Exploring Students’ Perceptions of their Experiences in a Social Justice Living–Learning Community

Contemporary higher education leaders continue to deem the development of civic-minded graduates as among the primary goals of postsecondary education (Astin, 1996Astin, H. S. (1996). Leadership for social change. About Campus, 1(3), 4–10. doi:10.1002/abc.v1.3[Crossref] , [Google Scholar]; Cress, Burack, Giles, Elkins, & Stevens, 2010Cress, C., Burack, C., Giles, D. E., Elkins, J. E., & Stevens, M. C. (2010). A promising connection: Increasing college access and success through civic engagement. Boston, MA: Campus Compact. [Google Scholar]; Hurtado, Ruiz, & Whang, 2012Hurtado, S., Ruiz, A., & Whang, H. (2012). Assessing student social responsibility and civic learning. Paper presented at the 2012 Annual Forum of the Association for Institutional Research, New Orleans, Louisiana. [Google Scholar]). Today’s undergraduates are poised to engage with their communities in numbers greater than their predecessors in previous generations, believing it is their responsibility to make society better (Kiesa et al., 2007Kiesa, A., Orlowski, A. P., Levine, P., Both, D., Kirby, E. H., Lopez, M. H., & Marcelo, K. B. (2007). Millennials talk politics: A study of college student political engagement. New York, NY: The Center for Information & Research on Civic Learning & Engagement. [Google Scholar]). In 2012, more than two-thirds of postsecondary students reported participation in community service over the past year, despite their overwhelming disillusionment with the United States government and social institutions (Levine & Dean, 2012Levine, A., & Dean, D. R. (2012). Generation on a tightrope: A portrait of today’s college student. San Francisco, CA: Wiley. [Google Scholar]) Civic engagement lacks a common definition in the literature (Jacoby, 2009Jacoby, B. (Ed.). (2009). Civic engagement in higher education: Concepts and practices. San Francisco, CA: Jossey-Bass. [Google Scholar]), however it typically includes involvement in the community with the purpose of “enhancing students’ understanding of civic life” (Cress et al., 2010Cress, C., Burack, C., Giles, D. E., Elkins, J. E., & Stevens, M. C. (2010). A promising connection: Increasing college access and success through civic engagement. Boston, MA: Campus Compact. [Google Scholar], p. 4). A growing body of research raised concerns with community service, service-learning, and other forms of civic engagement as reinforcing stereotypes (Dooley & Burant, 2015Dooley, J. C., & Burant, T. J. (2015). Lessons from pre-service teachers: Under the surface of service learning. In O. Delano-Oriaran, M. Penick-Parks, & S. Fondrie (Eds.), Service-learning and civic engagement: A sourcebook (pp. 325–332). Thousand Oaks, CA: SAGE Publications.[Crossref] , [Google Scholar]). These studies urged greater care when designing community involvement opportunities, including attention to students’ development and previous experience, meaningful curricular connections, and adequate contextualization and reflection (Dooley & Burant, 2015Dooley, J. C., & Burant, T. J. (2015). Lessons from pre-service teachers: Under the surface of service learning. In O. Delano-Oriaran, M. Penick-Parks, & S. Fondrie (Eds.), Service-learning and civic engagement: A sourcebook (pp. 325–332). Thousand Oaks, CA: SAGE Publications.[Crossref] , [Google Scholar]). Some campuses have linked social justice to civic engagement to advance students’ knowledge about inequity, thus moving them away from a savior orientation (Dooley & Burant, 2015Dooley, J. C., & Burant, T. J. (2015). Lessons from pre-service teachers: Under the surface of service learning. In O. Delano-Oriaran, M. Penick-Parks, & S. Fondrie (Eds.), Service-learning and civic engagement: A sourcebook (pp. 325–332). Thousand Oaks, CA: SAGE Publications.[Crossref] , [Google Scholar]) and deepening their understanding of the experience (Prentice, 2007Prentice, M. (2007). Service-learning and civic engagement. Academic Questions, 20(2), 135–145. doi:10.1007/s12129-007-9005-y[Crossref] , [Google Scholar]). Although conceptualized in varying ways, for this article social justice is defined as work toward ending the system of oppression giving certain social groups greater privilege and power over other groups (Broido, 2000Broido, E. M. (2000). The development of social justice allies during college: A phenomenological investigation. Journal of College Student Development, 41(1), 3–18.[Web of Science ®] , [Google Scholar]). When coupled, the terms civic engagement and social justice often indicate the educators’ desire to situate students in their broader communities and increase their awareness of social inequity, which may inspire them to work for social change at the individual, cultural, and institutional levels (Boyle-Baise & Langford, 2004Boyle-Baise, M., & Langford, J. (2004). There are children here: Service learning for social justice. Equity & Excellence in Education, 37(1), 55–66. doi:10.1080/10665680490422115[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Living–learning communities (LLCs) are increasingly utilized to deepen and cohere students’ collegiate experiences (Matthews, Smith, & MacGregor, 2012Matthews, R. S., Smith, B. L., & MacGregor, J. (2012). The evolution of learning communities: A retrospective. In K. Buch & K. E. Barron (Eds.), New directions for teaching and learning: No. 132. Discipline centered learning communities (pp. 99–111). San Francisco, CA: Jossey-Bass.[Crossref] , [Google Scholar]). Although variation exists in thematic and organizational type, these communities typically group students together in a residence hall, offer a shared academic experience, and provide co-curricular activities related to a theme (Inkelas & Soldner, 2011Inkelas, K. K., & Soldner, M. (2011). Undergraduate living–learning programs and student outcomes. Higher Education: Handbook of Theory and Research, 26, 1–55.[Crossref] , [Google Scholar]). Social justice LLCs, which focus on increasing students’ awareness of social inequity and providing them with opportunities to work for social change, are often found on college campuses (Inkelas, 2007Associates; Inkelas, K. K. (2007). National study of living–learning programs: 2007 report of findings. College Park, MD: Authors. [Google Scholar]). Yet little formal research has been done that explores the impact of these communities on students. Thus, the purpose of this study was to explore students’ experiences throughout their time in a social justice-focused LLC (hereafter referred by the pseudonym SJLLC) and one year after participation, focusing on how students described their participation in SJLLC and what aspects of the LLC had a lasting impression on them

