Seite - 256 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments

worthwhile to consider choice as a construct and as a set of individual factors in the prediction of use, endorsement, and outcomes of Web 2.0 tools in the classroom. The development of parsimonious predictive models with strong theoretical underpinnings and empirically-derived variables should also continue. The variables with the greatest known influence and generality that also conform to established theories should be prioritized. Systematic replications are necessary to create a hierarchy of variables according to their magnitude of effect. Replication will also achieve generality across students, geographic locations, disciplines, and course delivery modes. Finally, dependent variables of a behavioral nature should be measured directly, such as via observation, in-app tracking, or artifact analysis, rather than survey to maximize validity. A parsimonious model with generality based on valid measures of student response will afford the best understanding of how Web 2.0 influences learning. It may also increase instructor confidence to use it in their classrooms. References [1] K.F. Hashim, A. Rashid, S. Atalla, Social media for teaching and learning within higher education institution: A bibliometric analysis of the literature (2008-2018). International Journal of Interactive Mobile Technologies, 12(7) (2018), 4-19. [2] G. Zachos, E.-A. Paraskevopoulou-Kollia, I. Anagnostopoulos, Social medial use in higher education: A review. Education Sciences, 8 (2018), 194-207. [3] L. Niu, Using Facebook for academic purposes: Current literature and directions for future research. Journal of Educational Computing Research, 56(8) (2019), 1384-1406. [4] B. Mercer, A. Winger, Investigating Twitter use in lower division online classrooms. Distance Learning, 14(2) (2017), 1-8. [5] R. Chugh, U. Ruhi, Social media in higher education: A literature review of Facebook. Education and Information Technologies, 23 (2018), 605-616. [6] F. Moreira, A. Mesquita, P. Peres, Customized x-learning environment: Social networks & knowledge- sharing tools. Procedia Computer Science, 121 (2017), 178-185. [7] A.M. Price, K. Devis, G. LeMoine, S. Crouch, N. South, R. Hossain, First year nursing students use of social media within education: Results of a survey. Nurse Education Today, 61 (2018), 70-76. [8] G. Curro, N. Ainsworth, Social media and higher education: Does digitally enabled learning have a place in law schools? Journal of the Scholarship of Teaching and Learning, 18(3) (2018), 72-86. [9] A. Gavrin, R. Lindell, Engaging students in a large-enrollment physics class using an academically focused social media platform. The Physics Teacher, 55 (2017), 176-179. [10] A.D. Anders, Networked learning with professionals boosts students’ self-efficacy for social networking and professional development. Computers & Education, 127 (2018), 13-29. [11] C. Saini, J. Abraham, Modeling educational usage of social media in pre-service teacher education. Journal of Computing in Higher Education, 31(1) (2019), 21-55. [12] C. Liu, Social media as a student response system: New evidence on learning impact. Research in Learning Technology, 26 (2018). [13] P.D. Cunningham, Bridging the distance: Using interactive communication tools to make online education more social. Library Trends, 65(4) (2017), 589-614. [14] A.M. Kaplan, M. Haenlein, Higher education and the digital revolution: About MOOCs, SPOCs, social media, and the Cookie Monster. Business Horizons, 59(4) (2016), 441-450. [15] A. Bartolomé, M. Cebrian-de-la-Serna, Personal learning environments: A study among higher education students’ designs. International Journal of Education and Development using Information and Communication Technology, 13(2) (2017), 21-41. [16] R. Haworth, Personal learning environments: A solution for self-directed learners. TechTrends, 60 (2016), 359-364. [17] P. Josefsson, S. Hrastinski, D. Pargman, T.C. Pargman, The student, the private and the professional role: Students’ social media use. Education and Information Technologies, 21 (2016), 1583-1594. [18] I. Akman, C. Turhan, User acceptance of social learning systems in higher education: An application of the extended Technology Acceptance Model. Innovations in Education and Teaching International, 54(3) (2017), 229-237. E.Damianoetal. /Bridging theDivide: TheCurrentStatusofWeb2.0 inHigherEducation256