Utilizing a Restricted Access e-Learning Platform for Reform, Equity, and Self-development in Correctional Facilities
Abstract
Doi: 10.28991/ESJ-2022-SIED-017
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Fokides, E. (2017). Pre-service teachers’ intention to use MUVES as practitioners - A structural equation modeling approach. Journal of Information Technology Education: Research, 16(1), 47–68. doi:10.28945/3645.
Serdyukov, P. (2017). Innovation in education: what works, what doesn’t, and what to do about it? Journal of Research in Innovative Teaching & Learning, 10(1), 4–33. doi:10.1108/jrit-10-2016-0007.
Antonopoulou, H., Halkiopoulos, C., Barlou, O., & Beligiannis, G. N. (2020). Leadership types and digital leadership in higher education: Behavioural data analysis from University of Patras in Greece. International Journal of Learning, Teaching and Educational Research, 19(4), 110–129. doi:10.26803/ijlter.19.4.8.
Antonopoulou, H., Halkiopoulos, C., Barlou, O., & Beligiannis, G. N. (2021). Transformational leadership and digital skills in higher education institutes: During the covid-19 pandemic. Emerging Science Journal, 5(1), 1–15. doi:10.28991/esj-2021-01252.
Rajabalee, B. Y., Santally, M. I., & Rennie, F. (2020). A study of the relationship between students’ engagement and their academic performances in an eLearning environment. E-Learning and Digital Media, 17(1), 1–20. doi:10.1177/2042753019882567.
Antonopoulou, H., Halkiopoulos, C., Barlou, O., & Beligiannis, G. N. (2021). Associations between traditional and digital leadership in academic environment: During the COVID-19 pandemic. Emerging Science Journal, 5(4), 405–428. doi:10.28991/esj-2021-01286.
Antonopoulou, H., Mamalougou, V., & Theodorakopoulos, L. (2022). The Role of Economic Policy Uncertainty in Predicting Stock Return Volatility in the Banking Industry: A Big Data Analysis. Emerging Science Journal, 6(3), 569–577. doi:10.28991/ESJ-2022-06-03-011.
Nikolaidis, S., Nath, S., Procaccia, A. D., & Srinivasa, S. (2017). Game-Theoretic Modeling of Human Adaptation in Human-Robot Collaboration. Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. doi:10.1145/2909824.3020253.
UNESCO (2017). Working Group on Education: digital skills for life and work. Broadband Commission for Sustainable Development, UNESCO, Paris, France.
Al-Shabandar, R., Hussain, A. J., Liatsis, P., & Keight, R. (2018). Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach. IEEE Access, 6, 73669–73685. doi:10.1109/ACCESS.2018.2876755.
Al-Rahmi, W., Aldraiweesh, A., Yahaya, N., Bin Kamin, Y., & Zeki, A. M. (2019). Massive Open Online Courses (MOOCs): Data on higher education. Data in Brief, 22, 118–125. doi:10.1016/j.dib.2018.11.139.
Castaño-Muñoz, J., Kalz, M., Kreijns, K., & Punie, Y. (2018). Who is taking MOOCs for teachers’ professional development on the use of ICT? A cross-sectional study from Spain. Technology, Pedagogy and Education, 27(5), 607–624. doi:10.1080/1475939X.2018.1528997.
Bogdanova, D., & Snoeck, M. (2018). Using MOOC technology and formative assessment in a conceptual modelling course. Proceedings of the 21st ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings. doi:10.1145/3270112.3270120.
Giannoulis, A., Theodorakopoulos, L., & Antonopoulou, H. (2022). Learning in second-chance schools during COVID-19 Case study: Legal framework and distance learning platforms in Greek prisons. (2022). European Journal of Training and Development Studies, 9(1), 13–19. doi:10.37745/ejtds.14/vol9no1pp.13-19.
Brands, S. (2000). Rethinking public key infrastructures and digital certificates: building in privacy. Mit Press, Cambridge, Massachusetts, United States. doi:10.7551/mitpress/5931.001.0001.
Camenisch, J., Lysyanskaya, A. (2001). An Efficient System for Non-transferable Anonymous Credentials with Optional Anonymity Revocation. Advances in Cryptology — EUROCRYPT 2001. EUROCRYPT 2001, Lecture Notes in Computer Science, 2045, Springer, Berlin, Germany. doi:10.1007/3-540-44987-6_7.
Camenisch, J., & Groß, T. (2012). Efficient Attributes for Anonymous Credentials. ACM Transactions on Information and System Security, 15(1), 1–30. doi:10.1145/2133375.2133379.
Rannenberg, K., Camenisch, J., & Sabouri, A. (Eds.). (2015). Attribute-based Credentials for Trust. Springer, Cham, Switzerland. doi:10.1007/978-3-319-14439-9.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. doi:10.2307/249008.
Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. doi:10.1111/j.1540-5915.2008.00192.x.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall, Hoboken, United States.
Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. Action Control, 11–39, Springer, New York, united States. 10.1007/978-3-642-69746-3_2.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. doi:10.2307/30036540.
Esteban-Millat, I., Martínez-López, F. J., Pujol-Jover, M., Gázquez-Abad, J. C., & Alegret, A. (2018). An extension of the technology acceptance model for online learning environments. Interactive Learning Environments, 26(7), 895–910. doi:10.1080/10494820.2017.1421560.
Gkintoni, E., Meintani, P. M., & Dimakos, I. (2021). Neurocognitive And Emotional Parameters In Learning And Educational Process. ICERI Proceedings. doi:10.21125/iceri.2021.0659.
Tan, P. J. B., & Hsu, M.-H. (2018). Designing a System for English Evaluation and Teaching Devices: A PZB and TAM Model Analysis. EURASIA Journal of Mathematics, Science and Technology Education, 14(6). doi:10.29333/ejmste/86467.
Tarhini, A., Hone, K., & Liu, X. (2013). Factors Affecting Students’ Acceptance of e-Learning Environments in Developing Countries:A Structural Equation Modeling Approach. International Journal of Information and Education Technology, 3, 54–59. doi:10.7763/ijiet.2013.v3.233.
Gkintoni, E., Halkiopoulos, C., & Antonopoulou, H. (2022). Neuroleadership as an Asset in Educational Settings: An Overview. Emerging Science Journal, 6(4), 893–904. doi:10.28991/ESJ-2022-06-04-016.
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. doi:10.1016/j.chb.2016.10.028.
Chao, C.-M. (2019). Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Frontiers in Psychology, 10. doi:10.3389/fpsyg.2019.01652.
Fathema, N., Shannon, D., & Ross, M. (2015). Expanding The Technology Acceptance Model (TAM) to Examine Faculty Use of Learning Management Systems (LMSs) In Higher Education Institutions. Journal of Online Learning and Teaching , 11(2), 210–233.
Hu, P.Jh., Hui, W. (2011). Is Technology-Mediated Learning Made Equal for All? Examining the Influences of Gender and Learning Style. Technology Acceptance in Education. SensePublishers, Rotterdam, Netherlands. doi:10.1007/978-94-6091-487-4_6.
Moghavvemi, S. (2015). Impact of Perceived Self-Efficacy and Capability to Use IT Innovation on Individual Use Behaviour. SSRN Electronic Journal. doi:10.2139/ssrn.2561739.
Antonopoulou, H., Halkiopoulos, C., Gkintoni, E., & Katsimpelis, A. (2022). Application of Gamification Tools for Identification of Neurocognitive and Social Function in Distance Learning Education. International Journal of Learning, Teaching and Educational Research, 21(5), 367–400. doi:10.26803/ijlter.21.5.19.
Giannakos, M. N. (2013). Enjoy and learn with educational games: Examining factors affecting learning performance. Computers and Education, 68, 429–439. doi:10.1016/j.compedu.2013.06.005.
Wang, H., & Sun, C. T. (2011). Game reward systems: Gaming experiences and social meanings. Proceedings of DiGRA 2011 Conference: Think Design Play, 14-17, 2011, Hilversum, Netherlands.
Gkintoni, E., Boutsinas, B., & Kourkoutas, E. (2022). Developmental Trauma And Neurocognition In Young Adults: A Systematic Review. EDULEARN22 Proceedings. doi:10.21125/edulearn.2022.1332.
Gkintoni, E., Halkiopoulos, C., Antonopoulou, H., & Petropoulos, N. (2021). Gamification of Neuropsychological Tools as a Multi-Sensory Approach to Education. Stroop’s Paradigm. Technium Romanian Journal of Applied Sciences and Technology, 3(8), 92–102. doi:10.47577/technium.v3i8.4798.
Stamatiou, Y.C, Benenson, Z., Girard, A., Krontiris, I, Liagkou, V., Pyrgelis, A., Tesfay, W. (2015). Course Evaluation in Higher Education: the Patras Pilot of ABC4Trust. In: Rannenberg, K., Camenisch, J., Sabouri, A. (eds) Attribute-based Credentials for Trust. Springer, Cham, Switzerland. doi:10.1007/978-3-319-14439-9_7.
Gkintoni, E., & Dimakos, I. (2022). An Overview Of Cognitive Neuroscience In Education. EDULEARN22 Proceedings, Palma, Spain. doi:10.21125/edulearn.2022.1343.
Antonopoulou, H., Giannoulis, A., Theodorakopoulos, L., & Halkiopoulos, C. (2022). Socio-Cognitive Awareness of Inmates through an Encrypted Innovative Educational Platform. International Journal of Learning, Teaching and Educational Research, 21(9), 52–75. doi:10.26803/ijlter.21.9.4.
DOI: 10.28991/ESJ-2022-SIED-017
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Copyright (c) 2022 Yannis C. Stamatiou, Constantinos Halkiopoulos, Athanasios Giannoulis, Hera Antonopoulou