The Development of Blended Learning Theories of Learning Course for Educational Technology Student in FIP UNY

Education is intended to develop students’ potential ability to respond the emergent local, national, and global phenomenon. However, today’s disruption era has forced educational institutions to better prepare the students in facing the global dynamics. Thus, Educational Technology Department in Faculty of Ilmu Pendidikan UNY (State University of Yogyakarta) attempts to facilitate the students with various abilities to accommodate the needs above. Therefore, this research is aimed to develop Blended Learning learning model which is implemented in Teori Belajar dan Pembelajaran (Learning and Instruction Theory) course. This research adopts procedure of Borg and Gall (1983), learning system design model of C. M. Reigeluth, and combined with E. L. Criswell & Luther model, by; a) conducting preliminary research, b) devising plans, c) developing prototype model, d) testing materials and model experts followed by revisions, e) running user tests, and f) carrying out field experiment. Research produces Blended Learning learning model in Teori Belajar dan Pembelajaran course for undergraduates of Educational TechnologyDepartmentinFacultyofIlmuPendidikanUNYemploying besmart version 2 e-learning owned by UNY. To conclude, Blended Learning has proven feasible to be executed successfully, both from materials and learning media point of view as well as its convenience when used by students.     Keywords: learning model; Blended Learning; Learning and Instruction Theory course

Representing adaptive and adaptable Units of Learning:How to model personalized eLearning in IMS Learning Design

Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.In this chapter we examine how to represent adaptive and adaptable Units of Learning with IMS Learning Design in order to promote automation and interoperability. Based on a literature study, a distinction is drawn between eight types of adaptation that can be classified in three groups: a) the main group, with interfaced-base, learning-flow and content-base; b) interactive problem solving support, adaptive information filtering, adaptive user grouping; and c) adaptive evaluation and changes on-the-fly. Several sources of information are used in adaptation: user, teacher and set of rules. In this paper, we focus on the core group a). Taking the various possible inputs to an eLearning process, we analyze how to model personalized learning scenarios related to these inputs explaining how these can be represented in IMS Learning Design

Declarative Learning: Cognition without Primitives

Declarative learning by experience is a foundation cognitive c^ability, and w e argue that, over and above the normal processes of declarative learning, the ability for truly novel learning is the critical capability which bootstraps human cognition. Next w e assert that none of the established models of machine learning and no established architecture for cognition have adequate declarative learning capabilities, in that all depend for their success on some pre-characterisation of the learning domain in terms of state space or pre-existing primitives geared to the domain. Finally we describe briefly the Contextual Memory System, which was designed explicitly to sup{>ort all five declarative learning capabilities. The C M S underlies the Maths Understander machine learning system which 'reads' mathematics texts from scratch, assimilating mathematics concepts, and using them not only to check proofs but also to solve problems

How to improve students’ experience in blending learning? Evidence from the perceptions of students in a Postgraduate Master’s Degree

