Abstract
A smart university may have numerous components of a traditional university; however, it must have multiple additional “smart” components to implement, maintain and actively use distinctive “smartness” features such as adaptation, sensing, inferring, self-learning, anticipation, and self-optimization. This paper presents the outcomes of an ongoing research project at the InterLabs Research Institute, Bradley University (Peoria, IL, U.S.A.) aimed to validate the proposed “Smartness Features—Main Components” matrix for a smart university by finding relevant real-world examples and best practices from universities worldwide. This matrix contains relations between smart university’s smart features and main components—smart software and hardware systems, smart technologies, smart pedagogy, and smart classrooms—those that go well beyond the ones in a traditional university. More than 300 various pertinent examples have been identified and analyzed by our research team to support the proposed matrix; 36 selected examples are briefly presented in this paper. Research outcomes unambiguously prove the correctness of the proposed “Smartness Features—Main Components” matrix for a smart university.
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References
Tikhomirov, V., Dneprovskaya, N.: Development of Strategy for Smart University, 2015 Open Education Global International Conference, Banff, Canada, April, pp. 22–24 (2015)
Uskov, V., Howlet, R. Jain, L. (eds.): Smart Education and Smart e-Learning, June 17–19, 2015, Sorrento, Italy, Springer, Berlin-Heidelberg, Germany (2015)
Coccoli, M., et al.: Smarter Universities: a vision for the fast changing digital era. J. Vis. Lang. Comput. (Elsevier). 25 (2014)
IBM: Smart Education: https://www.ibm.com/smarterplanet/global/files/au__en_uk__cities__ibm_smarter_education_now.pdf
Adamko, A., Kadek, T., Kosa, M.: Intelligent and adaptive services for a smart campus visions, concepts and applications. In: Proceedings of 5th IEEE International Conference on Cognitive Infocommunications, November 5–7, 2014, Vietri sul Mare, Italy, IEEE (2014)
Uskov, V.L., Bakken, J.P., Pandey, A.: The ontology of next generation smart classrooms. In: Smart Education and e-Learning 2015, June 17–19, 2015, Sorrento, Italy, Springer, pp. 1–11 (2015)
Uskov, V.L., Bakken, J.P., et al.: Smart university: conceptual modeling and system design. In: Uskov, V.L., Bakken, J.P., Howlett, R.J., Jain, L.C. (eds.) Smart Universities: Concepts, Systems, and Technologies, 421 p. Springer (2018). ISBN 978-3-319-59453-8
Uskov, V.L, et al.: A smart university taxonomy: features, components, systems. In: Smart Education and e-Learning, pp. 3–14, 643 p. Springer (2016)
Uskov, V.L., Bakken, J., Shah, A., et al.: Software/ hardware systems and technology for smart engineering education. In: II IEEE World Engineering Education Conference - EDUNINE 2018. March 11–14, 2018, Buenos Aires: IEEE https://ieeexplore.ieee.org/document/8450962 (2018)
Uskov, V.L. Bakken, J.P., et al.: Building smart learning analytics system for smart university. In: Uskov, V.L., Howlett, R.J., Jain, L.C. (eds.) Smart Education and e-Learning, pp. 191–204. Springer. ISBN 978-3-319-59450-7. https://doi.org/10.1007/978-3-319-59451-4 (2017)
Suo, Y., Ishida, T.: Open smart classroom: extensible and scalable learning system in smart space using web service technology. IEEE Trans. Knowl. Data Eng. (2009)
Purdue University. https://www.researchgate.net/publication/254462830_Course_signals_at_Purdue_Using_learning_analytics_to_increase_student_success
Learning Analytics for Tracking Student Progress. Hanover Research. https://www.imperial.edu/research-planning/7932-learning-analytics-for-tracking-student-progress/file (2016)
Griffith University. https://intranet.secure.griffith.edu.au/computing/using-learning-at-griffith/students/communication-and-collaboration/jpoll
Arizona State University. https://events.educause.edu/annual-conference/2016/agenda/using-splunk-data-analytics-to-protect-students-faculty-and-the-university
Vanderbilt University. https://wp0.vanderbilt.edu/tophat/
University of Sussex. http://www.sussex.ac.uk/tel/learningtechnologies/iwb
Pekin University. https://nextshark.com/chinese-university-facial-recognition-system/
University of Illinois at Springfield. https://www.uis.edu/informationtechnologyservices/teaching-and-learning/attendance-taking/
University of Pittsburg. https://www.technology.pitt.edu/security
