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Original Articles

Modeling collective attention in online and flexible learning environments

ORCID Icon, , &
Pages 278-301 | Received 16 Jan 2019, Accepted 25 Mar 2019, Published online: 09 Apr 2019

References

  • Albert, R., Jeong, H., & Barabási, A. L. (1999). Internet: Diameter of the world-wide web. Nature, 401, 130–131. doi:10.1038/43601
  • Bauckhage, C., Kersting, K., & Rastegarpanah, B. (2014). Collective attention to social media evolves according to diffusion models. In Proceedings of the 23rd international conference on World Wide Web (pp. 223–224). New York, NY: ACM. doi:10.1145/2567948.2577298
  • Bonk, C. J., Lee, M. M., Reeves, T. C., & Reynolds, T. H. (Eds.). (2015). MOOCs and open education around the world. London, UK: Routledge.
  • Bozkurt, A., Akgün-Özbek, E., & Zawacki-Richter, O. (2017). Trends and patterns in massive open online courses: Review and content analysis of research on MOOCs (2008–2015). The International Review of Research in Open and Distributed Learning, 18(5), 118–147. doi:10.19173/irrodl.v18i5.3080
  • Brinton, C. G., & Chiang, M. (2015). MOOC performance prediction via clickstream data and social learning networks. In J. Cao (Ed.), Proceedings of the 2015 IEEE conference on computer communications (pp. 2299–2307). IEEE. doi:10.1109/INFOCOM.2015.7218617
  • Broadbent, D. E. (1958). Perception and communication. New York, NY: Pergamon.
  • Catledge, L. D., & Pitkow, J. E. (1995). Characterizing browsing strategies in the World-Wide Web. Computer Networks and ISDN Systems, 27(6), 1065–1073. doi:10.1016/0169-7552(95)00043-7
  • Cebrian, J. (2015). Energy flows in ecosystems. Science, 349, 1053–1054. doi:10.1126/science.aad0684
  • Cherkassky, B. V., Goldberg, A. V., & Radzik, T. (1996). Shortest paths algorithms: Theory and experimental evaluation. Mathematical Programming, 73(2), 129–174. doi:10.1007/BF02592101
  • Ciampaglia, G. L., Flammini, A., & Menczer, F. (2015). The production of information in the attention economy. Scientific Reports, 5, 9452–9458. doi:10.1038/srep09452
  • Clow, D. (2013). MOOCs and the funnel of participation In D. Suthers, K. Verbert, E. Duval, & X. Ochoa (Eds.), Proceedings of the third international conference on learning analytics and knowledge (pp. 185–189). New York, NY: ACM.
  • Crane, R., & Sornette, D. (2008). Robust dynamic classes revealed by measuring the response function of a social system. Proceedings of the National Academy of Sciences, 105(41), 15649–15653. doi:10.1073/pnas.0803685105
  • Crossley, S., Paquette, L., Dascalu, M., McNamara, D. S., & Baker, R. S. (2016). Combining click-stream data with NLP tools to better understand MOOC completion. In S. Dawson, H. Drachsler, & C. Rosé (Eds.), Proceedings of the Sixth International Conference on Learning Analytics and Knowledge (pp. 6–14). New York, NY: ACM.
  • Davenport, T. H., & Beck, J. C. (2001). The attention economy: Understanding the new currency of business. Boston, MA: Harvard Business Press.
  • Eom, Y. H., Puliga, M., Smailović, J., Mozetič, I., & Caldarelli, G. (2015). Twitter-based analysis of the dynamics of collective attention to political parties. PloS one, 10(7), e0131184. doi:10.1371/journal.pone.0131184
  • Falkinger, J. (2007). Attention economies. Journal of Economic Theory, 133(1), 266–294. doi:10.1016/j.jet.2005.12.001
  • Fischer, G. (2014). Beyond hype and underestimation: Identifying research challenges for the future of MOOCS. Distance Education, 35, 149–158. doi:10.1080/01587919.2014.920752
  • Garner, W. R. (1974). The processing of information and structure. Potomac, MD: Erlbaum.
  • Gleeson, J. P., Ward, J. A., O’Sullivan, K. P., & Lee, W. T. (2014). Competition-induced criticality in a model of meme popularity. Physical Review Letters, 112(4), 048701. doi:10.1103/PhysRevLett.112.048701
  • Golder, S. A., & Huberman, B. A. (2006). Usage patterns of collaborative tagging systems. Journal of Information Science, 32(2), 198–208. doi:10.1177/0165551506062337