[EN] This paper examines the perceptions of a group of students of a Postgraduate Master’s Degree in Cosmetics Industry at the Universitat de València, delivered with a blended learning modality, in relation to their experience in face-to-face learning and differentiating between those with or without a previous background in a remote online learning environment, with the added purpose of identifying strategies to enhance that experience, while offering further evidence for scholars, educators and institutions in this field. To this end, a survey with open questions devised ad hoc leaning on our literature review was submitted to a group of 114 students of the Master’s Degree in the period 2017-2020. Students were enquired about the pros and cons of their blended learning experience in relation to the traditional face-to-face learning, and which modality they would choose next time if both were offered, only considering the achievement, experience and satisfaction, regardless of the price. 77 students of our initial sample participated in the questionnaire, 38 of them without previous experience in blended or distance learning. The results show a certain predilection for face-to-face learning, especially in the group of newbies in blended or distance learning. They highlight how they miss a closer interaction with their peers and professors and the difficulties to assimilate certain content, while appraising the flexibility, autonomy, and the self-pace of the blended learning modality. Correspondingly, students with experience in remote online education settings generally show a better predisposal and find fewer disadvantages in blended learning. This suggests that the factor of experience and adaptation to new tools and methods improves student perception and confidence and shapes their preferences, with a foreseeable growing acceptance of blended learning in the future. Finally, the outcome allows us to define a series of strategies to improve the achievement, experience, and satisfaction of students in this learning context.Garcia-Ortega, B.; Galan-Cubillo, J. (2021). How to improve students’ experience in blending learning? Evidence from the perceptions of students in a Postgraduate Master’s Degree. WPOM-Working Papers on Operations Management. 12(2):1-15. https://doi.org/10.4995/wpom.15677OJS115122Al-Khanjari, Z. A. S. (2018). Applying online learning in software engineering education. In Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications (pp. 217-231). IGI Global. https://doi.org/10.4018/978-1-5225-3923-0.ch010Angeli, C., Valanides, N., & Bonk, C. J. (2003). Communication in a web‐based conferencing system: the quality of computer‐mediated interactions. British Journal of Educational Technology, 34(1), 31-43. https://doi.org/10.1111/1467-8535.00302Arroyo-Barrigüete, J. L., López-Sánchez, J. I., Minguela-Rata, B., & Rodriguez-Duarte, A. (2019). Use patterns of educational videos: a quantitative study among university students. WPOM-Working Papers on Operations Management, 10(2), 1-19. https://doi.org/10.4995/wpom.v10i2.12625Bonk, C. J., & Graham, C. R. (2012). The handbook of blended learning: Global perspectives, local designs. John Wiley & Sons.Clark, T., & Barbour, M. K. (2015). Online, Blended, and Distance Education: Building Successful School Programs.Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5-22. https://doi.org/10.1177/0047239520934018Garcia-Ortega, B., & Galan-Cubillo, J., (2021). Combining teamwork, coaching and mentoring as an innovative mix for self-aware and motivational learning. Imlementation case in teamwork sessions in the context of practices in a bachelor's degree. 15th Annual International Technology, Educationa and Development Conference. Valencia. Spain. https://doi.org/10.21125/inted.2021.2219Garrison, D. R., & Vaughan, N. D. (2008). Blended learning in higher education: Framework, principles, and guidelines. John Wiley & Sons. https://doi.org/10.1002/9781118269558Ginns, P., & Ellis, R. A. (2009). Evaluating the quality of e‐learning at the degree level in the student experience of blended learning. British Journal of Educational Technology, 40(4), 652-663. https://doi.org/10.1111/j.1467-8535.2008.00861.xGómez, W. A. R. (2014). Preguntas abiertas en encuestas ¿cómo realizar su análisis?. Comunicaciones en estadística, 7(2). https://doi.org/10.15332/s2027-3355.2014.0002.02Grasso, L. (2006). Encuestas. Elementos para su diseño y análisis. Editorial Brujas.Gros, B., & García-Peñalvo, F. J. (2016). Future trends in the design strategies and technological affordances of e-learning. Springer. https://doi.org/10.1007/978-3-319-17727-4_67-1Halverson, L. R., & Graham, C. R. (2019). Learner engagement in blended learning environments: A conceptual framework. Online Learning, 23(2), 145-178. https://doi.org/10.24059/olj.v23i2.1481Hong, J. C., Tai, K. H., Hwang, M. Y., Kuo, Y. C., & Chen, J. S. (2017). Internet cognitive failure relevant to users' satisfaction with content and interface design to reflect continuance intention to use a government e-learning system. Computers in Human Behavior, 66, 353-362. https://doi.org/10.1016/j.chb.2016.08.044López-Pérez, M. V., Pérez-López, M. C., & Rodríguez-Ariza, L. (2011). Blended learning in higher education: Students' perceptions and their relation to outcomes. Computers & education, 56(3), 818-826. https://doi.org/10.1016/j.compedu.2010.10.023Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3), 1-47. https://doi.org/10.1177/016146811311500307McGEE, E., & Poojary, P. (2020). Exploring Blended Learning Relationships in Higher Education Using a Systems-based Framework. Turkish Online Journal of Distance Education, 21(4), 1-13. https://doi.org/10.17718/tojde.803343Kemp, N. (2020). University students' perceived effort and learning in face-to-face and online classes. Journal of Applied Learning and Teaching, 3(1), 69-77. https://doi.org/10.37074/jalt.2020.3.s1.14Krause, K. (2007) "Griffith University blended learning strategy," Document number2008/0016252, 2007.Norberg, A., Dziuban, C. D., & Moskal, P. D. (2011). A time‐based blended learning model. On the Horizon. https://doi.org/10.1108/10748121111163913Poon, J. (2013). Blended learning: An institutional approach for enhancing students' learning experiences. Journal of online learning and teaching, 9(2), 271-288.Rafiola, R., Setyosari, P., Radjah, C., & Ramli, M. (2020). The Effect of Learning Motivation, Self-Efficacy, and Blended Learning on Students' Achievement in The Industrial Revolution 4.0. International Journal of Emerging Technologies in Learning (iJET), 15(8), 71-82. https://doi.org/10.3991/ijet.v15i08.12525Rovai, A. P., & Downey, J. R. (2010). Why some distance education programs fail while others succeed in a global environment. The Internet and Higher Education, 13(3), 141-147. https://doi.org/10.1016/j.iheduc.2009.07.001Rovai, A. P., & Jordan, H. M. (2004). Blended learning and sense of community: A comparative analysis with traditional and fully online graduate courses. International Review of Research in Open and Distributed Learning, 5(2), 1-13. https://doi.org/10.19173/irrodl.v5i2.192Sayed, M. (2013). Blended learning environments: The effectiveness in developing concepts and thinking skills. Journal of Education and Practice, 4(25), 12-17.Stein, J., & Graham, C. R. (2020). Essentials for blended learning: A standards-based guide. Routledge. https://doi.org/10.4324/9781351043991Tang, C. M., & Chaw, L. Y. (2016). Digital Literacy: A Prerequisite for Effective Learning in a Blended Learning Environment?. Electronic Journal of E-learning, 14(1), 54-65.Tseng, H., & Walsh, E. J. (2016). Blended vs. traditional course delivery: Comparing students' motivation, learning outcomes, and preferences. Quarterly Review of Distance Education, 17(1), 1-21.Volery, Thierry, and Deborah Lord. "Critical success factors in online education." International journal of educational management (2000). https://doi.org/10.1108/09513540010344731Woo, Y., & Reeves, T. C. (2007). Meaningful interaction in web-based learning: A social constructivist interpretation. The Internet and higher education, 10(1), 15-25. https://doi.org/10.1016/j.iheduc.2006.10.005Zhu, Y., Au, W., & Yates, G. (2016). University students' self-control and self-regulated learning in a blended course. Internet and Higher Education, 30, 54-62. https://doi.org/10.1016/j.iheduc.2016.04.00

Adoption of E-Learning at Higher Education Institutions: A Systematic Literature Review