Texas A&M University. https://utilities.tamu.edu/conservation-programs/building-automation-system/
Hamdan Bin Mohammed Smart University. https://www.ledsmagazine.com/articles/2018/03/university-shows-its-smarts-with-cloud-based-lighting-controls-and-indoor-positioning.html
University of Illinois - Urbana Champaign. http://techservices.illinois.edu/services/virtual-private-networking-vpn/details
King Abdulaziz University. https://www.researchgate.net/publication/262395796_Student_Tracking_in_Classrooms_using_RFID_Technology
Auburn University. https://campustechnology.com/articles/2017/03/09/auburn-u-rolls-out-smart-parking-management-system.aspx
Columbia University. https://engineering.columbia.edu/virtual-augmented-reality-lab
Kenyon College. https://webcpm.com/Articles/2014/12/01/Smart-Thermostats.aspx
University of Southern California. http://chariot.uscrossier.org/our-vision/
Clarion University. http://www.clarion.edu/about-clarion/computing-services/learning-technology-center/instructional-technologies/classroom-technology/videoconferencing-itv/index.html
University of Illinois at Springfield. https://www.uis.edu/informationtechnologyservices/teaching-and-learning/ars/
The Smart Classroom: Merging Technologies for Seamless Tele-education. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.67.1426&rep=rep1&type=pdf
University of British Columbia. https://www.topuniversities.com/student-info/choosing-university/universities-using-new-technologies
Arizona State University. https://www.researchgate.net/publication/244402564_Smart_Classroom_Enhancing_Collaborative_Learning_Using_Pervasive_Computing_Technology
La Trobe University (Australia). https://www.qs.com/cutting-edge-universities-using-the-latest-technology/
Boston University. http://www.bu.edu/ctl/guides/
Uskov, V.L., Bakken, J.P. et al.: Learning analytics based smart pedagogy: student feedback. In: Uskov V.L. et al. (eds.) Smart Education and e-Learning 2018, pp. 117–131. Springer (2018)
Learning Analytics in Higher Education, A Review of UK and International Practice. https://www.jisc.ac.uk/sites/default/files/learning-analytics-in-he-v2_0.pdf
Midstate College. https://online.midstate.edu/Downloads/Publications/Student_eLearning_Guide.Pdf
The University of Essex. https://www.panopto.com/blog/8-active-learning-examples-in-higher-education/
Uskov, V.L., Bakken, J.P., Aluri, L.: Crowdsourcing-based learning: the effective smart pedagogy for STEM education. In: Proceedings of 2019 IEEE Global Engineering Education Conference EDUCON, April 9–11, 2019, Dubai, UAE, IEEE (in print)
Massachusetts Institute of Technology, Student Disability Services For Students. http://studentlife.mit.edu/sds/students
Massachusetts Institute of Technology, Assistive Technology. http://studentlife.mit.edu/wellness-and-support/accessibility-usability/assistive-technology/software-mobile-apps-and-extensions
Massachusetts Institute of Technology, Assistive Technology. http://studentlife.mit.edu/wellness-and-support/accessibility-usability/assistive-technology/hardware-and-ergonomic-devices
University of Edinburgh. https://www.ed.ac.uk/information-services/learning-technology/learning-analytics
University of New England. https://analytics.jiscinvolve.org/wp/files/2016/04/CASE-STUDY-G-University-of-New-England.pdf
State University of New York. https://secure.onlinelearningconsortium.org/effective_practices/suny-learning-network-sln-online-teaching-self-assessment-survey-experienced-onl
Northeastern State University. https://www.topuniversities.com/student-info/choosing-university/universities-using-new-technologies
Collaborating to Offer Access for California Students Online. https://er.educause.edu/articles/2019/3/collaborating-to-offer-access-for-california-students-online?utm_source=Informz&utm_medium=Email&utm_campaign=ER#_zsM3xKe1_zlQFMe5
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Uskov, V.L., Bakken, J.P., Gayke, K., Jose, D., Uskova, M.F., Devaguptapu, S.S. (2019). Smart University: A Validation of “Smartness Features—Main Components” Matrix by Real-World Examples and Best Practices from Universities Worldwide. In: Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and e-Learning 2019. Smart Innovation, Systems and Technologies, vol 144. Springer, Singapore. https://doi.org/10.1007/978-981-13-8260-4_1
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DOI: https://doi.org/10.1007/978-981-13-8260-4_1
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