  • Goldhaber, M. H. (1997). The attention economy and the Net. First Monday, 2(4), Retrieved from https://journals.uic.edu/ojs/index.php/fm/index
  • Gregori, E. B., Zhang, J., Galván-Fernández, C., & de Asís Fernández-Navarro, F. (2018). Learner support in MOOCs: Identifying variables linked to completion. Computers & Education, 122, 153–168. doi:10.1016/j.compedu.2018.03.014
  • Guo, L., Lou, X., Shi, P., Wang, J., Huang, X., & Zhang, J. (2015). Flow distances on open flow networks. Physica A: Statistical Mechanics and Its Applications, 437, 235–248. doi:10.1016/j.physa.2015.05.070
  • Heiberger, R. H. (2015). Collective attention and stock prices: Evidence from Google trends data on Standard and Poor‘s 100. PloS one, 10(8), e0135311. doi:10.1371/journal.pone.0135311
  • Jacobson, M. J., Kapur, M., & Reimann, P. (2016). Conceptualizing debates in learning and educational research: Toward a complex systems conceptual framework of learning. Educational Psychologist, 51(2), 210–218. doi:10.1080/00461520.2016.1166963
  • Kamath, A. (2014). industrial innovation, networks, and economic development: Informal information sharing in low-technology clusters in India. New York, NY: Routledge.
  • Kammenhuber, N., Luxenburger, J., Feldmann, A., & Weikum, G. (2006). Web search clickstreams. In J. Almeida, V. Almeida, & P. Barford (Eds.), Proceedings of the 6th ACM SIGCOMM conference on internet measurement (pp. 245–250). New York, NY: ACM.
  • Khalil, M., & Ebner, M. (2017). Clustering patterns of engagement in massive open online courses (MOOCs): The use of learning analytics to reveal student categories. Journal of Computing in Higher Education, 29(1), 114–132. doi:10.1007/s12528-016-9126-9
  • Koseoglu, S., & Bozkurt, A. (2018). An exploratory literature review on open educational practices. Distance Education, 39, 441–461. doi:10.1080/01587919.2018.1520042
  • Lang, A. (2000). The limited capacity model of mediated message processing. Journal of Communication, 50(1), 46–70. doi:10.1111/j.1460-2466.2000.tb02833.x
  • Lehmann, J., Gonçalves, B., Ramasco, J. J., & Cattuto, C. (2012). Dynamical classes of collective attention in twitter. In A. Mille, F. Gandon, J. Misselis, M. Rabinovich, & S. Staab (Eds.), Proceedings of the 21st International Conference on World Wide Web (pp. 251–260). New York, NY: ACM.
  • Leontief, W. (Ed.). (1986). Input-output economics. New York, NY: Oxford University Press.
  • Lou, X., Li, Y., Gu, W., & Zhang, J. (2016). The atlas of Chinese world wide web ecosystem shaped by the collective attention flows. PloS one, 11(11), e0165240. doi:10.1371/journal.pone.0165240
  • Materu, P. (2004). Open source courseware: A baseline study. Washington, DC: World Bank. Retrieved from http://siteresources.worldbank.org/INTAFRREGTOPTEIA/Resources/open_source_courseware.pdf
  • Miller, R. E., & Blair, P. D. (2009). Input-output analysis: Ffoundationsand extensions. Cambridge, UK: Cambridge University Press.
  • Miotto, J. M., & Altmann, E. G. (2014). Predictability of extreme events in social media. PloS one, 9(11), e111506. doi:10.1371/journal.pone.0111506
  • Moussaid, M., Helbing, D., & Theraulaz, G. (2009, September). An individual-based model of collective attention. Paper presented at the European Conference of Complex Systems, Warwick, UK. Retrieved from https://www.researchgate.net/publication/45872706_An_individual-based_model_of_collective_attention
  • Nicolis, G. (1977). Self-organization in nonequilibrium systems: From dissipative structures to order through fluctuations. New York, NY: Wiley.
  • Noh, J. D., & Rieger, H. (2004). Random walks on complex networks. Physical Review Letters, 92(11), 118701. doi:10.1103/PhysRevLett.92.118701
  • Odum, H. T. (1983). Systems Ecology: An introduction. New York, NY: Wiley.
  • Pashler, H. E., & Sutherland, S. (1998). The psychology of attention (Vol. 15). Boston, MA: MIT Press.