[EN] The concept of e-learning offers a number of benefits, however, the effective adoption of e-learning systems at HEIs is a relatively new concept and thus a challenging task. The comprehensive review of extant literature on the topic of adoption of e-learning systems at HEIs is provided. Using PRISMA search technique, relevant articles published from 2005 to 2020 owing to the widespread adoption of e-learning since 2005 were selected. The paper identifies and puts forward the level of compatibility and readiness of students and teachers in adopting e-learning, factors that motivate and hinder the adoption of e-learning respectively, benefits of adopting an e-learning system, and the strategies for the effective implementation of e-learning at the higher education institutions. In this realm of COVID-19 and e-learning, this paper also envisage different strategies, policies and recommendations for implementing e-learning in an effective way at HEIs.Awan, RK.; Afshan, G.; Memon, AB. (2021). Adoption of E-Learning at Higher Education Institutions: A Systematic Literature Review. Multidisciplinary Journal for Education, Social and Technological Sciences. 8(2):74-91. https://doi.org/10.4995/muse.2021.15813OJS749182Abou El-Seoud, M. S., Taj-Eddin, I. A., Seddiek, N., El-Khouly, M. M., & Nosseir, A. (2014). E-learning and students' motivation: A research study on the effect of e-learning on higher education. International Journal of Emerging Technologies in Learning, 9(4), 20-26. https://doi.org/10.3991/ijet.v9i4.3465Ahmed, S. S., Khan, E., Faisal, M., & Khan, S. (2017). The potential and challenges of MOOCs in Pakistan: a perspective of students and faculty. Asian Association of Open Universities Journal. https://doi.org/10.1108/AAOUJ-01-2017-0011Akçayır, M., Akçayır, G., Pektaş, H. M., & Ocak, M. A. (2016). Augmented reality in science laboratories: The effects of augmented reality on university students' laboratory skills and attitudes toward science laboratories. 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The effectiveness of using augmented reality in teaching geography curriculum on the achievement and attitudes of Omani 10th Grade Students. Multidisciplinary Journal for Education, Social Technological Sciences, 7(2), 20-29. https://doi.org/10.4995/muse.2020.13014Alqahtani, A. Y., & Rajkhan, A. A. J. E. s. (2020). E-learning critical success factors during the covid-19 pandemic: A comprehensive analysis of e-learning managerial perspectives. 10(9), 216. https://doi.org/10.3390/educsci10090216Au, O. T.-S., Li, K., & Wong, T. (2019). Student persistence in open and distance learning: success factors and challenges. Asian Association of Open Universities Journal. https://doi.org/10.1108/AAOUJ-12-2018-0030Azlan, C. A., Wong, J. H. D., Tan, L. K., Huri, M. S. N. A., Ung, N. M., Pallath, V., Tan, C. P. L., Yeong, C. H., & Ng, K. H. (2020). Teaching and learning of postgraduate medical physics using Internet-based e-learning during the COVID-19 pandemic-A case study from Malaysia. 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Multidisciplinary Journal for Education, Social Technological Sciences, 6(2), 54-91. https://doi.org/10.4995/muse.2019.11869Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive coding and theme development. International journal of qualitative methods, 5(1), 80-92. https://doi.org/10.1177/160940690600500107Gerbic, P. (2011). Teaching using a blended approach-what does the literature tell us? Educational Media International, 48(3), 221-234. https://doi.org/10.1080/09523987.2011.615159Grimus, M. (2020). Emerging technologies: Impacting learning, pedagogy and curriculum development. In Emerging technologies and pedagogies in the curriculum (pp. 127-151): Springer. https://doi.org/10.1007/978-981-15-0618-5_8Hasan, R., Palaniappan, S., Mahmood, S., Abbas, A., Sarker, K. U., & Sattar, M. U. (2020). Predicting student performance in higher educational institutions using video learning analytics and data mining techniques. Applied Sciences, 10(11), 3894. https://doi.org/10.3390/app10113894Holt, D., Palmer, S., Munro, J., Solomonides, I., Gosper, M., Hicks, M., Sankey, M., Allan, G., & Hollenbeck, R. (2013). Leading the quality management of online learning environments in Australian higher education. Australasian Journal of Educational Technology, 29(3). https://doi.org/10.14742/ajet.84Huda, M., Maseleno, A., Atmotiyoso, P., Siregar, M., Ahmad, R., Jasmi, K., & Muhamad, N. (2018). Big data emerging technology: insights into innovative environment for online learning resources. International Journal of Emerging Technologies in Learning, 13(1), 23-36. https://doi.org/10.3991/ijet.v13i01.6990Ibrahim, M. M., & Nat, M. (2019). Blended learning motivation model for instructors in higher education institutions. 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Choosing the right learning management system (LMS) for the higher education institution context: A systematic review. International Journal of Emerging Technologies in Learning, 11(6). https://doi.org/10.3991/ijet.v11i06.5644Kennedy, G. E., Judd, T. S., Churchward, A., Gray, K., & Krause, K.-L. (2008). First year students' experiences with technology: Are they really digital natives? Australasian Journal of Educational Technology, 24(1). https://doi.org/10.14742/ajet.1233Khan, A. A., & Umair, S. (2017). Handbook of research on mobile devices and smart gadgets in K-12 education: IGI Global. https://doi.org/10.4018/978-1-5225-2706-0Kim, H. J., Hong, A. J., & Song, H.-D. (2019). The roles of academic engagement and digital readiness in students' achievements in university e-learning environments. International Journal of Educational Technology in Higher Education, 16(1), 1-18. https://doi.org/10.1186/s41239-019-0152-3Kjellsdotter, A. (2020). What matter (s)? A didactical analysis of primary school teachers' ICT integration. Journal of Curriculum Studies, 52(6), 823-839. https://doi.org/10.1080/00220272.2020.1759144Kobusińska, A., Leung, C., Hsu, C.