptions of Racial/Ethnic Minority Parents of Young Children. Journal of Child and Family Studies, 22(6), 749–756. https://doi.org/10.1007/s10826-012-9629-6 Jones, I., & Park, Y. (2015). Virtual worlds: Young children using the internet. Young children and families in the information age. Educating the young child (Advances in theory and research, implications for practice) (I. K. Heider & J. M. Renck (eds.); Volume 10). Springer. Lauricella, A. R., Wartella, E., & Rideout, V. J. (2015). Young children’s screen time: The complex role of parent and child factors. Journal of Applied Developmental Psychology, 36, 11–17. https://doi.org/10.1016/j.appdev.2014.12.001 Livingstone, S, Görzig, A., & Ólafsson, K. (2011). Disadvantaged children and online risk. http://eprints.lse.ac.uk/39385/ Livingstone, Sonia, Mascheroni, G., Dreier, M., Chaudron, S., & Lagae, K. (2015). How parents of young children manage digital devices at home: The role of income, education and parental style (Issue September). Livingstone, Sonia, Ólafsson, K., Helsper, E. J., Lupiáñez-Villanueva, F., Veltri, G. A., & Folkvord, F. (2017). Maximizing Opportunities and Minimizing Risks for Children Online: The Role of Digital Skills in Emerging Strategies of Parental Mediation. Journal of Communication, 67(1), 82–105. https://doi.org/10.1111/jcom.12277 M, S. (2017). The Impact of using Gadgets on Children. Journal of Depression and Anxiety, 07(01), 1–3. https://doi.org/10.4172/2167-1044.1000296 Marsh, J., Hannon, P., Lewis, M., & Ritchie, L. (2017). Young children’s initiation into family literacy practices in the digital age. Journal of Early Childhood Research, 15(1), 47–60. https://doi.org/10.1177/1476718X15582095 Mifsud, C. L., & Petrova, R. (2017). Young Children (0-8) and Digital Technology. In JRC Science and Policies Reports. Nevski, E., & Siibak, A. (2016). The role of parents and parental mediation on 0–3-year olds’ digital play with smart devices: Estonian parents’ attitudes and practices. Early Years, 36(3), 227–241. https://doi.org/10.1080/09575146.2016.1161601 Nikken, P. (2017). Implications of low or high media use among parents for young children’s media use. Cyberpsychology, 11(3 Special Issue). https://doi.org/10.5817/CP2017-3-1 Nikken, P., & de Haan, J. (2015). Guiding young children’s internet use at home: Problems that parents experience in their parental mediation and the need for parenting support. Cyberpsychology, 9(1). https://doi.org/10.5817/CP2015-1-3 Piotrowski, J. (2017). Media exposure during infancy and early childhood: The effect of content and context on learning and development. In I. R. Barr & D. Linebarger (Eds.), The parental media mediation context of young children’s media use.(pp. 205–219). Springer International Publishing. Plowman, L., Stevenson, O., Stephen, C., & McPake, J. (2012). Preschool children’s learning with technology at home. Computers and Education, 59(1), 30–37. https://doi.org/10.1016/j.compedu.2011.11.014 Rasmussen, E. E., Shafer, A., Colwell, M. J., White, S., Punyanunt-Carter, N., Densley, R. L., & Wright, H. (2016). Relation between active mediation, exposure to Daniel Tiger’s Neighborhood, and US preschoolers’ social and emotional development. Journal of Children and Media, 10(4), 443–461. https://doi.org/10.1080/17482798.2016.1203806 Smahelova, M., Juhová, D., Cermak, I., & Smahel, D. (2017). Mediation of young children’s digital technology use: The parents’ perspective. Cyberpsychology, 11(3 Special Issue). https://doi.org/10.5817/CP2017-3-4 Troseth, G. L., Strouse, G. A., & Russo Johnson, C. E. (2017). Early Digital Literacy: Learning to Watch, Watching to Learn. In Cognitive Development in Digital Contexts. Elsevier Inc. https://doi.org/10.1016/B978-0-12-809481-5.00002-X Vaala, S. E. (2014). The Nature and Predictive Value of Mothers’ Beliefs Regarding Infants’ and Toddlers’ TV/Video Viewing: Applying the Integrative Model of Behavioral Prediction. Media Psychology, 17(3), 282–310. https://doi.org/10.1080/15213269.2013.872995 Zaman, B., & Mifsud, C. L. (2017). Editorial: Young children’s use of digital media and parental mediation. Cyberpsychology, 11(3 Special Issue), 9. https://doi.org/10.5817/CP2017-3-x

On potential cognitive abilities in the machine kingdom

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.Hernández-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., Hernández-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.Hernández-Orallo, J. (2000a). Beyond the Turing Test. Journal of Logic, Language & Information, 9(4), 447–466.Hernández-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.Hernández-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.Hernández-Orallo, J., & Dowe, D. L. (2010). Measuring universal intelligence: Towards an anytime intelligence test. Artificial Intelligence, 174(18), 1508–1539.Hernández-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 .Hernández-Orallo J., Dowe D. L., España-Cubillo S., Hernández-Lloreda M. V., & Insa-Cabrera J. (2011). On more realistic environment distributions for defining, evaluating and developing intelligence. In: J. Schmidhuber, K. R. Thórisson, & M. Looks (Eds.), Artificial general intelligence 2011, volume 6830, LNAI series, pp. 82–91. New York: Springer.Hernández-Orallo, J., Dowe, D. L., & Hernández-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.Hernández-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.Hernández-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., Hernández-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., Hernández-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., Hernández-Lloreda, M. V., & Hernández-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., & Hernández-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., Vitányi, 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