  • Patil, V. N., & Patil, H. D. (2015). Prediction of web users’ browsing behavior: A review. International Journal of Computer Science and Mobile Computing, 4, 209–212. Retrieved from https://www.ijcsmc.com/
  • Peter, S., & Deimann, M. (2013). On the role of openness in education: A historical reconstruction. Open Praxis, 5(1), 1–8. doi:10.5944/openpraxis.5.1.23
  • Posner, M. I., & Rothbart, M. K. (2007). Research on attention networks as a model for the integration of psychological science. Annual Review of Psychology, 58(1), 1–23. doi:10.1146/annurev.psych.58.110405.085516
  • Raa, T. T. (2005). The economics of input-output analysis. Cambridge, UK: Cambridge University Press.
  • Salmon, G. (2003). E-moderating: The key to online teaching and learning (2nd ed.). London, UK: Routledge.
  • Searls, D. (2012). The intention economy: When customers take charge. Boston, MA: Harvard Business Press.
  • Sheail, P. (2018). Temporal flexibility in the digital university: Full-time, part-time, flexitime. Distance Education, 39, 462–479. doi:10.1080/01587919.2018.1520039
  • Shi, P., Huang, X., Wang, J., Zhang, J., Deng, S., & Wu, Y. (2015). A geometric representation of collective attention flows. PloS one, 10(9), e0136243. doi:10.1371/journal.pone.0136243
  • Simon, H. A. (1971). Designing organizations for an information-rich world. In M. Greenberger (Ed.), Computers, communication, and the public interest (pp. 0–41). Baltimore, MD: The Johns Hopkins Press.
  • Tang, J. K., Xie, H., & Wong, T. L. (2015). A big data framework for early identification of dropout students in MOOC. In J. Lam, K. Ng, S. Cheun, T. Wong, K. Li, & F. Wang (Eds.), Technology in education: Technology-Mediated Proactive Learning. Proceedings of ICTE 2015, Second International Conference on Technology in Education (pp. 127–132). Berlin, Germany: Springer. doi:10.1007/978-3-662-48978-9_12
  • Treisman, A. M. (1969). Strategies and models of selective attention. Psychological Review, 76(3), 282–299. doi:10.1037/h0027242
  • Weng, L., Flammini, A., Vespignani, A., & Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific Reports, 2, 1–8. doi:10.1038/srep00335
  • Wu, F., & Huberman, B. A. (2007). Novelty and collective attention. Proceedings of the National Academy of Sciences, 104(45), 17599–17601. doi:10.1073/pnas.0704916104
  • Wu, L., Baggio, J. A., & Janssen, M. A. (2016). The role of diverse strategies in sustainable knowledge production. PloS one, 11(3), e0149151. doi:10.1371/journal.pone.0149151
  • Wu, L., & Zhang, J. (2013). The decentralized flow structure of clickstreams on the web. The European Physical Journal B, 86(6), 266. doi:10.1140/epjb/e2013-40132-2
  • Wu, L., Zhang, J., & Zhao, M. (2014). The metabolism and growth of web forums. PloS one, 9(8), e102646. doi:10.1371/journal.pone.0102646
  • Yang, D., Sinha, T., Adamson, D., & Rosé, C. P. (2013, December). Turn on, tune in, drop out: Anticipating student dropouts in massive open online courses. Paper presented at the NIPS Data-Driven Education Workshop, Lake Tahoe, NV. Retrieved from http://www.cs.cmu.edu/~diyiy/docs/nips13.pdf
  • Yousef, A. M. F., Chatti, M. A., Schroeder, U., Wosnitza, M., & Jakobs, H. (2014). The state of MOOCs from 2008 to 2014: A critical analysis and future visions. In S. Zvacek, M. T. Restivo, J. Uhomoibhi, & M. Helfert (Eds.), Proceedings of the International Conference on Computer Supported Education (pp. 305–327). Cham, Switzerland: Springer. doi:10.1007/978-3-319-25768-6_20
  • Zhang, J., Skryabin, M., & Song, X. (2016). Understanding the dynamics of MOOC discussion forums with simulation investigation for empirical network analysis (SIENA). Distance Education, 37, 270–286. doi:10.1080/01587919.2016.1226230
  • Zhang, X., Gao, Y., Yan, X., de Pablos, P. O., Sun, Y., & Cao, X. (2015). From e-learning to social-learning: Mapping development of studies on social media-supported knowledge management. Computers in Human Behavior, 51, 803–811. doi:10.1016/j.chb.2014.11.084

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