-H., Raghavendra, S., & Chang, V. (2018). Emerging trends, issues and challenges in Internet of Things, Big Data and cloud computing. In: Elsevier. https://doi.org/10.1016/j.future.2018.05.021Lange, C., & Costley, J. (2020). Improving online video lectures: learning challenges created by media. International Journal of Educational Technology in Higher Education, 17(1), 1-18. https://doi.org/10.1186/s41239-020-00190-6Leo, S., Alsharari, N. M., Abbas, J., & Alshurideh, M. T. (2021). From Offline to Online Learning: A Qualitative Study of Challenges and Opportunities as a Response to the COVID-19 Pandemic in the UAE Higher Education Context. The Effect of Coronavirus Disease on Business Intelligence, 334, 203. https://doi.org/10.1007/978-3-030-67151-8_12Maldonado, U. P. T., Khan, G. F., Moon, J., & Rho, J. J. (2011). E‐learning motivation and educational portal acceptance in developing countries. Online Information Review. https://doi.org/10.1108/14684521111113597Mayer, R. E. (2014). Multimedia instruction. In Handbook of research on educational communications and technology (pp. 385-399): Springer. https://doi.org/10.1007/978-1-4614-3185-5_31Mehall, S. (2021). Purposeful interpersonal interaction and the point of diminishing returns for graduate learners. The Internet Higher Education, 48, 100774. https://doi.org/10.1016/j.iheduc.2020.100774Memon, A. B., & Meyer, K. (2017). Why we need dedicated web-based collaboration platforms for inter-organizational connectivity? A research synthesis. International Journal of Information Technology and Computer Science, 9(11), 1-11. https://doi.org/10.5815/ijitcs.2017.11.01Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). e-Learning, online learning, and distance learning environments: Are they the same? The Internet Higher Education, 14(2), 129-135. https://doi.org/10.1016/j.iheduc.2010.10.001Mtebe, J. S., & Raphael, C. J. A. J. o. E. T. (2018). Key factors in learners' satisfaction with the e-learning system at the University of Dar es Salaam, Tanzania. 34(4). https://doi.org/10.14742/ajet.2993Mumtaz, N., Saqulain, G., & Mumtaz, N. (2021). Online academics in Pakistan: COVID-19 and beyond. Pakistan Journal of Medical Sciences, 37(1), 283. https://doi.org/10.12669/pjms.37.1.2894Naveed, Q. N., Muhammed, A., Sanober, S., Qureshi, M. R. N., & Shah, A. (2017). Barriers Effecting Successful Implementation of E-Learning in Saudi Arabian Universities. International Journal of Emerging Technologies in Learning, 12(6). https://doi.org/10.3991/ijet.v12i06.7003Ngampornchai, A., & Adams, J. (2016). Students' acceptance and readiness for E-learning in Northeastern Thailand. International Journal of Educational Technology in Higher Education, 13(1), 1-13. https://doi.org/10.1186/s41239-016-0034-xOlum, R., Atulinda, L., Kigozi, E., Nassozi, D. R., Mulekwa, A., Bongomin, F., Kiguli, S. J. J. o. M. E., & Development, C. (2020). Medical education and E-learning during COVID-19 pandemic: awareness, attitudes, preferences, and barriers among undergraduate medicine and nursing students at Makerere University, Uganda. 7, 2382120520973212. https://doi.org/10.1177/2382120520973212Ouatik, F., & Ouatik, F. (2021). Learning Management System Comparison: New Approach Using Multi-Criteria Decision Making. Paper presented at the International Conference on Business Intelligence. https://doi.org/10.1007/978-3-030-76508-8_17Panda, S., & Mishra, S. (2007). E‐Learning in a Mega Open University: Faculty attitude, barriers and motivators. Educational Media International, 44(4), 323-338. https://doi.org/10.1080/09523980701680854Paul, J., & Criado, A. R. (2020). The art of writing literature review: What do we know and what do we need to know? International Business Review, 29(4), 101717. https://doi.org/10.1016/j.ibusrev.2020.101717Paul, J., Lim, W. M., O'Cass, A., Hao, A. W., & Bresciani, S. (2021). Scientific procedures and rationales for systematic literature reviews (SPAR‐4‐SLR). International Journal of Consumer Studies. https://doi.org/10.1111/ijcs.12695Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 1-26. https://doi.org/10.1186/s41239-019-0136-3Popoola, S. O., & Olajide, O. (2021). Influence of Library Anxiety and Computer Literacy Skills on Use of Library Information Resources by Undergraduates in Private Universities in Southwest Nigeria. International Information Library Review, 1-19. https://doi.org/10.1080/10572317.2021.1873051Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers Education, 144, 103701. https://doi.org/10.1016/j.compedu.2019.103701Richardson, M., Abraham, C., & Bond, R. J. P. b. (2012). Psychological correlates of university students' academic performance: a systematic review and meta-analysis. 138(2), 353. http://doi.org/2012-04281-001Saeed Al-Maroof, R., Alhumaid, K., & Salloum, S. (2021). The continuous intention to use e-learning, from two different perspectives. Education Sciences, 11(1), 6. https://doi.org/10.3390/educsci11010006Sahibzada, U. F., Xu, Y., Afshan, G., & Khalid, R. (2021). Knowledge-oriented leadership towards organizational performance: symmetrical and asymmetrical approach. Business Process Management Journal. https://doi.org/10.1108/BPMJ-03-2021-0125Sánchez-Sordo, J. M. (2019). Data mining techniques for the study of online learning from an extended approach. Multidisciplinary Journal for Education, Social Technological Sciences, 6(1), 1-24. https://doi.org/10.4995/muse.2019.11482Sayaf, A. M., Alamri, M. M., Alqahtani, M. A., & Al-Rahmi, W. M. (2021). Information and Communications Technology Used in Higher Education: An Empirical Study on Digital Learning as Sustainability. Sustainability, 13(13), 7074. https://doi.org/10.3390/su13137074Singh, V., & Thurman, A. (2019). How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018). American Journal of Distance Education, 33(4), 289-306. https://doi.org/10.1080/08923647.2019.1663082Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. 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The Implementation of Multi-sensory Learning at Elementary Schools in Jakarta

This research aims to identify the implementation of multisensory learning at elementary schools in Jakarta. The method used through surveys to 50 elementary schools’ teachers in 5 schools. Data was collected by using questionnaire that revealed the implementation of multisensory learning. The result of this study showed that the use of multisensory learning could be more effective in maximizing learning. Through multisensory learning, teacher can in-volve students actively in the learning process and facilitate all students with different learning styles. Multisensory learning can be used in all lesson that integrated with curriculum and has significant implications in the real-life learning. The obstacle in implementing this learning model is founded about the lack of using of audiovisual technology and many schools do not implemented the multisensory learning. Keywords: Multisensory learning, Elementary School, Audiovisual Media. References Aja, S. N., Eze, P. I., Igba, D. I., Igba, E. C., Nwafor, C. C., & Nnamani, S. C. (2017). Using multi-sensory instruction in managing classroom for effective teaching and learning. International Journal of Applied Engineering Research, 12(24), 15112–15118. Blomert, L., & Froyen, D. (2010). Multi-sensory learning and learning to read. International Journal of Psychophysiology, 77(3), 195–204. https://doi.org/10.1016/j.ijpsycho.2010.06.025Child1st. (2019). What is multisensory learning why it so effective. Retrieved April 25, 2019, from child1st.com website: https://child1st.com/blogs/resources/what-is-multisensory-learning-why-is-it-so-effective Finotti, G., Migliorati, D., & Costantini, M. (2018). Multisensory integration, body representation and hyperactivity of the immune system. Consciousness and Cognition, 63(October 2017), 61–73. https://doi.org/10.1016/j.concog.2018.06.009 Gorjian, B., Hayati, A., & Barazandeh, E. (2012). An evaluation of the effects of art on vocabulary learning through multi-sensory modalities. Procedia Technology, 1, 345–350. https://doi.org/10.1016/j.protcy.2012.02.072 Heikkilä, J., & Tiippana, K. (2016). School-aged children can benefit from audiovisual semantic congruency during memory encoding. Experimental Brain Research, 234(5), 1199–1207. https://doi.org/10.1007/s00221-015-4341-6 Jurban, S. (2011). Using Multi Sensory Approach for Teaching English Skills and Its Effect on Students ’ Achievement at Jordanian School. European Scientific Journal, 8(22), 50–61. Komalasari, M. D. (2005). Metode Multisensori untuk Meningkatkan Kemampuan Membaca pada peserta didik Disleksia di Sekolah Dasar. Proseding Seminar Nasional PGSD UPY, 97–110. Yogyakarta. Krueger Fister, J., Stevenson, R. A., Nidiffer, A. R., Barnett, Z. P., & Wallace, M. T. (2016). Stimulus intensity modulates multisensory temporal processing. Neuropsychologia, 88, 92–100. https://doi.org/10.1016/j.neuropsychologia.2016.02.016 Matusz, P. J., Wallace, M. T., & Murray, M. M. (2017). A multisensory perspective on object memory. Neuropsychologia, 105, 243–252. https://doi.org/10.1016/j.neuropsychologia.2017.04.008 Morin, A. (2019). Multisensory Instruction: What You Need to Know. Retrieved April 25, 2019, from https://www.understood.org/en/school-learning/partnering-with-childs-school/instructional-strategies/multisensory-instruction-what-you-need-to-know Nidiffer, A. R., Stevenson, R. A., Krueger Fister, J., Barnett, Z. P., & Wallace, M. T. (2016). Interactions between space and effectiveness in human multisensory performance. Neuropsychologia, 88, 83–91. https://doi.org/10.1016/j.neuropsychologia.2016.01.031 Nurjanah, E. (2017). Metode Multisensori Terhadap Kemampuan Mengenal Lambang Bilangan 1-10 Pada Anak Autis. Jurnal Pendidikan Khusus, 1–10. Olivia, P. F. (1992). Developing the Curriculum (Third Edit). New York: Harper Collins Publishers Inc. Praveen, A. V. (2019). What is Multisensory Teaching Techniques? Retrieved April 25, 2019, from https://www.lexiconreadingcenter.org/what-is-multisensory-teaching-techniques/ Shams, L., & Seitz, A. R. (2008). Benefits of multisensory learning. Trends in Cognitive Sciences, 12(11), 411–417. https://doi.org/10.1016/j.tics.2008.07.006 Taljaard, J. (2016). A review of multi - sensory technologies in a Science , Technology , Engineering , Arts and M athematics ( STEAM ) classroom. Journal of Learning Design, 9(2), 46–55

Evaluating E-Learning systems success to understand student’s performance during Covid Pandemic

[EN] The present work arises as a consequence of the current situation that is being experienced worldwide due to the COVID 19 and the associated repercussions on education. E- Learning has demonstrated to be the only resource capable of replacing traditional in-person learning methods in the present global gridlock due to the COVID-19 pandemic. Academic institutions around the world have heavily invested in E-Learning and it is necessary to ensure the success of E-Learning initiatives in order to make a learning model with the same guarantees of traditional models. The objective of this study is to propose and validate a model to measure the E-learning success based on different dimensions and it is an extended of the Technology Acceptance Model (TAM) and Information Systems Success (ISS), which has been empirically tested. For this purpose, an e-learning questionnaire was used in order to test academical performance with students from secondary education in València during the pandemic. Results show a significant relationship between Intention To Use for Sustainability and Students Satisfacction, a significant relationship between Students Satisfacction and Student Performance and finally a significant relationship between Student Performance and Learning Achievements.Bustamante García, E.; Martínez Gómez, M.; Berna Escriche, C. (2022). Evaluating E-Learning systems success to understand student’s performance during Covid Pandemic. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 286-286. http://hdl.handle.net/10251/18970228628

Foreign Language Learning In Knowledge Forums: using a knowledge-building forum in an EFL classroom

[EN] This paper presents the first phase of a study conducted to analyze Knowledge Building forums for evidence of second language acquisition. This study is an analysis of the posts within an existing forum in search of evidence of foreign language learning. The analysis found that the collaborative writing project shows evidence that the students passed through the stages of construction of knowledge within their foreign language classroom, however factors, such as confounding variables, inconsistencies in error types, and the small number of posts by the participants made it challenging to determine whether there is evidence of language acquisition for each student. The forum posts show evidence of knowledge acquisition, but further investigation is required to determine whether collaborative writing in knowledge forums is effective for foreign language acquisition.Manegre, M.; Gutiérrez-Colón, M.; Gisbert, M. (2019). Foreign Language Learning In Knowledge Forums: using a knowledge-building forum in an EFL classroom. The EuroCALL Review. 27(1):3-13. https://doi.org/10.4995/eurocall.2019.11150OJS313271Al-Jarf, R. (2007). Teaching Vocabulary to EFL College Students Online. CALL-EJ, 8(2). 1-16. http://econf.uob.edu.bh/conf1/pdf%20files/133.pdfBielaczyc, K. & Collins, A. (2005). Technology as a catalyst for fostering knowledge-creating communities. A. M. O'Donnell, C. E. Hmelo-Silver & J. van der Linden (Eds.), Using technology to enhance learning. Mahwah NJ: Lawrence Erlbaum Associates.Bielaczyc, K. & Collins, A. (2006). Fostering knowledge-creating communities. A. M. O'Donnell, C. E. Hmelo-Silver & G. Erkens (Eds.), Collaborative Learning, Reasoning, and Technology. Mahwah NJ: Lawrence Erlbaum Associates.Bereiter, C. & Scardamalia, M. (2010). Can Children Really Create Knowledge?. Canadian Journal of Learning and Technology / La revue canadienne de l'apprentissage et de la technologie, 36 (1). Canadian Network for Innovation in Education. https://doi.org/10.21432/T2ZP43Bereiter C., Scardamalia M. (2014) Knowledge Building and Knowledge Creation: One Concept, Two Hills to Climb. In: Tan S., So H., Yeo J. (Eds.) Knowledge Creation in Education. Education Innovation Series, pp. 35-52. Singapore: Springer. https://doi.org/10.1007/978-981-287-047-6_3Bikowski, D. & Vithanage, R. (2016). Effects of Web-Based Collaborative Writing on Individual L2 writing Development. Language Learning & Technology, 20(1), 79-99. https://scholarspace.manoa.hawaii.edu/bitstream/10125/44447/1/20_01_bikowskivithanage.pdfBrantlinger, E., Jimenez, R., Klinger, J., Pugach, M. & Richardson, V. (2005). Qualitative Studies in Special Education. Exceptional Children. 71(2), 195-207. https://doi.org/10.1177/001440290507100205Chen-Chung, L., Pin-Ching, W. & Shu-Ju, T., (2016). An analysis of student engagement patterns in language learning facilitated by Web 2.0 Technologies. ReCALL 28(2), 104- 122. https://doi.org/10.1017/S095834401600001XChuy, M., Scardamalia, M., Bereiter, C., Prinsen, F., Resendes, M., Messina, R., Hunsburger, W., Teplovs, C., & Chow, A. (2010). Understanding the nature of science and scientific process: A theory building approach. Canadian Journal of Learning and Technology, 36(1). https://doi.org/10.21432/T2GP4RCingel, D. P. & Sundar, S. (2012). Texting, techspeak, and tweens: The relationship between text messaging and English grammar skills. New Media & Society. 14(8).https://journals.sagepub.com/doi/10.1177/1461444812442927. https://doi.org/10.1177/1461444812442927Comas-Quinn, A., Mardomingo, R. & Valentine, C. (2009). Mobile blogs in language learning: Making the most of informal and situated learning opportunities. ReCALL 21(1), 96-112. https://doi.org/10.1017/S0958344009000032Consell Superior d'Avaluació del Sistema Educatiu (2015). Avaluació del projecte COMconèixer. Barcelona, Departament d'Ensenyament, Consell Superior d'Avaluació del Sistema Educatiu, col·lecció 'Documents' 32. http://cdl3.cdl.cat/COMconeixer/docs/Avaluacio_Projecte_COMconeixer.pdfCook, J. & Smith, M. (2004). Beyond formal learning: Informal community eLearning. Computers & Education. 43(1-2), 35-47. https://doi.org/10.1016/j.compedu.2003.12.003Deming, W. E. (1986). Out of the Crisis. MIT Press.Gunawardena, C. N, Lowe, C. A., & Anderson, T. (1997). Analysis of a Global Online Debate and the Development of an Interaction Analysis Model for Examining Social Construction of Knowledge in Computer Conferencing. Journal of Educational Computing Research. 17(4). https://doi.org/10.2190/7MQV-X9UJ-C7Q3-NRAGHeiser, S., Stickler, U. & Furnborough, C. (2013). Student training in the use of an online synchronous conferencing tool. CALICO Journal, 30(2), 226-251. https://doi.org/10.11139/cj.30.2.226-251Johnson, D.W. & Johnson, R.T. (1999). Making cooperative learning work, Theory Into Practice, 38:2, 67-73. https://doi.org/10.1080/00405849909543834Kim, B., Tan, L., & Bielaczyc, K. (2015). Learner-generated designs in participatory culture: What they are and how they are shaping learning. Interactive Learning Environments, 23(5), 545-555. https://doi.org/10.1080/10494820.2015.1067974Kimmerle, J., Moskaliuk, J., Brendle, D. & Cress, U. (2017). All in Good Time: Knowledge Introduction, Restructuring, and Development of Shared Opinions as Different Stages in Collaborative Writing. International Journal of Computer Supported Collaborative Learning. 12(2), 195-213. https://doi.org/10.1007/s11412-017-9258-6Laferriere, T., Law, N. & Montaine, M. (2012). An International Knowledge Building Network for Sustainable Curriculum and Pedagogical Information. International Education Studies, 5(3), 148-160. https://doi.org/10.5539/ies.v5n3p148Montane, M., Amaros, C. & Gisbert, M. (2017). The COMknowledge project: evaluation of methodological aspects of the project based on pupils' perceptions. Unpublished conference paper.Moss, J. & Beatty, R. (2006). Knowledge building in mathematics: Supporting collaborative learning in pattern problems. International Journal of Computer Supported Collaborative Learning, 1(4), 441- 465. https://doi.org/10.1007/s11412-006-9003-zNami, F, Marandi, S.S., Sotoudehnama, E., (2018). Interaction in a discussion list: An exploration of cognitive, social, and teaching presence in teachers' online collaborations. ReCALL,30(3), 375-398. https://doi.org/10.1017/S0958344017000349Paavola, S., Lipponen, L. & Hakkarainen, K. (2004). Models of Innovative Knowledge Communities and Three Metaphors of Learning. Review of Educational Research. 74(4), 557-576. https://doi.org/10.3102/00346543074004557Scardamalia, M. & Bereiter, C. (1991). Higher levels of agency for children in knowledge building: A challenge for the design of new knowledge media. Journal of the Learning Sciences, 1,37-68. https://doi.org/10.1207/s15327809jls0101_3Scardamalia, M. & Bereiter, C. (1994). Computer Support for Knowledge Based Communities. Journal of the Learning Sciences 3(3), 265-283. https://doi.org/10.1207/s15327809jls0303_3Scardamalia, M. & Bereiter, C. (2006). Knowledge building: Theory, Pedagogy, and Technology. In K. Sawyer (Ed.) Cambridge Handbook of the Learning Sciences, pp. 97-118. New York: Cambridge University Press. https://doi.org/10.1017/CBO9781139519526.025Scardamalia, M., Bereiter, C., Brett, C., Burtis, P.J., Calhoun, C., & Smith Lea, N. (1992). Educational applications of networked communal database. Interactive Learning Environments. 2(1), 45-71. https://doi.org/10.1080/1049482920020105Sun, Y., Franklin, T. & Gao, F. (2015). Learning Outside of Classroom: Exploring the Active Part of an Informal Online English Learning Community in China. British Journal of Educational Technology. https://doi.org/10.1111/bjet.12340Thorne, S., Black, R. W. & Sykes, J. M. (2009). Second language use, socialization, and learning in internet interest communities and online gaming. The Modern Language Journal, 93(1), 802-821. https://doi.org/10.1111/j.1540-4781.2009.00974.xYim, S., Warschauer, M., (2017). Web-Based Collaborative Writing in L2 Contexts: Methodological Insights From Text Mining. Language Learning & Technology, 21(1), 146-165. https://scholarspace.manoa.hawaii.edu/bitstream/10125/44599/1/21_01_yimwarschauer.pdfZhan, Z., Xu, F. & Ye, H. (2011). Effects of an online learning community on active and reflective learners' learning performance and attitudes in a face-to-face undergraduate course. Computers & Education, 56(4), 961- 968. https://doi.org/10.1016/j.compedu.2010.11.01

Employees\u27 perceptions of barriers in e-Learning : the relationship among barriers, demographics, and e-Learning self-efficacy.

The purpose of this empirical study was to examine the types of e-learning barriers and to establish the nature of relationships among (a) barriers perceived by employee e-learners in the process of starting, continuing, and completing online training; (b) demographic variables; (c) background characteristics; and (d) e-learning self-efficacy. The population was comprised of employees (N = 4807; n = 865) who had participated in Web-based training delivered 100 percent online. Convenient samples of employees were drawn from seven organizations representing (a) IT Manufacturing, (b) Oil Exploration & Manufacturing, (c) Public School District, (d) Health insurance, (e) Wholesale Distribution, (f) IT Consulting, and (g) US Military. The social cognitive learning theory\u27s dimension of self-efficacy examined e-learners\u27 Internet and computer self-efficacy. Schilke\u27s (2001) conceptual framework on e-learning barriers and ideas from various critics of the technological study guided the present study. The E-learning Barriers and Self-Efficacy (ELSE) survey was used to collect data from volunteer employees. This Web-based anonymous survey had 82 questions in three scales: (a) demographics and background characteristics; (b) Barriers in E-leaming (BEL) scale (alpha = .9496) and one open-ended question; and (c) E-learning Self-Efficacy (ELSE) scale (alpha = .9487). The instrument was validated using subject matter experts and a pilot study. Response rates were 52.5% (pilot study) and 18% (main study). Data were analyzed using exploratory factor analysis, multiple regression, MANOVA, and Pearson correlation. Open coding was used for the open-ended responses. Seven categories of barriers (factors) emerged: (1) Dispositional, (2) learning style, (3) instructional, (4) organizational, (5) situational, (6) content-suitability, and (7) technological barriers. The barriers means ranged from 1.29 to 3.00 on a 5-point scale (1 = weak and 5 = strongest barrier). Barrier ratings were weak on all categories. Personal barriers (M = 1.54) were the least common while situational barriers were the most prevalent (M = 2.81). The multidimensional nature of these barriers demands a systemic approach to reduce them. A MANOVA test indicated significant differences in barriers among the seven organizations. The test of relationships using multiple regression revealed four predictors of e-learning barriers: (a) organization type, (b) computer competence, (c) computer training, and (d) e-learning self-efficacy. Results, implications for practice, conclusions, and recommendations for further research are discussed